DocumentCode :
3071558
Title :
Identification of agricultural crops in early stages using remote sensing images
Author :
Valero, S. ; Ceccato, Pietro ; Baethgen, Walter E. ; Chanussot, Jocelyn
Author_Institution :
CESBIO - CNES, Univ. de Toulouse, Toulouse, France
fYear :
2013
fDate :
21-26 July 2013
Firstpage :
4229
Lastpage :
4232
Abstract :
Real-time monitoring of agricultural crops is increasingly important because of the involved huge economic impact. The automatic identification of crops, as early as possible during the agricultural season, is an important issue supporting agricultural policies. In this context, the objective of this article is to evaluate the possibilities of remote sensing data to identify corn and soybean crops in the early growing season. The proposed study evaluates the potential of hyperspectral data and multispectral NDVI times series. Experimental results illustrate the challenges of crop detection in early stages.
Keywords :
crops; remote sensing; time series; vegetation mapping; agricultural crop identification; agricultural crop real-time monitoring; agricultural policies; agricultural season; automatic crop identification; corn crop identification; crop detection challenges; early growing season; early stages; huge economic impact; hyperspectral data potential; multispectral NDVI time series; remote sensing data; remote sensing images; soybean crop identification; Agriculture; Hyperspectral imaging; MODIS; Spatial resolution; Time series analysis; NDVI times series; crop monitoring; hyperspectral imagery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
ISSN :
2153-6996
Print_ISBN :
978-1-4799-1114-1
Type :
conf
DOI :
10.1109/IGARSS.2013.6723767
Filename :
6723767
Link To Document :
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