摘要
干旱是最为突出的极端自然现象，其造成的影响与损失在所有的自然灾害中比重最大。长期以来对干旱监测与预测，国内外已开展多专题多手段的理论与技术研究，已建立多个业务应用系统对区域或全球尺度旱情进行监测。国内外研究与应用表明，利用遥感技术可以在很高的时间分辨率与空间分辨率获取地表光谱信息进行旱情监测。但是现有的众多旱情遥感监测并没有对旱情遥感指标在时空上的适应性与不确定性进行分析，因此旱情监测精度较低。本文通过对旱情遥感监测指标在全国的适应性与不确定性分析，建立农业旱情遥感监测指标集，以满足全国农业旱情监测需要。
本文先在样点尺度与区域尺度分别对山西太谷与山东济宁实验区进行农业旱情遥感指数适应性与不确定性进行分析，再在省级尺度(山西省)上进行遥感指数的适应性与不确定性分析；最后在以上分析基础上，使用相同的方法，利用2001-2004年的NOAA AVHRR旱情指数与全国土壤相对湿度数据，对全国农业旱情遥感指数进行适应性与不确定性分析，同时建立适合于全国尺度的农业旱情遥感监测指标集，并利用以上指标集，对2005年农业旱情监测结果与气象综合指数——NCC旱情监测结果进行比较。本文的主要成果及创新点主要体现在以下几个方面：
1) 综合考虑作物叶面状态与冠层温度对农业干旱的反映，通过对农业旱情遥感指数在时空上的适应性分布特点，提出作物健康指数cVHI概念，并在农业旱情区划基本单元框架下构建适合于中国农业旱情监测的遥感指标集；
2) 利用1991-2005年NDVI、TS以及2001-2005年全国土壤湿度数据，已构建适应于中国农业旱情监测的植被状态条件指数(VCI)、温度状态条件指数(TCI)、植被健康指数(VHI)组成的旱情遥感监测指标集；
3) 在样点(山西太谷)、样区(山东济宁)、大区域(山西省)三个尺度上分别进行农业旱情遥感监测指数适应性与不确定性分析，并以此为基础提出适应于全国尺度的旱情遥感指数适应性分析方法与框架；
4) 综合考虑作物受地貌、气候、土壤以及作物种植方式等因素的影响，制作适合于农业旱情遥感监测指数适应性分析与农业旱情遥感监测的农业旱情区划基本单元图；
5) 利用2001-2004年全国土壤相对湿度数据与遥感指数数据，在农业旱情区划基本单元基础上，对农业旱情遥感监测指数进行适应性分析，结果表明：在头年11月到来年2月，TCI指数对农业旱情反映敏感，适合于全国农业旱情监测；3月份TCI在北方地区对农业旱情反映敏感，华南地区VCI与
Drought is the most outstanding extreme natural phenomena, which leads to the largest damage to human being among the natural disasters. The drought monitoring and research has being developed for a long time, and more and more drought monitoring systems are working over the world. The drought monitoring research and application has shown that remote sensing data can get the drought information with high spatial and temporal resolution. However, the current drought systems based on remote sensing don't analyse the Suitability and uncertainty, so the accuracy of the drought monitoring result is not so high. Based on Suitability and uncertainty analysis of agricultural drought indicator, this paper built up the agricultural drought indicator dataset to satisfy the China agricultural drought monitoring.
At first, the suitability and uncertainty was discussed at small-scale in Taigu ,Shanxi Province, and then at big scale in Jining, Shandong Province. Secondly, in Shanxi Provinc, the suitability and uncertainty was analysed at a bigger scale. At last, using the same method and frame, this paper got the suitability and uncertainty of agricultural drought indicator with TCI, VCI, VHI and soil moisture during 2001-2004, and set up the drought indicator dataset to monitor drought of 2005. The main achievements of this paper are as following:
1) Considering the spatial and temporal characteristics of suitability of agricultural drought indicator derived from remote sensing, this paper brought forward Crop Vegetation Health Index (cVHI) and got the China agricultural drought indicator dataset based on the suitability analysis and basally agricultural drought district map.
2) Using NDVI, TS and soil moisture data, this paper has set up drought
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