DocumentCode :
255155
Title :
Impacts of crop rotation on vegetation condition index for species-level drought monitoring
Author :
Yonglin Shen ; Xiuguo Liu ; Youxin Huang
Author_Institution :
Fac. of Inf. Eng., China Univ. of Geosci., Wuhan, China
fYear :
2014
fDate :
11-14 Aug. 2014
Firstpage :
1
Lastpage :
5
Abstract :
Understanding crop rotation on satellite remote sensing derived vegetation indices is very necessary, because it helps us develop more scientific methods or indices for revealing the mechanism of agricultural drought in the species-level. In this paper, the impacts of crop rotation on vegetation condition index (VCI) was explored. First, we tried to justify that whether crop rotation is a typical agricultural practice in the study area, and counted the proportion of crop planting changes over any pixel in multi-year; and second, a neighbor-average based VCI index was developed for species-level cases, and the comparison with traditional VCI index had been conducted. The experimental study was conducted in state of Iowa, the primary corn-producing state in the Corn Belt of the United States. Moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) time series and NASS´s cropland data layer (CDL) among years 2002-2013 were utilized for data analysis. The results shown that crop rotation limited impacts the VCI index on corn drought monitoring across the study area. Even so, the research inspires a more accurate and valuable mean in the future for examining the mechanisms and processes of species-level drought monitoring.
Keywords :
agriculture; crops; rain; time series; MODIS; NDVI time series; corn drought monitoring; crop rotation; cropland data layer; moderate resolution imaging spectroradiometer; neighbor-average based VCI index; normalized difference vegetation index; satellite remote sensing; species-level drought monitoring; vegetation condition index; Agriculture; Indexes; MODIS; Monitoring; Remote sensing; Satellites; Vegetation mapping; corn; crop rotation; drought; remote sensing; vegetation condition index (VCI);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Agro-geoinformatics (Agro-geoinformatics 2014), Third International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/Agro-Geoinformatics.2014.6910603
Filename :
6910603
Link To Document :
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