Local area coverage data acquired aboard the TIROS-N satellite family by the advanced very high resolution radiometer systems was examined to determine the agricultural information current. Albedo differences between channel 2 and channel 1 of the advanced very high resolution radiometer LAC (called EVI) are shown to be closely correlated to the Ashburn vegetative index produced from LANDSAT multispectral scanner data which have been shown to vary in response to "greenness", soil moisture, and crop production. The statistical correlation between the EVI and the Ashburn Vegetative Index (+ or - 1 deg) is 0.86

Gray, T. I., Jr.

Mccrary, D. G.

Scott, L.

English

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AgRISTARS
Early Warning and Crop
Condition Assessment
-1.02040 'T	 leo
EW-N1-04042
JSC-17112
MAR I 1 1981
A Joint Program for
Agriculture and
Resources Inventory
Surveys Through
Aerospace
Remote Sensing
February 1981
METEOROLOGICAL SATELLITE DATA - A TOOL TO DESCRIBE THE
HEALTH OF THE WORLD'S AGRICULTURE
1,
T. I. Gray, J;-. arid D. G. McCrary
National Oceanic and Atmospheric Administration
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U.S. Department of Lommerce
1050 Bay Area BlvJ.
Houston. Texas 77058
Lyndon B. Johnson Space Center
Houston, Texas 77058
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E"1-04042;	 JSC-17712
4. T" and Subble 5 Row*, ate
Meteorological Satellite Data - A Tool To Describe the February 1981
6. Pa too.. m',OrpnitationCodeHealth of the World's Agriculture
7. *A~$) S. fte"mg Orwmatron Report No
T. I. Gray. Jr. and D. G. McCrary
U.S. Department of Commerce 10. work Unit No.
a hrbrw" orS Muftn Noon OW A*W t
National Oceanic and Atmospheric Administration, USDC
1050 Bay Area Blvd.
11. Contr;ct or Gram No.
Houston. Texas	 77058
13. Type of Report and Panod covered
Technical Memorandum12. spormerins Adanty Nam aad Addreer
Early Warning/Crop Condition Assessment AgRISTARS
1050 Bay Area Blvd.
14. sporoerrn/ Adaney code
1s. SupplargwttarY Nona
ta. Aftataet	 y
Local Area Coverage data acquired aboard the TIROS-N satellite family by the Advanced Very
High Resolution Radiometer systems have been examined to determine the agricultural 	 infor-
mation content.	 Albedo differences between Channel 2 and Channel 1 of the Advanced Very
High Resolution Radiometer LAC (called EVI) are shown to be closely correlated to the
Ashburn Vegetative Index produced from Landsat multispectral scanner data which have been
shown to vary in response to "greenness", soil moisture, and crop production. 	 The
statistical correlation between the EVI and the Ashburn Vegetative Index (+ 1 day) is 0.86.
17. err vrerot fsuwmtad by AudwfilI I& oiWftAwn Stan or-
Vegetative Index
Early Warning
1e. Suerity Ono. faf tftia "Wo 20. secunty 006f. lof Min ow) 21. No. of Padre 22.	 ►ice'
Unclassifigd Unclassified 12
EW-N1-04042
JSC-17112
METEOROLOGICAL SATELLITE DATA - A TOOL TO DESCRIBE
THE HEALTH OF THE WORLD'S AGRICULTURE
PRINCIPAL INVESTIGATORS
T. I. Gray and 0. G. McCrary
APPROVED BY
oatwright, anager
Early Warning/Crop Condition Assessment Project
AgRISTARS Program
Earth Observations Division
Space an! Life Sciences Directorate
NATIONAL AERONAUTICS AND SPACE ADMINISTRATION
LYNDON B. JOHNSOk SPACE CENTER
HOUSTON, TEXAS
February 1981
W. .
LEMSCO-15978
AIM 	
^ ♦ \i .. Y^ ^f.!}^/1• •
Page intentionally left blank 
PREFACE
The Agriculture and Resources Inventory Surveys Through Aerospace Remote
Sensing is a 6-year program of research, development, evaluation, and appli-
cation of aerospace remote sensing for-agricultural resources which began in
fiscal year 1980. This program is a cooperative effort of the U.S. Department
of Commerce, the National Aeronautics and Space Administration, the U.S.
Department of Agriculture, and the U.S. Department of the Interior. Under
Contract NAS 9-15800, personnel of Lockheed Engineering and Management
Services Company, Inc., assisted the Early Warning/Crop Condition Assessment
project in preparing this document for publication.
The expertise of mop;, individuals was required in the course of this work.
The authors acknowledge the contributions of the following persuns:
• P. Ashburn, U.S. Department of Agriculture, Foreign Services Department,
Crop Condition Assessment Division, who provided the Ashburn Vegetative
Index data set
S L. Scott. U.S. Department of Agriculture, Economic Statistics Cooperative
Service, who prepared the manuscript
• L. Lautenschlager, U.S. Department of Agriculture, Economic Statistics
Cooperative Service, who provided statistical support
• F. Ravet, Earth Observations Division, National llc rnnautics and Space
Administration, Lyndon B. Johnson Space Center, who provided leadership in
software development
• G. Boatwright, Manager, Early Warning/Crop Condition Assessment project,
U.S. Department of Agriculture, who provided encouragement and support
• M. Helfert, Oceans and Atmosphere service, National Oceanic and Atmospheric
Adminstration, who provided helpful suggestions
AFFILIATION OF PRINCIPAL INVESTIGATORS
• T. I. GRAY JR.: U.S. Department of Commerce, National Oceanic and
Atmospheric Administration, National Earth Satellite Service, Land Services
Branch. Liason detailed to the Agriculture and Resources Inventory Surveys
through Aerospace Remote Sensing program at the Lyndon B. Johnson Space
Center.
• D. G. McCra • U.S. Department of Commerce, National Oceanic and
A rigosphierTc Wdministration, Environmental Data and Information Service,
Center for Environmental Assessment Services. Assigned to support Early
Warning/Crop Condition Assessment project.
CONTENTS
Section	 Page
1. Background ........................................................ 1
2. Experimental Design .................................:............. 1
3. Conclusion and Study Suggestions .................................. 4
4. References ........................................................ 1
PRECF. ING PAGE SLAW NOT
vii
.	 J,,.i.,....
1. BACKGROUND
In the Large Area Crop Inventory Experiment (LACIE) and the research activi-
ties that followed, the response variations within the several channels of
multispectral scanner (MSS) data sets over known earth target areas were
investigated. The MSS instruments were placed on board the two Earth
Resources Technology Satellites (ERTS-1 and E9 TS-2), which subsequently were
renamed Landsat-1 and Landsat -2 by the National Aeronautics and Space
Administration (NASA). These instruments have been placed on subsequent
Landsats, also. The vegetative indexes, which comprise one set of research
products derived from MSS data, respond to changes in "greenness" of
vegetation. Although several indexes have been proposed, the auto-correlation
between them is so strong that any one can be considered representative.
The LACIE project results indicated that the MSS remote sensor system is a
potential tool for Monitoring global agricultural conditions. To exploit this
tool, the Foreign Agriculture Service (FAS) of the U.S. Department of
Agriculture (USDA) formed the Crop Condition Assessment Division (CCAD), which
was chartered to devise operational techniques for monitoring world food
production. The CCAD has established an operational digital computer facility
to ingest and process Landsat MSS data sets into agricultural analytical prod-
ucts. They recognized that a massive storage impact would exist if all of the
daily output of the MSS was retained. Accordingly, several products have been
developed for retention in a time series. This product list includes sample
segments, skip-pixel-skip-line images, and vegetative indexes. The indexes
file for the South American area which was used in this study was initiated in
January 1980.
2. EXPERIMENTAL DESIGN
With the initiation of the Agriculture and Resources Inventory Surveys Through
Aerospace Remote Sensing (AgRISTARS) project, National Oceanic and Atmospheric
Administration (NOAA) personnel D. McCrary and R. Smith proposed the investi-
gation of the polar-orbiting environmental satellite system capabilities as a
1
complementary data source to that of the Landsat `ISS. The Landsat system
design provides one observation per site every 18 days ner satellite, while
the environmental satellite system, Television Infrared Observation Satellite
(TIROS-N/tIOAA), can provide a daily observation. nuring LACIE, cloudi ws at
the time of the•Landsat overpass frequently precluded ac quisition of suitable
da,.a for the selected target areas. Thus- the named researchers designed
tasks for study which might provide data sets to complement MSS products for
agricultural and resources inventories.
With the acceptance of these tasks within the Early Warning/Crop Condition
Assessment project of AgRISTARS, 0. McCrary requested that the Local Area
Coverage (LAC) data acquired through the Advanced Very High Resolution
Radiometer (AVHRR) systems be collected and archived for a series of dates for
the South American principal crop areas. S. Schneider, Environmental Products
Branch, National Earth Satellite Services, provided the support necessary to
acquire these data sets. Meanwhile, the data sets from the MSS source were
delivered to the CCAO FAS in an operational mode.
The first proposed task called for relatin g timely (3 3 days) MSS data pro-
ducts to the similiarly configured environmental data products. Although
image displays of the LAC data could be produced, only subjective worthiness
of such products for agricultural monitoring was possible. The two problems
that existed may be described as follows.
a. The image device design needs 3 or 4 channels of data, whereas only 2
channels were available in the LAC.
b. The stability of the imaging of the LAC data varied with respect to the
amount of cloud in the image area.
The best opportunity to compare the two systems appeared to be with vegetative
indexes. For South America there were several LAC data sets which were nearly
synoptic to the operational products of the MSS for that continent. The spec-
tral characteristics o f the AVHRR channel 1 are very similar to the
f
2
combination of channels 4 and 5 of the MSS, and AVHRR channel 2 is similar to
the combination of channels 6 and 7 of the MSS, as shown in the table below.
Channel i AVHRR wave length,	 Channel	 MSS wave length,
c
	 vm	 um
1	 0.55 - 0.68	 4	 0.5 - 0.6
5	 .6 - .7
r	
2	 .7 - 1.1	 6	 .7 - .8
7	 .8 - 1.1
Thus, we formulated our Environmental Vegetative Index (EVI) to be
EVI = Alb.(channel 2) - Alb.(channel 1)
where Alb. = aibedo, except that if EVI < 0.0, the value is ignored. The
Ashburn vegetative Index (AVI) is screened in the same manner. A data point
has a cloud response if EVI < 0, and has a water response if EVI < 0.
The initial computations of the EVIs were made by using the digital counts in
each of channels 1 and 2 rather than the actual calibrated albedos. However,
the slopes and intercepts of the calibration curves for the two channels form
nearly the same line. The major correction to the AVHRR LAC data is that of
correcting the data to an apparent overhead sum: data value/cos z, where
z is the solar zenith angle. Since the EVI is computed as a difference
between the simultaneous responses of the two channels from the same field of
view, this correction was made upon the EVI.
EVI (corrected) = EVI/cos z
The first data set, based upon AVHRR LAC data for South America for
16 March 1980 and Landsat MSS data sets from the period 15 March 1980 through
17 March 1980, consists of EVI and AVI pairs computed for identical land
target areas. These data pairs were processed by SAS* programs PLOT, CORR,
	
a st caJ Analysis System	 programs are provided y the 	 .
SAS Institution, Inc., Raleigh, North Carolina.
3
and GLM. Whithin this time restraint, the correlation between the pairs was
0.86. However, with a wirier ti p' window, using Landsat data acouired on
10 March 1980, the additional points added an excessive number of cloud-
contaminated pixels which then decreased the correlation to 0.69, (See fig-
ures 1 and 2.)
3. CONCLUSION AND STUDY SUGGESTIONS
In this short study, the EVI is shown as being closely related to the AVI,
inferring, then, that the AVHRR LAC data sets may be used to complement the
MSS data (or substitute when necessary) for agricultural monitoring through
time series products of w:getative indexes. Further study is necessary to
qualify more fully the environmental satellite data sets as a tool for agri-
cultural and resource inventories. Suggestions for such study are as follows.
A. Develop a method to adjust for mixed scene pixels.
B. Determine the variations within and between AVHRR LAC data associated with
viewing angle, solar illumination, and atmospheric effects.
C. Determine the acceptability and adaptabililty of AVHRR LAC data sets in
maintaining the indexes time series.
D. Determine the scalar variations of the i-dexes with respect to ground
truth to calibrate the indexes for interpretation capability.
E. Establish applicable techniques which may be transferable to the proposed
operational computer system.
F. Establish techniques to use EVI data for Early Warning/Crop Condition
Assessment tasks.
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4. REFERENCES
Ashburr, P.: Utilization of the Vegetative Index Number in the USSR. Tech-
nical Memorandum 011, U.S. Department of Agriculture, Foreign Agricultural
Service, Washington, D.C., October 1979.
Davis, L.: Utilization and Evaluation of Vegetative Indexes for Crop Con-
dition Assessment. Technical Memorandum 010, U.S. Department of Agriculture,
Foreign Agricultural Service, Washington, D.C., September 1979.
Aaronson, A.; and Davis, L.: An Evaluation of Relationships Between Vegeta-
tive Indices, Soil Moisture and Wheat Yields. Technical Memorandum 09, U.S.
Department of Agriculture, Foreign Agric-P tural Service, Washington, D.C.,
September 1979.
Thompson, D.; and Wehmanen, 0. A.: The Use of Landsat Digital Data to Detect
and Monitor Vegetation Water Deficiencies. 11th Int. Symp. on Remte Sensing
of Fnvironment, Environmental Research institute of Michigan. (Ann Arbor),
pp. 925-931, April 1977.
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Meteorological satellite data: A tool to describe the health of the world's agriculture

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