Abstract
In this study, modified perpendicular drought index (MPDI) models based on the red-near infrared spectral space are established for the first time through the analysis of the spectral characteristics of GF-1 wide field view (WFV) data, with a high spatial resolution of 16 m and the highest frequency as high as once every 4 days. GF-1 data was from the Chinese-made, new-generation high-resolution GF-1 remote sensing satellites. Soil-type spatial data are introduced for simulating soil lines in different soil types for reducing errors of using same soil line. Multiple vegetation indices are employed to analyze the response to the MPDI models. Relative soil moisture content (RSMC) and precipitation data acquired at selected stations are used to optimize the drought models, and the best one is the Two-band enhanced vegetation index (EVI2)-based MPDI model. The crop area that was statistically significantly affected by drought from a local governmental department, and used for validation. High correlations and small differences in drought-affected crop area was detected between the field observation data from the local governmental department and the EVI2-based MPDI results. The percentage of bias is between −21.8% and 14.7% in five sub-areas, with an accuracy above 95% when evaluating the performance via the data for the whole study region. Generally the proposed EVI2-based MPDI for GF-1 WFV data has great potential for reliably monitoring crop drought at a relatively high frequency and spatial scale. Currently there is almost no drought model based on GF-1 data, a full exploitation of the advantages of GF-1 satellite data and further improvement of the capacity to observe ground surface objects can provide high temporal and spatial resolution data source for refined monitoring of crop droughts.
Highlights
Regional temperature and precipitation anomalies resulting from global climate change may cause droughts
The development of the crop drought monitoring algorithm for the GF-1 wide field view (WFV) data consisted of new soil lines for two soil classes in the study area, with their average slopes used to build the several
The EVI2-based modified perpendicular drought index (MPDI) for the GF-1 WFV data was validated with ground measurements
Summary
Regional temperature and precipitation anomalies resulting from global climate change may cause droughts. Drought is a type of natural disaster that has significant impacts on the economy, society, food security and the human living environment [1]. Situated in the southeastern East Asian continent, China has a typical monsoon climate with uneven temporal and spatial distributions of precipitation as well as susceptibility to frequent droughts over large areas. The impacts on agricultural production are especially impressive. Zhou estimated the economic loss caused by drought. Sensors 2018, 18, 1297 at, up to 7.1–11.8 billion Renminbi (RMB) in the early 1990s [2]. During 2004–2007, each year drought affected approximately 16% of farmers nationwide, which resulting in an income loss of about 20% [3]
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