Remote sensing of agro-droughts in Guangdong province of China using MODIS satellite data

文献类型: 外文期刊

第一作者: Gao, Maofang

作者: Gao, Maofang;Qin, Zhihao;Yang, Xiuchun;Qin, Zhihao;Zhang, Hong'ou;Zhou, Xia;Qin, Zhihao;Lu, Liping

作者机构:

关键词: Guangdong province;agricultural drought;drought monitoring;remote sensing;MODIS data

期刊名称:SENSORS ( 影响因子:3.576; 五年影响因子:3.735 )

ISSN: 1424-8220

年卷期: 2008 年 8 卷 8 期

页码:

收录情况: SCI

摘要: A practical approach was developed in the study for drought monitoring in Guangdong province of China on the basis of vegetation supply water index (VSWI) and precipitation distance index (PDI). A comprehensive index for assessment of agro-drought severity (SADI) was then established from the normalized VSWI and PDI. Using MODIS satellite images and precipitation data from ground-observed meteorological stations, we applied the approach to Guangdong for drought monitoring in 2006. The monitoring results showed that the drought severity on average was very low in the province during the main growing season from May to September in 2006. However, seasonal variation of the severity was also obvious in difference counties of the province. Higher severity of drought could be seen in the periods of late-June ( In China each month is traditionally divided into 3 periods. Each is with 10 days and has different names. This division system is mainly with consideration of farming seasons hence has been widely used as the basis of drought monitoring periods in China. In order to keep this tradition, we define, for example, for June, the early-June as the period from 1(st) to 10(th) of June, the mid-June as the period from 11(th) to 20(th), and the late-June as the period from 21(st) to 30(th). So mid- August denotes the period from 11(th) to 20(th) of August, and early-July the period from 1(st) to 10(th) of July, and so on.), early-July, mid- August and late-September. Regionally, Leizhou Peninsula in the west had the most serious drought before mid-May. Validation indicated that our monitoring results were generally consistent with the drought statistics data and the results from Chinese National Satellite Meteorological Center (CNSMC), which used only remote sensing data. This consistence confirmed the applicability of our approach for drought monitoring. Our better identification of drought severity in Leizhou Peninsula of western Guangdong than that of CNSMC might suggest that the approach developed in the study was able to provide a better alternative to increase the accuracy of drought monitoring for agricultural administration and farming.

分类号:

  • 相关文献

[1]Applicability Research of Drought Monitoring Indexes on Mongolia Plateau Based on the EOS/MODIS Time Sequence. Duwala,Narisu,Yushan,Liu, Guixiang. 2016

[2]Satellite Observations on Agricultural Adaptation to Drought in Southwestern China. Dong, Yansheng,Li, Cunjun,Chen, Hongping. 2012

[3]Progress in soil moisture estimation from remote sensing data for agricultural drought monitoring. Yan, Feng,Qin, Zhihao,Yan, Feng,Qin, Zhihao,Li, Maosong,Li, Wenjuan. 2006

[4]Study on Drought Index in Major Planting Area of Winter Wheat of China. Sun, Li,Li, Baoguo,Sun, Li,Wu, Quan,Pei, Zhiyuan,Chen, Xiwei.

[5]THE POTENTIAL OF MODIS FOR DROUGHT MONITORING IN NORTHERN CHINA. Long Huiling,Huang Wenjiang,Yang Xiaodong,Dong Yansheng. 2012

[6]Reproduction of Captive Asian Giant Softshell Turtles, Pelochelys cantorii. Zhu Xinping,Hong Xiaoyou,Zhao Jian,Zhu Xinping,Hong Xiaoyou,Liang Jianhua,Feng Zicheng. 2015

[7]Evaluating Agricultural Catastrophe Risk in Guangdong Province. Xu, Lei,Xu, Lei. 2016

[8]Risk assessment on storm surges in the coastal area of Guangdong Province. Li, Kuo,Li, Guo Sheng.

[9]REMOTE SENSING OF REGIONAL CROP TRANSPIRATION OF WINTER WHEAT BASED ON MODIS DATA AND FAO-56 CROP COEFFICIENT METHOD. Li, Heli,Li, Heli,Luo, Yi,Li, Heli,Zhao, Chunjiang,Yang, Guijun. 2013

[10]Effects of vegetation indices to the spatial changes of desert environment using EOS/MODIS data: A case study to Sangong inland arid ecosystem. Lu, Liping,Qin, Zhihao,Qin, Zhihao,Gao, Maofang,Zhao, Chengyi,Li, Wenjuan. 2006

[11]EXTRACTION OF PLANTING AREAS OF MAJOR CROPS AND CROP GROWTH MONITORING IN NORTHEAST CHINA. Huang, Qing,Zhou, Qingbo,Wu, Wenbin,Wang, Limin,Zhang, Li,Huang, Qing,Zhou, Qingbo,Wu, Wenbin,Wang, Limin,Zhang, Li. 2012

[12]Evaluating and Classifying Field-Scale Soil Nutrient Status in Beijing using 3S Technology. Xue, Yong-An,Huang, Lin-Sheng,Zhang, Dong-Yan,Zhao, Jin-Ling,Yang, Hao. 2012

[13]Monitoring of Rapid Urban Sprawl in Beijing with Time Series Remote Sensing Data and Analysis of Driving Forces. Zhao, Jinling,Yang, Yao,Zhang, Dongyan,Huang, Linsheng. 2013

[14]Integrating Remotely Sensed and Meteorological Observations to Forecast Wheat Powdery Mildew at a Regional Scale. Zhang, Jingcheng,Nie, Chenwei,Yang, Guijun,Pu, Ruiliang,Yuan, Lin,Huang, Wenjiang. 2014

[15]Development of a web temporal-spatial information application for main crops based on integration of remote sensing and crop model. Yang Xiaodong,Xu Xingang,Gu Xiaohe,Yang Hao,Yu Haiyang,Yang Fuzeng. 2014

[16]Survey of Support Vector Machine in the Processing of Remote Sensing Image. Li, Su,Wang, Wenchao. 2013

[17]Quick image processing method of HJ satellites applied in agriculture monitoring. Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong,Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong. 2016

[18]Agricultural crop harvest progress monitoring by fully polarimetric synthetic aperture radar imagery. Yang, Hao,Zhao, Chunjiang,Yang, Guijun,Yuan, Lin,Yang, Xiaodong,Xu, Xingang,Yang, Hao,Li, Zengyuan,Chen, Erxue. 2015

[19]Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM plus Thermal Infrared Images. Ling, Feng,Ban, Xuan,Li, Xiaodong,Zhang, Yihang,Du, Yun,Foody, Giles M.,Du, Hao. 2017

[20]Remote-Sensing Based Winter Wheat Growth Dynamic Changes and the Spatial-Temporal Relationship with Meteorological Factor. Huang Qing,Zhou Qingbo,Wu Wenbin,Li Dandan. 2014

作者其他论文 更多>>