NTRS - NASA Technical Reports Server

As of October 27, 2023, NASA STI Services will no longer have an embargo for accepted manuscripts. For more information visit NTRS News.

Back to Results
Physically-based parameterization of spatially variable soil and vegetation using satellite multispectral dataA stochastic-geometric landsurface reflectance model is formulated and tested for the parameterization of spatially variable vegetation and soil at subpixel scales using satellite multispectral images without ground truth. Landscapes are conceptualized as 3-D Lambertian reflecting surfaces consisting of plant canopies, represented by solid geometric figures, superposed on a flat soil background. A computer simulation program is developed to investigate image characteristics at various spatial aggregations representative of satellite observational scales, or pixels. The evolution of the shape and structure of the red-infrared space, or scattergram, of typical semivegetated scenes is investigated by sequentially introducing model variables into the simulation. The analytical moments of the total pixel reflectance, including the mean, variance, spatial covariance, and cross-spectral covariance, are derived in terms of the moments of the individual fractional cover and reflectance components. The moments are applied to the solution of the inverse problem: The estimation of subpixel landscape properties on a pixel-by-pixel basis, given only one multispectral image and limited assumptions on the structure of the landscape. The landsurface reflectance model and inversion technique are tested using actual aerial radiometric data collected over regularly spaced pecan trees, and using both aerial and LANDSAT Thematic Mapper data obtained over discontinuous, randomly spaced conifer canopies in a natural forested watershed. Different amounts of solar backscattered diffuse radiation are assumed and the sensitivity of the estimated landsurface parameters to those amounts is examined.
Document ID
Document Type
Contractor Report (CR)
Jasinski, Michael F.
(Massachusetts Inst. of Tech. Cambridge, MA, United States)
Eagleson, Peter S.
(Massachusetts Inst. of Tech. Cambridge, MA, United States)
Date Acquired
September 6, 2013
Publication Date
September 1, 1989
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
NAS 1.26:185957
Accession Number
Funding Number(s)
Distribution Limits
Work of the US Gov. Public Use Permitted.
No Preview Available