| 引用本文: | 玉院和,王金亮,李晓鹏.基于MODIS数据的滇中地区干旱监测[J].灌溉排水学报,2018,37(11):91-98. |
| YU Yuanhe,WANG Jinliang,LI Xiaopeng.基于MODIS数据的滇中地区干旱监测[J].灌溉排水学报,2018,37(11):91-98. |
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| 摘要: |
| 【目的】开展滇中地区干旱监测研究，分析旱情时空变化。【方法】以2012―2016年的MODIS地表反射率产品和地表温度产品数据为数据源，利用植被状态指数（VCI）、距平植被指数（AVI）和温度条件指数（TCI）进行滇中地区的干旱监测，并利用上述指数建立了适用于滇中地区的干旱模型DI，结合滇中地区气象站观测的资料而建立的相对湿度指数（RMI），对滇中地区旱情进行综合评价。【结果】通过VCI、AVI和TCI反演干旱发现，滇中地区旱情主要发生在1―5月、11―12月，VCI与AVI反演效果一样，而TCI弱于二者。干旱模型指数DI1比DI2效果好，基于DI1旱情监测分析认为，滇中地区旱情主要以轻、中旱为主，滇中西北部、东部干旱发生率较高。1―5月，极旱、重旱发生率较高，11―12月以中、轻旱为主。【结论】干旱模型指数DI1能够很好地表达滇中地区干旱情况。 |
| 关键词: 干旱； 滇中地区； MODIS； 植被指数； 干旱模型指数； 相对湿度指数 |
| DOI：10.13522/j.cnki.ggps.20180097 |
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| Monitoring the Occurrence of Drought in Central Yunnan Province Based on MODIS Data |
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YU Yuanhe, WANG Jinliang, LI Xiaopeng
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1. College of Tourism and Geographic Sciences, Yunnan Normal University, Kunming 650500, China; 2. Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China; 3. Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming 650500, China; 4. Kunming meteorological observatory, Kunming 650500, China
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| Abstract: |
| 【Objective】 Air-born based technologies have been increasingly used to monitor real time change in many hydrological and soil processes and in this paper, we studied the feasibility of using them to monitor the emergence of drought in central Yunnan province, and analyzed its spatiotemporal variation. 【Method】The MODIS reflectance data and the surface temperature measured from 2012 to 2016 were used in the study. We analyzed the vegetation condition index (VCI), anomaly vegetation index (AVI) and the temperature condition index (TCI). These indices were used to calculate the drought index model (DI) which was then combined with the relative moisture index (RMI) measured from meteorological station to evaluate the occurrence of droughts in this region. 【Result】The drought in the central Yunnan occurred mainly from January to May, and between November and December. The results inversely calculated using VCI and AVI were comparable, both being superior to TCI. The drought index DI1 works better than DI2. Based on DI1, the probability of occurrence of extreme drought or severe drought between January and May was high, while November and December were dominated by moderate or mild drought. 【Conclusion】 The drought index (DI1) can represent the occurrence of drought in Central Yunnan well. |
| Key words: drought; central Yunnan; MODIS; vegetation index; drought model index; relative moisture index |
