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Remote sensing for resources management: to assess post-harvest ground cover conditions in the South Interlake Region of Manitoba / Joan Simonton

By: Material type: TextTextPublication details: Winnipeg, MB : University of Manitoba, 1988.Description: viii, 87 leaves : ill. ; 29 cmOnline resources: Abstract: Remote sensing provides a means of obtaining accurate and timely information on the location, extent, and condition of the agricultural land base. This study assessed the value of remote sensing techniques in providing reliable, and detailed distribution patterns and area values for post-harvest ground cover conditions in the South Interlake region of Manitoba. The methodology used involved a series of stages based on a computer classification of an October 20, 1986 Landsat 5 TM image in conjunction with ancillary data on soil texture criteria and field measurements and observations collected two weeks prior. 42.14% of the study area was classified as crop residue, 63.96% of which was classified as having 33%-66% crop residue cover, 25.74% as 0%-33% crop residue cover or bare soil, and 10.3% as 67%-100% crop residue cover or stubble. The results of the classification revealed that the crop residue cover types of interest were spectrally separable, and that the information generated (t

Thesis(M.N.R.M.)--University of Manitoba, 1988.

Includes bibliographical references (leaves 63-67).

Remote sensing provides a means of obtaining accurate and timely information on the location, extent, and condition of the agricultural land base. This study assessed the value of remote sensing techniques in providing reliable, and detailed distribution patterns and area values for post-harvest ground cover conditions in the South Interlake region of Manitoba. The methodology used involved a series of stages based on a computer classification of an October 20, 1986 Landsat 5 TM image in conjunction with ancillary data on soil texture criteria and field measurements and observations collected two weeks prior. 42.14% of the study area was classified as crop residue, 63.96% of which was classified as having 33%-66% crop residue cover, 25.74% as 0%-33% crop residue cover or bare soil, and 10.3% as 67%-100% crop residue cover or stubble. The results of the classification revealed that the crop residue cover types of interest were spectrally separable, and that the information generated (t

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