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01-06-2016

Research on spatial and temporal characteristics of drought based on GIS using Remote Sensing Big Data

Authors: Xinhui Xu, Fei Xie, Xingyu Zhou

Published in: Cluster Computing | Issue 2/2016

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Abstract

Drought is a stochastic natural hazard that is caused by intense and persistent shortage of precipitation. Spatial and temporal patterns of drought have been analyzed by several methods, ranging from satellite images to historical records; however, drought is generally identified by climate elements. Drought indices are quantitative measures that characterize drought levels by assimilating data from one or several variables (indicators). A number of different indices have been developed to quantify droughts, each with its own strengths and weaknesses. In this paper, using the remote sensing image to acquire the vegetation cover data, and combined with meteorological data and the Geographic Information System (GIS) technology to discuss the spatial and temporal characteristics of the drought. Based on precipitation observations Pu’er City, Yunnan Province, ten counties (districts) ten meteorological observation stations from 1961 to 2010 monthly for 50 years, mainly in ArcGIS10.1 analysis platform, using Mann–Kendall nonparametric trend test method for time-series trends in precipitation was tested, using ArcGIS in inverse distance weighting interpolation tool were precipitation the amount and distribution of precipitation anomaly percentage. Finally, precipitation anomaly percentage grading standards drought intensity distribution of drought The results showed that: Pu’er City under the effect of temperature, altitude, vegetation cover, and many other factors, forming the situation that the rainfall is a little more in north–south and less in east–west, the drought incidence appears more in northwest and less in southeast, more in spring and winter and less in summer and fall.

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Title: Research on spatial and temporal characteristics of drought based on GIS using Remote Sensing Big Data
Authors: Xinhui Xu
Fei Xie
Xingyu Zhou
Publication date: 01-06-2016
Publisher: Springer US
Published in: Cluster Computing / Issue 2/2016
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-016-0556-y

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