# [Southern Africa Validation of EOS (SAVE)]{.underline}

**Implementation Plan**

### Jeffrey L. Privette, PI

The document contains the implementation plan for SAVE, a
multidisciplinary project designed to validate operational and
experimental products from Terra---the flagship satellite platform of
NASA\'s Earth Observing System (EOS). The plan includes SAVE\'s goals,
background, schedule, personnel and outlines of activities and
procedures. It is written at sufficiently general level such that it
should be accessible to project participants as well as non-scientists.

**1.0 Goals**

The prioritized goals of SAVE are:

1)  Validate EOS Terra's *LAI\*, FPAR, albedo, VI, % woody cover, ozone*
    *and aerosol products* over key biomes (*primary products*)

2)  Validate Terra's *1b radiance, surface reflectance, LC, LCC, fires,
    burn scar, surface temperature, BRDF, NPP* (*secondary products*)

3)  Improve methods to measure and scale field data over discontinuous
    canopies

4)  Support parameterization and validation of ecosystem & SVAT models

5)  Improve methods to remotely quantify fire fuel load (emphasis on
    litter accumulation and understory LAI) and combustion completeness

6)  Determine primary spatial/temporal aerosol sources and deposition
    specifications

7)  Validate products of AVHRR, Landsat 7, EO-1, IKONOS and Data
    Assimilation

> Office (DAO).

\* See Appendix VI for List of Acronyms.

*Research must be published in peer-reviewed journals to be of use to
the science community.*

**2.0 Background**

SAVE is a 3-year project (FY98 through FY00) funded by the EOS
Validation Program Office (D. Starr, Project Scientist) in response to
NASA NRA97-MTPE-03 (Type II). A fourth year (FY01) may be funded due to
delays in Terra's launch. The primary aim of SAVE is to validate
Terra\'s atmospheric and land products in association with the Terra
instrument teams, particularly MODLAND, by augmenting and leveraging off
existing scientific capacity and programs in southern Africa (e.g.,
SAFARI 2000). Atmospheric measurements are largely limited to aerosol
distribution and source attribution, and ozone profiles. Land
measurements include nearly all products from MODLAND, ASTER and MISR.
We prioritized the products as those which SAVE independently validates
(primary products), and those which SAVE validates in collaboration with
others (secondary products).

The geographical distribution of SAVE atmospheric measurement sites is
roughly circular, corresponding to the circumference of the atmospheric
high-pressure system frequently overlying the region. The distribution
of land measurements is transect-oriented, roughly covering the
north-south precipitation gradient along the IGBP Kalahari Transect and
the east-west soil gradient of the miombo woodlands. There are several
other sites outside these transects.

The proposing SAVE team included:

PRINCIPAL INVESTIGATOR: Jeffrey L. Privette NASA's GSFC (land lead)

CO-PRINCIPAL INVESTIGATORS: Anne Thompson NASA's GSFC (ozone lead)

Steve Prince Univ. of Maryland

Robert Scholes CSIR/Forestek (in-country lead)

CO- INVESTIGATORS: Robert Swap Univ. of Virginia (aerosol lead)

Niall Hanan Colorado State Univ. (flux lead)

Peter Dowty Univ. of Virginia

PRIMARY COLLABORATORS: Marc Leroy CNES/CESBIO

Paul V. Desanker Univ. of Virginia (miombo lead)

Peter G. H. Frost Univ. of Zimbabwe

After the proposal stage, many additional scientists began collaborating
with SAVE.

**3.0 Relationship to SAFARI-2000**

As a funded, regional project, SAVE was a catalyst for moving SAFARI
2000 from concept to implementation stage. SAFARI is an organizational
umbrella under which scientists can coordinate independent activities in
southern Africa (SAFARI's Science Plan is available from
http://safari.gecp.virginia.edu). SAVE investigators helped initiate
SAFARI and currently serve in its management structure. SAFARI is
nominally a three-year activity, with four Intensive Field Campaigns
(IFCs) as shown in Table 1. The most extensive of these is the Aug/Sept
'00 campaign, in which NASA aircraft with Terra instrument simulators
will be deployed in the region. SAVE will participate in each of these,
but will emphasize the wet season (peak biomass) campaigns.

Table 1. SAFARI Intensive Field Campaigns (IFCs)

+-------------------+-----+--------------------------------------------+
| > **Period**      | > * | > **Primary Goal**                         |
|                   | *Se |                                            |
|                   | aso |                                            |
|                   | n** |                                            |
+-------------------+-----+--------------------------------------------+
| >                 | >   | > Air and ground characterisation of Mongu |
| August-September, | dry | > and Skukuza field sites; instrument      |
| > 1999            |     | > shipping and deployment in region.       |
+-------------------+-----+--------------------------------------------+
| > February-March, | >   | > Characterisation of vegetation           |
| > 2000            | wet | > structure, optics, and functioning at    |
|                   |     | > peak biomass along Kalahari Transect     |
|                   |     | > (precipitation gradient).                |
+-------------------+-----+--------------------------------------------+
| >                 | >   | > Assess dynamics of dry-season emissions  |
| August-September, | dry | > from biomass burning and other sources;  |
| > 2000            |     | > Fire fuel load and remote sensing        |
|                   |     | > relationships; Major airborne            |
|                   |     | > activities.                              |
+-------------------+-----+--------------------------------------------+
| > December, 2000  | >   | > Characterisation of vegetation structure |
|                   | wet | > and optics at peak biomass over Miombo   |
|                   |     | > transect (soil gradient).                |
+-------------------+-----+--------------------------------------------+

During the first international SAFARI workshop (July, '98), participants
identified a set of "Test Sites" which would serve as foci for
measurements and modeling (see Figure 1). This strategy aims to minimize
redundant and fractionated efforts, and encourage cost sharing and
activity synergy. For example, high-resolution satellite imagery
(Landsat, ASTER) will be acquired most frequently over these sites.
Thus, most SAVE activities occur at these sites. Two of the Test Sites,
Skukuza, South Africa and Mongu, Zambia, are also EOS Land Validation
Core Sites. The latter include 24 field sites around the world
designated for more intensive and sustained validation of NASA satellite
products. Thus, SAVE and SAFARI are linked with global land measurement
programs.

SAVE presently is one of only two SAFARI projects dedicated to Terra
validation (the other is a fire validation effort led by Wei Min Hao,
http:www.xmission.com/\~rmrs/staffs/labs/missifsl/ifsl_int4404.html),
although some EOS instrument teams plan to participate in some IFCs.
SAVE coordinates satellite data acquisitions in the region on behalf of
SAFARI.

![](media/image1.pct){width="4.055555555555555in"
height="4.596527777777778in"}

**Figure 1**. SAFARI-2000 Test Sites (large dots) and the distribution
of Kalahari sandy soils with isohyets of mean annual precipitation
(millimeters). The EOS Land Validation Core Sites in Mongu, Zambia and
Skukuza, S.Africa, are the solid black dots. The IGBP Kalahari Transect
is outlined with a blue rectangle, and the Miombo woodlands transect is
outlined with a red rectangle.

**4.0 General Approach**

SAVE resources are allocated according to test site capacity, spatial
representativeness, and biogeochemical importance. The priority
landcovers include Kalahari woodland, *acacia*/*combretum* woodland
savanna, dry miombo, wet miombo, mopane woodland, desert
grassland/shrubland, and wetland.

The specific site emphases are as follows. SAVE is conducting intensive
measurements at the two Core test sites, Skukuza, South Africa
(*acacia*/*combretum* woodland savanna) and Mongu, Zambia (Kalahari
woodland), and has constructed an above-canopy tower (climb-up) at each.
Upward and downward looking radiation sensors will be deployed on the
towers in early 2000. Eddy covariance systems, include infrared gas
analyzers for CO2 flux measurement, were proposed independently. The
Skukuza flux system was funded and will be deployed in Jan'00. A
decision on the Mongu flux proposal has not been made, however at least
a temporary flux system will be deployed for IFC2 (wet season).

Ground transect measurements are made around each tower over flagged
grids (see Figure 2). Moreover, SAVE will fly a light aircraft over the
towers and surrounding area (to roughly 20 km x 20 km). The aircraft
will be equipped with a 3-band (blue, red and NIR) CCD imager, whose
data will be used to extrapolate tower and transect measurements. ASTER,
Landsat 7, IKONOS and possibly EO-1 data are acquired for this purpose
as well. The ground and aircraft measurements occur continuously or
periodically, as appropriate. Measurements of non-EOS products,
including auxiliary parameters required for validation of the LAI/FPAR
algorithms (see Appendix IV), are measured during the IFCs only.

SAVE is conducting less intensive measurements at Etosha National Park,
Namibia (desert sands/grassland, Namibia), Tshane, Botswana (desert
shrubland/savanna), Kasungu, Malawi (dry miombo), and Nampula,
Mozambique (wet miombo). SAVE land measurement are also being conducted
at some transect sites during the IFCs (e.g., Bokspit, Kasane and Okwa
River Crossing, Botswana).

SAVE has located aerosol instrumentation around the atmospheric gyre at
sites chosen to maximize differences in the aerosol regimes (e.g.,
industrial, dust, biomass burning, etc.). Key instruments include
sunphotometers and aerosol streaker samplers, complimented with various
airborne sensors during IFCs. Ozonesonde releases will occur in Zambia
during IFCs and South Africa periodically. Regular satellite data
collection will also occur at these sites.

**4.1 Intensive Field Campaigns**

SAVE will have a unique emphasis during each IFC, including IFC1:
Deployment of initial instrumentation and initial ground and atmosphere
characterizations of Skukuza and Mongu; IFC2: Characterization of canopy
structural and optical properties over Kalahari Transect; IFC3:
Characterization of aerosol distribution and properties, fire and scar
assessment, and BRDF/albedo of northern test sites; IFC4:
Characterization of canopy structural and optical properties over Miombo
transect.

Activities during IFC2 and IFC4 will occur via traveling caravans
composed of SAFARI investigators and local students. For example, the
Kalahari Transect caravan (IFC2) will include \~30 investigators
assembling in Mongu. There, investigators will characterize the field
site over a 4-day period, then travel south to the next site to repeat
the procedure (see Figure 3). The caravan will terminate at Bokspit,
Botswana. This intensive approach allows relatively large areas to be
intensively measured in a synoptic time frame. It overlaps existing test
sites such that the episodic campaign measurements can be assessed in
the context of the continuous test site measurements.

![](media/image1.pct){width="4.055555555555555in"
height="4.596527777777778in"}

> **Figure 3**. Field sites to be characterized during the SAFARI 2000
> IFC2 (Feb/March '00). Green dots represent Test Sites, black dots
> represent Core Test Sites, and red dots represent auxiliary transect
> sites. From south-to-north, these sites include: Bokspit, Tshane, Okwa
> River Crossing, Maun, Kasane, Senanga, and Mongu. The IGBP Kalahari
> Transect is outlined with a blue rectangle.

During the dry season IFCs, extensive aerosol and trace gas data will be
collected both remotely and in situ by several aircraft flown via SAFARI
2000. These data will be combined with SAVE atmospheric data for more
rigorous validation of the MODIS, MISR and MOPITT aerosol and trace gas
products. In addition, SAVE will team with the SHADOZ project (A.
Thompson, PI) to release ozonesondes from South Africa and Zambia.

**4.2 Modeling**

Although SAVE's primary purpose is to validate Terra's products, the
team is acquiring data required for modeling such that EOS model-based
products (e.g., NPP) can be validated as time and resources permit. SAVE
collaborates primarily with three process modeling studies: 1) an
integrated 1-D trace gas and energy flux ecosystem model (Gu, UVA),
developed for a boreal forest, is being modified to simulate the Mongu
woodland site; 2) a phenological/structural dynamics model of NPP is
being developed and tested at SAVE sites for fire fuel and NPP
simulation (Dowty, UVA), a coarse-scale SVAT model (SiB2) is being tuned
to simulate southern African systems, and its hydrological and radiative
energy subsystems will be validated (Pinheiro, GSFC). In addition, a gap
model for savannas is planned and will be related to land cover/use and
climate trends (Caylor, UVA). SAVE works with these groups to ensure
proper measurements (equipment, temporal and spatial resolutions) are
obtained for model inputs, constraints and validation.

**5.0 Schedule of Activities**

  ----------------------- ---------- --- --- --- --- --- --- --- --- --- --- --- ---------- --- --- --- --- --- --- --- --- --- --- --- ---
  **ACTIVITIES**          **1999**                                               **2000**                                               

                          J          F   M   A   M   J   J   A   S   O   N   D              J   F   M   A   M   J   J   A   S   O   N   D

  Terra/Aqua launches                                                                                                                   

  Skukuza tower                                                                                                                         
  installation                                                                                                                          

  Mongu tower                                                                                                                           
  installation                                                                                                                          

  Pilot field campaign                                                                                                                  

  Intensive field                                            1   1                              2   2                   3   3           4
  campaign (IFC)                                                                                                                        

  **Ground/Aircraft                                                                                                                     
  Data**                                                                                                                                

  Core Site tower                                                                                                                       
  operations                                                                                                                            

  Core Site ground                                                                                                                      
  transects                                                                                                                             

  Core Site aircraft                                                                                                                    
  transects                                                                                                                             

  Core Site auxiliary                                                                                                                   
  properties                                                                                                                            

  Auxiliary site                                                                                                                        
  atmosphere data                                                                                                                       

  Auxiliary site ground                                                                                                                 
  transects                                                                                                                             

  Ozonesonde releases                                                                                                                   

  **Remote Sensing Data**                                                                                                               

  AVHRR 1 km products                                                                                                                   

  Landsat 7 images                                                                                                                      

  ASTER images                                                                                                                          

  MODIS/MISR/MOPITT/\                                                                                                                   
  CERES products                                                                                                                        

  IKONOS images                                                                                                                         

  **Analysis/Modeling**                                                                                                                 

  Primary product                                                                                                                       
  analysis                                                                                                                              

  Secondary product                                                                                                                     
  analysis                                                                                                                              

  1-D flux modeling (Gu)                                                                                                                

  3-D flux modeling                                                                                                                     
  (Dowty, Pinheiro)                                                                                                                     
  ----------------------- ---------- --- --- --- --- --- --- --- --- --- --- --- ---------- --- --- --- --- --- --- --- --- --- --- --- ---

**6.0 Ground Rules for Use of SAVE-funded Resources/Results**

1.  All publications, presentations, and other reports describing SAVE
    activities/results must acknowledge SAVE.

2.  Significant use of SAVE resources, including data, equipment and/or
    personnel, should result in an offer of coauthorship to one or more
    of the SAVE investigators.

3.  All SAVE data will be publicly available within 6 months of
    acquisition as required under EOS program rules. However, users of
    SAVE data and resources should notify J. Privette of the intended
    use.

**Appendix I. Investigator Roles and Activities**

[Proposing Investigators]{.underline}

• Privette assumes overall responsibility for the project. He deploys
the ground instruments and guides the sampling design. He conducts
measurements of auxiliary parameters (non-EOS products) during the IFCs
and leads development of the Africa MQUALs (without an Exotech profile
radiometer). He will oversee comparisons of field and EOS products, and
collaborate on modeling activities. He also serves on the SAFARI
Steering Committee.

• Swap is responsible for the aerosol components, specifically the
deployment and maintenance of the streaker and sunphotometer equipment.
He conducts equipment procurement, MOUs, SAVE/SAFARI-2000 integration,
subcontracts (including those associated with the light aircraft
program) and student worker oversight (via UVA). He will conduct
comparisons of field vs. EOS aerosol products and ensure inputs for
atmospheric models are developed. He will assist in the atmospheric
chemistry and aerosol measurements obtained by aircraft during the IFCs
to the extent that this serves SAVE (re. MOPITT val). He also serves on
the SAFARI Steering Committee.

• Scholes has overall responsibility for the Skukuza site and relations
with the S. Africa Parks Board. He supplies historical data, and
provides technical backstopping and guidance. He will also conduct eddy
covariance+CO2 measurements at Skukuza (with Hanan). He is the PI of the
LEAD project (regional study of nitrogen and sulphur deposition), which
he is integrating with SAVE and in which he is focusing on vegetation
structure variability. He also serves on the SAFARI Steering Committee.

• Prince will provide guidance on the light aircraft sampling approach,
and may provide additional assistance and site coverage through his
funded Miombo LCLUC work, particularly around Chunga/Kafue National Park
(dry miombo, Zambia).

• Thompson provides overall guidance on atmospheric chemistry and
aerosol sampling. She is PI of SHADOZ (a global tropical ozonesonde
release program), and will organize the sonde deployments during the '00
IFCs. For SAVE, she is emphasizing Mongu, Skukuza and S. Africa. She
will compare retrieved tropospheric ozone from the sondes and TOVS data.
She is primary liaison to the MOPITT team.

• Desanker leads with Miombo Network and its relationship to SAVE. He
will help guide Landsat 7, ASTER and IKONOS acquisition decisions, and
identify subcontracted personnel for the Kasungu site.

• Frost will primarily act as a technical advisor to SAVE, particularly
on fires and LCLUC.

• Hanan is conducting eddy covariance flux measurements at Skukuza
(funding: NASA TEP, with Scholes), and will assist with additional field
measurements (temporal, spatial resolutions, equipment, parameters) as
required for SiB2 modeling. He will assist Pinheiro with SiB2 model runs
in '00 and '01.

• Leroy\'s and Roujean\'s activities are to be determined pending
funding from EU. Potential contributions include deployment of a dense
PAR sampling array and acquisition of fine resolution canopy structure
measurements and modeling (extinction-based) at Mongu. They will assist
in acquiring data from EU-funded satellite missions for the region
(e.g., POLDER, MERIS, CHRIS, and SEVERI).

[Subcontracted Investigators]{.underline}

*UVA*

• Gu guides the collection of ground data required for his 1-D BGC
model. He is modifying a 1-D boreal system model to simulate savanna
woodland systems, and running the model to estimate C (primary
variable), H20 vapor, sensible heat and net radiation fluxes. His
emphasis is on understanding the effects of aerosol-influenced
diffuse/direct radiation on NPP for improved dynamic estimates of
epsilon via remote sensing. He is focusing on the Mongu site.

• Dowty provides guidance on the vegetation structure sampling, and
assists in ground data collection (basal area, grass biomass and % woody
cover, possibly leaf and soil fluxes \[short term\]), analysis and
phenological model runs. In contrast to Gu's modeling, Dowty emphasizes
spatial (3D) modeling, and is developing maps of fire fuel load and NPP
(including comparisons with MODIS NPP). He is particularly concerned
with effects of soil moisture on NPP. He is using field LAI to validate
predicted leaf phenology curves (LAI and leaf reflectance maps).

• Caylor (UVA PhD Student) is developing methods for estimating
historical (past 30 years) and current % woody cover, LAI, inter-tree
distance and crown size from various data sets (Dig. Photography,
DISP/CORONA, IKONOS, TM, AVHRR). This information is used to develop and
validate a savanna structural dynamics model, and will be related to
trends in land cover use and disturbance. He will validate the MODIS
continuous field products with Hansen and Privette. He is coleader of
the IFC2 field data collection.

• Regional PhD Student (TBD). Student will oversee ground data
collection operations, including collection of data, guidance to others
collecting data, data reduction, QA, formatting, transmission to U.S.
archive, and field vs. EOS product comparisons.

[Collaborating or Associated Investigators]{.underline}

*European*

• Roberts (Univ. Coll., London) is developing methods for relating BRDF
parameter temporal trajectories with LC types and subpixel mixtures.
They are conducting gridded structural (LAI, % cover, perhaps albedo and
spectra) sampling at Mongu with LAI-2000s and hemispherical photography.
They will validate MODIS BRDF/albedo through empirical relations to
aircraft digital photography, and then scaling. They may use AVHRR and
SPOT VEGETATION.

*U.S.*

• Holben/AERONET (GSFC) provides calibration and major maintenance of
CIMEL sunphotometers, as well as data ingest, processing, QA, WWW
posting and archiving. Holben also supplies the downwelling PAR sensors
for the tower sites. Mukulabai (Muke) is in charge of the Mongu
sunphotometer, Bengis (Bibi) is in charge of the Skukuza sunphotometer.

• Morisette (UMD) is responsible for ordering and disseminating of
SAFARI Test Site satellite data, including IKONOS, ASTER, L7, MISR,
MODIS and MOPITT. He also assists Hom with MQUALS integration and
support, and is providing LC analysis of digital photography and Landsat
7 imagery (semivariograms).

• Hansen (UMD) is the liaison with the MODLAND/UMD LC and LCCC effort,
particularly the continuous fields (e.g., % cover fraction).

• Roy, Giglio (GSFC) and Justice are liaisons with the fire and burn
scar validation.

• Tucker and Kendall are providing rapid browse-quality AVHRR images
during the IFCs. Further, they will provide the appended list of AVHRR 1
km calibrated products (as funded by EOS Validation Program/D. Starr \--
see Appendix V).

• Shu (NASA's GSFC Code 553), La and Babu are developing a transect NDVI
sensor for vegetation assessment on ground transects. The instrument
looks both up and down, and samples at 100 Hz. Campbell 21X data loggers
from Code 923 will be used with these. Shu is also developing the "next
generation" sunphotometer in association with AERONET and Privette.

• Hom (NASA's GSFC Code 923) provides MQUALS integration, transect NDVI
sensor, and general technical support. He is working in collaboration
with Morisette and Huete/Univ. of Arizona.

• Pinheiro (NASA's GSFC Code 923/New Univ. of Lisbon, Portugal) leads
soil moisture, temperature and characterization activities. She will
parameterize and validate SiB2 for the region.

• Albertson and Scanlon (UVA) are deploying and a CO2/eddy covariance
system on the Mongu tower, and will deploy a mobile flux system at each
site during IFC transects.

• Myneni (Boston Univ.) is conducting canopy optical and structural
characterizations during IFC2 as part of his PI activities for MODIS and
MISR LAI/FPAR products.

*Regional*

• Annegarn (WITS) manages the WITS subcontract and provides PIXE
analysis for aerosol streaker sample data.

• Piketh (WITS) conducts atmospheric modeling and incorporate SAVE data.
He is in charge of the Ben MacDhui site and equipment, and is lead
investigator for ARREX.

• Eckhardt (Skukuza, Kruger National Park) is analyzing historical
ground-based, Landsat and light aircraft imagery to quantify fractional
woody landcover, and landcover change. Other KNP staff supporting SAVE
include Harry Biggs and Nick Zambatis.

• Otter (CSIR) provides logistical, shipping and technical assistance,
and provides soil characterization via her LEAD work in association with
Pinheiro.

• Mukulabai (Muke), Bengis (Bibi), Lucio (Filipe), and Versfeld
(Wilferd) are on-site technicians at Mongu, Skukuza, Mozambique and
Etosha NP, respectively.

**Appendix II. Measurement and Research Activity Notes**

[LAI, FPAR, % woody cover (Privette, Caylor, Hansen, Scholes)
*Primary.*]{.underline}

1.  For each site, develop relationships (regressions) between overstory
    (crown) LAI/FPAR and crown transmission.

    a.  LAI/FPAR: destructive measurements, models, leaf fall and
        ceptometer/TRAC/LAI 2000 measurements

    b.  transmission: calibrated ASD FR spectrometer and portable NDVI
        meter

2.  Develop relationships (regressions) between understory (grass)
    LAI/FPAR and NDVI (both between crown and under crown).

    a.  LAI/FPAR: destructive and LAI-2000 measurements

    b.  NDVI: calibrated ASD FR spectrometer and portable NDVI meter, at
        Terra overpass time.

3.  Using portable NDVI meter (up and down looking), carry along ground
    transects (Figure 2) to sample overstory gap fraction and light
    transmission, and understory NDVI variation. With relationships from
    Tasks 1 and 2, estimate total LAI/FPAR and % cover relationships.

    a.  sensor being developed by Shu (GSFC), integrated with 21X

    b.  biweekly, possibly daily during leaf out and leaf fall (for
        Dowty)

4.  Conduct light aircraft transects and extrapolation region flights
    with 3-band aerial photography. Calibrated with ground % cover data
    on transects, then use relationships from 3 to estimate total
    LAI/FPAR. Develop NDVI vs. total LAI/FPAR relationship for imagery.

5.  Using ASTER and Landsat 7 data, correlate total LAI/FPAR with NDVI
    and extrapolate over full scene.

6.  Compare ASTER and L7 estimates of total LAI/FPAR with MODLAND
    LAI/FPAR

7.  Strong algorithm collaboration with Myneni/BU LAI/FPAR team.

[VI (Privette) *Primary.*]{.underline}

1.  On light aircraft transects, continuously sample canopy with ASD
    spectrometer. Calibrate with panel on ground. Conduct sampling at
    Terra overpass time

    a.  IFC activity only

2.  Convolve MODIS spectral sensitivity functions for bands 1-5 with ASD
    data, and estimate MODIS spectral response.

3.  Derive relationship between light aircraft 3-band image data and
    estimated MODIS responses as a function of % cover and LC type (%
    cover from above).

4.  Using results from 3, develop a 20 x 20 km\^2 estimate of the MODIS
    VI response.

5.  Repeat 2-4 for ASTER and L7.

6.  Compare MODLAND VI product with estimated (nadir) values from fine
    resolution data.

[Albedo/BRDF (Privette, MODIS and MISR instrument teams).
*Primary/Secondary.*]{.underline}

*Note: the most meaningful BRDF evaluation will occur during IFC 3 when
CAR, AirMISR and PARABOLA III data are available. Poorer quality BRDF
evaluation is possible before that time. Shortwave albedo evaluations
should be of reasonable quality throughout. Below outlines a possible
method.*

1.  Co-locate the light aircraft albedometer on the tower with the
    continuous albedometers. Cross-calibrate.

2.  Overfly the tower and transects with the light aircraft carrying the
    albedometer (dual CM21 pyranometers, full range).

    a.  Conduct flight at Terra overpass time.

3.  Assess relationship between transect albedo and % woody cover and
    NDVI.

4.  If relationships exist for 3, develop map based on aircraft, ASTER
    and L7 NDVI. If relationships do not exist, grid aircraft data
    (optimal interpolation?) to MODLAND albedo grid.

5.  Compare field albedo from 3 or 4 above with MODLAND albedo product.

6.  Roberts compare temporal trajectories from kernel-based models with
    LC structure. Parameterize BRDF model (shadow-based, such as
    Myneni's or DART) using ancillary data (see Appendix).

7.  Compare model-predicted albedo and BRDF at tower with measurements.
    If reasonable relationship is found in 6, develop gridded BRDF and
    albedo maps from %cover, NDVI etc. data with BRDF model.

8.  Compare model-generated BRDF and albedo with MODLAND BRDF and albedo
    products.

9.  Compare "SZA-extrapolated" albedo. Fit BRDF model with AMBRALS, and
    compare retrieved parameters in MODLAND product.

10\. MISR team will deploy PARABOLA III at Etosha in IFC3.

[Surface temperature (Pinheiro, Hanan, Privette)
*Secondary*]{.underline}

1.  Deploy endmember-targeted radiometers on towers at Skukuza

2.  Assess effects of slope, aspect, crown, grass, and shading on
    effective surface temperature

3.  Compare with aircraft-based TIR measurements

4.  Scale with ASTER and compare to MODIS land temperatures

[Aerosols (Swap, Piketh, Holben/AERONET, Mukulabai)
*Primary*]{.underline}

1.  Deploy sunphotometers at Mongu, Skukuza and Etosha National Park.

2.  Streaker samplers modified for field use and deployed alongside
    sunphotometers

3.  Compare retrieved optical depths with MODIS and MISR values

4.  Compare aerosol size and source attributions with standard
    assumptions in MODIS and MISR algorithm

5.  Develop spatial variability and trend information for
    interpolation/extrapolation

[Land Cover Land Use Change (Desanker, Hansen, Morisette)
*Secondary*]{.underline}

1.  Build a fine resolution database using aerial photos, with % woody
    cover and other parameters, at sample grids across TM scenes

    a.  emphasizes Mongu, Skukuza; possible also Kasungu

    b.  may include deployment of a weather station and soil moisture
        probes at Kasungu

    c.  possibly include overstory fractional cover and understory NDVI
        transect measurements or IKONOS

2.  Comparisons to MODIS LC and LCCC and continuous parameters
    (DeFries/Hansen) products.

[Fire and burn scar (below provided by Justice, Roy, Giglio)
*Secondary*]{.underline}

1.  Validate MODIS active fire product:

    a.  opportunistic comparison of MODIS data with airborne remotely
        sensed data captured as part of other SAFARI worker\'s
        activities

    b.  examination of MODIS data at prescribed burns around Mongu and
        Skukuza (TBD)

    c.  comparison of MODIS data with L7, ASTER and the prototype MODIS
        burned area product

2.  Validate prototype MODIS burned area product:

    a.  L7 and ASTER photographic products used to define
        burned/unburned ground reference maps every 16 days over each
        campaign

    b.  select field measurements to identify the burn status of
        ambiguous regions identified on the photos: mapping the location
        (GPS) and also state (Kodak gray scale, hand held spherical
        densiometer, hand held basal area prism)

    c.  opportunistic assessment of the timing and location of active
        fires where possible

3.  Validation locations

    a.  field work in areas no bigger than a L7 scene (\~185km by 185km)
        preferably concentrating on regions defined by an overlapping
        ASTER scene (\~60km\*60km)

        i.  Mongu, Zambia (175,71) - coordinated with SAVE + Daryl Ward
            prescribed burns (tbd)

        ii. Skukuza, South Africa (168,77) - coordinated with SAVE +
            prescribed burns (tbd)

        iii. Mutoko, Zimbabwe (169,72) - coordinated with Peter Frost
             (LULC)

        iv. Maun, Botswana (174.74) - coordinated with Botswana Range
            Inventory and Monitoring project (tbd), SAVE (?)

        v.  possibility of other sites

    b.  satellite data comparisons performed at other Southern African
        locations

4.  Timing

    a.  1999 (probably just AVHRR & L5): 1 month dry season (shakeout
        and training of validation workers)

    b.  2000 (MODIS, L7, ASTER): 2 month dry season

    c.  2001 (MODIS, L7, ASTER): 1 month wet season (?), 1 month dry
        season.

[NPP/biogeochemical modeling (Gu, Dowty, Scholes, Hanan, Pinheiro)
*Process modeling*]{.underline}

1.  Gu's lead: *Parameterize* a boreal forest model for savanna
    woodlands, which requires

    a.  Radiation decomposition in an aerosol-rich atmosphere (diffuse
        PAR, direct PAR, diffuse NIR and direct NIR);

    b.  Soil respiration responses to soil temperature and moisture;

    c.  Sapwood volume and respiration rate;

    d.  responses of leaf stomatal conductances to environmental
        factors;

    e.  leaf photosynthetic capacity,

    f.  aerodynamic parameters (zero-plane displacement and roughness
        length) of savanna vegetation

    g.  For model *validation* , the following tower flux measurements
        are needed:

        i.  sensible heat,

        ii. latent heat,

        iii. CO2 flux

        iv. net radiation.

2.  Hanan's lead: Adapt SWAPS biophysical model (savanna SVAT) for Core
    Sites

    a.  extend for SAVE/SAFARI-measured inputs (particularly useful:
        fluxes)

    b.  validate hydrological and soil physical aspects with
        measurements (T, H2O)

*The model will be driven by commonly available meteorological variables
(air temperature, vapor pressure deficit, precipitation, wind speed and
global solar radiation). Long wave radiation can be either modeled or
measured.*

3.  Pinheiro\'s lead: Tune SiB2 for savanna and woodland systems using
    measurements from Skukuza and Mongu.

    a.  Validate fluxes and study hydrology effects on radiative fluxes.

    b.  Focus on soil parameterization with J. Berry/Carnegie.

[Woodland BGC and reflectance modeling (Dowty, Gu, et al.) *Process
modeling*]{.underline}

1.  Measure

    a.  vegetation structural attributes

    b.  leaf and soil fluxes (short term, \~2 weeks growing season)

2.  Model Mongu site

    a.  integrated model includes biophysical, biogeochemical, leaf
        phenology and canopy spectral components

    b.  development, integration and evaluation of the phenological
        model

    c.  required input: continuous canopy light attenuation data

    d.  output of LAI and reflectance at plot and daily-to-annual time
        scales

[Historical Analysis of vegetation structure (Caylor, Dowty, Privette)
*Remote sensing*]{.underline}

1.  Acquire historical CORONA data at near consistent time-of-year.

2.  Acquire historical AVHRR (incl. Pathfinder), MSS, TM and in-country
    aerial photography data, some of which will overlap with CORONA
    imagery and current IKONOS scenes

3.  Determine relationship between %woody cover and satellite-derived VI

4.  Develop historical maps and temporal profiles of burning and %woody
    cover

    a.  structural dynamics of tree/grass ratio, woody cover, and LAI

5.  develop a dynamic vegetation model that can predict vegetation
    structure over the Kalahari

6.  Develop statistics on fire frequency with location, LC-type, etc.

7.  Estimate historical emissions for biomass

8.  Quantify land cover conversion with societal trends (e.g., tarred
    roads, governments)

**Appendix III: Equipment**

[Procured by SAVE]{.underline}

2 climb-up towers

3 Streaker Samplers from PIXE

2 CM 21 fast response pyranometers (shortwave) for aircraft

2 sets Kipp and Zonen CM14 albedometers (2 each of red, shortwave)

1 3-band digital camera (for aircraft) with GPS capability and case

3 GPS receivers

3 IBM Thinkpads

2 tool sets

2 tape measures (100m)

ground flags

1 TRAC canopy gap sensor

1 Accupar ceptometer

1 ASD Handheld spectrometer

1 Spectralon panel (18\"x18\")

8 Soil water reflectometers (TDRs)

5 Temperature Probes (soil thermistors)

1 Munsell Soil Charts

1 Campbell CR10x Datalogger

4 environmental enclosures

1 set fire validation tools

1 power converter/inverter/transformer set

1 box soil cannisters (for gravimetric measurements)

[Borrowed from GSFC]{.underline}

3 CIMEL sunphotometers (Mongu, Skukuza, Etosha Nat\'l Park) + tower
mounts

ASD FR spectrometers

Licor PAR sensors (AERONET)

Licor LAI-2000s

Licor line quantum sensor (PAR)

Dycam digital NDVI camera

StowAway simple light data logger

leaf pressure chamber

3 Campbell 21X dataloggers

Campbell CR 10x datalogger

custom red/NIR sensor (up and down)

TIR handheld sensors

Konica GPS camera

Soil infiltration ring and trowel (Levine)

**Appendix IV: Auxiliary parameters required for LAI/FPAR Algorithm
validation (from Myneni)**

1\. LAI and FPAR

2\. nadir or bi-directional canopy (plot) spectra (or in MODIS spectral
bands, particularly red, NIR, blue and green bands)

3\. leaf optical properties (raw spectra preferred, although MODIS bands
acceptable;

only the mean value of the species in the vertical direction needed)

4\. nadir soil/background spectra (or MODIS bands)

5\. Fractional vegetation cover (a high IDS need was noted here)

6\. Canopy allometric data (height, gap size, crown width)

7\. Phenological stage (green-up, mature, senescent) and species
composition (either

by MODLAND structural classification or traditional taxonomy).

8\. Additional parameters useful: wet/dry status (is canopy wet?), and
the amount

of non-photosynthesizing vegetation (litter, etc.) which could be
measured at one \"minimum photosynthesis\" stage of the year.

**Appendix V: Tucker's 1 km AVHRR product for SAFARI-2000**

TO: David Starr

FROM: Jackie Kendall and Jim Tucker, code 923

RE: Safari-2000 AVHRR 1-km Proposal

Date: December 15, 1998

We propose the following activities in 1999-2000:

**1**. Provide near-real time (within 6 hours of acquisition) \"quick
look\" data products for flight planning for three periods:

August/September 1999

January/February 2000

August/September 2000

At least one day time and one night time 1-km AVHRR acquisition will be
acquired and distributed within six hours of the overpass.

A. Develop simple procedures for deriving flight planning materials for
fire occurrence in the Safari-2000 mission region from NOAA AVHRR 1-km
data;

B. Assist local group (Satellite Applications Center of CSIR/Mikomtek)
in implementing \"quick look\" fire product capability including
distribution to Safari-2000 designated mission control center.

**2**. Provide post-Safari-2000 analysis products, consisting of day and
night single day full-resolution AVHRR 1-km products below, from 5^o^ to
35^o^ S and as far west as the 1-km AVHRR data allow, for three periods:

July 15 - October 15, 1999

December 15, 1999 - March 15, 2000

July 15 - October 15, 2000

Products: channel 1 and 2 reflectances (day only); channels 3, 4, and 5
brightness temperatures; latitude, longitude, solar and viewing
geometry; and NDVI, cloud, and fire.

All data will be calibrated, geometrically corrected, and mapped to
common equal area projection (TDB).

3.  We will maintain a digital archive of all NOAA AVHRR 1-km data
    collected during the time periods in #2 above. These data will be
    made available to any interested requester for the marginal cost of
    reproduction.

**Appendix VI: Acronym List**

AirMISR Airborne Multi-Angle Imaging Spectroradiometer

AERONET Aerosol Robotic Network

ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer

AVHRR Advanced Very High Resolution Radiometer

BRDF Bidirectional Reflectance Distribution Function

CSIR Council for Scientific and Industrial Research

DAAC Distributed Active Archive Center

DAO Data Assimilation Office

EOS Earth Observing System

ER-2 Earth Resources-2 (high altitude airplane)

ETM+ Enhanced Thematic Mapper+

EU European Union

FPAR Fraction of Absorbed Photosynthetically Active Radiation

GIMMS Global Inventory Mapping and Modeling System

GPS Global Positioning System

GSFC Goddard Space Flight Center

IDS InterDisciplinary Science

IFC Intensive Field Campaign

IGBP International Geosphere Biosphere Program

IRGA Infrared Gas Analyzer

LAI Leaf Area Index

LCLUC Land Cover and Land Use Change

MAS MODIS Airborne Simulator

MISR Multi-Angle Imaging Spectroradiometer

MODIS Moderate-Resolution Imaging Spectroradiometer

MOPITT Measurements of Pollution in The Troposphere

PARABOLA III Portable Apparatus for Rapid Acquisition of Bidirectional
Observations of Land and Atmosphere III

PI Principal Investigator

PIXE Proton Induced X-Ray Emission Spectroscopy

NPP Net Primary Production

NRA NASA Research Announcement

POLDER Polarization and Directionality of Earth's Reflectances

SAFARI 2000 Southern African Regional Science Initiative 2000

SAGE Stratospheric Aerosol and Gas Experiment

SAVE Southern Africa Validation of EOS

TOMS Total Ozone Mapping Spectrometer

UMD University of Maryland

UVA University of Virginia

VI Vegetation Index

WITS University of the Witwatersrand

WWW World Wide Web