Crop growth condition monitoring and analyzing in county scale by time series MODIS medium-resolution data

Abstract

Crop Growth Condition (CGC) monitoring is one of the most important methods for the yield estimation and the food security. The needs for CGC monitoring not only exist in large scale but also in medium or small scale. In this work, Sihong County was chosen to test the ability of the 10-day CGC monitoring by remote sensing data. Over 600 Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m resolution images of Sihong County from 2000 to 2012 were used to monitor CGC. Two vegetation indices were compared to evaluate their effectiveness in monitoring CGC. These were the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). EVI was less sensitive than NDVI to aerosol effects. Therefore, EVI was chosen to monitor CGC of Sihong County. By the long-term monitoring, ground survey and correlation analyses, we found the following results: 1. the 10-day CGC of 2012 were better than the corresponding time periods of the typical and reference year; 2. the area of CGC worse than the typical and reference year are counted, and the statistical results show the highest percentage were 13% and 10%, respectively. 3. the winter wheat sowing and reaping progress of the dry fields were earlier than the paddy fields. Because of the free availability and frequent coverage of the MODIS data, the cost-effective assessment here by using MODIS 250-m resolution images may serve as a template applicable to other counties of China. Moreover, CGC monitoring in county scale and regular time period will be critical to help implement effective management plans to reduce and prevent the agricultural disaster, and will be useful to promote CGC monitoring methods.