**[NASA Earth-Sun Science]{.smallcaps}**

**[Applied Sciences Program]{.smallcaps}**

Research, Education and Applications Solutions Network (Earth Science
REASoN)

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

*Ecological Forecasting Project on*

*An Agent-Based Interface to Terrestrial Ecological Forecasting*

***Terrestrial Observation Prediction System (TOPS)***

***Evaluation Report***

*Revised December 30, 2005*

> ![](media/image1.wmf){width="1.2in" height="0.99375in"}

Acknowledgments

This work is supported by a grant from the NASA Earth-Sun Science
Directorate, Applied Sciences Program, National Applications Project.

+-----------------------------------+-----------------------------------+
| TOPS-NPS Team                     |                                   |
+-----------------------------------+-----------------------------------+
| Ramakrishna Nemani, NASA Ames     |                                   |
| Research Center*--PI & Team       |                                   |
| Leader*                           |                                   |
+-----------------------------------+-----------------------------------+
| [TOPS]{.underline}                | [National Park                    |
|                                   | Service]{.underline}              |
| Forrest Melton, Applications      |                                   |
| development                       | Niki Nicholas, Chief, Resource    |
|                                   | Mgmt. & Science                   |
| Petr Votava, Software development |                                   |
| management                        | John Gross, Inventory &           |
|                                   | Monitoring Program, NPS Ft.       |
| Andy Michaelis, Climate component | Collins                           |
| and security development          |                                   |
|                                   | Bill Kuhn, GIS, Project Point of  |
| Wanlin Pang, QSS Group, AI        | Contact                           |
| planning and scheduling           |                                   |
|                                   | Samantha Weber, Resource          |
| [Component Models and             | Information for Plans & Projects  |
| Tools]{.underline}                |                                   |
|                                   | Andi Heard, Inventory and         |
| Steve Running, University of      | Monitoring                        |
| Montana, ecosystem model          |                                   |
| development (ecological           | Meryl Rose, Inventory and         |
| forecasting)                      | Monitoring                        |
|                                   |                                   |
| Michael White, Utah State         | Lisa Acree, Park Botanist         |
| University, modeling &            |                                   |
| integration into TOPS             | Kent Van Wagtendonk, GIS/Fire     |
|                                   |                                   |
| Christina Tague, San Diego State  |                                   |
| University, RHESSyS model         |                                   |
| development                       |                                   |
+-----------------------------------+-----------------------------------+

**Table of Contents**

Table of contents iii

tables iv

figures iv

executive summary 1

1 introduction 3

**1.1** **Document Purpose** 3

**1.2** **Project Goals & Objectives** 3

**1.3** **NASA Mission traceability** 4

**1.4** **inventory monitoring program, tops, and protected area
management** 4

1.5 [sierra nevada network & Yosemite National Park]{.smallcaps} 6

1.6 [Systems Engineering Approach]{.smallcaps} 6

2 overview of decision support SYSTEM: Inventory & monitoring & TOps 7

**2.1** **i&M overview** 7

**2.2** **functional and technical needs** 8

**2.3 remote sensing and modeling requirements** 11

> 2.3.1 Data inputs and sources 13
>
> 2.3.2 Data outputs 13
>
> 2.3.3 Data usage (who, what actions and decisions, and impact of these
> decisions) 15
>
> 2.3.4 NPS Data Integration and User Interface Requirements 16

**2.4** **plans for TOPS development and utilization** 16

[2.5 System prototype: sierra nevada network & Yosemite National Park
19]{.smallcaps}

[2.6 Extension of the Prototype System 22]{.smallcaps}

[2.7 Data Management 23]{.smallcaps}

[2.8 Systems Engineering Approach]{.smallcaps} 24

3 consideration of nasa inputs 25

**3.1** **Comparison of NASA INPUTS against technical requirements** 25

3.2 [Past and Current nasa contributions]{.smallcaps} 25

3.3 [opportunity to improve DSS using nasa inputs (models &
Measurements)]{.smallcaps} 28

3.4 [limitations of nasa data and inputs]{.smallcaps} 29

4 conclusions and recommendations 29

**4.1** **findings** 29

**4.2** **recommendations** 30

**4.3** **next steps** 30

# Tables {#tables .Heading-NoTOC}

Table 1. I&M data framework and examples of vital signs 11

Table 2. Summary of TOPS data inputs and sources 13

Table 3. Summary of TOPS data outputs 14

Table 4. TOPS products proposed for integration in the prototype system
21

# Figures {#figures .Heading-NoTOC}

Figure 1. The role of the I&M program in adaptive management 9

Figure 2. I&M DSS Data Management Framework 12

Figure 3. Model predicted vs. observed values for Glacier National Park.
26

Figure 4. Comparison of MODIS snow cover (1 km) against predicted snow
cover 27

Figure 5. Sample 30m LAI products for Yosemite National Park 27

Figure 6. MODIS DB Image showing a fire event in the Yosemite
backcountry. 28

# Executive Summary {#executive-summary .Heading-NoTOC}

National Parks within the U.S. are under continuous threat from climate
change, invasive species, pollutant influxes from atmospheric deposition
and hydrologic transport, and sub-urban and urban encroachment. Knowing
the condition of ecosystems and natural resources in national parks is
fundamental to the National Park Service's (NPS) ability to manage park
resources. National Park managers across the country are confronted with
increasingly complex and challenging issues that require a broad-based
understanding of the status and trends of park resources as a basis for
making decisions, working with other agencies, and communicating with
the public to protect park ecosystems. To address this need, the NPS has
developed the Vital Signs Inventory & Monitoring (I&M) Program to
provide a framework for collecting and archiving data pertaining to park
vital signs including physical, chemical, and biological elements of
ecosystem processes within parks. Under the I&M program, 270 park units
have been organized into 32 networks that share funding and a core
professional staff to conduct long-term ecological monitoring. The I&M
program is one of the primary decision support systems (DSSs) used
throughout the NPS system to manage scientific data for use in decision
making related to park management.

One limitation of the I&M DSS is that it does not currently utilize
remote sensing data for continuous monitoring and assessment of park
ecosystem conditions, in part due to the extensive processing and
computational resources required to utilize daily feeds of satellite
data from the Distributed Active Archive Centers. In addition, current
use of modeling data within the I&M DSS is often limited to
retrospective analysis of ecosystem conditions pertaining to a
particular problem of interest at a single location or set of locations.

An opportunity exists to significantly increase the routine use of
remote sensing data and ecosystem models within the I&M DSS for
monitoring, forecasting, and scenario evaluation, particularly for
parameters related to weather and climate, hydrology, vegetation, and
fire. NASA remote sensing data, especially when combined with ecosystem
models, provides an important capability for continuous park-wide
monitoring of critical ecosystem conditions. The goal of this project is
to use the Terrestrial Observation and Prediction System (TOPS) at NASA
Ames Research Center to integrate a suite of automated monitoring and
forecasting data and information products into the I&M DSS to assist the
NPS in management of U.S. National Parks. These products will be
incorporated as additional data and information layers within the NPS
I&M Program and other DSSs in operation at individual parks.

Work conducted under this project will leverage TOPS capabilities to
integrate thirty different TOPS data products derived from NASA sensors
and ecosystem models into the I&M DSS. These TOPS products will provide
a new capability for continuous monitoring of park-wide ecosystem
conditions. TOPS will be used to reliably deliver nowcasts and forecasts
at resolutions ranging from 30 m to 1 km. TOPS will also be used to
facilitate on-demand retrieval of high-resolution satellite imagery to
aid in monitoring of areas of special significance within the park.
Finally, ecosystem models within TOPS will provide an important
capability for simulation and scenario evaluation to aid NPS staff in
the development of long-term management plans for park resources (e.g.,
the Tuolomne Corridor Management Plan). As part of this project's
systems engineering approach, development of a prototype system for
Yosemite National Park has been evaluated and is currently being
implemented. Following verification, validation, and benchmarking of the
prototype system, TOPS products will be extended for integration with
other I&M networks. This evaluation report documents the existing I&M
DSS, evaluates TOPS capabilities in the context of the I&M DSS,
describes a prototype system for Yosemite National Park, and provides a
strategy for integrating TOPS products into the I&M DSS.

# Introduction {#introduction .Heading-NoTOC}

**1.1 Document Purpose**

The purpose of this document is to evaluate technologies and decision
support systems (DSSs) associated with the "*Agent-Based Interface to
Terrestrial Ecological Forecasting"* project, which extends the
capabilities of the Terrestrial Observation and Prediction System (TOPS)
to provide NASA data for the National Park Service (NPS) Vital Signs
Inventory and Monitoring (I&M) Program DSS. Baseline system
capabilities, data inputs, data outputs, and data used in
decision-making are described as of September 2005. This evaluation
report also describes a strategy for incorporating NASA data and models
into the I&M DSS and other operational decision support systems in use
by the NPS throughout the U.S. Work described under this task will be
conducted jointly with scientists and staff from the NPS pursuant to the
Memorandum of Agreement (MOA) signed by NASA and NPS in January 2005.
Additional information about this effort is available in the Project
Plan for this task, available at: http://aiwg.gsfc.nasa.gov/dss.html.

##  **Project Goals & Objectives** 

The overall goal of this project is to develop a flexible ecological
nowcasting and forecasting system that combines multiple distributed
data sources and models to provide near-real-time answers to questions
about the state of the Earth system. By providing a framework for
ecological forecasting as well as the post-processing of model outputs
needed to visualize the results, TOPS will facilitate rapid data
exploration and what-if analysis. This capability will be essential to
fully achieve the promise of a Sensor Web, in which multi-terabyte
volumes of real-time data are used to support activities ranging from
basic science to monitoring and tracking severe weather, natural
disasters, and other critical events.

The results of near-real-time analysis, short-term predictions, and
long-term scenario evaluations and forecasts are very useful for
managers of large protected areas and tasked with infusing science into
both the short and long-term decision making process (e.g., national
park managers monitoring for change and potential threats). In order for
these results to be accurate, TOPS will account for quality, resolution,
and availability of the input data and provide the means of obtaining,
processing, and fusing data from a wide range of sensors, encompassing
satellite observations, ground observations, and other modeled data.

The immediate goal of the project is to use the TOPS software system to
develop a suite of automated monitoring and forecasting data and
information products to assist the National Park Service (NPS) in
management of U.S. National Parks by project end within three years.
These products will be incorporated as additional data and information
layers within the NPS I&M Program and other DSSs in operation at
individual parks.

##  **NASA Mission Traceability** 

The management and processing of Earth science data has been gaining
importance over the last decade due to the substantial data volumes
generated by a growing number of instruments and ground stations, and
due to the increase in complexity of Earth science models that use these
data. With the launch of NASA\'s Terra and Aqua missions during the last
6 years, the need for more efficient and scalable data systems is even
more apparent. The volume of data itself is often a limiting factor in
obtaining the information required by scientists; without more
sophisticated automation technologies, possibly key information may not
be discovered. In order to realize the goal of a sensor web data
environment new technologies must be developed by NASA.

Under this project, TOPS will address many of the issues facing the NASA
Earth System Science (ESS) missions by developing an efficient and
scalable technology that will incorporate automation in access,
transport, translation, distributed processing and analysis of the Earth
science data. Moreover, the technology will provide a capability for
fusion of data from multiple satellites and ground stations. This will
enable TOPS to process more data more efficiently and in an intelligent
way, and thus give the Earth scientists better foundations for their
research and, by doing so, improve our ability to understand and predict
Earth system processes.

As described in the following sections, through the use of TOPS to
integrate data from NASA satellites and ecosystem models into the I&M
DSS, this project is increasing the use of NASA products to assist in
the protection of some of our most important natural resources. Nowcasts
and forecasts from TOPS will assist NPS scientists and staff in
establishing baseline conditions for ecosystems within and adjacent to
the parks, monitoring ecosystem conditions and identifying trends and
anomalies, and forecasting future conditions to develop and evaluate
management plans. In particular, this project directly supports the NASA
objectives, roadmaps, and program plans listed below.

-   NASA objective 1.2: Expand and accelerate the realization of
    economic and societal benefits from Earth science, information, and
    technology.

-   The Earth-Sun Science, Applied Sciences Program roadmap for
    Ecological Forecasting.

-   ESE roadmaps for Climate, Carbon Cycle, and Ecosystems; especially
    with regards to model development for decision support.

-   The Earth science road map for Earth System Observations and
    Modeling (ch. 7).

##  **Inventory & Monitoring Program, TOPS, & Capabilities for Protected Area Management** 

Knowing the condition of ecosystems and natural resources in National
Parks is fundamental to the National Park Service's ability to manage
park resources. National Park managers across the country are confronted
with increasingly complex and challenging issues that require a
broad-based understanding of the status and trends of park resources as
a basis for making decisions, working with other agencies, and
communicating with the public to protect park natural systems and native
species. Vital signs monitoring is a key component in the Service's
strategy to provide scientific data and information needed for
management decision-making and education. Vital signs also contribute
information needed to understand and measure performance regarding the
condition of watersheds, landscapes, and marine resources, and
biological communities.

To address this need, NPS has developed the I&M Program to provide a
framework for collecting and archiving data pertaining to park vital
signs including physical, chemical, and biological elements of ecosystem
processes within parks. Under the I&M program, 270 park units have been
organized into 32 networks that share funding and a core professional
staff to conduct long-term ecological monitoring. Each network links
parks that share similar geographic and natural resource characteristics
to improve efficiency and reduce costs. The I&M program is one of the
primary DSSs used throughout the NPS system to manage scientific data
for use in decision making related to park management.

One limitation of the I&M DSS is that it does not currently utilize
remote sensing data for continuous monitoring and assessment of park
ecosystem conditions, in part due to the extensive processing and
computational resources required to utilized daily feeds of satellite
data from the Distributed Active Archive Centers (DAACs). In addition,
current use of modeling data is often limited to retrospective analysis
of ecosystem conditions pertaining to a particular problem of interest
at a single location or set of locations. Routine utilization of
ecosystem models to complement the continuous stream of observational
data and provide forecasts and simulations of ecosystem conditions is
not common within the NPS.

TOPS is a modeling framework that integrates and preprocesses EOS data
fields so that land surface models can be run in near real-time.
Currently, a modified version of the BIOME-BGC model is used to estimate
various water (evaporation, transpiration, stream flows, and soil
water), carbon (net photosynthesis, plant growth) and nutrient flux
(uptake and mineralization) processes. TOPS forecasts parameters at a
variety of spatial scales, from global net primary productivity (NPP)
anomalies at 0.5 x 0.5-degree resolution to local estimates of ecosystem
parameters at resolutions as fine as 250m. At each spatial resolution,
TOPS uses different sources of satellite data (Moderate Resolution
Imaging Spectroradiometer (MODIS) to Ikonos) and meteorological data
(single weather station to global atmospheric model outputs).

Using TOPS, scientists at NASA Ames Research Center currently produce a
comprehensive suite of 30 datasets describing land surface conditions.
These products are generated daily in both nowcast and forecast modes to
facilitate near real-time monitoring of ecosystem conditions. Products
include satellite (land cover, snow cover, surface temperature,
vegetation density, vegetation productivity), surface weather (max/min
temperatures, humidity, solar radiation and rainfall), and modeled
fluxes (soil moisture, vegetation stress). TOPS also maintains an
extensive historical record for California and the western US including
climate data that extend from 1950 onwards, and remote sensing data that
extend from the beginning of the NOAA Advanced Very High Resolution
Radiometer (AVHRR) satellite data in 1982 to the present. This data
record allows TOPS to calculate historical averages for all products to
identify and track anomalies in climate and ecosystem parameters.

TOPS provides an ideal mechanism for integrating NASA remote sensing
data and Earth science model outputs into the NPS I&M DSS to aid park
managers in identifying threats to park health, and evaluating the
impacts of decisions pertaining to park management. Additional
information about TOPS and the I&M DSS is provided in Section 2 of this
report.

## **Sierra Nevada Network & Yosemite National Park**

Initial integration of TOPS products into the I&M DSS will require
careful prototyping prior to extension of the system to other parks and
monitoring networks. After consultation with NPS staff, the NPS Sierra
Nevada Monitoring Network (SNN) and Yosemite National Park were selected
as the site for the development of a prototype system, described in
Section 2.5. The extensive data records and high visibility of Yosemite
National Park make it an ideal site for developing and testing a
prototype system.

## **System Engineering Approach**

This project will employ a system engineering approach to integrate data
from NASA satellites and ecosystem models into the NPS I&M DSS. This
project will use the strategy of evaluating, verifying, validating, and
benchmarking TOPS and the I&M system to ensure that products delivered
are high quality and reliable, and that the project tracks the impact of
the new products on the NPS decision making process. Integration will
occur in three phases: 1) development and review of a prototype system
for Yosemite National Park, as described in Section 2.5, 2) integration
of data from the prototype system into the Sierra Nevada I&M Network
(pending review and approval by NPS staff), and 3) extension of the
prototype system to other parks, I&M networks, and international
protected area networks (i.e., SERVIR).

The NPS is implementing the I&M DSS according to rigorous system
engineering principles and detailed program specifications. These
specifications are summarized in Section 2 and available in detail in
the reports and plans posted at
http://science.nature.nps.gov/im/monitor/. All products developed under
this project will comply with the requirements of the NPS I&M program.

One focus of this project is transfer of technology from NASA to NPS as
the customer. Preliminary plans for transfer are described in Section
2.6, but at minimum, will include tools for automated retrieval of data
products and training and assistance with the installation of any
hardware and software required for integration of TOPS products into the
I&M DSS.

**2.0 OVERVIEW OF DECISION SUPPORT SYSTEM: INVENTORY & MONITORING &
TOPS**

**2.1 Background**

As described in Section 1.4, monitoring and understanding the condition
of ecosystem and natural resources in national parks is fundamental to
the National Park Service's ability to manage park resources. To address
the need for a comprehensive data system for compiling monitoring data
and information, the NPS has developed the Vital Signs Inventory &
Monitoring (I&M) Program to provide a framework for collecting and
archiving data pertaining to park vital signs. The NPS I&M program is
described in detail in the NPS Vital Sign Inventory and Monitoring
Program plan, and the following summary is drawn from project documents
available at http://science.nature.nps.gov/im/monitor/.

Park vital signs addressed in the I&M program include physical,
chemical, and biological elements and processes of park ecosystems that
represent the overall health or condition of the park, known or
hypothesized effects of stressors, or elements that have important human
values. Monitoring data help to define the normal limits of natural
variation in park resources and provide a basis for understanding
observed changes and possible management connections. Understanding the
dynamic nature of park ecosystems and the consequences of human
activities is essential for management decision-making aimed to
maintain, enhance, or restore the ecological integrity of park
ecosystems and to avoid, minimize, or mitigate ecological threats to
these systems.

The I&M program reports directly to two strategic NPS planning goals
(Goal 1b3A, Vital Signs Identification, and Goal 1b3B, Vital Signs
Implementation), and provides data and information systems needed to
report to several other Department of Interior (DOI) goals. The
monitoring program's emphasis on integration and coordination across
programs and agencies, and the development of modern information systems
and practices to build institutional knowledge and make the resulting
information more available and useful, will have a major effect on the
Service's ability to meet its mission and serve future generations. The
monitoring program contributes also to the DOI goals for management
excellence by implementing practices that promote efficiency,
collaboration among programs and agencies, and accountability.

Under the I&M program, 270 park units have been organized into 32
networks that share funding and a core professional staff to conduct
long-term ecological monitoring. Each network links parks that share
similar geographic and natural resource characteristics to improve
efficiency and reduce costs. The amount of new funding available through
the Natural Resource Challenge for vital signs monitoring would allow
most parks to monitor only a few vital signs. To more efficiently and
effectively track resource condition and address performance goals, the
NPS adopted a strategic approach that leverages the new funding with
existing park staffing, funding, and other park service programs, and
encourages parks to partner with universities and federal and state
agencies to monitor the condition of selected resources. This strategy
is intended to maximize the use and relevance of the monitoring data for
management decision-making and other park operations by allowing each
network of parks to determine what they will monitor based on their most
critical data needs and local partnership opportunities. This approach
has resulted in major contributions of time, expertise, and money from
more than 150 universities and other federal and state agencies that are
allowing the networks to accomplish far more than what the NPS funding
would allow. Parks are encouraged to use or modify standard protocols
and partner with existing programs wherever possible to allow
comparability and synthesis of data at multiple scales, but the primary
use of the data is at the park level for management decision-making and
integration with park operations.

The long-term programmatic goals of the I&M Program are as follows:

-   Establish natural resource inventory and monitoring as a standard
    practice throughout the National Park system that transcends
    traditional program, activity, and funding boundaries.

-   Inventory the natural resources and park ecosystems under NPS
    stewardship to determine their nature and status.

-   Monitor park ecosystems to better understand their dynamic nature
    and condition and to provide reference points for comparisons with
    other, altered environments.

-   Integrate natural resource inventory and monitoring information into
    National Park Service planning, management, and decision-making.

-   Share NPS accomplishments and information with other natural
    resource organizations and form partnerships for attaining common
    goals and objectives.

**2.2 Functional and Technical Needs**

To guide the monitoring program, all 32 networks address the following
five Goals of Vital Signs Monitoring in the implementation of integrated
natural resource monitoring:

1)  Determine the status and trends in selected indicators of the
    condition of park ecosystems to allow managers to make
    better-informed decisions and to work more effectively with other
    agencies and individuals for the benefit of park resources.

2)  Provide early warning of abnormal conditions of selected resources
    to help develop effective mitigation measures and reduce costs of
    management.

3)  Provide data to better understand the dynamic nature and condition
    of park ecosystems and to provide reference points for comparisons
    with other altered environments.

4)  Provide data to meet certain legal and Congressional mandates
    related to natural resource protection and visitor enjoyment.

5)  Provide a means of measuring progress towards performance goals.

Monitoring is an integral part of the adaptive management cycle
(Figure 1) and a critical component of performance management. As part
of the Service's efforts to improve park management through greater
reliance on scientific knowledge, a primary purpose of the monitoring
program is to develop, organize, and make available natural resource
data and to contribute to the Service's institutional knowledge by
facilitating the transformation of data into information and knowledge
through analysis, synthesis, and modeling. To help provide information
needed at the park, network, regional, and national levels, the vital
signs networks provide a system for scientific data collection,
analysis, and reporting that is unprecedented in the NPS, and that
directly contributes to the Department's strategy to "Improve
information base, information management, and technical assistance".

![](media/image2.jpeg){width="4.439583333333333in"
height="3.1798611111111112in"}

Figure 1. The role of the I&M program in adaptive management.

Information and understanding provided through the vital signs program
contributes to each step of the adaptive management cycle, as described
in the following examples:

1.  As part of the initial investment in monitoring planning and design,
    networks compile and summarize existing information and
    understanding of park ecosystems and develop an information base
    that is also used for park planning, performance management,
    identification of research and restoration needs, interpretation,
    and other park operations. Through scoping workshops, literature
    reviews, interviews with superintendents, and other means, networks
    identify important park resources and issues of concern, summarize
    existing understanding of park ecosystems using conceptual models
    and other products, and facilitate collaboration among parks,
    programs, and agencies that will help parks identify desired
    conditions for selected resources.

2.  Information compiled and organized by the I&M program (e.g., GIS
    layers, vegetation maps, water quality data) contributes to
    assessments of resource conditions in relation to desired
    conditions.

3.  Monitoring provides site-specific information needed to understand
    and identify meaningful change in natural systems characterized by
    complexity, variability, and surprises. Monitoring results help
    managers determine whether observed changes are within natural
    levels of variability or may be indicators of unwanted human
    influences. The improved understanding of trends in resource
    condition and "how park systems work" helps managers make decisions
    about how to allocate funding and staffing and implement management
    actions to address the most critical issues.

4.  Quantitative trend data for a selected set of park vital signs and
    other scientific data, in combination with effectiveness monitoring
    by other programs (e.g., fire effects monitoring, exotic plant
    management teams) and qualitative resource assessments (e.g., to
    report on strategic land health goals), provides feedback on
    resource sustainability and the effectiveness of management
    practices.

5.  Scientific data and understanding collected by, or coordinated by,
    the vital signs monitoring program are used by managers to adjust
    management practices that sustain or improve the health of park
    resources, such as reallocating funding and staffing to achieve
    desired outcomes, initiating or modifying restoration activities, or
    working with State or federal partners to achieve desired outcomes.

For most parks, vital signs monitoring is the primary means of measuring
the status and trends in the condition of park natural resources, and in
conjunction with qualitative resource assessments done by the parks,
will be used to report to the DOI strategic Land Health Goals. Periodic
condition assessments using best available information and expert
opinion can provide a rapid, qualitative "snapshot" of current resource
conditions across an entire park or all resource categories, and may be
used to demonstrate major changes in resource condition. Vital signs
monitoring, in comparison, provides quantitative trend information with
known confidence intervals for a subset of park resources or ecological
processes, and is able to detect more subtle changes in resource
condition and provide early warning of impending threats. However,
because of funding and logistical realities, only a few selected
resources can be monitored.

To promote collaboration among networks and with other programs and
agencies, and to combine results for national reporting, vital signs
being monitored by the parks are organized into a hierarchical Vital
Signs Monitoring Framework that will also be used for reporting to the
DOI Land Health Goals and for other purposes. Analysis and reporting of
data are done at several different scales (park, network, national)
depending on the level of detail needed for the intended audiences.
Examples of vital signs and how they are grouped into higher-level
resource categories are shown in Table 1.

To report to the DOI Land Health Goals, parks will use a combination of
quantitative trend information from vital signs monitoring and other
efforts, and qualitative assessments based on the best available
scientific information and expert opinion, to report on the condition of
resources within each land type (e.g., uplands, wetlands, marine and
coastal) and resource category (Level 1; e.g., Air, Water, Biological
Integrity). The I&M DSS can also be used as an information gateway to
the large body of detailed, complex scientific information that is used
as the basis for the resource assessments.

  ------------------------------------------------------------------------------
  **Vital Signs                     
  Monitoring                        
  Framework**                       
  ------------- ------------------- --------------------------------------------
  **Level 1     **Level 2           **Examples of Vital Signs Selected by First
  Category**    Category**          12 Networks**

  Air and       Air Quality         Ozone, wet and dry deposition, visibility
  Climate                           and particulate matter, air contaminants

                Weather and Climate Weather and climate

  Geology and   Geomorphology       Glaciers, shoreline change, channel
  Soils                             morphology, physical habitat index

                Subsurface Geologic Cave air quality, seismic activity
                Processes           

                Soil Quality        Biological soil crusts, soil structure and
                                    stability, soil cover, permafrost

  Water         Hydrology           Groundwater dynamics, surface water
                                    dynamics, stream flow, lake and pond
                                    elevation, saltwater marsh water table

                Water Quality       Water chemistry, chloride flux, kettle pond
                                    acidification, nutrient loading and
                                    eutrophication, pollutant metals, aquatic
                                    macroinvertebrates

  Biological    Invasive Species    Invasive/Exotic plants early detection,
  Integrity                         areal extent of established populations,
                                    exotic aquatic assemblages

                Infestations and    Whitebark pine disease, forest
                Disease             insect/disease outbreaks

                Focal Species or    Land birds, forest vegetation structure &
                Communities         composition, fish communities, intertidal
                                    communities, salt marsh vegetation, seagrass
                                    communities, wetland vegetation, riparian
                                    plant communities, prairie grassland
                                    communities, freshwater mussels, cave
                                    aquatic fauna, amphibians, white-tailed
                                    deer, caribou, wolves

                At-risk Biota       T&E plants, western prairie fringed orchid,
                                    northern spotted owl, western snowy plover,
                                    Ozark hellbender, Allegheny woodrat, Topeka
                                    shiner

  Human use     Point-Source Human  Contaminants, illegal roads and trails
                Effects             

                Non-point Source    Estuarine nutrient inputs
                Human Effects       

                Consumptive Use     Fisheries harvest, poaching of native plants
                                    and animals

                Visitor and         Visitor usage
                Recreation Use      

  Landscapes    Fire and fuel       Fire occurrence and extent, fuel loading
  (Ecosystem    dynamics            
  Pattern and                       
  Processes)                        

                Landscape Dynamics  Land cover and use

                Soundscape          Soundscape

                Nutrient Dynamics   Nutrient cycling

                Productivity        Productivity, plant phenology
  ------------------------------------------------------------------------------

Table 1. I&M data framework and examples of vital signs.

**2.3 Remote Sensing and Modeling Requirements**

The I&M data framework (Figure 2) is designed to accommodate data from a
wide variety of sources including remote sensing data and output from
ecosystem models. Current use of remote sensing data within the National
Park Service is primarily limited to acquisition and utilization of data
for individual scientific studies, primarily for retrospective analysis
for a single location or set of locations. While still limited, use of
ecosystem models is more prevalent, and NPS scientists and university
researchers working within U.S. National Parks use ecosystem models to
study processes such as forest growth (e.g., Forest-BGC) and wildfire
(e.g., WX), and NPS-wide efforts such as the Landfire Project
(http://www.landfire.gov/) have implemented these models within multiple
parks to facilitate integrated analysis and evaluation of management
scenarios. However, routine utilization of ecosystem models to
complement the continuous stream of observational data and provide
forecasts and simulations of ecosystem conditions is not common within
the NPS.

![](media/image3.jpeg){width="6.0in" height="4.5in"}

Figure 2. I&M DSS Data Management Framework

An opportunity exists to assist the NPS I&M program by significantly
increasing the routine use of remote sensing data for monitoring,
forecasting, and scenario evaluation, particularly for parameters
related to the following elements from Table 1: weather and climate,
hydrology, biologic integrity, and landscapes. NASA remote sensing data,
especially when combined with ecosystem models, provides an important
capability for continuous park-wide monitoring of critical ecosystem
conditions. This project will develop the following general capabilities
in support of this objective:

1)  Continuous, near real-time, park-wide monitoring of ecosystem
    conditions at a minimum resolution of 1-km using satellite data and
    ecosystem models;

2)  Short-term forecasting of a suite of parameters related to ecosystem
    function through the integration of NASA remote sensing data and
    ecosystem models;

3)  On-demand acquisition and delivery of high-resolution satellite data
    to periodically monitor critical habitats or events within a park;
    and

4)  Implementation of hydrologic and ecosystem models to facilitate high
    resolution model runs for evaluation of the impacts of alternate
    management scenarios on hydrologic and vegetative patterns in the
    park.

2.3.1 Data Inputs and Sources

The focus of this project will be the integration of data from NASA
satellites and ecosystem models into the NPS I&M DSS through the use of
TOPS to automate data retrieval, pre-processing and integration, and
model runs. As such, the primary inputs to the system will be those
currently in use by TOPS and summarized below in Table 2.

  -----------------------------------------------------------------------
  **TOPS Inputs**            
  -------------------------- --------------------------------------------
  **Input**                  **Data Sources**

  FPAR                       NASA -- Terra/MODIS, Aqua/MODIS

  LAI                        NASA -- Terra/MODIS, Aqua/MODIS

  Landcover                  NASA -- Terra/MODIS

  Land Surface Temperature   NASA -- Terra/MODIS, Aqua/MODIS

  DEM                        NASA - SRTM, USGS -- GTOPO30

  Snowcover                  NASA -- Terra/MODIS, SNOTEL - USDA

  NDVI/EVI                   NASA -- Terra/MODIS, Aqua/MODIS

  Soil Database              USDA -- STATSGO

  Temperature                CIMIS -- State of California, CPC -- NOAA,
                             NCDC- NOAA, NWS, RUC2 - NOAA

  Precipitation              CIMIS -- State of California, CPC -- NOAA,
                             NCDC- NOAA, NWS, RUC2 -- NOAA, SNOTEL - USDA

  Radiation                  CIMIS -- State of California, CPC -- NOAA,
                             NCDC- NOAA

  GPP/NPP                    NASA -- Terra/MODIS, Aqua/MODIS
  -----------------------------------------------------------------------

Table 2. Summary of TOPS data inputs and sources.

In addition to these inputs, TOPS will also ingest datasets available
for individual parks, such as park meteorological station records, data
from hydrologic monitoring stations within the park, fire records, GIS
data sets (e.g., coverages of boundaries, roads, trails, and structures)
and high-resolution soil and vegetation classification maps such as
those currently being finalized for Yosemite National Park.

2.3.2 Data Outputs

Routine, near real-time, park-wide monitoring data products and
information from TOPS will include: high resolution weather data
including solar radiation, air temperature, humidity, rainfall; and
satellite and model-derived data on ecosystem variables including soil
moisture, vegetation water stress, phenological stage, and biomass.
These products are collectively referred to as the TOPS-30 products
(Table 3). TOPS will be able to provide these products at scales ranging
from 30m to 1000m for both park-wide monitoring and targeted monitoring
for areas of special concern to the NPS. In support of the I&M
objectives to establish baseline conditions and identify trends, the
system will also provide historical information from 1982 to the
present. This historical data will provide an important baseline for
interpreting current monitoring data on park conditions, allowing for
the identification of anomalies in ecosystem conditions that may be
indicative of ecosystem change or a potential threat to the park. In
addition to near-real time monitoring of park conditions, TOPS will be
also be used to provide short-term forecasts for these data products.

+------------------------------------------+---------------------------+
| **TOPS-30 Data Products to be            |                           |
| Incorporated**                           |                           |
+==========================================+===========================+
| **MODIS (8 day and annual products)**    | **Meteorology (Daily)**   |
|                                          |                           |
| 1.  LAI (Leaf Area Index)                | 11. Maximum Temperature   |
|                                          |                           |
| 2.  FPAR (Fraction of absorbed           | 12. Minimum Temperature   |
|     Photosynthetically Active Radiation) |                           |
|                                          | 13. Rainfall              |
| 3.  GPP / NPP (Gross / Net Primary       |                           |
|     Production)                          | 14. Solar Radiation       |
|                                          |                           |
| 4.  LST (Land Surface Temperature)       | 15. Dew Point / VPD       |
|                                          |     (Vapor Pressure       |
| 5.  NDVI (Normalize Difference           |     Deficit)              |
|     Vegetation Index)                    |                           |
|                                          | 16. Degree Days           |
| 6.  EVI (Enhanced Vegetation Index)      |                           |
|                                          |                           |
| 7.  Landcover (Annual)                   |                           |
|                                          |                           |
| 8.  Albedo                               |                           |
|                                          |                           |
| 9.  Snow                                 |                           |
|                                          |                           |
| 10. Fire                                 |                           |
+------------------------------------------+---------------------------+
| **TOPS Ecosystem**                       | TOPS-BGC Forecasts (5 to  |
|                                          | 180 day advance           |
| 17. Snow                                 | forecasts)                |
|                                          |                           |
| 18. Soil Moisture                        | 24. LAI/Phenology         |
|                                          |                           |
| 19. ET (Evapotranspiration)              | 25. Soil Moisture         |
|                                          |                           |
| 20. Outflow                              | 26. Outflow               |
|                                          |                           |
| 21. GPP / NPP                            | 27. ET                    |
|                                          |                           |
| 22. Phenology                            | 28. Vegetation Stress     |
|                                          |                           |
| 23. Vegetation Stress                    | 29. Snow                  |
|                                          |                           |
|                                          | 30. GPP / NPP             |
+------------------------------------------+---------------------------+

Table 3. Summary of TOPS data outputs.

Another key feature of the system will be the ability to acquire
high-resolution imagery to aid in detailed monitoring of areas where
anomalies have been detected using MODIS data and ecosystem models.
Acquisitions of high-resolution data will also be made to verify the
utility of this data for periodic monitoring of areas of particular
interest to park managers, such as riparian corridors, restoration
sites, and habitat for endangered species. This high-resolution
information will be from sensors such as ASTER, LANDSAT/TM , or SPOT,
depending upon availability.

Finally, this project will utilize component models within the TOPS
modeling framework such as RHESSys and Biome-BGC to facilitate high
resolution (30 m) modeling to aid in scenario evaluation and forecasting
of potential impacts of management decisions. In particular, these tools
will allow park managers to simulate the effects of different management
scenarios on the hydrologic and vegetation patterns within the park.
Incorporation of additional models into the TOPS framework will also be
considered to assist in simulation of other key ecosystem parameters of
interest to NPS scientists and park managers. For example, FlamMap may
be incorporated into TOPS to aid in evaluation of the impacts of
alternate management strategies on fire regimes within parks. The
provision of relevant remote sensing and model-derived information on
demand relieves park managers from the potential burden of compiling and
processing large, heterogeneous data sets and allows them to focus on
analysis and decision-making.

This project is primarily focused on monitoring, modeling, and
forecasting of processes that occur at the ecosystem scale. Past work
using TOPS has shown that changes in these processes can be detected at
resolutions of 8-km and higher. Anomalies in key parameters such as LAI,
soil moisture, and NPP are often caused by processes that affect entire
ecosystems such as climate change, nutrient deposition from pollution,
and invasive species. Furthermore, given the large geographic areas
contained within national parks and the often constrained resource
management budgets, NPS staff and scientists can only respond to changes
which occur or are predicted to occur over sustained time periods and
that affect relatively large portions of the park (multiple square
kilometers).

It is anticipated that 1-km will be the appropriate resolution for
continuous monitoring of park-wide ecosystem conditions. As such,
initial products developed for a prototype system in Yosemite National
Park will be generated at a resolution of 1-km, which will provide over
3000 data points daily for a suite of ecosystem parameters for the
entire park. Higher resolution data from NASA sensors and ecosystem
models, as well as data from commercial satellite platforms will also be
included in the prototype to supplement the moderate resolution data for
use in specific applications described in Section 2.5. This data will
also be used to evaluate the comparative utility of the moderate and
high-resolution data products for decision support in protected area
management.

2.3.3 Data Usage

The data products described above will be used to aid park staff in both
operational decision-making and long-term planning for park management.
TOPS products will be integrated into the I&M networks where they will
be accessed primarily by NPS staff within the Resources Management and
Science Division at each park or monitoring network. These NPS staff
will use the products to 1) establish baseline conditions for park
ecosystems, 2) identify trends and anomalies in ecosystem conditions, 3)
relate these trends and anomalies to potential threats or management
conditions, and 4) integrate the data with other I&M datasets for
presentation to other park management divisions and to the general
public for use in decision making, outreach, and education.

NPS staff may use the data provided by TOPS to make a number of
management decisions directly-related to the I&M program goals listed in
Section 2.2, and including decisions regarding infrastructure placement,
invasive species, fire management, visitor management, and resource
allocation. The key feature of the TOPS data products are that they will
allow NPS staff to continuously monitor large areas of the park for
trends and anomalies, allowing NPS staff to identify potential threats
quickly and before they pose a significant threat to park ecosystems. In
addition, the modeling and simulation capabilities provided by component
models within TOPS will enable park managers and scientists to evaluate
alternate management responses. The following examples are provided to
illustrate the range of potential uses of the TOPS data products in NPS
decision-making:

-   Deploy a scientist / park ranger to investigate the possibility of
    disease or invasive species infestation at a site where satellite
    data has detected that leaf area index (LAI) has been anomalously
    low throughout the season;

-   Determine whether or not to initiate a prescribed natural fire based
    on data from TOPS including current gridded meteorological
    conditions, and estimates of soil moisture, vegetation moisture, and
    gross primary production;

-   Close or re-route a hiking trail near sensitive habitat based on
    satellite-derived estimates of current and historical net primary
    production in the sensitive habitat;

-   Issue public warnings or take additional precautions based on flood
    forecasts as determined by predictions of outflow from NASA
    ecosystem models;

-   Remove or relocate a road, campsite, or building based on simulated
    impacts of the structure on hydrologic and vegetation patterns;

-   Allocate additional resources for invasive species removal or
    habitat restoration based on forecasts of future conditions.

    4.  NPS Data Integration and User Interface Requirements

As shown in the I&M Data Management Framework (Figure 2), the NPS
currently uses two types of tools to access and analyze data from the
I&M system. A suite of desktop database query tools based on MS Access
provides I&M users with an interface for locating and retrieving I&M
data products. Analysis of data by NPS scientists and staff is conducted
primarily through the use of GIS-based tools such as ArcView, ArcInfo,
and GRASS.

To minimize additional data management overhead, it is important that
the integration of data from TOPS complies with existing I&M procedures
for data access and analysis. As such, the primary requirement is that
data products from TOPS must be produced in a GIS compatible format, and
metadata included with the products must be in a format that is
compatible with the I&M MS Access database templates. NPS is currently
working to consolidate management of park-related data using the I&M
system, and the addition of interfaces and tools outside of the I&M
framework will undermine this effort. Integration, delivery, and
visualization of data from TOPS should focus on tools for automated
machine-to-machine data transfer, should use the existing I&M framework,
and should not introduce additional layers of data management or user
interface tools outside of the I&M framework.

**2.4 Plans for TOPS Development and Utilization**

Detailed plans for the development of new technologies within TOPS are
provided in the Project Plan for this task
(http://aiwg.gsfc.nasa.gov/dss.html) and summarized below.

The technology development component of TOPS is focused on developing a
software system to provide the capabilities outlined in the previous
sections, specifically aimed at supporting access, delivery, and
interoperability among heterogeneous data sources and software
components. As a foundation for many of our activities, we are using AI
planning technology developed during the first two years of this
project.

Work conducted under this project will build upon ongoing work in the
development of a flexible framework for data processing and integration.
Planned technology development will be focused on the areas of data
fusion, metadata, distributed and parallel processing, component
architecture and interoperability, QA/QC, and extension of user
interfaces and interfaces for machine-to-machine access and data
delivery. In order to provide the best possible datasets to our users,
we will continue to improve our data fusion technologies together with
new metadata and QA tracking capabilities. Because TOPS will be also
operating in near-real-time mode, we need to ensure that we respond to
data requests within specific timeframes. To achieve this, we will
continue development of our direct broadcast system for real-time
satellite data acquisition and we will parallelize our existing
applications to speed-up processing time. This will also enable us to
more efficiently process climate datasets (which in some cases span the
last 100 years) that are key inputs to our system. We will continue to
develop our existing flexible application framework based on the (Java)
Distributed Application Framework (JDAF), for improvements in
interoperability, and model and data integration. Finally, we will work
closely with our partners in the NPS to develop an optimal interface
that will support automated integration of data products from TOPS into
the I&M system.

We will extend the JDAF framework to facilitate access to all databases,
processing components and models that are part of the TOPS system. In
addition, we will improve the automation of model and data integration
by developing a code generator for producing a standard interface
between the JDAF framework and external components. We will fully
integrate both the high-resolution RHESSys modeling framework and the
climate gridding system (SOGS) into the components accessible by JDAF.
Furthermore, we will build on our previous work in developing a Web
service interface to access certain aspects of the JDAF framework.

In order to quickly take advantage of new data streams as they become
available, we will use Earth Science Markup Language (ESML), an
XML-based description language that significantly eases the data fusion
process, and supports one of our design goals - separation of the data
from the processing algorithms. The algorithms obtain their inputs
through a data translator that has a detailed knowledge about the
structure of the data, while the processing component does not have to
know anything about the source or the format of the data. The knowledge
of the data translator comes from external XML descriptions of the data,
and this external description is often the only thing needed to
integrate a new data stream\--no code change is required.

Further developments include completion of fully automated spatial
autocorrelation, theoretical variogram modeling which we will
incorporate into the product stream. We will also extend the I/O
capabilities of TOPS to include GeoTIFF, HDF5, and shapefiles for both
input and output. To improve our meteorological output data streams, we
will add GOES satellite data, which will enable us to further refine
estimates of precipitation and the other meteorological variables output
by TOPS. We will also improve our radiation gridding algorithm and will
conduct several reprocessing campaigns to improve our historic data
holdings, which will have a significant impact on both the nowcast and
forecast data products. To take advantage of the processing power of the
Columbia supercomputer at NASA Ames, we will parallelize additional
portions of the TOPS code so that we can improve both temporal and
spatial resolution of our historic runs. In addition, we will re-design
parts of our database system that holds all station data, in order to
improve performance and provide an improved interface to this new
database.

Metadata, QA/QC and parallel-processing components are in their initial
stages and we will develop them in a way to best accommodate
requirements both of our internal subsystems, and the requirements of
the NPS I&M system specifications. These improvements should increase
our processing capabilities as well as the ability of the users to
access and manipulate TOPS outputs. The technology development work
conducted under this task will build on extensive experience with
parallelization, ECS metadata model, and QA/QC development on MODIS
instruments on both Terra and Aqua platforms.

User interface development will primarily be focused on the automated
integration of data products from TOPS into the I&M system. To
accomplish this goal, we will first extend the existing Planner
capabilities within TOPS to automate the extraction of regional subsets
of data (e.g., Yosemite National Park plus a buffer zone) from existing
data archives using shapefiles provided by NPS collaborators. We will
also implement tools to automate the conversion of data from binary to
GIS compatible formats (e.g., GeoTIFF) and convert existing TOPS
metadata structures into formats compatible with the I&M database
templates. Concurrent with verification of these tools, we will work
with I&M staff to design and build client-side tools that will reside on
I&M servers and will query the Planner interface to retrieve data from
TOPS.

In addition to these tools for automated machine to machine transfer and
integration of data products into the I&M system, we are currently
evaluating additional web-based interfaces to facilitate the use of TOPS
data for NPS-related uses outside of the I&M system and for use by other
potential customers. Current options include: 1) expansion of the
existing data browsing tools contained within the TOPS website
(http://ecocast.arc.nasa.gov) to allow browsing of the full data
archive, data subsetting, data query, and automated data retrieval; 2)
implementation of an ArcIMS server to distribute TOPS data products
related to U.S. National Parks and facilitate data visualization and
query; 3) distribution of park-related data via a WMS server for
visualization using the NASA WorldWind application. As described in
Section 2.4, however, all of these interfaces are outside the scope of
the current I&M framework. As such, the primary purpose of these
interfaces would be to facilitate use of data developed for NPS decision
making for outreach and education, and to support use of the system by
non-NPS users. While important, the primary purpose of this project is
to support operational decision making by the NPS. Extension of the data
for use by the general public using the interfaces described above will
be further evaluated in 2006 upon completion of the integration of TOPS
data within the I&M system.

**2.5 System Prototype: Sierra Nevada Network Yosemite National Park**

This project will establish procedures for the routine use of data from
NASA sensors and ecosystem models for decision making within U.S.
National Parks. As such, it is important that procedures for data
integration, distribution, and utilization are verified at a manageable
scale for a single I&M network prior to extension of the system to other
networks and geographic regions. As part of our systems engineering
approach, we will first implement a prototype system in Yosemite
National Park where we will validate, verify, and benchmark the system
before extending it to other I&M networks and other geographic regions.

The NPS Sierra Nevada Monitoring Network (SNN) is one of the 32 NPS wide
monitoring networks, and includes three national parks in California:
Yosemite National Park, Sequoia-Kings Canyon National Park, and Devil's
Postpiles National Monument. Due to the size of these parks, high
visitor volume, prominence, and the existence of extensive biological
and geological data records, this I&M network was selected for
demonstration of an initial prototype for the integration of NASA remote
sensing data and ecosystem models from TOPS. In addition, the proximity
of these parks to NASA Ames Research Center will facilitate meetings and
collaboration development between the NASA and NPS teams without
incurring substantial travel expenses for the project.

Yosemite National Park in particular is currently completing revised,
high-resolution soil type and vegetation cover maps, both key inputs to
the NASA TOPS modeling framework. As such, prototype products from TOPS
will first be evaluated for use in Yosemite National Park prior to
integration with the SNN. Initial efforts in Yosemite will focus on the
TOPS-30 products and capabilities that are relevant to all three parks
in the SNN, as well as parks in the other 32 I&M networks.

The prototype system will be comprised of four components and will focus
on the integration of data from NASA satellites and ecosystem models to
provide information on vegetation patterns and change, hydrologic
patterns, and wildfire. Integration of these products with the I&M DSS
will provide new capabilities for monitoring and modeling of ecosystem
conditions within parks to provide advance warning of potential threats
to park ecosystems. The components of the prototype system will include:

1)  Continuous, near real-time, park-wide monitoring of ecosystem
    conditions at a minimum resolution of 1-km;

2)  Short-term forecasting of a suite of parameters related to ecosystem
    function through the integration of NASA remote sensing data and
    ecosystem models;

3)  On-demand acquisition and delivery of high-resolution satellite data
    for periodic monitoring of critical habitats or events within a
    park; and

4)  Implementation of hydrologic and ecosystem models to facilitate high
    resolution model runs for evaluation of the impacts of alternate
    management scenarios on hydrologic and vegetative patterns in the
    park.

Upon completion, the prototype system will provide data and information
to support NPS scientists and staff in identifying trends and events,
and making decisions related to the following issues in Yosemite
National Park:

-   Detection of major disturbance events;

-   Ecosystem water balance monitoring;

-   Runoff monitoring and flood prediction;

-   Monitoring and modeling of sensitive areas in parks: riparian
    corridors, restoration sites, campsites, backcountry;

-   Vegetation monitoring to aid in invasive species detection;

-   Fire occurrence monitoring and fire behavior prediction;

-   Detection and prediction of landcover change, and the predicted
    impact of climate change on vegetation, fire, and hydrologic
    patterns in the park;

-   Modeling of impacts of park infrastructure placement on ecosystem
    function;

-   Nitrogen deposition modeling and water quality monitoring; and

-   Support of a range of ongoing research efforts within the park.

The first stage of implementation of the prototype system will involve
the delivery of daily and 8-day average, park-wide, 1-km resolution data
products from TOPS for Yosemite National Park and a buffer area
surrounding the park. These data products are listed in Tables 3 and 4,
and will be delivered daily in binary and GeoTIFF format for automated
retrieval by NPS staff as described in Section 2.4. Historical averages
will also be calculated for all of these products, and areas that
deviate from these averages (anomalies) will be identified in the data
products or images. Finally, additional data layers such as roads,
trails, and sensitive habitat (e.g., riparian zones) may be combined
with these data products automatically or using a GIS system to
facilitate utilization of these data products by NPS staff.

The second stage of the prototype system will be to extend each of the
products listed in Table 3 to include forecasts of these parameters
ranging from 5- to 180-day advance forecasts. These forecasts of
ecosystem conditions will give park managers advance warning of
potential changes in ecosystem conditions, providing time to consider
adjustment to current management strategies and funding levels for
different management activities.

  ------------------------------------------------------------------------
  **Planned Yosemite                                
  Monitoring Products**                             
  -------------------------- ---------------------- ----------------------
  **Parameter**              **Spatial Resolution** **Temporal
                                                    Resolution**

  MODIS Direct Broadcast     250 m                  Daily

  FPAR                       1 km                   8-day

  LAI                        1 km                   8-day

  GPP / NPP                  1 km                   8-day

  LST                        1 km                   8-day

  Snowcover                  30m to 500m            8-day & daily

  NDVI/EVI                   1 km                   8-day

  Phenology                  30 m to 1 km           8-day

  Evapotranspiration         30 m to 1 km           8-day & daily

  Vegetation stress          30 m to 1 km           8-day & daily

  Soil Moisture              30 m to 1 km           Daily

  Outflow                    30 m to 1 km           Daily

  Landcover                  30 m to 250 m          Annual

  Thermal Anomalies (Fire)   500 m                  Daily

  Temperature (Max / Min)    30 m to 1 km           Daily

  Precipitation              30 m to 1 km           Daily

  Vapor Pressure Deficit     30 m to 1 km           Daily

  Solar Radiation            30 m to 1 km           Daily

  Degree Days                30m to 1 km            Daily
  ------------------------------------------------------------------------

Table 4. TOPS products proposed for integration in the prototype system.

The third stage will be to acquire a limited set of high-resolution
satellite imagery for key areas of interest to the park managers to
verify the utility of these data products for monitoring of sensitive
areas within the park such as riparian zones, camp sites, areas impacted
by invasive species or fire, or areas where anomalies in conditions have
been detected in the coarser resolution data. In addition to the
acquisition of high-resolution satellite data, high-resolution ecosystem
model simulations may also be used in combination with coarser
resolution satellite data to provide more detailed products for these
areas of interest.

Yosemite National Park is currently developing the Tuolomne Corridor
Management Plan. This high-profile effort will involve significant
scientific input and analysis and provides an important opportunity for
the use of NASA products to support and enhance decision-making within
Yosemite. The fourth and final stage of the implementation of the
prototype system will utilize ecosystem models within TOPS (e.g.,
RHESSys, Biome-BGC) to evaluate the effects of alternate management
scenarios on hydrologic and vegetative patterns within the Tuolomne
Corridor. RHESSys in particular will be used to simulate the impact of
park infrastructure (roads, buildings, campsites, trails) on hydrologic
flow, and TOPS will be used to extend the results from this work to
evaluate the effects on vegetation patterns. As a final component of
this effort, the FlamMap model may be implemented in TOPS to evaluate
alternate scenarios for prescribed natural fire management.

6.  **Extension of the Prototype System**

Concurrent with the validation, verification, and benchmarking of the
prototype system in Yosemite, specifications and documentation for the
prototype system will be compiled to facilitate implementation at other
parks and integration with other I&M networks. Under this project, we
will implement the final system for at least two additional parks:
Sequoia Kings Canyon and Yellowstone National Park, in the SNN and
Greater Yellowstone I&M networks respectively. Through this
implementation we will verify that the specifications and documentation
provided are sufficient to allow the NPS to implement data from TOPS for
multiple parks throughout the NPS I&M system.

The general requirements for integration of TOPS at other parks
include: 1) a map which includes park boundaries and infrastructure, and
demarcates a buffer zone to be included in the continuous monitoring
products; 2) a vegetation map; and 3) a soil type map. Nearly all parks
have prepared GIS maps of their boundaries and a buffer zone can easily
be added to these maps. While some parks have prepared high resolution
vegetation and soil maps, MODIS landcover and data from the NRCS State
Soil Geographic (STATSGO) database are available for all parks.

In addition to these general requirements, implementation of the RHESSys
modeling component within TOPS for high resolution hydrological modeling
and scenario evaluation for decision making will also require the
development of a patch model. Documentation will be provided describing
how to develop the patch model which will facilitate implementation of
this TOPS' capability within multiple parks within the NPS system.

While this project is primarily focused upon support of operational
decision making within U.S. National Parks, the tools and technologies
being developed under this project are applicable for decision support
for any geographic location worldwide. Managers of state parks and U.S.
National Forests in particular would be able to directly implement and
utilize many of the products being developed under this project. Tools
for data retrieval and delivery would require minor modification to
provide data for integration with frameworks other than the I&M system,
however, ftp data pools and other simple data delivery mechanisms could
fulfill this need. In addition, this system could have broad utility for
monitoring and management of protected areas worldwide. While the often
limited availability of data on meteorological conditions and soil types
within developing countries would make it difficult to implement the
high resolution modeling components of this project, efforts such as the
SERVIR project have already demonstrated the utility of moderate and
coarse resolution monitoring for management of international protected
areas. An opportunity to work with the SERVIR project has recently
arisen, and plans are currently being developed to implement a subset of
the TOPS-30 products at 1-km resolution for much of Central America.
These products will be provided to support the SERVIR project and
enhance the datasets currently available for Central America.

**2.7 Data Management**

A primary purpose of the I&M Program is to develop, organize, and make
available natural resource data and to contribute to the Service\'s
institutional knowledge by facilitating the transformation of data into
information through analysis, synthesis, and modeling. The I&M Program
is designed to identify, catalog, organize, structure, archive, and make
available relevant natural resource information for U.S. national parks.
As part of the I&M effort, the NPS is developing a modern information
management infrastructure (e.g., staffing, hardware, software) and
procedures to ensure that relevant natural resource data collected by
NPS staff, cooperators, researchers and others are entered,
quality-checked, analyzed, reported, archived, documented, cataloged,
and made available to others for management decision-making, research,
and education.\
\
The National Park Service is a highly decentralized agency with complex
data requirements. The primary audience for many of the products from
the I&M program is at the park level, and the I&M system is designed to
provide park managers with the information they need to make
better-informed decisions and to work more effectively with other
agencies and individuals for the benefit of park resources. However,
certain data are also needed at the regional or national level for a
variety of purposes, and as stated by the National Park Advisory Board,
the findings \"must be communicated to the public, for it is the broader
public that will decide the fate of these resources\".

The I&M Program Data Management framework (Figure 2) was designed to
promote integration and collaboration among parks, programs and agencies
and to provide standardized, master databases for those common datasets
needed at multiple levels (e.g., park, network, region, national). At
the same time, the framework provides parks and networks with the
flexibility to develop data structures and procedures that increase the
availability and utility of data at the local level and allow them to
take advantage of local partnership opportunities. The framework
includes a series of internet-based, master databases to promote
integration and enable linkages and data sharing to other external
databases (e.g., NPS permitting system, Integrated Taxonomic Information
System, USFWS T&E species database, NatureServe, eNature). A second
component of the data management framework is a series of desktop
applications in MS Access (the NPS standard for desktop relational
databases) that can accommodate the same data as the master web-based
databases. The desktop versions increase the availability and utility of
each park\'s data by allowing users (with the appropriate permissions)
to download the latest data from the corresponding master web database
and develop customized displays or analysis of the data or integrate
them with other local datasets. A third component of the framework is a
collection of relational databases that follow the database template
scheme, with an integrated link to GIS and associated tools through an
Arc-Access Link Tool or geodatabase model. The Natural Resource Database
Template is a flexible, relational database model in MS Access for
storing inventory and monitoring data (including raw data collected
during field studies). The template has a core data structure that can
be modified and built upon by different parks and networks depending on
the components of their inventory and monitoring program and the
specific sampling protocols they use. Modules that will include a
written sampling protocol, database table structure, data entry forms
and quality checking routines, and queries and reports will be
coordinated by the Service-wide I&M Program and made available through a
web-based monitoring protocol clearinghouse. Each module will be based
on a standard sampling protocol.\
\
The guidance to the networks and prototypes as they plan and design
long-term ecological monitoring programs is to view inventorying and
monitoring as an information system (Figure 2) that can serve as a key
component of resource stewardship and building institutional knowledge
about the status and trends in resource condition. Efforts conducted
under this project to integrate NASA data from TOPS into the I&M systems
will adhere to the protocols listed in the I&M project plans and
specifications and summarized above. In particular, all data provided by
TOPS will be compatible with GIS systems and will include extensive
metadata compliant with OGC and ESML standards. As described previously,
a primary goal of this project is automate much of the data processing
and integration of data from NASA satellites and ecosystem models to
help ensure that "scientifically sound information obtained through
inventory and monitoring is available for management decision-making,
research, education, and promoting public understanding of park
resources".

8.  **Systems Engineering Approach**

This project is being implemented using a systems engineering approach.
Under this approach, the project has evaluated existing decision-making
processes and decision support systems used by NPS to identify key NASA
products that can be used to support NPS decision-making. The project is
currently in the process of verifying strategies for system integration
using Yosemite National Park as a system prototype. The next stage of
the project will focus on the validation of system data products within
Yosemite and re-verification to ensure that the integrated system
functions smoothly and delivers data reliably to end users in a format
that is easy to work with and thus will impact decision making.
Following this re-verification, we will finalize the integrated system
and establish benchmarks for improvements in decision-making
capabilities in Yosemite National Park before proceeding with
implementation of the integrated system in other parks and NPS I&M
networks, as well as international protected areas.

**3.0 CONSIDERATION OF NASA INPUTS**

**3.1 Consideration of NASA Inputs Against Technical Requirements**

This project will provide the tools and technology to integrate data
from NASA sensors and ecosystem models into the NPS I&M DSS. NPS
requirements for data integration into the I&M DSS include:

-   Inclusion of meta-data for all data products in an MS Access
    compatible format;

-   Delivery of all data in a GIS compatible format;

-   Capability for automated retrieval and integration of data from NASA
    sources into the I&M DSS.

Through utilization of TOPS, this project will meet all necessary
technical requirements. In addition, this project will meet the
following additional requirements to ensure that data delivered has
utility for decision support:

-   Data products will be spatially and temporally continuous for the
    regions and time periods of interest, whether retrospective
    analyses, near real-time monitoring, or forecasts.

-   Data products for continuous monitoring will be provided reliably on
    regular intervals (daily, weekly, monthly, or annual).

-   All data products will be evaluated, validated, and approved by NPS
    scientists and staff prior to integration with the I&M DSS.

**3.2 Past and Current NASA Contributions**

NASA and the NPS have a long history of collaborating to develop
technologies and data systems to assist with management of U.S.
protected lands, and recently signed a MOA to "collaborate on mutually
beneficial Earth science programs for the preservation, enhancement and
interpretation of U.S. natural resources". Previous and ongoing efforts
have focused on wildfire, invasive species, hydrology, and forest
productivity, as well as science education and public outreach. Many of
these activities are described elsewhere (e.g.,
http://www.nasa.gov/centers/goddard/earthandsun/nps_data.html), and the
following examples describe past contributions directly related to this
project.

Previous efforts to use TOPS to assist in ecosystem management were
supported by a grant from the NASA Earth Science Enterprise. This
project explored the application of component models within TOPS to
develop nowcasts and forecasts of estimates of net primary production,
ecosystem growth efficiency, snowpack, and stream discharge for Glacier
National Park. This work proved the validity of the approach and
validated the ability of ecosystem models within TOPS to produce
accurate estimates of parameters related to ecosystem function within
national parks. The project was primarily a research and demonstration
project, however, and did not result in the continued use of these
products within the parks. Under the current project, these early
prototype products will be further developed and implemented within the
NPS I&M DSS.

![](media/image4.png){width="5.173611111111111in"
height="4.076388888888889in"}

Figure 3. Model predicted vs. observed values for aboveground NPP and
stream discharge for Glacier National Park.

In addition to this work on ecosystem modeling, the NASA CICT
Intelligent Systems, Intelligent Data Understanding Project provided
support for the development of tools within TOPS to automate the
integration of data from satellite and ground-based observation
networks. These efforts resulted in new capabilities within TOPS for
automated retrieval, pre-processing, and integration of heterogeneous
data sources, allowing TOPS to generate near real-time nowcasts and
forecasts of ecosystem conditions. This advance is now being applied
under the current project to provide nowcasts and forecasts for use by
NPS scientists.

Finally, under the current project, scientists at NASA Ames Research
Center and California State University Monterey Bay (CSUMB) have already
developed a number of prototype products for Yosemite National Park
using TOPS, and these products are currently being evaluated by NPS
scientists. Examples of these prototype products are provided below and
include data on snow cover, leaf area index, and fire event monitoring
(Figures 4-6).

![](media/image5.jpeg){width="2.125in" height="1.9340277777777777in"}

Figure 4. Comparison of MODIS snow cover (1 km) with predicted snow
cover from TOPS / RHESSys (30m) for the Merced watershed, May 14, 2005.

These prototype products represent a new capability for spatially
continuous monitoring of ecosystem conditions within Yosemite National
Park. Under the systems engineering approach being used by this project,
these and other prototype products will undergo extensive validation and
verification conducted jointly by NPS and NASA staff before being
integrated into the NPS I&M SNN.

![](media/image7.png){width="2.2083333333333335in"
height="3.0388888888888888in"}

Figure 5. Sample 30m LAI products for Yosemite National Park for July
1984 and July 2004 derived from Landsat data using TOPS.

![](media/image9.jpeg){width="2.2777777777777777in"
height="2.2777777777777777in"}

Figure 6. MODIS DB Image from Sept. 14, 2005 showing a fire event in the
Yosemite backcountry. Using TOPS, MODIS DB data can be delivered to NPS
staff within hours of collection onboard the satellite.

**3.3 Opportunity to Improve the NPS I&M DSS Using NASA Inputs**

The size, topography, and science budgets of many parks limit the
ability of park staff to continuously monitor park ecosystems. The use
of ecosystem models to integrate satellite data with ground-based
observation networks provides an important opportunity to develop a
capability for spatially and temporally continuous monitoring of park
ecosystem conditions. Within the I&M DSS, however, use of satellite data
and ecosystem models is often limited to retrospective analysis for
relatively small geographical areas and limited time periods. Issues
related to data access, storage, formatting, and integration present
substantial barriers to routine use of NASA satellite data and ecosystem
models for park management.

Under this project, technology and tools within TOPS will be used to
automate much of the data retrieval and integration process, allowing
for routine use of NASA satellite data and ecosystem models in
monitoring and decision-making. Data and information provided by TOPS
will fulfill a need for park-wide monitoring, forecasting, and
simulation products not otherwise easily available to NPS staff,
particularly for use within multiple parks. In addition, the data
products described in Section 2 will also allow NPS staff to monitor
buffer zones around the park to provide advance warning of potential
threats to park ecosystems due to urban encroachment, air pollution, and
invasive species. Using TOPS ecosystem models, it will be possible to
integrate data from satellite and ground-based observation networks to
provide data and information to address NPS needs for monitoring of
vegetation, hydrology, and fire within U.S. National Parks.

**3.4 Limitations of NASA Data and Inputs**

The primary source of satellite data utilized in this project will be
the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the
Terra and Aqua satellites. The resolution of data products from MODIS
ranges from 250m to 1km ground-projected instantaneous field of view
(GIFOV). While data from NASA satellites and ecosystem models will
fulfill an important need with the NPS I&M DSS, the resolution of MODIS
data will limit the utility of this data for certain applications of
interest to the park. Ecosystem models within TOPS will be used to
downscale the data whenever possible, but for the majority of data
products, the finest resolution available from TOPS will range from 30m
to 500m.

Routine datasets will be supplemented with a limited number of
acquisitions from high-resolution satellite instruments to investigate
anomalies detected in the TOPS products and to aid in monitoring in
areas within the parks that are particularly sensitive. The cost of
continuous monitoring of park-wide ecosystem conditions through daily or
weekly acquisitions of park-wide coverages from high-resolution
commercial instruments such as SPOT, however, would be cost prohibitive
and is beyond the scope of this project. As such, applications requiring
continuous, high-resolution data cannot be supported using NASA data
alone. For example, while it may be possible to detect anomalies in
LAI/FPAR that may be indicative of an infestation of invasive species,
data products provided under this project will not provide support for
mapping of individual stands of invasive species. Likewise, TOPS
products may be useful for tracking landscape level changes in
ecosystems for monitoring habitat change, but will not be of a fine
enough resolution to aid in mapping microhabitats for individual
organisms, or monitoring wildlife directly.

**4.0 CONCLUSIONS AND RECOMMENDATIONS**

**4.1 Findings**

The primary finding of this report is that an opportunity exists to make
a significant advance in the capabilities of the NPS I&M DSS through
integration of data from NASA satellites and ecosystem models as
provided by the Terrestrial Observation and Prediction System at NASA
Ames Research Center. Through this integration, NASA data products will
be used to aid NPS staff and scientists in managing the natural
resources and ecosystem within U.S. National Parks.

TOPS products summarized in Tables 3 and 4 will provide a new capability
for spatially and temporally continuous monitoring of park-wide
ecosystem conditions. TOPS will be used to deliver 30 different nowcasts
and forecasts at resolutions ranging from 30 m to 1 km. TOPS will also
be used to facilitate on-demand retrieval of high-resolution satellite
imagery to aid in monitoring of areas of special significance within the
park. Finally, ecosystem models within TOPS will provide an important
capability for simulation and scenario evaluation to aid NPS staff in
the development of long-term management plans for park resources. All
TOPS products will first be prototyped, evaluated, and validated by NPS
staff prior to integration with the I&M DSS.

**4.2 Recommendations**

Based upon the contents of this report, it is recommend that the project
proceed with the development of the prototype system in Yosemite
National Park following the systems engineering approach outlined in
Section 2.8. In particular, I&M DSS specifications for data formats and
meta-data structure should be closely followed to facilitate integration
of TOPS products into the I&M DSS, and ensure widespread distribution
and use of the NASA products from TOPS. The prototype system should
provide capabilities to support science objectives for the development
of the Yosemite National Park Tuolomne Corridor Management Plan, as
requested by NPS staff.

NASA staff should work closely with Dr. Niki Nicholas and her team in
the Resource Management and Science Division at Yosemite National Park
to ensure that TOPS products are easy to retrieve, analyze, and use in
decision making. NASA should work closely with NPS staff to validate
prototype products, develop benchmark evaluations, and obtain guidance
with regards to the application of TOPS products to park management.
NASA and NPS should meet on a quarterly basis to facilitate close
collaboration. NASA staff should also reserve 1-2 weeks per year to
provide support and training on data management systems for NPS staff
upon request.

Finally, the current project plan calls for implementation of TOPS at
Sequoia-Kings Canyon National Park, Yellowstone National Park, Glacier
National Park, and others. Prior to implementation of TOPS at these
parks, it is recommended that at minimum, an initial integration of the
prototype system should be completed and validated in Yosemite National
Park.

**4.3 Next Steps**

To date, this project has completed extensive technology development on
TOPS and the IMAGEbot data processing planner, conducted a review and
evaluation of the NPS I&M DSS and identified opportunities for
integration of NASA data products, and developed prototype products for
Yosemite National Park.

Overall project milestones and scheduled activities for FY 2006 are
described in Section 4.4 of the project plan for this task. For those
elements of the project which are focused on integration of TOPS
products into the I&M DSS, next steps include the following:

1)  Preparation and delivery of a suite of prototype monitoring products
    to Yosemite National Park in a format which complies with the I&M
    program specifications as described in Section 2 of this report.

2)  Joint verification and validation of prototype products by NPS and
    NASA teams.

3)  Automation of production and delivery of the prototype suite to the
    SNN I&M team.

4)  Implementation of additional planned TOPS / IMAGEbot capabilities to
    aid in automated, machine-to-machine delivery and utilization of
    TOPS products.

5)  Extension of the TOPS user-interface to facilitate manual web-based
    visualization, manipulation, and retrieval of TOPS data.

6)  Benchmarking of the utilization of these products and their impact
    on decision-making within Yosemite National Park.

7)  Extension of the suite of TOPS products to include scenario
    evaluation modeling tools within TOPS for evaluation of management
    strategies for the Tuolomne Corridor.

8)  Initiation of integration efforts at other parks and within other
    I&M monitoring networks.

These activities are scheduled to occur in FY '06 and FY '07. Upon
completion of these tasks, it is anticipated that a fully functional
prototype system will be in operation in Yosemite National Park. This
prototype system will use TOPS to extend the capabilities of the SNN I&M
network for Yosemite National Park to include data from NASA satellites
and ecosystem modeling. The prototype system will enhance the ability of
park scientists and managers to continuously monitor and evaluate
ecosystem conditions throughout the park.