![](media/image1.png){width="1.75in" height="1.4465277777777779in"}

**Regional Visualization and Monitoring System (SERVIR)**

**Verification, Validation and Benchmark Report**

**Sistema Regional de Visualizacion y Monitoreo**

Thomas L. Sever and Daniel E. Irwin

Earth and Planetary Science Branch

NASA Marshall Space Flight Center, Huntsvile, Alabama

With contributions from

Joel Perez, Water Center for the Humid Tropics of Latin America and the
Caribbean (CATHALAC)

Wilfredo Fuentes, Ministry of Environment and Natural Resources, El
Salvador

Enrique Barraza, Ministry of Environment and Natural Resources, El
Salvador

Danny Hardin, University of Alabama Huntsville

Timothy Gubbels, Science Systems and Applications Inc.

**September 30, 2006**

**Contact Information**

[Thomas L. Sever, SERVIR Principal Investigator]{.underline}

NASA Marshall Space Flight Center

Earth and Planetary Science Branch

NASA MSFC/XD11

Huntsville, AL. 35805

Phone: 256-961-7958

Fax: 256-961-7788

Email: Tom.Sever@.nasa.gov

[Daniel E. Irwin]{.underline}

NASA Marshall Space Flight Center

Earth and Planetary Science Branch

NASA MSFC/XD11

Huntsville, AL. 35805

Phone: 256-961-7945

Fax: 256-961-7788

Email: Daniel.Irwin@nasa.gov

**Table of Contents**

[Executive Summary 3](#executive-summary)

[1.0 Introduction 4](#introduction)

[1.1 NASA Application Mission Traceability
4](#nasa-application-mission-traceability)

[1.2 Introduction to SERVIR 4](#introduction-to-servir)

[1.3 Systems Engineering Approach 6](#systems-engineering-approach)

[1.4 Purpose of this Report 7](#purpose-of-this-report)

[2.0 Evaluation Summary of SERVIR 7](#evaluation-summary-of-servir)

[2.1 MODIS SERVIR Red Tide Product 7](#modis-servir-red-tide-product)

[2.2 MODIS SERVIR Fire Extent Product
8](#modis-servir-fire-extent-product)

[2.3 SERVIR Mesoamerican Climate Modeling System
10](#servir-mesoamerican-climate-modeling-system)

[3.0 Design and Implementation 10](#design-and-implementation)

[3.1 SERVIR Design Philosophy 10](#servir-design-philosophy)

[3.2 Processing of SERVIR Input Data Sets
11](#processing-of-servir-input-data-sets)

[3.2.1 MODIS SERVIR Red Tide Product
11](#modis-servir-red-tide-product-1)

[3.2.2 MODIS SERVIR Fire Extent Product
15](#modis-servir-fire-extent-product-1)

[3.2.3 SERVIR Mesoamerican Climate Modeling System
19](#servir-mesoamerican-climate-modeling-system-1)

[4.0 Verification and Validation 22](#verification-and-validation)

[4.1 Description of Verification and Validation (V&V) Methods and
Results
22](#description-of-verification-and-validation-vv-methods-and-results)

[4.1.1 MODIS SERVIR Red Tide Product V&V
22](#modis-servir-red-tide-product-vv)

[4.1.2 MODIS SERVIR Fire Extent Product V&V
22](#modis-servir-fire-extent-product-vv)

[4.1.3 SERVIR Mesoamerican Climate Modeling System V&V
23](#servir-mesoamerican-climate-modeling-system-vv)

[4.2 Verification and Validation Gaps and Recommendations
24](#verification-and-validation-gaps-and-recommendations)

[*5.0* Benchmarking 24](#benchmarking)

[5.1 Overview of Benchmark Design 24](#overview-of-benchmark-design)

[5.2 Overview of Benchmark Metrics 25](#overview-of-benchmark-metrics)

[5.2.1 SERVIR Feedback 25](#servir-feedback)

[5.2.2 SERVIR Media Statistics 28](#servir-media-statistics)

[5.3 SERVIR Products Web Hits 28](#servir-products-web-hits)

[5.3.1 MODIS SERVIR Red Tide Product Web Hits
29](#modis-servir-red-tide-product-web-hits)

[5.3.2 MODIS SERVIR Fire Extent Product
29](#modis-servir-fire-extent-product-2)

[5.3.3 Mesoamerican Climate Modeling System Findings
30](#mesoamerican-climate-modeling-system-findings)

[5.3.4 Identification of Useful Decision Support Products for
Decision-Makers
31](#identification-of-useful-decision-support-products-for-decision-makers)

[5.3.5 Metric of SERVIR Usage 32](#metric-of-servir-usage)

[5.3.6 SERVIR Training and Capacity Building
32](#servir-training-and-capacity-building)

[5.3.7 Acceptance of SERVIR by Governments of Central America to
Continue Operation Beyond NASA Involvement.
33](#acceptance-of-servir-by-governments-of-central-america-to-continue-operation-beyond-nasa-involvement.)

[6.0 Benchmarking Gaps 33](#benchmarking-gaps)

[7.0 Summary and Conclusion 34](#summary-and-conclusion)

[8.0 References 34](#references)

#   {#section .unnumbered}

# Executive Summary

The NASA Applications Program seeks to transfer NASA data, models, and
knowledge into the hands of end-users through forming links with partner
agencies and associated decision support tools (DSTs). This report
details an effort to further this goal by strengthening the existing
partnership between NASA and Central American Commission for Environment
and Development (CCAD) using NASA resources to improve environmental and
disaster management and decision making. NASA resources utilized in this
effort include Landsat ETM and TM, MODIS/Aqua, MODIS/Terra, SRTM and
TRMM data.

The pages which follow detail the results of the benchmark experiments
which focused on red tides, fires, and climate modeling as well as the
verification, and validation activities that were completed in
association with this work. Although this report is divided into two
main sections---verification and validation, and benchmark---it is
formulated as a continuous report, progressing from project inception
and formulation, to benchmark results and recommendations.

# Introduction

## NASA Application Mission Traceability

NASA's vision and mission statements include a clear focus on
understanding the Earth system in order to improve life on Earth. NASA's
Science Mission Directorate includes NASA's Earth science activities. As
part of a systematic approach to extending the benefits of NASA Earth
science to the broader community, NASA identified 12 applications of
national priority using such criteria as consideration of potential
socio-economic return, application feasibility, appropriateness for
NASA, and partnership opportunities. The Applied Sciences Program of the
Science Mission Directorate, in partnership with public and private
sector organizations, employs *a systems engineering process* to
integrate and benchmark NASA inputs into operational Decision Support
Systems (DSSs) of partner institutions across these 12 application
areas. This report is an element of the Ecological Forecasting national
application.

Ecological Forecasting utilizes observation data and models to predict
the impacts of environmental change on ecosystems. In doing so, it
applies information from the physical, biological, and social sciences.
NASA is working in partnership with the U.S. Agency for International
Development (USAID), the World Bank, the Central American Commission for
Environment and Development (CCAD), and others to develop a Mesoamerican
Regional Visualization and Monitoring System (known as SERVIR) for the
eight countries that comprise Mesoamerica: Belize, Costa Rica, El
Salvador, Guatemala, Honduras, Mexico, Nicaragua, and Panama. Ecological
forecasting draws on various Earth observation measurements, such as
land cover/land use, precipitation, and topography, while addressing
issues related to transboundary conservation, protected area management,
and marine fisheries. Near-term validation and benchmarking efforts
include data products derived from the Terra, Landsat, and Aqua
satellites. Future missions such as Global Precipitation Measurement
(GPM) and Aquarius will provide precipitation and salinity data of
relevance to this application.

This report also satisfies FY05 IBPD metrics 5ESA6.F (Benchmarking at
least 5 DSSs through Earth system science models) using the Mesoamerican
Climate Modeling System and 5ESA10.B (Benchmark use of Earth science
observations and predictions in two scenario assessment tools) using
TRMM, Terra and Aqua data.

## Introduction to SERVIR

SERVIR[^1] is a decision support system that intensively utilizes
satellite imagery and other data sources for ecological forecasting and
environmental and disaster management in Mesoamerica. It is currently
utilized by scientists, educators, local NGOs and policy makers to
monitor and forecast ecological changes, and respond to disasters such
as forest fires, red tides, tropical storms, and floods. SERVIR also
provides user-friendly, interactive tools geared towards students and
the general public. A SERVIR development and rapid prototyping facility
is located at the NASA Marshall Space Flight Center (MSFC) in
Huntsville, Alabama, and the SERVIR operational facility is based at
CATHALAC[^2] in the City of Knowledge, Republic of Panama. SERVIR is
principally funded through NASA/REASoN and USAID. It is developed in
conjunction with the Central America Commission for Environment and
Development (CCAD) and serves as the regional geospatial node of the
Mesoamerican Environmental Information System (SIAM). Several agencies
and organization provide additional support to SERVIR including Oak
Ridge National Laboratory, Science Systems and Applications, Inc., the
University of Arkansas, and Universities Space Research Association.

> The following are the primary goals of the SERVIR:

-   To develop a SERVIR development and rapid prototyping facility at
    MSFC to benchmark NASA and non-NASA funded application capabilities
    to address environmental management and disaster response in
    Mesoamerica.

-   To have a fully operational and independent SERVIR regional facility
    located in Panama by the end of FY 2008, providing decision supports
    tools, products, and services throughout Mesoamerica.

-   To ensure fully functional SERVIR National Nodes in each Central
    American country which are coordinated with the SERVIR regional
    facility at CATHALAC.

-   To develop a living SERVIR web page to include: 1) a data archive
    and distribution system, 2) online maps via a Web Map Service
    (WMS) 3) thematic decision support tools and 4) 3D visualization
    incorporating items 1-3.

-   To be a model for other regional decision support systems of systems
    around the world and serve as a GEOSS case study for the Americas.

The following are objectives of the SERVIR project

-   To intensively utilize several NASA Earth Science data products,
    technology, and other non-NASA spatial data as inputs to produce new
    value added information products and tools for use by Mesoamerican
    regional decision makers (CCAD and others), government environmental
    ministries and mapping institutes, scientific and educational
    institutions, conservation non-governmental organizations (NGOs),
    and the general public. The SERVIR MesoStor archive and distribution
    system is expandable to meet increasing demand by its end-users, and
    is fully OpenGIS compliant. SERVIR's MesoStor system has been
    operating in beta since October 2004 and operationally since
    February 2005.

-   To provide a baseline interactive map capability of Mesoamerica
    using eighteen (18) regional framework data layers with a resolution
    scale of 1:250,000. These layers are integrated with satellite
    sensors such as Landsat and ASTER. These framework data layers were
    developed under World Bank funding, in conjunction with the CCAD and
    SERVIR.

-   To develop an accurate translation of SERVIR's web pages into the
    Spanish language.

-   To utilize the following data sets and models for decision support
    to detect, determine extent, and make predictions: MODIS data
    products for fire; MODIS and SeaWiFS (based upon availability) data
    products for red tides; GOES data products for hurricanes and
    floods; MODIS products for volcanoes (using in-situ data from the
    USGS); and MM5 and RAMS models for climate variability.

-   To utilize Skyline visualization products (Terra Explorer Pro, Terra
    Builder, and Terra Gate), Google Earth, and NASA's open-source World
    Wind visualization software to incorporate decision support products
    in a 3D environment.

-   To train Central American scientists and researchers to utilize the
    data products and technology of SERVIR enabling them to generate
    their own similar but different projects when new events occur in
    their countries .

-   To leverage the Central American Integration System (SICA) to enable
    many other users to become part of its operations and data
    distribution network. (For example: regional banks, other
    commissions of SICA---such as the sister organization of CCAD which
    addresses agriculture and fisheries (OPESCA); national ministries
    such as ministries of health which address flu outbreaks every March
    & September/October due to the changing seasons, etc.).

-   To serve as a focused information system for Central America.

-   To provide a more level playing field for discussing regional
    environmental and planning issues by acting as an honest information
    broker not as an advocate.

-   To help in the quantification and visualization of the regional
    effects of economic and political activities and human impacts.

-   To develop a Verification & Validation/Benchmark report for three
    SERVIR products (red tides, fires, and climate change), as a joint
    document created by NASA and its Central American partners. This
    report will include the following information: a description of the
    design and implementation process for integrating NASA data products
    into the SERVIR environment; verification that NASA data products
    meet SERVIR's technical requirements; validation that NASA data
    products meet the functional needs of SERVIR's user community;
    methods and metrics used to gauge success; data collection and user
    feedback results; analysis of findings; and lessons learned.
    Quantitative assessments will be emphasized in this report to the
    greatest extent possible. Due to the nature of SERVIR's impact on
    its user community, qualitative assessments will be described when
    quantitative assessments cannot be determined.

## Systems Engineering Approach

This report is based on the systems engineering approach outlined in
Figure 1, which entails evaluation, verification and validation (V&V),
and benchmarking of the SERVIR. In terms of this approach, the purpose
of this report is to 1) document the results of verification and
validation efforts of the SERVIR project to date and 2) employ an
initial benchmarking process to evaluate how SERVIR has been used by the
governments (such as civil protection agencies, NGOs and environmental
ministries) in Mesoamerica and the effect SERVIR has had on their
environmental and disaster management decision making processes.

![](media/image2.jpeg){width="7.05in" height="4.094444444444444in"}

Figure 1. Systems Engineering Approach

## Purpose of this Report

The purpose of this report is to capture, through the application of
system engineering principles, the current status and future course of
SERVIR, and its mainstreaming within environmental and disaster
management decision making processes throughout Mesoamerica. This report
focuses on three SERVIR products: 1) red tides, 2) fires, and 3) climate
modeling.

#  Evaluation Summary of SERVIR

## MODIS SERVIR Red Tide Product

MODIS Ocean Color data sets were selected to produce SERVIR Red Tide
(harmful algal bloom) products for El Salvadoran, Guatemalan, and
Nicaraguan environmental and tourism agencies and private and public
fisheries to meet their requirements for better detection and location
of red tide events off the Pacific coast in these countries. In June
2004, the SERVIR project was contacted by the environmental ministry of
El Salvador, which urgently requested remote sensing imagery of the
location, direction and extent of a red tide event off the coast of El
Salvador and Guatemala. In 2004, the relative locations of red tide
events in these countries were reported orally by fishermen. Such
information was then inserted into their national geographical
information systems which provided limited data to assist these
countries in responding to such events. It was determined that MODIS
Ocean Color data products would enhance this current system by providing
a higher degree of prediction of the location, direction and extent of
red tides in these areas. MODIS Ocean Color data products allow the
detection of chlorophyll a in marine environments with a twice daily
temporal resolution; hence better mitigating cloud cover issues. With
the implementation of the SERVIR Red Tide product, the El Salvadoran and
Guatemalan governments have successfully alerted their tourism and
fishing industries as to the location of red tide events and to where
they may spread. This has enabled these countries to save millions of
dollars for their industries.

The MODIS Ocean Color data used to generate the SERVIR Red Tide products
comes from two satellites: MODIS Aqua and MODIS Terra. At the early
stage of the SERVIR project, only MODIS-Aqua data were used. The data
and the SEADAS processing software were provided by the NASA Ocean Color
group at the NASA Goddard Space Flight Center (GSFC). The SERVIR team
uses software applications to subset the chlorophyll data over the
Central American region and the SEADAS software to generate color images
using the color pallet provided by the Ocean Color Group. SeaDAS is a
comprehensive image analysis package for the processing, display,
analysis, and quality control of ocean color data. It was developed and
released by the GSFC Ocean Color group for processing Level 0, Level 1,
and Level 2 MODIS Aqua/Terra Ocean Color data. The SeaDAS software can
process MOD01 data to produce Level 1A, Level 1B and Level 2 data
products, including "Chlor_a" which is used for creating Red Tide
images.

Since only one Aqua orbit per day covers the Central American region, in
Fall 2004, SERVIR started to provide MODIS Terra data as a supplement to
the MODIS-Aqua data.

The calibration of the MODIS instrument onboard the *Terra* platform has
been unstable over the lifetime of the mission. In February 2004, the
decision was\
made by the GSFC Ocean Color Group to discontinue operational production
of ocean color products from the MODIS-*Terra* and focus efforts on
MODIS-Aqua, which appeared to be behaving in a more stable manner. For
more information, see:
(http://ocforum.gsfc.nasa.gov/forum/topic_show.pl?pid=2280;hlm=adv;hl=terra#pid2280).

Because the MODIS Terra data were not calibrated by the GSFC Ocean Color
Group, the SERVIR team provides a disclaimer indicating that the imagery
should only be used as a qualitative reference, and should not be used
as the base for decision making or scientific research.

## MODIS SERVIR Fire Extent Product

The MODIS SERVIR Fire Extent Product was developed to meet the
requirements of the Guatemalan Park Service and was later extended
throughout Mesoamerica. During 2003, the fire season in Guatemala was
particularly severe (Figure 2), necessitating the need for greater
reporting and evaluation of fire locations and extent in the sparsely
populated northern half of the country. In that year, the Guatemalan
Park Service did not possess the capability to effectively evaluate fire
potential and location because they relied on visual and oral reports.
The Guatemalan Park Service requested the SERVIR project to provide
MODIS fires data sets to significantly enhance their current system in
providing a twice daily mapping capability that had higher temporal and
spatial characteristics. The MODIS data sets were evaluated to see if
they met the technical requirements of the Guatemalan Park Service. It
was determined that the MODIS thermal anomalies data burned into a land
cover map twice daily would enhance the country's ability to identify
and evaluate fire events in a timely and effective manner. This data was
also merged into the Guatemalan Park Service's existing GIS to allow
them to respond and allocate their resources more efficiently to fire
events.

![](media/image3.jpeg){width="4.325694444444444in"
height="5.038194444444445in"}

Figure 2. Fires in Guatemala, Honduras, and Yucatan, Mexico on March 19,
2003 as

detected by MODIS visible and thermal bands.

## SERVIR Mesoamerican Climate Modeling System

Landsat 7 ETM+ and MODIS MOD/12 (land cover) data were selected to
produce more accurate land use/cover maps for input into the MM5 model
(Mesoscale Model version 5). This model is used to develop climate
change scenarios for the Mesoamerican region (which can include, for
example, precipitation, temperature, soil moisture, and vegetation index
measurements). Landsat 7 ETM+ and MODIS MOD/12 data are more accurate
than default, out-of-date USGS data that existed in MM5 prior to 2005.
This higher accuracy data allows MM5 to produce more precise climate
change scenarios resulting in a higher degree of predictability of
climate change in the Mesoamerican region. TRMM data was used to
validate the results of the MM5 model.

In 2001, the countries of Mesoamerica signed CONCAUSA (the Central
American-United States of America Joint Accord) which stipulated climate
change and disaster preparedness as two new areas of cooperation. In
order to pursue the goals of CONCAUSA and to carry out the various
activities envisioned within the framework of this initiative, a plan of
action was established with the goal of strengthening the Central
American countries' capacity to adapt to climate change and to mitigate
greenhouse gas emissions. To facilitate this, the SERVIR project was
requested to provide NASA Landsat and MODIS data sets to improve the
accuracy of the MM5 model, a main product of which is climate change
scenarios. These climate change scenarios are a critical component of
the national communications of all the Central American countries, which
are required under the United Nations Framework Convention on Climate
Change.

#  Design and Implementation 

## SERVIR Design Philosophy

The countries of Central America historically have been faced with
political and institutional challenges---both among and within
countries, that inhibit the free and open distribution of scientific
data and model output for environmental monitoring and disaster
management. This led to a situation where certain institutions acquired
and maintained datasets, but they were often not provided to
institutions which could utilize the datasets effectively. A principal
objective of SERVIR is to level the playing field by making NASA and
other data, as well as model output, freely available and readily
accessible. Prior to SERVIR, data in the region was often provided in
hard copy or via physical digital media (tapes, CD/DVDs). To reach a
larger number of users and potential users, SERVIR offers data and model
output via its website, making information immediately available to
anybody with an Internet connection.

As previously stated, the SERVIR design includes a development and rapid
prototyping regional node at MSFC and an operational regional node at
CATHALAC in Panama. SERVIR also coordinates with its National Nodes in
each Central American country. The purpose of the rapid prototyping node
at MSFC is to develop, explore and test capabilities resulting from
NASA-funded research. Through years of working in Central America, MSFC
researchers are known in the region and can generally function as an
intermediary between national institutions. When capabilities are tested
and determined useful, they are transitioned to the operational regional
node at CATHALAC. CATHALAC is a regional non-governmental institution
and also the UNESCO node for water for Latin America and the Caribbean.
The CATHALAC node then directly interfaces with the national nodes to
ensure the capabilities are integrated within the national system.

The SERVIR regional facility at CATHALAC and the National Nodes in each
Central American country are also sites whereby users can download
information should they need technical assistance in obtaining specific
datasets or model output.

## Processing of SERVIR Input Data Sets

### MODIS SERVIR Red Tide Product

SERVIR has MODIS Aqua Ocean Color data for generating Red Tide images
since June 2004. The GSFC Ocean Color group is responsible for
processing the original satellite data (L0 data) into Level 1A, Level
1B, and finally Level 2 data. This group is also responsible for
calibration and validation of the data. (For details of the MODIS Aqua
data processing, please refer to

<http://oceancolor.gsfc.nasa.gov/DOCS/MODISA_processing.html>.)

The SERVIR team receives MODIS Aqua ocean color data via a subscription
service from oceancolor.gsfc.nasa.gov. The Red Tide images are generated
by extracting chlorophyll information from the data file in the
following steps (Figure 3)

![](media/image4.png){width="4.829861111111111in"
height="4.259722222222222in"}

Figure 3. Steps for generating MODIS Aqua Red Tide Imagery

Extracting cholorphyll and subsetting over Central America is achieved
by using software called "swplatecar", which was provided by the GSFC
Ocean Color Group. The parameter used in extracting cholorphyll is
"chlor_a"; and the subsetting parameters are: North Latitude: 22, South
Latitude: 4, West Longitude: -94, East Longitude: -76.

The output of the "swplatecar" program is an image in PBM format. It is
recommended by the Ocean Color Group that the open source NetPBM
software should be used for further processing. NetPBM is used for image
processing.

#### Adding MODIS Aqua Cloud Cover Data to Red Tide Imagery

The MODIS Aqua Red Tide image shows the chlorophyll concentration in
oceans. This measurement is affected by clouds, as MODIS is a passive
optical sensor. The SERVIR team produces a cloud cover image to
supplement the Red Tide imagery. This gives users the ability to
determine regions where the red tide data are obscured by clouds.

The SERVIR team selected MODIS/Aqua Calibrated Radiances (5-Min L1B
Swath 500m data) for cloud coverage. Each data tile covers exactly the
same area as the Red Tide data. Figure 4 shows the steps for generating
the cloud cover imagery.

![](media/image5.png){width="4.989583333333333in"
height="3.772222222222222in"}

Figure 4. Adding Cloud Cover to Red Tide Imagery

The main step is to generate a high resolution true color image from
MODIS/Aqua L1B 500m data. This is accomplished by using the HDFLook
software. HDFLook is a multifunctional data processing and visualization
tool for MODIS (Radiometric and Geolocation, Atmosphere, Ocean and Land)
data and AIRS L1B data.

After the cloud image is generated, it is overlaid with the Red Tide
image using the NetPBM programs. The final image is transferred into the
SERVIR web server and added into the Red Tide web page.

#### Processing MODIS Terra Data for Red Tides

Because the calibration of the MODIS instrument onboard the *Terra*
platform has been unstable, the GSFC Ocean Color Group does not make
MODIS Terra Ocean Color products. However, they do provide software
(SEADAS) that can be used to process MODIS Terra data. The SERVIR team
began generating Red Tide products with MODIS Terra data even though
these data are not calibrated (Figure 5). The resulting imagery is still
valuable for the fishing industry in Central America since it shows
extent and location of the algae blooms. The actual, non-validated,
color values are ignored. The SERVIR team provides a disclaimer with
this imagery to notify users that these data should not be used for
decision making purposes or scientific research. They are to be used
only as a supplement to MODIS Aqua.

![](media/image6.png){width="4.327083333333333in"
height="5.819444444444445in"}

Figure 5. Creating MODIS Terra Red Tide Imagery from MODIS Terra Data

The MODIS Terra Red Tide imagery is created from MODIS Terra level 0
data (MOD01 data). The GSFC data center provides a daily MOD01 data feed
to the SERVIR ingest server. These data are processed by the SeaDAS
software to create a level 2 Chlor_dataset.

The rest of the processing steps, after Chlor_a data, are similar to the
ones used in the MODIS/Aqua Red Tide imagery processing. The same
"swplatecar" program is used to subset chlor_a data over the Central
American region. The resulting pbm image is converted into a ppm image
and then further converted into a jpg image using the NetPBM program.

#### Adding MODIS Terra Cloud Cover Data onto Red Tide Imagery

This process is similar to that used for adding MODIS Aqua cloud cover
to Aqua Red Tide imagery. The MODIS/Terra calibrated radiances (5-Min
L1B Swath 500m data) are used for cloud coverage determination. The
MODIS Terra cloud image is produced by using HDFLook software. Figure 6
shows the steps involved.

![](media/image7.png){width="6.0in" height="4.029861111111111in"}

Figure 6. Adding MODIS/Terra Cloud Cover onto Terra Red Tide Imagery

### MODIS SERVIR Fire Extent Product

#### Algorithmic Basis for MODIS Rapid Response Fire products

The MODIS Active Fire Products for Mesoamerica are derived from
reflected and emitted radiation received by the MODIS instrument from
the Earth's land surface. The reflected radiation provides a
representation of surface features and is conveyed by the Rapid Response
Corrected Reflectance Product. The emitted radiation provides the fire
detections and is conveyed by the Rapid Response Fire Detection Product.
The two products are described below. Both products are produced in
near-real-time within the Rapid Response system from the MODIS L0 data
stream intercepted at the NOAA "Bent Pipe" Server.

##### Corrected Reflectance Product

The reference imagery product is based on a modified version of the
MOD09 product. The MODIS Corrected Reflectance product (MOD09) includes
the visible and near-infrared bands (1 to 7). This product is described
extensively under <http://LPDAAC.usgs.gov/modis>. This product is of
critical importance, since bands 1 (at 250m) and 4 and 3 (at 500m) are
used for MODIS true-color Rapid Response imagery backdrop.

The transformation from radiance to reflectance is made by calculating
the ratio of the measured at-sensor radiance and the known solar
irradiance at the time of the observation. Onboard calibration devices
provide the solar irradiance information and also allow for correction
of other instrumental errors and artifacts.

The MODIS Rapid Response processing algorithm provides for correction
for molecular (Rayleigh) scattering and gaseous absorption by water
vapor and ozone. There is no real-time input or ancillary data
necessary; the algorithm uses climatological values for gas parameters.
The near-real time MODIS surface reflectance product is similar to MOD09
surface reflectance in clear atmospheric conditions (based on 5S/6S
radiative transfer model), but departs from MOD09 in the presence of
aerosols. In order to preserve the signature of smoke plumes caused by
fires, no aerosol correction is made.

For ease of interpretation, the Rapid Response reflectance product is
depicted as "true-color" imagery. This means that the colors red, green,
and blue as observed by the sensor, in MODIS bands 1 (670 nm), 4 (565
nm), and 3 (479 nm), are depicted in the same colors in the resulting
digital color-composite image. These images are called "true-color" or
"natural color" because this combination of wavelengths is similar to
what the human eye would see. The advantage of this method is that it
produces intuitive, natural-looking images of land surface, oceanic and
atmospheric features. This imagery serves as the backdrop, or reference
image, upon which the fire outlines are "burned-in" as red polygons.

##### Fire Detection Product

Fire detects at 1 km resolution from MODIS are the most important inputs
to the production system. The Rapid Response Fire Detection product is
based entirely on the MOD14 MODIS/Terra Thermal Anomalies/Fire 5-Min L2
Swath 1km product; it is identical to the DAAC product. This product is
described extensively under <http://LPDAAC.usgs.gov/modis>. The fire
detection strategy is based on a combination of absolute detection of
fire size/intensity and on detection relative to the background, to
account for variability of the ambient surface temperature and
reflection by sunlight. The principal inputs to the Enhanced Contextual
Detection Algorithm are the 4- and 11-micrometer brightness
temperatures. There are actually two 4 micrometer channels, a low
saturation channel (band 22 -- 331°K), and a high saturation channel
(band 21 -- 500°K). The low saturation channel (22) is more sensitive to
lower temperatures and is used when possible. When it saturates, the
high saturation channel (21) is used in its place. The 11 micrometer
thermal channel (31) provides additional long wavelength fire
temperature information critical to the calculation (Giglio et al.,
2003).

Additional MODIS channels are further used to condition the data and to
provide numerous tests to identify and reject typical false alarms.
Cloud masking is provided by a combination of bands 31 and 32, while
reflected bands 1, 2, and 7, assist in cloud masking, sun glint, bright
surface, and coastal false alarm detection (Giglio et al., 2003).

Because the Terra MODIS instrument acquires data twice daily (10:30 am
and 10:30 pm), as does the Aqua MODIS (2:30 pm and 2:30 am), four daily
MODIS observations area available to contribute to global fire
monitoring. The MODIS/Terra Thermal Anomalies/Fire 5-Min L2 Swath
product, MOD14, is the most basic data in which active fires and other
thermal anomalies, such as volcanoes, are identified. It is used to
generate all of the higher-level fire products. Note that the MODIS
Rapid Response image products are daytime only.

The sensitivity threshold is quantified as the probability of detection,
which is strongly dependent upon the temperature and area of the fire
being observed. Specifically, the detection of any given fire is
dependent on its magnitude, which is the product of its temperature and
size. The probability of detection is summarized as a detection matrix
(Figure 7), in which the fire temperature and area form the rows and
columns. Hot fires as small as \~10 m in diameter can be readily
detected. Cooler fires of larger sizes, such as \~30 m in diameter, are
likewise readily detected. In any given area, the detection matrix is
related to biome type and characteristics; the detection matrix
displayed in Figure 7 is generalized (Giglio et al., 2003).

![](media/image8.png){width="3.0956692913385826in"
height="2.322047244094488in"}![](media/image9.png){width="2.382677165354331in"
height="0.4807086614173228in"}

Figure 7. MODIS Fire Detection Matrix

The fire detection algorithm used in the MOD14 algorithm in both MODAPS
and Rapid Response is an improved algorithm that offers increased
sensitivity to smaller, cooler fires, as well as a significantly lower
false alarm rate. Performance of both the original and replacement
algorithm has been established using theoretical simulations and ASTER
scenes (Giglio et al., 2003). In general, the new algorithm can detect
fires roughly half the minimum size that could be detected with the
original algorithm while having an overall false alarm rate 10-100 times
smaller. The algorithm performance has been subsequently confirmed by
numerous field validation experiments (see for example Morisette et al.,
2005).

##### SERVIR Rapid Response Tailored Products

The Corrected Reflectance true color image and the Fire Detection
product are used as the primary inputs to the Fire Extent product as
produced in MODIS Rapid Response. The daytime Terra and Aqua MODIS
observations are used to make the morning and afternoon products,
respectively. The outlines of the fires are depicted in red,
superimposed on the true color image. This has the effect of showing the
fire extent, clouds, and smoke.

The L0 data stream upon which the products are based is intercepted at
the NOAA Data server within the Goddard DAAC. The data are then ingested
in the Rapid Response system. The data are processed within the Rapid
Response system into fire products within 3-4 hours after acquisition.
Image subsets with active fire overlay are then generated after a short
time delay (about two hours). Products are projected into a modified
Plate Carree projection. The Plate Carree projection, or Simple
Cylindrical, is a cylindrical projection with the cylinder tangent to
the Earth at the equator. Equally spaced parallel meridians and latitude
lines cross at right angles on a rectangular map. Scale is constant
along any meridian, but varies with latitude along a parallel. To
correct for the north-south distortion, we apply a correction factor
that varies by latitude, such that the modified projection is
quasi-equal-area. For convenience, the coastlines and political
boundaries are fused into each map in blue and the resultant JPEG images
posted to the web <http://rapidfire.sci.gsfc.nasa.gov/servir/>. The
georeferencing information is conveyed in JPEG World Files that may be
downloaded to ease the import of the data into a GIS (instructions are
available in the FAQ section).

It was determined that Mesoamerica was simply too large to convey the
fire locations in adequate detail in a single frame. In response to
this, six subframes were designed to capture the region in greater
detail. They are named Mexico, GuatBelSal, Honduras, Nicaragua, Costa
Rica, and Panama. The subframes are:

•) Mexico

UL 103° W, 23° N

LR 86° W, 14° N

•) GuatBelSal (Guatemala, Belize, El Salvador)

UL 93° W, 19° N

LR 87° W, 13° N

•) Honduras

UL 90° W, 17° N

LR 83° W, 13° N

•) Nicaragua

UL 88° W, 15° N

LR 83° W, 10° N

•) Costa Rica

UL 86° W, 12° N

LR 82° W, 8° N

•) Panama

UL 84° W, 10° N

LR 77° W, 7° N

When a region is selected, the archive of subsets is presented
chronologically as a list of image dates. The most recent images are at
the top of the list. The days are listed in Julian date format. By
clicking on a date, the corresponding Terra and Aqua images are brought
up with annotation in Calendar date as well. Click on More Info to
review the projection details.

These products have been produced since March 1, 2004 for each
Mesoamerican fire season.

### SERVIR Mesoamerican Climate Modeling System

#### Construction of the MM5 modeling system

SERVIR uses the Penn State/NCAR Mesoscale Model version 5 (MM5) for our
work. This is a publicly-available and widely used regional climate
model. The model has been customized for the SERVIR project by allowing
it to be forced with output from a large-scale climate model. In
addition, the capability has been developed to introduce new land use
types based on the Landsat and MODIS work.

The MM5 is a limited-area, nonhydrostatic, terrain-following
sigma-coordinate model designed to simulate or predict mesoscale and
regional-scale atmospheric circulation. It has been developed at Penn
State and NCAR as a community mesoscale model and is continuously being
improved by contributions from users at several universities and
government laboratories. The Fifth-Generation NCAR / Penn State
Mesoscale Model\--MM5\--is the latest in a series that developed from a
mesoscale model used by Anthes at Penn State in the early 1970's. Since
that time, it has undergone many changes designed to broaden its usage.
These include: (i) a multiple-nest capability, (ii) nonhydrostatic
dynamics, which allows the model to be used at a few-kilometer scale,
(iii) multitasking capability on shared- and distributed-memory
machines, (iv) a four-dimensional data-assimilation capability, and (v)
more physics options.

#### Configuration of the MM5 Model at NASA MSFC

We use a nested domain approach for these runs. We set the model
resolution to 36 km for the outer domain and 12 km for the inner domain.
The inner domain (which includes all of Mesoamerica and adjacent oceans
is the one from which we obtain our main results. The outer domain
serves two purposes: 1) It steps the forcing down from the scale of the
global model (approximately 140 km) to the fine resolution of the inner
domain; and 2) it allows for analysis of large-scale effects and
forcings influencing Mesoamerican climate. At this resolution and large
domain, it takes almost two days of wall-clock time to run a single
model month on one of the world's fastest supercomputers at Oak Ridge
National Laboratory. Figure 8 shows the model domains we employed.

![](media/image10.png){width="6.252083333333333in"
height="3.2055555555555557in"}

Figure 8. Model domains employed in MM5 for Mesoamerican Climate
Modeling System

The key task is to evaluate the relative roles on climate change for
Central America of effects such as global warming due to greenhouse gas
emissions and continuing land use changes. For the global warming study,
we used global climate model results from the The Intergovernmental
Panel on Climate Change (IPCC). The IPCC (http://www.ipcc.ch) has
devised a series of global climate model runs starting over the period
of the 20th century (for which observations exist) and then projecting
scenarios of greenhouse gas emissions through the 21st century. These
runs have been repeated several times over the past two decades as
modeling capabilities have improved. The most recent ensemble IPCC runs
were completed in late 2004. We used a business as usual (BAU) scenario,
so as to maximize possible effects due to greenhouse gas-induced
warming. Four years were chosen in conjunction with Central American
partners: 2005; 2010; 2015; 2025; 2050; 2099. 2005 serves as a
'present-day control' and the remaining years project possible
short-term climate changes over the next 20 years. Figure 9 shows
surface temperature and precipitation differences between 2025 and 2005
for the month of September. Changes are fairly small, with conditions
generally warmer and wetter everywhere, except along the Caribbean
coast, which has overall slightly drier conditions.

![](media/image11.png){width="6.129133858267717in"
height="2.4047244094488187in"}![](media/image12.png){width="6.129133858267717in"
height="2.795275590551181in"}

Figure 9. Surface temperature and precipitation differences between 2025
and 2005 for the month of September in Mesoamerica

#  {#section-1 .unnumbered}

# Verification and Validation

## Description of Verification and Validation (V&V) Methods and Results

### MODIS SERVIR Red Tide Product V&V

As stated above, prior to 2004, the El Salvadoran, Guatemalan, and
Nicaraguan governments obtained information on red tides events through
oral reports from their fishing industries and often these reports were
not coordinated between these countries. This resulted in less accurate
estimations of the extent and severity of the red tide event despite the
information being loaded into these countries respective national
geographical information systems. When SERVIR was contacted by the
environmental ministry of El Salvador, it was determined that the best
remote sensing data to fulfill the requirements of this request would be
the use of MODIS Ocean Color data products for the following reasons: 1)
MODIS Ocean Color data sets are high calibrated; 2) they are freely
available; 3) they provide daily coverage which is valuable for cloud
cover issues and tracking daily movements of red tide events; and 4) its
wide area coverage over the Mesoamerican region. Future MODIS Ocean
Color data are refreshed daily on the SERVIR node located at CATHALAC in
the city of Knowledge, Panama. Access to these types of data on a daily
basis allows these countries to quickly divert their fishing industries
away from potential red tide events as well as alert their tourism
industries of the impact of such events. The MODIS Ocean Color data were
verified and validated using ground truth data that were gathered by the
El Salvadoran national node and were found to be 85% accurate in the
central region of the red tide event that occurred during June 4-13,
2004. However, there were only a limited number of points used in the
validation. Moreover, the spatial distribution of the validation points
was biased towards the coast, as these data are easier and less costly
to acquire.

### MODIS SERVIR Fire Extent Product V&V

During 2003, the fire season in Guatemala was particularly severe
necessitating the need for greater reporting and evaluation of fire
locations and extent in the sparsely populated northern half of the
country. Upon request, the SERVIR project selected MODIS data products
for the following reasons: 1) they are highly calibrated; 2) they are
freely available; 3) they provide twice daily coverage; 4) they provide
wide area coverage; and most importantly, 5) they provide the best
thermal anomaly detection of any satellite sensor currently available
which allows for precise location of fire hot spots, intensity and burn
scar progression.

In conjunction with the Guatemala Park Service (CONAP), the MODIS SERVIR
Fire Extent Product was validated and verified in the 2003 fire seasons.
The process involved park employees visiting hot spot locations and
verifying if fire occurred. The process also involved visiting fire
locations and checking if a hotspot was recorded on the MODIS SERVIR
Fire Extent Product. Overall, the fires product performed extremely
well. The most significant problem, however, was false negatives due to
cloud cover. Because MODIS is an optical sensor, it does not penetrate
cloud thick cover. Hence, fires occurring in cloud cover do not show up
in the product. This is mitigated somewhat due to four overpasses per 24
hours with MODIS Terra and Aqua. However, data assimilation from other
sensors such as GOES and AVHRR could prove extremely valuable to
mitigate the problem.

### SERVIR Mesoamerican Climate Modeling System V&V

Prior to 2005, the default USGS data used in the MM5 model were verified
and validated through field campaigns (i.e., ground truthing) across
every Central American country. The results of these field campaigns
determined the USGS data to be approximately 40% accurate for developing
land use/cover maps for the MM5 model. The USGS data also did not
include urban areas for all the Central American countries.

The default land cover map in MM5 for Central America was developed by
USGS using 1976 AVHRR data. This map also lacks utility because it is
outdated. In the 1980's and 1990's, Central America suffered from some
the highest deforestation rates in the world. To provide improved
climate change scenarios for Central America, it is critical to utilize
current land cover maps as inputs to the model. This challenge was
addressed by leveraging the year 2000 Landsat-generated GeoCover LC maps
and country-developed, verified land cover maps for year 2000. Then, the
land cover information was transitioned to years 2003, 2004, and 2005
using MODIS data in an October 2005 SERVIR workshop at the City of
Knowledge, Panama. Details from the workshop can be found at:
<http://servir.nsstc.nasa.gov/workshops>. The countries intend to update
the information for subsequent years using the methodology from the
workshop. Regional land cover data produced from MODIS for 2003, 2004,
2005 and future years is critical because the source data are freely
available and has a frequent revisit time which mitigates cloud cover,
which is most problematic in Nicaragua, Costa Rica, and Panama.
Transitioning to MODIS from higher resolution Landsat facilitates
sustainability for the region so future land cover maps can be produced
annually.

#### Methodology to Transition Landsat to MODIS

An enhanced multi-temporal land cover classification tool was developed
by SERVIR. The tool leverages the flexibility of the C5.0 (RuleQuest
Research) machine learning decision tree classifier through ArcGIS 9x
customization. A baseline year 2000 Landsat 7 ETM+ land cover product
(Geocover LC) and other country-specific ancillary datasets act as
potential C5.0 training sites or as default values (tropical clouds are
a defining challenge in optical remote sensing over Central America).
Continuity of training data for future years is controlled by
semi-automated selection through change/no-change thresholds (i.e.
training data can be reutilized if it is still valid) and expert input
(some new training may be required from year to year to replenish the
training site database). As the pivotal challenge to multi-temporal
change detection in Central America is cloud cover, the tool tracks
information sources and can generate seamless maps using best known data
(e.g. last known class) or maps with some unknown classes. The results
are stored in a relational database such that SQL can be used to query
and produce reports about the output maps. For this specific
application, MODIS scenes and derived products (in particular the MOD09
Surface Reflectance Product and the MOD13 Vegetation Indices Product)
were chosen in order to: 1) minimize the cloud effect by maximizing the
number of passes over the region, especially in summer months; 2) make
use of the extensive processing available from the USGS Land Processes
Distributed Active Archive Center (LP DAAC) to calibrate scene
reflectance across the region and across time; and 3) provide a
low-cost, sustainable source of regional imagery so that information
about land cover age is available in the future.

## Verification and Validation Gaps and Recommendations

The SERVIR project is unique in that it incorporates elements of both an
applications project (NASA funding) and a development project (USAID
funding). It addresses real-world problems and provides real-world
solutions, which generally require quick turn around. Rapid prototyping
of capabilities is critical to meet the demand from the Mesoamerican
stakeholders. Moreover, funds are often limited to develop detailed
field campaigns. The cost of these field campaigns is very expensive due
to limited accessibility in many regions of Central America. As a
result, verification and validation tends to be more qualitative than
quantitative. Qualitative analyses are typically from experts in the
field, local scientists, and environmental authorities, such as a
country's environmental minister.

Although qualitative analyses are useful, and certain quantitative
analyses have been performed, the SERVIR team recommends a standardized
methodology for future product development. This methodology needs to be
both functional and cost effective, and should be developed in
conjunction with our Mesoamerican partners at the National Nodes.
Because SERVIR is the regional node of the Mesoamerican Environmental
Information System (SIAM), we should rely heavily on the National Node
counterparts to provide ongoing V&V and to provide critical feedback to
modify the products as appropriate. This will facilitate the
sustainability of SERVIR and the bi-directional flow of information and
analysis.

#  Benchmarking

## Overview of Benchmark Design

Prior to SERVIR, there were limited capabilities in Mesoamerica to
assess the location and extent of fires and red tides and perform
climate change scenarios based on greenhouse gas increases and forest
cover change. Fires and red tides were often characterized from
irregular and inconsistent ground reports that were sometimes provided
days after the incident. The ground reports also provided limited
knowledge as to the spatial extent of the event. SERVIR has dramatically
changed this situation. For fires and red tides, products are updated
daily. This has led to a paradigm shift in the countries of Mesoamerica.
SERVIR is being mainstreamed by the environmental and disaster response
communities of the region and has become the preferred method to assess
these events. For example, National Node coordinators review fires and
red tides products daily and then inform ground teams as to the location
and extent of an event. This enables the ground teams to respond hours
or days before ground reports might come in. In the event of a
ground-based report, the SERVIR products are frequently consulted prior
to taking action.

## Overview of Benchmark Metrics

Because virtually nothing existed prior to the development of the SERVIR
products, it is challenging to find a gauge to benchmark them. The
principal benchmark metrics we are using include: 1) Feedback from
Mesoamerican scientists, researchers, and environmental authorities
(e.g. environmental ministers of the CCAD); 2) media statistics about
SERVIR; and 3) number of unique web hits for SERVIR products. Regarding
the number of unique web hits, it is important to realize that SERVIR
products are developed for a niche user group and web hits are seemingly
low compared to other NASA web pages. Considering the niche user
community, it is necessary to put web hits into perspective. Web
statistics are gathered using Webalizer and are described in Section 5.3
below.

### SERVIR Feedback

There are numerous examples of SERVIR feedback from scientists,
researchers, environmental authorities, and the general public. Below
are examples that demonstrate the utility of SERVIR products and its
mainstreaming in the region.

The following letter is from Ana Luisa Noguera Morales, the Executive
Secretary (Director) of Guatemala's National Park Service, CONAP. The
original letter, in Spanish, is in Appendix A.

> May 25, 2005
>
> Mr. Daniel Irwin
>
> SERVIR Project
>
> NASA/Marshall Space Flight Center
>
> Huntsville, Alabama, USA
>
> Dear Mr. Irwin
>
> Warmest regards from the Executive Secretary of the National Council
> for Protected Areas, and wishing you much successes in your daily
> activities.
>
> In this manner, and in the name of the National Council for Protected
> Areas of the Government of Guatemala, I want to thank you and the
> SERVIR Project for the information in the framework of your Project
> which has produced continual information for our country, especially
> related to the monitoring of forest fires.
>
> The National Council of Protected Areas\--CONAP\--is the entity within
> the Government in charge of the administration of the National System
> of Protected Areas (SIGAP) and within the responsibilities of this, we
> have been incredibly pleased by the opportunity to utilize relevant
> and timely information to accomplish our activities related to the
> management and control of fires. In addition to the fire hot spots, I
> can assure you that we are currently working to incorporate the
> various products produced by SERVIR within our routine institutional
> decision processes.
>
> We hope that SERVIR will continue for the long term, and for the
> foreseeable future, it will be a basis for much of our work in the
> conservation of Guatemala.
>
> Cordially,
>
> Lic. Ana Luisa Noguera Morales
>
> Executive Secretary - CONAP

The following letter is from Roan McNab, Director of the Wildlife
Conservation Society's Guatemala Program. The original letter, in
Spanish, is in Appendix A.

> May 24, 2005
>
> Daniel E. Irwin
>
> SERVIR Project Manager
>
> NASA/Marshall Space Flight Center
>
> Huntsville, AL
>
> Dear Mr. Irwin
>
> In the name of the program of Wildlife Conservation Society in Peten,
> Guatemala, I want to thank the SERVIR Project that you manage for the
> invaluable assistance that you have provided in the management of our
> forest fire problem in the Maya Biosphere Reserve.
>
> As you are aware, WCS has specific projects where is it necessary to
> carry out activities related to the prevention and control of forest
> fires. For the management of these activities, the information
> provided by SERVIR is fundamental to develop our action plans in the
> field.
>
> I sincerely believe that this project is a substantial contribution to
> the management of natural resources, not only in our project and in
> Guatemala, but for all of Mesoamerica. I therefore look forward to the
> continuity and expansion of SERVIR thematic areas. Again, I reiterate
> my thanks to you and all of the institutions that contribute to
> SERVIR, as well as the persons that are daily involved in SERVIR
> operations.
>
> Roan Balas McNab
>
> Director, WCS Guatemala Program
>
> Flores, Peten

The following is a letter from Erick Mata, Associate Director of Costa
Rica's Institute of Biodiversity (InBio) to Ecological Forecasting
Program Manager, Woody Turner:

> Dear Mr. Turner:
>
> My name is Erick Mata, Associate Director of INBio, the National
> Biodiversity Institute of Costa Rica.
>
> I am writing to let you know about the impact that the SERVIR
> software, and associated data is having in the environmental education
> activities of INBio. Furthermore, I would like to thank your Program
> and Mr. Dan Irwin for his extraordinary collaboration in making a
> dream come true for INBio and for many elementary and high school
> students. In a few words, the result has been that students and the
> general public can "board an aircraft" where they have the experience
> of a virtual fly over Central America, have interactive access to
> information from our biodiversity databases via this interface, and,
> in general, enjoy an innovative educational experience that we hope
> has an important effect in the appreciation of the rich biodiversity
> of this region of the world.
>
> Last year, the CR-USA Foundation (Costa Rica -- U.S.A. Foundation for
> collaboration, http://www.cr-usa.org/english/) funded a very exciting
> environmental education project, which is part of our Bioliteracy
> Program. This project, which we have called Cibercolmenas (Cyber bee
> hives, in English), aims at improving the way Sciences are taught in
> schools, especially, public schools. Although it has several
> components, the flight simulator is one of the key ones. Ten schools
> and ten high schools have been visiting the place where we have built
> the flight simulator and, for 18 months we will follow up on the visit
> through a Virtual Community of Learning Portal that we have set up.
>
> We are very excited about this exhibit because this is only the
> beginning. Thanks to the training that Ronny Hernandez, our multimedia
> specialist, received at NSSTC in NASA's Marshall Space Flight Center
> last April, and the collaboration that Mr. Dan Irwin has been
> providing us, we have been able to integrate information about species
> and ecosystems from the Central American region. This adds
> considerable information and educational value to the flight
> simulation experience. INBio has extensive databases of information
> about the biodiversity of Costa Rica and Central America that now have
> yet another outlet to be presented in a very exciting, user-friendly
> way thanks to the use of this software.
>
> This exhibit was successfully inaugurated last September 31st. The
> event received extensive media coverage, as you can see from the
> attached front page of La Nacion, the most influential newspaper in
> the country (more details can be found at
> http://www.nacion.com/ln_ee/2005/octubre/01/aldea1.html). Almost a
> moth after the inauguration, I am very glad to inform you that it has
> become the major attraction of INBioparque, our thematic park about
> tropical biodiversity,
>
> Once again Mr. Turner, thank you very much for the support that your
> Program has provided us. If you would like to know more about this
> project, please do not hesitate to contact me directly
>
> The following is a letter from Panama's Vice-Minister of the
> Environment following a flood event in Panama to which SERVIR
> responded with satellite-based products, animations, and analysis.
>
> Dear Daniel
>
> In the name of the Government of Panama we want to thank you for the
> GOES images and animations provided to Panama showing the causes of
> the severe flooding that affected our population. These images were
> used by ANAM (the Ministry of the Environment), first by the new
> authorities to understand the phenomena that occurred, and at the same
> time as a justification for the need of a National Meteorological
> Institute that will serve to develop an early alert system for these
> types of events. In this context, yesterday we had conversations with
> the national director of ETESA that will install a
> hydro-meteorological network in Panama to start negotiations so that
> the Meteorological Institute will be under the jurisdiction of the
> Ministry of the Environment in less than six months. We will ensure
> that the new Meteorological Institute will have full coordination with
> the NASA (SERVIR) Regional Node.
>
> Once again, thank you for all your support.
>
> Eduardo Reyes
>
> Vice-Minister of the Environment
>
> Panama.

### SERVIR Media Statistics

In 2005, SERVIR was highlighted in the newspapers in Panama, Guatemala
and Costa Rica. The articles in Panama focused principally on the
dedication of SERVIR in March 2005. The articles in Guatemala focused on
the fires products, and in fact, a MODIS SERVIR Fire Extent Product was
on the front page of Guatemala's national newspaper, *La Prensa Libre*,
in 2005. The articles in Costa Rica focused on the SERVIR educational
outreach we are conducting in that country.

SERVIR also received significant publicity resulting from a NASA public
outreach campaign in conjunction with the SERVIR dedication. On February
14, 2005, the MSFC Public Affairs office reported 28 print stories and
60 Web news stories, including stories in the Los Angeles Times, New
York Newsday, the Washington Post and reprints of the AP Wire story in
numerous U.S. papers, plus newspaper Web sites in Mexico, Guatemala,
Panama, India, Indonesia, Germany, Russia and Great Britain. Federal
News Radio (WFNR-AM) in Washington D.C. ran the story February 4-5 and
posted it on the Web. WAFF-TV in Huntsville aired a brief news report
February 4. All told, the story reached a potential readership in excess
of 5 million households (not counting the potential worldwide Web
audience), delivering an advertising-rate value of nearly \$35,000. Some
342,000 Tennessee Valley households may have seen the TV report, and the
radio story may have reached as many as 606,000 listeners in the D.C.
area.

## SERVIR Products Web Hits

Using the Webalizer Software\--a free web server log file analysis
program available at <http://www.mrunix.net/webalizer/>\--web statistics
were acquired for both the MODIS SERVIR Red Tide Product and the MODIS
SERVIR Fire Extent Product. Web statistics were not collected for the
SERVIR Mesoamerican Climate Modeling System because as of December 2005,
data dissemination for this product was principally through workshops
and coordination with the SERVIR National Nodes. A web debut of the
SERVIR Mesoamerican Climate Modeling System is scheduled for July 2006.

### MODIS SERVIR Red Tide Product Web Hits

Table 1 summarizes the MODIS SERVIR Red Tide Product unique web hits.
The number of hits generally corresponds to actual red tide events in
the region. For example, the MODIS SERVIR Red Tide Product was developed
in response to a request from the Environmental Ministry of El Salvador
to address an actual even in the region in June 2004. In this month,
there were 808 hits. In September 2005, there was another red tide event
in the region, and the number of hits shot up to 1722. The October and
November hits are misleading because of Hurricane Stan in Guatemala and
Hurricane Beta in Nicaragua and Honduras. SERVIR was providing response
mode products for these events and the number of hits for all SERVIR web
pages increased considerably during this time.

Table 1. MODIS SERVIR Red Tide Product Web Hits

  ---------------------------- ------------------------------------------
  **Month/Year**               **Number of Unique Hits**

  November 2005                1362

  October 2005                 5602

  September 2005               1722

  August 2005                  \< 250 (No accurate count)

  July 2005                    328

  June 2005                    255

  May 2005                     \< 500 (No accurate count)

  April 2005                   409

  March 2005                   \< 350 (No accurate count)

  February 2005                \< 400 (No accurate count)

  January 2005                 331

  December 2004                177

  November 2004                370

  October 2004                 624

  September 2004               372

  August 2004                  378

  July 2004                    342

  June 2004                    808 (First month of operation)
  ---------------------------- ------------------------------------------

### MODIS SERVIR Fire Extent Product

Unique webpage hits for the MODIS SERVIR Fire Extent Product were first
captured in March 2004. The product was actually realized in beta in
March 2003 for the intense fire season that year in northern
Mesoamerica. However, web statistics were not acquired until March 2004.
The product is currently being used by environmental ministries,
disaster/civil protection agencies, NGOs, and the science/research
communities. Fire season in Mesoamerica peaks in March and April, as
farmers are employing slash and burn agriculture techniques before the
onset of the May/June rains. The number of unique web hits for both 2004
and 2005 were notably higher in these months as shown in the table
below.

  ---------------------------- ------------------------------------------
  **Month/Year**               **Number of Unique Hits**

  November 2005                173

  October 2005                 234

  September 2005               \< 400 (No accurate data)

  August 2005                  \< 248 (No accurate data)

  July 2005                    \< 265 (No accurate data)

  June 2005                    307

  May 2005                     706

  April 2005                   879

  March 2005                   1050

  February 2005                599

  January 2005                 567

  December 2004                200

  November 2004                271

  October 2004                 295

  September 2004               316

  August 2004                  312

  July 2004                    273

  June 2004                    452

  May 2004                     550

  April 2004                   1375

  March 2004                   54
  ---------------------------- ------------------------------------------

### Mesoamerican Climate Modeling System Findings

Although web statistics were not collected for the Mesoamerican Climate
Modeling System, we have performed a detailed comparison of MM5
'present-day' results to NASA TRMM precipitation products (we developed
a 5 year climatology from TRMM). The model agrees quite well with the
TRMM observations in both spatial pattern and in magnitude of
precipitation. Figure 10 shows modeled precipitation for July 2005 and
average TRMM surface precipitation for July in the years 2000 to 2004.
We have also compared the overall model climate (e.g., temperatures, and
wind speeds) to available station data for Central America, finding
again that, outside of very mountainous regions the model performs quite
well.

![](media/image13.png){width="4.9374015748031495in"
height="2.5700787401574803in"}![](media/image14.wmf){width="4.677165354330708in"
height="2.7681102362204726in"}

Figure 10. Comparison of modeled precipitation and TRMM in Mesoamerica
for the month of July.

### Identification of Useful Decision Support Products for Decision-Makers

As demonstrated above, the three decision support products in this
report: 1) the MODIS SERVIR Red Tide Product, 2) the MODIS SERVIR Fire
Extent Product, and 3) the SERVIR Mesoamerican Climate Modeling System
have been extremely valuable for environmental ministries, disaster and
civil protection agencies, and other key organizations throughout
Mesoamerica. These three products were identified as "high need"
products by the CCAD and USAID when SERVIR was initiated. Now, our
challenge is to integrate these products with other datasets to provide
value added products. For example, fires products could be integrated
with short-term weather prediction products to predict "fire weather"
for several days in advance. Moreover, we are working with the National
Nodes, CCAD, USAID, and other stakeholders to identify and prioritize
other highly useful decision support products for the region. This is a
structured process that is occurring at meetings of the Mesoamerican
Environmental Information System (SIAM).

### Metric of SERVIR Usage

Overall SERVIR Website Unique Visit statistics (Figure 11) were acquired
starting in March 2004. The Spanish language version of the website was
developed in beta in March 2005, and statistics were acquired beginning
in July 2005. With the exception of outlier months, SERVIR usage has
grown steadily. Outlier months include April 2004, February 2005, and
October 2005. Increased activity due to the Mesoamerican fire season
results in the higher usage in April 2004 and February 2005. Website
visits nearly doubled in October 2005 due to Hurricane Stan and the
various products developed by the SERVIR team.

![](media/image15.wmf){width="6.804166666666666in"
height="4.110416666666667in"}

Figure 11. SERVIR website unique visits for English and Spanish site.

### SERVIR Training and Capacity Building

Training and capacity building are critical elements of SERVIR to
develop sustainability in the region. To date, SERVIR has provided five
regional workshops on system usage, land cover and land use change, and
climate modeling. In addition, SERVIR staff at the NASA/MSFC facility
have provided five trainings to SERVIR staff at CATHALAC. Weekly
telecons and daily communication via Skype (audio and video) are also
critical in building a sustainable infrastructure at SERVIR. In 2006,
via USAID funding, SERVIR will be developing the *SERVIR Regional
Training Facility for Strategic Environmental Information.* This
training center will be a fully equipped with hardware and software to
enable scientists and researchers to train directly on the SERVIR
decision support tools, as well as its visualization and monitoring
capabilities, during and beyond the lifetime of the project. This will
further facilitate sustainability of this regional effort. The center
will be available to all SERVIR project participants and collaborators
and can also be utilized by visiting scientists to enable their capacity
building efforts, which are critical to the SERVIR project. This will
ensure longer term sustainability for dissemination and public outreach
efforts and promote the use of information and communication
technologies and knowledge for sound decision making.

### Acceptance of SERVIR by Governments of Central America to Continue Operation Beyond NASA Involvement.

In less than a year and a half after the SERVIR operational system was
dedicated at CATHALAC in Panama, the system is becoming mainstreamed in
the decision making process of Central American countries. For example,
the Guatemalan park service, CONAP, routinely uses SERVIR products for
fire management. The government of El Salvador routinely uses SERVIR
products for red tide/harmful algae bloom monitoring. Moreover, SERVIR
provided time-critical disaster related products after Hurricane Stan in
October 2005. As a result, CATHALAC---where the SERVIR operational
system is located---is becoming a project manager under the United
Nations Charter---Space and Major Disasters. This will position CATHALAC
to access commercial satellite data and provide products should the
charter be enacted over Central America. To ensure a successful
operation beyond NASA involvement, CATHALAC is developing a business
plan. The majority of SERVIR products will be free-of-charge for the
foreseeable future. However, CATHALAC will charge for value-added
products and services to maintain the SERVIR staff and operations.
CATHALAC has also acquired independent funding through a public-private
partnership for 2007-8. It is expected that NASA funding will cease at
the termination of the NASA/REASoN grant in October 2008; however it is
expected that SERVIR will successfully continue its operation for
several more years.

As a result of a successful implementation in Central America, several
countries throughout Latin America (e.g. Colombia, Chile, Argentina)
have expressed a strong interest in an expansion of the SERVIR
geographic domain. This potential expansion is in progress at the
writing of this report.

# Benchmarking Gaps

The benchmarking process for SERVIR products (MODIS SERVIR Red Tide
Product, the MODIS SERVIR Fire Extent Product and the SERVIR
Mesoamerican Climate Modeling System) is challenging in the sense that
almost nothing existed before the project. Therefore, we have had to
rely on metrics such as those described above. It is clear from the
communication and response from environmental authorities and disaster
managers, that SERVIR---in its short existence\--has become mainstreamed
into the decision making process of the CCAD and other organizations in
Mesoamerica. Moreover, the media and web statistics demonstrate that we
have informed a large number of people about SERVIR and that the site is
being utilized. In addition, we have received several high-level
requests to expand the SERVIR domain to the countries of South America
and the Caribbean, and we are exploring these possibilities. We will
continue to work with the National Nodes and SIAM to facilitate a more
robust benchmarking process as SERVIR itself continues to grow.

# Summary and Conclusion

In 2002, prior to the existence of SERVIR, NASA scientists at MSFC
produced fire products manually when they received email or telephone
requests from Mesoamerican collaborators. This process was
labor-intensive, tedious, time consuming and often resulted in major
delays when MSFC scientists were on travel or when request were made
over the weekend. As a result of SERVIR, the current situation is
remarkably different. Now, anybody on the planet with an Internet
connection can access fires, red tides and climate change scenario
information via the SERVIR webpage. These data are being used throughout
Mesoamerica and have been mainstreamed in the environmental management
and disaster support decision making of the region. These three
products, in fact, only represent a subset of resources available
through SERVIR. Additional resources are available under the SERVIR
webpage headings of Mesoamerica Data, Online Maps, Decision Support, and
3D Visualization. By making data freely and openly available, SERVIR has
in effect, leveled the playing field. Spatial datasets and satellite
imagery that were---only a few years ago---available to limited
individuals and organizations, are now in the hands of many. In doing
so, SERVIR is also demonstrating the potential for multinational
environmental management at a regional scale. Furthermore, SERVIR has
created a new model whereby NASA is partnering with critical development
agencies such as USAID and the World Bank. In the case of SERVIR, NASA
is developing the capability, and through development agencies, handing
it off to operational entities such as CATHALAC and the CCAD.

Since 2003, over sixty countries, the European Commission and more than
40 international organizations have joined forces to support the
development of a Global Earth Observation System of Systems (GEOSS)
that, over the next decade, will revolutionize the understanding of
Earth and how it works. SERVIR currently represents the leading GEOSS
case study in the Americas and is staged to function as a GEOSS template
for other parts of the world.

#  References

Giglio, L., Descloitres, J., Justice, C.O., and Kaufman, Y., 2003, An
Enhanced Contextual Fire Detection Algorithm for MODIS, Remote Sensing
of the Environment, v. 87, pp. 273-282.

Morisette, J., Gilio, L., Csiszar, I., and Justice, C.O., 2005,
Validation of the MODIS active fire product over Southern Africa with
ASTER data, International Journal of Remote Sensing, v. 26, pp.
4239-4264.

Appendix A.

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height="7.792361111111111in"}

![](media/image17.jpeg){width="6.795833333333333in" height="8.83125in"}

[^1]: SERVIR is derived from the Spanish name of the capability: Sistema
    Regional de Visualizacion y Monitoreo. SERVIR is also a Spanish verb
    meaning "to serve" or "to be useful". This is precisely the intent
    of this project -- both in terms of information and access to data.

[^2]: CATHALAC is the Water Center for the Humid Tropics of Latin
    America and the Caribbean.