Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016

Abstract

Drought disaster space agglomeration assessment is one of the important components of meteorological disaster prevention and mitigation. Agriculture affected by drought disaster is not only a serious threat to world food security, but also an obstacle to sustainable development. Additionally, China is an important agricultural import and export country in the world. Therefore, we used the global Moran’s I and the local indicators of spatial autocorrelation (LISA) to reveal the spatial agglomeration of agricultural drought disaster in China from1978 to 2016, respectively. The results showed that China’s agricultural drought disaster presents local spatial autocorrelation of geographical agglomeration at national level during the study period. The spatial agglomeration regions of China’s agricultural drought disaster were in Inner Mongolia, Jilin province, Heilongjiang province, Liaoning province, Shanxi province, Hebei province, Shandong province, Shaanxi province and Henan province, indicating that agricultural drought disaster mainly distributed in North and Northwest China, especially occurred in the Yellow River Basin and its north areas. We also found that the overall movement direction of agricultural drought disaster agglomeration regions was northwest, and the maximum moving distance was 722.16 km. Our results might provide insight in early warning and prevention for drought disaster.

Fractional Linear Regression Equation in Agricultural Disaster Assessment Model Based on Geographic Information System Analysis Technology

“…RSI is the rainfall intensity comprehensive index. Its calculation method is shown in formula (1). V H is the sensitivity index, and the calculation method is shown in formula (2).…”

“…Foreign scholars have done a lot of research on the methods of storm disaster risk assessment. They believe that the formation of disasters results from the comprehensive effects of the carrier's vulnerability, hazards and exposure [1]. The risk assessment method proposed by scholars has certain practicability.…”

Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province

“…Abebe Senamaw et al ( 2021 ) used the Vegetation Condition Index eMODIS NDVI and SPI between 2000–2016 to show the spatial and temporal variations of agricultural drought and meteorology in Ethiopia. Qian Wang et al ( 2019 ) assessed the spatial aggregation of the agricultural drought crisis in China between 1978–2016 using the Global Moran's Index (GMI) and the Local Indicators of Spatial Association. They reported that the direction of the drought crisis was toward the northwest.…”

Agricultural Drought Prediction Based on Conditional Distributions of Vine Copulas

“…China is a major agricultural‐producing country but is highly drought‐prone (Wang et al., 2019; Zhang et al., 2018). As per relevant statistical data from the period of 1978–2016, the average annual agricultural loss area due to droughts is approximately 2.27 million hectares, accounting for more than half of the total agricultural loss area (Wang et al., 2018).…”