Title :
Exploiting multisensor spectral data to improve crop residue cover estimates for management of agricultural water quality
Author :
Galloza, M.S. ; Crawford, M.
Author_Institution :
Lab. for the Applic. of Remote Sensing, Purdue Univ., West Lafayette, IN, USA
Abstract :
Crop residue is an important factor in determining soil structure relative to soil organic matter content, water infiltration, evaporation, and soil temperature [1]. There is also a direct impact related to production of biofuels. The use of the NDTI (Normalized Difference Tillage Index [2]) from multispectral data and the CAI (Cellulose Absorption Index [3]) from hyperspectral data are investigated as a means of calibrating indices derived from the Advanced Land Imager (ALI) on the EO-1 satellite and Landsat TM, with the goal of improving residue cover estimates over extended areas.
Keywords :
vegetation; vegetation mapping; water quality; Advanced Land Imager; EO-1 satellite; Landsat TM; agricultural water quality; biofuel production; cellulose absorption index; crop residue; hyperspectral data; multisensor spectral data; normalized difference tillage index; soil organic matter content; soil structure; soil temperature; water infiltration; Agriculture; Computer aided instruction; Hyperspectral imaging; Indexes; Soil; Cellulose Absorption Index; Crop residue cover; Normalized Difference Tillage Index; hyperspectral; multispectral; water content;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6050020
