Impacts of crop rotation on vegetation condition index for species-level drought monitoring

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 cornproducing 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 utilizedfor 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.

Evaluating an Enhanced Vegetation Condition Index (VCI) Based on VIUPD for Drought Monitoring in the Continental United States

“…In locations with a limited number of sampling gauges, remote sensing data may be the only available information source for drought monitoring [6,7]. Satellite-based drought indices such as the normalized difference vegetation index (NDVI)-based vegetation condition index (VCI) [8] have been widely used for detecting the onset of drought and measuring the intensity, duration, and impact of drought globally [8][9][10][11][12][13][14][15]. The obvious advantage of VCI is that it can be easily computed owing to the fact that it does not require station observation data, and as a satellite-based drought product it can provide near real-time data over the globe at a relatively high spatial resolution [16].…”