The estimation of the spatially variable surface moisture and heat fluxes of natural, semivegetated landscapes is difficult due to the highly random nature of the vegetation (e.g., plant species, density, and stress) and the soil (e.g., moisture content, and soil hydraulic conductivity). The solution to that problem lies, in part, in the use of satellite remotely sensed data, and in the preparation of those data in terms of the physical properties of the plant and soil. The work was focused on the development and testing of a stochastic geometric canopy-soil reflectance model, which can be applied to the physically-based interpretation of LANDSAT images. The model conceptualizes the landscape as a stochastic surface with bulk plant and soil reflective properties. The model is particularly suited for regional scale investigations where the quantification of the bulk landscape properties, such as fractional vegetation cover, is important on a pixel by pixel basis. A summary of the theoretical analysis and the preliminary testing of the model with actual aerial radiometric data is provided

Eagleson, Peter S.

Jasinski, Michael F.

English

NASA Technical Reports Server

!USE OF LANDSAT IMAGES OF VEGETATION COVER
TO ESTIMATE EFFECTIVE HYDRAULIC PROPERTIES OF SOILS
Peter S. Eagleson
Principal Investigator
and
Michael F. Jasinski
Research Assistant
Department of Civil Engineering
Massachusetts Institute of Technology
Cambridge, Massachusetts 02139
Addendum to
Final Technical Report of 1 August 1988
Covering the Period
1 August 1988 -30 September 1988
NAG 5-510 "
23 November 1988
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Final Technical Report
On NAG 5-510
The estimation of the spatially variable surface moisture and heat fluxes of
natural, semivegetatedlandscapesis difficult due to the highly random nature of the
vegetation (e.g., plant species, density, and stress) and the soil (e.g., moisture
content, and soil hydraulic conductivity). The solution to that problem lies, in part,
in the useof satellite remotely senseddata, and in the interpretation of those data
in terms of the physical propertiesof the plant and soil.
This work has focused on the development and testing of a stochastic
geometric canopy-soil reflectance model, which can be applied to the
physically-based interpretation of Landsat images. The model conceptualizes the
landscapeas a stochastic surfacewith bulk plant and soil reflectanceproperties. The
model is particularly suited for regional scale investigations where the quantification
of the bulk landscapeproperties, such as fractional vegetation cover, is important on
a pixel by pixel basis. A summary of the theoretical analysesand the preliminary
testing of the model with actual aerial radiometric data is provided below.
Theoretical Analysis
Theoretical analysis has included (i) an investigation of the relation between
the shape of red-infrared scattergrams and the physical structure of the scene and
(ii) the development of a methodology, based on (i), for the retrieval of subpixel
properties. That work was previously reported (Eagleson and Jasinski, 1988) and is
only summarized below.
The information content of red-infrared scattergrams was investigated through
the simulation of a series of scenes of varying complexity. The role of several
variables was determined by sequentially introducing them into the scene, and
-2-
observing their individual correspondingeffect on the scattergram. In particular,
that analysis led to an understanding of several principal mechanisms which
contribute to the often observed triangular shape, or "tasseled cap" of typical
red-infrared scattergrams. They included (i) variable vegetation density, (ii)
variable soil background reflectance, and (iii) the covariance between vegetation
cover and shadow which exists, especially when the scale of the pixel is large
compared to the length scale of the shadow. The details of the above theoretical
analyses are summarized in the appended report (updated version, sent to
IEEE Transactionson Geoscienceand Remote Sensing,October, 1988).
It was also demonstrated that the fractional (i.e. subpixel) vegetation cover of
the simulated scenescan be retrieved by applying the method of moments to the
red-infrared scattergram of the aggregatedscene. The method consistsof equating
the theoretical momentsof the canopy-soil reflectanceto the actual moments of the
scene,and then solving for the unknown variables. At least sevenmoment equations
can be written for the reflectancemodel, including five reflectancemoments (i.e., the
mean and variance of the reflectanceequation in the red and infrared bands, and the
cross-covariance)and two cover moments (i.e., the mean and variance). Conditional
moments can also be written through the a priori understanding of the structure of
the red-infrared scattergram. For instance, the means and variances of the soil
reflectance terms can be written for the locus of pixels which constitute the soil line.
The inverse problem was applied to two test cases. For the Case II simulation
(referred to in the appended report), the fractional vegetation cover was estimated
by writing conditional moment equations along lines parallel to the soil line, as
shown in the scattergram in Figure 1. For the Case V simulation, the analysis
includes the writing of conditional moments for statistically homogeneous areas as
shown in Figure 2. Comparisons of the estimated and actual mean vegetation cover
-3-
for a range of cover types are provided in Figures 3 and 4, respectively. Results
indicate very good agreement. Details of these results are currently being
summarizedfor publication in an appropriate journal.
The stochastic canopy-soil reflectancemodelhas also provided a mechanismfor
studying the influence of scenevariability on commonvegetation indices, such as the
normalized vegetation index (NVI). One important conclusionof that study is that
the maximum NVI of a scene does not necessarilyrepresent maximum vegetation
amount, but it is affected by both shadowsand soil variability. A third journal
article detailing those results will be completedshortly.
Model Testing
The canopy model was tested on a Pecan orchard for which aerial radiometric
observations and corresponding ground truth were obtained. The orchard is located
near Maricopa, Arizona, about 40 km south of Phoenix. Aerial radiometric
measurements were collected on June 12, 1988, in conjunction with the MAC III
experiment organized by the Water Conservation Laboratory, Agricultural Research
Service, Phoenix, Arizona. Radiometric observations were made using an Exotech
radiometer with Thematic Mapper red (0.62--0.69 _m) and IR (0.78-0.90 #m) filters
at a ground resolution of about 40 meters.
Model testing consisted of comparing the plots of the actual radiometric data
in the red-infrared reflectance space, with the hypothetical scattergram constructed
from ground truth measurements taken at the time of overflight. Construction of
the hypothetical scattergram required the development of the appropriate analytical
relationships among canopy cover, shadowed soil, and illuminated soil (Figure 13 of
appended report). The good agreement between the actual radiometric data and the
hypothetical scattergram (Figure 14 of appended report) provides preliminary
confirmation of the validity of the stochastic model for explaining the structure of
-4-
red-infrared scattergrams. Details of the above work are also provided in the
appendedreport.
Two additional data sets were acquired as part of the present study. The first
is a set of aerial radiometric data taken in June 1988over three specifiedwatersheds
in the Beaver Creek Basin of the Coconino National Forest in Northern Arizona.
Second, a geocoded Landsat Thematic Mapper scene was purchased over the same
region in Northern Arizona. Testing of the canopy-soil model on those two data
sets is currently under way under separate support.
Hypotheses Testing.
Most of the climatological, hydrological, and soils data required to test
Eagleson's climate-soil-vegetation equilibrium hypotheses have been obtained for the
Beaver Creek Basin in northern Arizona. Testing has begun but its conclusion
awaits continued NASA support.
-5-
Publications
Eagleson, P. S. and M. F. Jasinski, "Use of Landsat Images of Vegetation Cover to
Estimate Effective Hydraulic Properties of Soils." Final TechnicaZ Report,
NAG 5-510. 1 August 1988.
Jasinski, M. F. and P. S. Eagleson, "The Structure of Visible-Infrared Scattergrams
of Semivegetated Landscapes,°' submitted to IEEE Transactions on Geoscience
and Remote Sensing. February, 1988.
Jasinski, M. F. and P. S. Eagleson, "Estimation of Subpixel Vegetation Cover
Using Red-Infrared Scattergrams." In preparation.
Jasinski, M. F. and P. S. Eagleson, "The Physical Basis of Comm6n Vegetation
Indices for Semivegetated Landscapes." In preparation.
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Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

This work focuses on the characterization of natural, spatially variable, semivegetated landscapes using a linear, stochastic, canopy-soil reflectance model. A first application of the model was the investigation of the effects of subpixel and regional variability of scenes on the shape and structure of red-infrared scattergrams. Additionally, the model was used to investigate the inverse problem, the estimation of subpixel vegetation cover, given only the scattergrams of simulated satellite scale multispectral scenes. The major aspects of that work, including recent field investigations, are summarized

Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

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