CAJ | 학술논문

　　目前用于中国干旱监测的遥感方法大多是可见光和热红外指数法，受云雨、植被和地形的影响较大，不能满足中国南方地区干旱监测的需求。该研究基于被动微波辐射传输方程，首先构建了基于 AMSR-E（advanced microwave scanning radiometer-EOS）数据的地表温度反演模型，R2=0.79，RMSE（root mean square error）为2.54℃，实现了中国地表温度的被动微波遥感监测。然后，拟合了不同下垫面归一化植被指数（normalized difference vegetation index，NDVI）与微波极化差异指数（microwave polarization difference index，MPDI）的关系。在此基础上改进了植被供水指数（vegetation supply water index，VSWI），构建了基于AMSR-E数据的被动微波遥感气象干旱指数，并以中国2009年的旱情为例进行实例验证。研究表明，该干旱指数与AMSR-E L3土壤湿度数据有着显著的负相关关系（R2=0.75），且能基本表征2009年中国实际的气象干旱状况。
　　목전용우중국간한감측적요감방법대다시가견광화열홍외지수법，수운우、식피화지형적영향교대，불능만족중국남방지구간한감측적수구。해연구기우피동미파복사전수방정，수선구건료기우 AMSR-E（advanced microwave scanning radiometer-EOS）수거적지표온도반연모형，R2=0.79，RMSE（root mean square error）위2.54℃，실현료중국지표온도적피동미파요감감측。연후，의합료불동하점면귀일화식피지수（normalized difference vegetation index，NDVI）여미파겁화차이지수（microwave polarization difference index，MPDI）적관계。재차기출상개진료식피공수지수（vegetation supply water index，VSWI），구건료기우AMSR-E수거적피동미파요감기상간한지수，병이중국2009년적한정위례진행실례험증。연구표명，해간한지수여AMSR-E L3토양습도수거유착현저적부상관관계（R2=0.75），차능기본표정2009년중국실제적기상간한상황。
Drought is a recurrent complex phenomenon that affects nearly all climatic zones in the world. It is one of the major natural hazards in China, resulting in considerable economic, social, and environmental costs. Preparation for drought should be an important part of policies. Therefore, it is necessary to develop a dynamic and real-time drought monitoring approach in China. Remote sensing technology is one feasible way. However, the main drought indices of remote sensing for monitoring drought dynamics at present are based on visible and near infrared bands. They are always seriously impacted by rainfalls, clouds, vegetation, and terrain conditions. Hence, current drought monitoring technologies cannot meet the needs in south China, where the weather is always cloudy. Passive microwave emissions can penetrate non-precipitating clouds, thereby providing a better representation of land surface parameters under nearly all sky conditions. What is more, daily passive microwave data are available from microwave radiometers as compared to optical sensors like Landsat TM, ASTER, or MODIS, of which only weekly series products are available. So passive microwave remote sensing has unique advantages in long-time drought monitoring over those based on visible and near infrared bands. In this study, we first developed a semi-empirical model for retrieving land surface temperature using the AMSR-E C-band (6.9GHz) and X-band (10.7GHz) passive microwave remote sensing data. The approach provided a good retrieval accuracy of land surface temperature (error=2.54℃,R2=0.79). Next, this paper built an empirical relation between the AMSR-E 6.9GHz Microwave Polarization Difference Index (MPDI) and the NOAA-AVHRR Normalized Differential Vegetation Index (NDVI). Further, we improved the Vegetation Supply Water Index (VSWI) on the basis of the relation between NDVI and MPDI. Then, we used the new-developed drought index to monitor the drought dynamics of China in 2009. Results showed that many regions and cities of China (with red and yellow color) were attacked by the drought disaster in different degrees at the national level. The drought conditions were mainly distributed in Southwest (Yunnan, Guizhou and Guangxi Province, etc.), the Inner Mongolia Autonomous Region, northeast of Heilongjiang Province, Bohai region ( Liaoning, and Hebei Province), Jianghuai and Huanghuai region (Henan, Anhui, Shanxi and Shaanxi Province), and the Western region (Xinjiang Autonomous Region, Tibet Autonomous Region and Qinghai Province). The remote-sensed droughts were on the whole consistent with the actual situation of China in 2009 (http:www.gov.cn/jrzgv/). The field statistical data of the Meteorological Bureau showed that the average rainfall of China in 2009 was 565.8 mm, about 10 percent less than the same periods of past years (606 mm). What is more, the average temperature of China was 10.7℃ in 2009, about one degree higher than the same periods of past years (9.7℃). Analysis results indicated that sustained high temperatures and fewer rainfalls were direct factors that induced the serious drought disaster of China in 2009. The new drought index had a significant negative correlation with the corresponding AMSR-EL3 soil moisture data (R2=0.75;RMSE=0.02 g/cm3). In all, the drought monitoring method proved to be effective in describing the land surface drought conditions of China.