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The distribution of arable land drought in the Belt and Road area, ,

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Extremely Drought
Severely Drought
Moderately Drought
Mildly Drought
No Drought
Thematic knowledge service for the spatio-temporal distribution of arable land drought in the Belt and Road area
spatial

Drought refers to a shortage of precipitation or a circumstance in which the water supply does not meet the water requirements. Due to their high frequencies, long duration, wide range of impacts, and a large number of accompanying disasters, droughts have been known to cause great economic losses to the national economies, especially to agricultural production, in many countries. The United Nations report in March 2015 showed that the worldwide annual economic losses caused by natural dis-asters, such as earthquakes, floods, droughts, and tornadoes, have reached an average of $250–300 billion (China News Service, 2015). In February, 2016, the Belgian Center for Disaster Epidemiology Research(CRED) issued a bulletin entitled "Disaster data for 2015" jointly with the United Nations International Strategy for Disaster Reduction(UNISDR) and the United States Agency for International Development(USAID). The report pointed out that in 2015 meteorological disasters were the main global natural disaster. Additionally, 32 major droughts were recorded through the year, a number twice the annual average of the past decade. The number of people affected by drought was 50.5 million, much higher than the average of 35.4 million over the past 10 years.

Considering the urgent demand for the spatio-temporal distribution of drought disasters over long periods of time in the Belt and Road region, this knowledge service utilized the Tropical Rainfall Measuring Mission satellite (TRMM) precipitation data to calculate the monthly spatio-temporal distribution of drought in the Belt and Road arable area from 2001 to 2013 based on the Precipitation Abnormity Percentage drought model. This knowledge service expect to provide the results of drought remote sensing monitoring and methods for drought disaster prevention and reduction as well as for agricultural development in the region.

Yearly spatio-temporal distribution from 2001 to 2013 of cropland in OBOR area was extracted based on the MODIS MCD12Q1 dataset and there were 156 monthly drought levels in the cropland region according to the overlaying of drought and agricultural land distribution. The cropland in OBOR area mainly distributed in four main relatively complanate regions including Central and Eastern Europe, South Asia, Southeast Asia and Northeast Asia. The area of cropland in the research region had a trend of increasing firstly and then decreasing from 2001 to 2013. The result that the cropland area distributed in dry region occupied large proportion of the total cropland area was revealed by overlaying the drought distribution with cropland distribution, the proportions in Northeast Asia, Southeast Asia, South Asia, West Asia and North Africa, Central and Eastern Europe, Central Asia were 45.06%, 37.76%, 57.71%, 41.34%, 28.19% and 39.41% respectively. The drought had most serious influence on cropland in South Asia where 29.2% cropland located in extremely dry region. Analysis of monthly drought distribution in agricultural area indicated that the cropland area under dry environment had a higher proportion in winter than summer in Northeast Asia, Southeast Asia, South Asia area, but the proportion in Central and Eastern Europe, Central Asia area showed very opposite characteristics.

  • The Belt and Road arable land in temporal and spatial display of the topic of knowledge service
  • Spatio-temporal Distribution of Drought in the Belt and Road Area during 1998-2015 Based on TRMM Precipitation Data
  • Drought levels in the cropland in Belt and Road area from 2001 to 2013
  • The Belt and Road arable land in temporal and spatial display of the topic of knowledge service
  • The thematic knowledge service of “The spatio-temporal distribution of arable land drought in the Belt and Road area” released
  • Data More