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Determining crop residue type and class using satellite acquired dataLANDSAT Thematic Mapper (TM) data for March 23, 1987 with accompanying ground truth data for the study area in Miami County, IN were used to determine crop residue type and class. Principle components and spectral ratioing transformations were applied to the LANDSAT TM data. One graphic information system (GIS) layer of land ownership was added to each original image as the eighth band of data in an attempt to improve classification. Maximum likelihood, minimum distance, and neural networks were used to classify the original, transformed, and GIS-enhanced remotely sensed data. Crop residues could be separated from one another and from bare soil and other biomass. Two types of crop residue and four classes were identified from each LANDSAT TM image. The maximum likelihood classifier performed the best classification for each original image without need of any transformation. The neural network classifier was able to improve the classification by incorporating a GIS-layer of land ownership as an eighth band of data. The maximum likelihood classifier was unable to consider this eighth band of data and thus, its results could not be improved by its consideration.
Document ID
19910009153
Acquisition Source
Legacy CDMS
Document Type
Thesis/Dissertation
Authors
Zhuang, Xin (Purdue Univ. West Lafayette, IN, United States)
Date Acquired
September 6, 2013
Publication Date
January 1, 1990
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
NAS 1.26:188961
NASA-CR-188961
Accession Number
91N18466
Funding Number(s)
CONTRACT_GRANT: NAGW-1472
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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