Remote sensing agricultural drought monitoring methods

This demonstration project will focus on the identification of agricultural drought characteristics and will elaborate a monitoring method through the application of remote sensing data.

By applying the results, an early warning monitoring system can be establised which can forecast the effect of drought on irreversible yield loss and/or quality degradation before symptoms occur. The monitoring system could provide the opportunity to assess possible future yield damages, which contribute to food security and facilitate drought mitigation. For water management today, remote sensing (RS) is one of most important solutions for measuring agricultural drought and its effects. The broad application of RS has few technological barriers, although the accumulated knowledge on RS is slowly being implemented into practice. This project aims to help fill the knowledge gap in this field, through spectral MODIS satellite time series datasets, in order to develop agricultural drought monitoring to facilitate decision-making in practice. While it is possible to continuously gather satellite data on plant water content, the direct interpretation of these data is not feasible for farmers. Using field reference data (i.e. data of green and brown water content) as a calibration for remote sensing data, the real drought situation of plants can be quickly and effectively mapped in both space and time on the surface.