DocumentCode :
640726
Title :
Detection of flood and its impact on crops using NDVI - Corn case
Author :
Shrestha, Ranjay ; Liping Di ; Genong Yu ; Yuanzheng Shao ; Lingjung Kang ; Bei Zhang
Author_Institution :
Center for Spatial Inf. Sci. & Syst., GMU, Fairfax, VA, USA
fYear :
2013
fDate :
12-16 Aug. 2013
Firstpage :
200
Lastpage :
204
Abstract :
Understanding the event of flood and its impacts, especially towards agriculture, is an extremely significant component; however is exceedingly complicated process at the same time. That said research on identifying flood and its damages in the agricultural sector is not getting as much of attention as it should be. Flood damages on agricultural are directly depends on the impact it exert on the crops and needs as accurate of a prediction as possible to quantify these damages. Various remote sensing techniques and productions have been used in the past for this purpose. This paper will utilize MODIS weekly Normalize Difference Vegetation Index (NDVI) product to detect and quantify flood damages on crops. The analysis is based on time-series contrast and comparison of weekly NDVI between the flood years against the normal (standard) year (average/mode between years 2000-2012). As NDVI value indicates the greenness of the vegetation, a sharp/significant drop can be observed compare to the normal year due to the damages on crops during the flooded duration. This research selected two scenarios based on the timeframe of the flood: (1) Early season - two flooding events in March and May of 2011 and in June of 2008. The weekly NDVI for the flooded areas (pixel) was extracted and compared with 12 years of normal (Median) NDVI trend. (2) Growing season - flooding event during the month of September 2006. Again the weekly NDVI for the flooded region was extracted and compared with 12 years of normal weekly NDVI trend. The comparative NDVI results for both scenarios not only illustrated the flooding events, but also demonstrated its impact crop production based on the time-series graph.
Keywords :
crops; floods; remote sensing; AD 2000 to 2012; AD 2008 06; AD 2011 03; AD 2011 05; MODIS NDVI product; NDVI value; NDVI-corn case; Normalize Vegetation Index; agricultural sector; crop production; flood damages; flood detection; flood event; growing season; remote sensing techniques; time-series contrast; time-series graph; Floods; Crop Damage; Flood Detection; MODIS; NDVI; Remote Sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Agro-Geoinformatics (Agro-Geoinformatics), 2013 Second International Conference on
Conference_Location :
Fairfax, VA
Type :
conf
DOI :
10.1109/Argo-Geoinformatics.2013.6621907
Filename :
6621907
Link To Document :
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