旱情监测中高植被覆盖区热惯量模型的应用

干旱区地理 ›› 2014, Vol. 37 ›› Issue (3): 539-547.

旱情监测中高植被覆盖区热惯量模型的应用

王艳姣^1，2，闫峰³

（1 中国气象局农业气象保障与应用技术重点开放实验室，河南郑州 450003；2 中国气象局国家气候中心，北京 100081； 3 中国林业科学研究院荒漠化研究所，北京 100091）

收稿日期:2013-07-28 修回日期:2013-09-30 出版日期:2014-05-25
通讯作者: 闫峰（1973-），男，江苏连云港人，博士，主要从事环境遥感与灾害学研究. Email：njuyf@163.com
作者简介:王艳姣（1976-），女，湖北人，博士，副研究员，主要从事环境遥感与气候学研究. Email：wangyj@cma.gov.cn
基金资助:
中国气象局农业气象保障与应用技术重点开放实验室开放基金项目（AMF201107、AMF201204）；国家自然科学基金项目（41301458）

Application of thermal inertia model in high vegetation coverage area for drought monitoring

WANG Yan-jiao^1，2，YAN Feng³

（1 Key Laboratory of Agrometeorological Support and Applied Technique, CMA, Zhengzhou 450003, Henan, China;2 National Climate Center, CMA, Beijing 100081, China; 3 Institute of Desertifieation Studies, CAF, Beijing 100091, China）

Received:2013-07-28 Revised:2013-09-30 Online:2014-05-25

摘要/Abstract

摘要： 热惯量模型在植被盖度较高地区应用存在局限，以河北省为例研究了高植被覆盖区热惯量模型的应用扩展，得出以下结论：（1）热惯量ATI与近地表土壤水分RSM₁₀具有较好的相关性，3、4和5月RSM₁₀～ATI拟合方程的决定系数R²分别为0.387、0.265和0.249，[RSM10]估算值平均相对误差MRE分别为20.89%、28.91%和31.54%。（2）高植被覆盖区热惯量模型可用扩展热惯量ETI表示，5月0<[ETI]≤0.015地区面积为112 140.05 km²，主要分布在北部、南部和东南部；0.015<ETI≤0.030地区面积为58 513.31 km²，主要分布在中部；ETI>0.030地区面积为14 460.54 km²，主要分布在东北部。（3）5月高植被覆盖区旱情监测中，RSM₁₀～ATI方程的决定系数（R²=0.359）显著高于RSM₁₀～ATI方程（R²=0.249），ETI估算RSM₁₀的MRE（25.47%）低于ATI估算RSM₁₀的MRE（31.54%）。

关键词: 高植被覆盖, 热惯量, 旱情监测

Abstract: Drought is one of the most serious meteorological disasters in China and remote sensing technology shows greater potential for agricultural drought monitoring. Thermal inertia model derived from energy-balance equation has been proved to can monitor drought successfully in bare land and sparse vegetation coverage areas，but there are still certain limitations of the application in higher vegetation coverage regions. In this paper，MYD11A2 and MYD09A1 （DOY：081/113/115） derived from AQUA- MODIS （Moderate Resolution Imaging Spectroradiometer） data and relative soil moisture （RSM） in 10，20 and 50 cm soil depths near the surface were used to analyze the relationships between apparent thermal inertia （ATI） and RSM in March，April and May，2011. Besides，extended thermal inertia （ETI） established with vegetation index and temperature difference was applied to estimate surface soil moisture in higher vegetation coverage areas of Hebei Province. Results showed as follows：（1） Good correlation existed between ATI and RSM₁₀ near surface. Coefficients of determination （R²） of RSM₁₀-ATI fitting equations from March to May were 0.387，0.265 and 0.249，and the correlations between RSM₁₀ and ATI passed t-test at significance level α= 0.001. Both RSM₁₀ estimated from [RSM10-ATI] fitting equation and measured RSM₁₀ were analyzed and the mean relative error （MRE） values were 20.89%，28.91% and 31.54%，respectively. From March to May，with the vegetation coverage rising，the surface soil moisture estimation ability of ATI model was decreased. （2） ATI model in March was analyzed and result showed there was significant positive correlation between ATI and reciprocal of temperature difference. Hence，in high vegetation coverage area，thermal inertia model could be expressed as extended thermal inertia （ETI） coupled with vegetation index and reciprocal of temperature difference. In May 2011，area with ETI≤0 was 977.50 km²，which was mainly water body and distributed in the eastern part of Hebei Province. Area with 0<ETI≤0.015 was 112 140.05 km²，which mainly distributed in the northern，southern and southeastern parts. Area with 0.015<ETI≤0.030 was 58 513.31 km²，which mainly distributed in the central. Area with ETI>0.030 was 14 460.54 km²，which was mainly in the northeastern part. （3） In May 2011，drought monitoring by ETI model showed RSM₁₀-ETI fitting equation coefficient of determination （R²=0.359） was significantly higher than that of RSM₁₀-ATI（R²=0.249）. Moreover，MRE of RSM₁₀ estimated from ETI was 25.47%，which was markedly lower than that from ATI model （31.54%）. Furthermore，ETI was also used to estimate RSM in April to test its applicability and result showed that MRE of RSM₁₀ estimated from ETI model （25.47%） was lower than that from ATI model （28.91%）. So ETI model could retrieve surface soil moisture successfully in the area with higher vegetation coverage and the retrieval abilities of ETI for RSM₁₀ and RSM₂₀ were relatively higher than that for RSM₅₀.

Key words: high vegetation coverage, thermal inertia, drought monitoring

中图分类号:

S152.7

王艳姣，闫峰. 旱情监测中高植被覆盖区热惯量模型的应用[J]. 干旱区地理, 2014, 37(3): 539-547.

WANG Yan-jiao，YAN Feng. Application of thermal inertia model in high vegetation coverage area for drought monitoring[J]. , 2014, 37(3): 539-547.

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