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基于条件温度植被指数(VTCI)的中国北方地区土壤水分估算
引用本文:王鸣程,杨胜天,董国涛,白娟. 基于条件温度植被指数(VTCI)的中国北方地区土壤水分估算[J]. 干旱区地理, 2012, 35(3): 446-455
作者姓名:王鸣程  杨胜天  董国涛  白娟
作者单位:1.北京师范大学地理学与遥感科学学院,遥感科学国家重点实验室,环境遥感与数字城市北京市重点实验室,北京100875;2.北京师范大学地理学与遥感科学学院,遥感科学国家重点实验室,环境遥感与数字城市北京市重点实验室,北京100875;3.北京师范大学地理学与遥感科学学院,遥感科学国家重点实验室,环境遥感与数字城市北京市重点实验室,北京100875;4.北京师范大学地理学与遥感科学学院,遥感科学国家重点实验室,环境遥感与数字城市北京市重点实验室,北京100875
基金项目:水利部公益项目,林业公益性行业科研专项,中央高校基本科研业务费专项资金资助
摘    要:利用中国北方13省2000-20008年的Terra-MODIS归一化植被指数(NDVI)和地表温度(LST)数据,以及相同时间段农业气象观测站点的0~10 cm表层土壤水分资料,建立基于条件温度植被指数的表层土壤水分遥感估算模型,计算出2000-2008年北方13省各月份表层土壤水分,主要结论有:(1)空间分布上,表层土壤水分最高的是分区一和分区四,平均值均达到了0.2以上,表层土壤水分最低的是新疆沙漠地区,低于0.05,土壤水分空间分布基本呈“南高北低,东高西低”的趋势;(2)受降雨量和农作物需水的影响,年内月份之间,7、8两月表层土壤水分最高,4、5、9、10月表层土壤水分最低;(3)年际变化上,2000- 2001、2001- 2002、2005 - 2006年北方大部分区域表层土壤水分增加,增加区域面积分别占总面积的79.2%、59.3%和71.4%,而2002 - 2003、2004 -2005年大部分区域表层土壤水分减少,减少区域面积分别占总面积的53.9%和64.1%;(4)降水是影响土壤水分时空分布的一个重要因素.误差分析结果表明,基于条件温度植被指数的土壤水分遥感反演达到了较好的效果,能够较准确地反映北方地区干旱的分布及变化状况.

关 键 词:土壤水分  遥感  条件温度植被指数  干旱
收稿时间:2011-09-18;

Estimating soil water in Northern China based on Vegetation Temperature Condition Index (VTCI)
WANG Ming-cheng , YANG Sheng-tian , DONG Guo-tao , BAI Juan. Estimating soil water in Northern China based on Vegetation Temperature Condition Index (VTCI)[J]. Arid Land Geography, 2012, 35(3): 446-455
Authors:WANG Ming-cheng    YANG Sheng-tian    DONG Guo-tao    BAI Juan
Affiliation:(School of Geography,Beijing Normal University,State Key Laboratory of Remote Sensing Science, Beijing Key Laboratory of Environmental Remote Sensing and Digital City,Beijing 100875,China)
Abstract:Drought is one of the main meteorological disasters in Northern China and it does great harm to national economic and agriculture of China.Soil moisture is an important parameter to study the characteristics of drought.A lot of methods were developed to monitor soil moisture both in field scale and macro scale regions,and there are too many limitations for these methods to monitor soil moisture.A near-real time drought monitoring approach called Vegetation Temperature Condition Index(VTCI) integrates land surface reflectance and thermal properties and can invert soil conditions of land surface in macro scale region more accurately.It is calculated based on the triangular space of NDVI-Ts and closely related to soil moisture.On the basis of Terra-Moderate Resolution Imaging Spectoradiometer(MODIS) Normalized Difference Vegetation Index(NDVI) and Land Surface Temperature(LST) products and soil moisture observation data during 2000-2008,we employed this method to monitor land surface soil moisture of northern China.Considering the complexity of geography environment and weather characteristics in northern China,we divided the study area into four division: the North region,the Northeast region,the Northwest region and the Qinghai region,and the soil moisture between 0-10 cm during 2000-2008 were calculated separately.We extracted the intercept and slope of the Wet edge and Dry edgeand calculated VTCI,and soil moisture was calculated according to the linear relationship between VTCI and observation data.The results show that land surface soil moisture is various in different regions and different time:it is lower in the northern and western regions than that in the southern and eastern regions;it is greater than 0.2 cm3/ cm3 in the Northeast and the Qinghai region and less than 0.05 cm3/ cm3 in the desert region of Xinjiang;it is high in July and August and low in March and April,September and October due to the variety of rainfall and crop water requirement;it increased from 2000 to 2001,2001 to 2002,2005 to 2006,and decreased from 2002 to 2003,2004 to 2005 in most part of the study area;the changes of soil moisture are various in different years and regions,precipitation is highly correlated to the temporal and spatial distribution of soil water.Compared with ground measurements,it shows that the inversion based on VTCI method has good precision and can monitor the drought conditions in northern China more accurately.
Keywords:soil moisture  remote sensing  Vegetation Temperature Condition Index  drought
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