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

fYear

2011

fDate

24-29 July 2011

Firstpage

3668

Lastpage

3671

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International

Conference_Location

Vancouver, BC

ISSN

2153-6996

Print_ISBN

978-1-4577-1003-2

Type

conf

DOI

10.1109/IGARSS.2011.6050020

Filename

6050020