基于TVDI和Landsat-8的喀斯特峡谷区干旱监测
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摘要
[目的]探索适用于喀斯特地表干旱遥感监测的技术方法,为石漠化治理监测以及抗旱减灾工作提供技术参考。[方法]运用大气校正法反演地表温度(Ts)和归一化植被指数(NDVI),构建花江峡谷区2013年、2014年和2015年旱季的温度—植被干旱指数(TVDI),并结合地面实测数据对TVDI作为旱情指标进行了验证。[结果](1)反演的TVDI与同时期实测的0—10cm土壤体积含水量数据呈显著的负相关关系(p<0.05)。(2)3个时期的干旱等级以轻旱为主;轻旱、干旱和重旱累计面积占全区比重大,呈现2014年旱情重于2015年和2013年的特点。(3)3个时期的旱情在空间分布上,湿润和正常等级在地形上主要分布在海拔900～1 100m地带,15°～35°的斜坡和缓陡坡,以及阴坡和半阳坡;在石漠化等级上,主要分布在无石漠化区、轻度石漠化区和潜在石漠化区;在土地利用类型中主要分布在有林地、旱地、灌木林地和其他林地。轻旱、干旱和重旱在地形上主要分布在海拔500～900m,6°～25°的缓坡和斜坡,以及阳坡和半阳坡;在石漠化等级上,轻旱和干旱主要分布在轻度石漠化区、潜在石漠化区、中度石漠化区和强度石漠化区,重旱主要分布在非喀斯特区;在土地利用类型上,轻旱、干旱和重旱主要分布在旱地、园地和其他林地。[结论]TVDI可作为研究区的干旱监测指标,基于TVDI和Landsat-8数据的干旱监测方法在喀斯特峡谷区具有一定适用性。
[Objective]To explore the technology and method of remote sensing monitoring of karst surface drought,in order to provide technical reference for the monitoring of rocky desertification control and drought mitigation.[Methods]The atmospheric temperature correction method was used to derive the surface temperature(Ts)and the normalized difference vegetation index(NDVI)to construct the temperature vegetation dryness index(TVDI)of Huajiang gorge in the dry season of 2013,2014 and 2015.The TVDI was validated as a drought indicator based on the ground measured data.[Results](1) The TVDI showed a significant negative correlation with the measured soil water content of 0—10 cm in the same period(p<0.05).(2) Light drought was the main drought grade in the three periods,and the cumulative areas of light drought,drought and heavy drought accounted for a large proportion of the whole region.It showed that the drought in 2014 was heavier than drought in 2015 and 2013.(3) The wet and normal grades were mainly distributed on slopes and gentle steep slopes of 900～1100 mheight above sea leval,slope of 15°～35°,and shady and semi-sunny slopes.In terms of rock desertification,it was mainly distributed in non-rocky desertification areas,light rocky desertification areas and potential rocky desertification areas.Land use types were mainly forest land,dry land,shrubbery land and other forest land.Light drought,drought and heavy drought were mainly distributed on gentle slopes,and slopes of 6°～25°,500～900 mheight as well as sunny and semi-sunny slopes.Light drought and drought were mainly distributed in light desertification area,the potential rocky desertification area,the moderate rocky desertification area and the intensity rocky desertification area.The heavy drought was mainly distributed in the non-karst area.In terms of land use types,the light drought,drought and heavy drought were mainly distributed in dry land,gardens and other wooded land.[Conclusion]TVDI can be used as the drought monitor index in the study area.The drought monitor method based on Landsat-8 data and TVDI is applicable in the karst gorge area.
[Objective]To explore the technology and method of remote sensing monitoring of karst surface drought,in order to provide technical reference for the monitoring of rocky desertification control and drought mitigation.[Methods]The atmospheric temperature correction method was used to derive the surface temperature(Ts)and the normalized difference vegetation index(NDVI)to construct the temperature vegetation dryness index(TVDI)of Huajiang gorge in the dry season of 2013,2014 and 2015.The TVDI was validated as a drought indicator based on the ground measured data.[Results](1) The TVDI showed a significant negative correlation with the measured soil water content of 0—10 cm in the same period(p<0.05).(2) Light drought was the main drought grade in the three periods,and the cumulative areas of light drought,drought and heavy drought accounted for a large proportion of the whole region.It showed that the drought in 2014 was heavier than drought in 2015 and 2013.(3) The wet and normal grades were mainly distributed on slopes and gentle steep slopes of 900～1100 mheight above sea leval,slope of 15°～35°,and shady and semi-sunny slopes.In terms of rock desertification,it was mainly distributed in non-rocky desertification areas,light rocky desertification areas and potential rocky desertification areas.Land use types were mainly forest land,dry land,shrubbery land and other forest land.Light drought,drought and heavy drought were mainly distributed on gentle slopes,and slopes of 6°～25°,500～900 mheight as well as sunny and semi-sunny slopes.Light drought and drought were mainly distributed in light desertification area,the potential rocky desertification area,the moderate rocky desertification area and the intensity rocky desertification area.The heavy drought was mainly distributed in the non-karst area.In terms of land use types,the light drought,drought and heavy drought were mainly distributed in dry land,gardens and other wooded land.[Conclusion]TVDI can be used as the drought monitor index in the study area.The drought monitor method based on Landsat-8 data and TVDI is applicable in the karst gorge area.
引文
[1]Dai Aiguo.Erratum:Drought under global warming:Areview[J].Wiley Interdisciplinary Reviews Climate Change,2011,2(1):45-65.
[2]白力改,燕琴,张丽,等.MODIS干旱指数对华北干旱的敏感性分析[J].干旱区地理,2012,35(5):708-716.
[3]李强子,闫娜娜,张飞飞,等.2010年春季西南地区干旱遥感监测及其影响评估[J].地理学报,2010,65(7):771-780.
[4]Wang Wei,Wang Wenjie,Li Junsheng,et al.The impact of sustained drought on vegetation ecosystem in Southwest China based on remote sensing[J].Procedia Environmental Sciences,2010,2(6):1679-1691.
[5]赵志平,吴晓莆,李果,等.2009-2011年我国西南地区旱灾程度及其对植被净初级生产力的影响[J].生态学报,2015,35(2):350-360.
[6]李阳兵,王世杰,李瑞玲,等.花江喀斯特峡谷地区石漠化成因初探[J].水文地质工程地质,2004,31(6):37-42.
[7]覃换勋.喀斯特石漠化地区水利水保措施优化配套与极度干旱应急调控技术示范[D].贵阳:贵州师范大学,2016.
[8]林巧,王鹏新,张树誉,等.不同时间尺度条件植被温度指数干旱监测方法的适用性分析[J].干旱区研究,2016,33(1):186-192.
[9]Yu Xiaolei,Guo Xulin,Wu Zhaocong.Land surface temperature retrieval from landsat 8 TIRS:Comparison between radiative transfer equation-based method,split window algorithm and single channel method[J].Remote Sensing,2014,6(10):9829-9852.
[10]李兴华,李云鹏,杨丽萍.内蒙古干旱监测评估方法综合应用研究[J].干旱区资源与环境,2014,28(3):162-166.
[11]Price J C.Using spatial context in satellite data to infer regional scale evapotranspiration[J].Ieee Transa-Ctions on Geoscience&Remote Sensing,1990,28(5):940-948.
[12]Carlson T N,Gillies R R,Schmugge T J.An interpretation of methodologies for indirect measurement of soilwater content[J].Agricultural&Forest Meteorology,1995,77(3):191-205.
[13]Sandholt I,Rasmussen K,Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J].Remote Sensing of Environment,2002,79(2):213-224.
[14]荣祁远,何祺胜,刘宝柱.基于Landsat 8数据的干旱监测研究[J].科学技术与工程,2015,15(31):205-211.
[15]姚春生,张增祥,汪潇.使用温度植被干旱指数法(TVDI)反演新疆土壤湿度[J].遥感技术与应用,2004,19(6):473-479.
[16]薛天翼,白建军.基于TVDI和气象数据的陕西省春季旱情时空分析[J].水土保持研究,2017,24(4):240-246.
[17]刘立文,张吴平,段永红,等.TVDI模型的农业旱情时空变化遥感应用[J].生态学报,2014,34(13):3704-3711.
[18]闫娜,李登科,杜继稳,等.基于MODIS产品LST/NDVI/EVI的陕西旱情监测[J].自然灾害学报,2010,19(4):178-182.
[19]伍漫春,丁建丽,王高峰.基于地表温度-植被指数特征空间的区域土壤水分反演[J].中国沙漠,2012,32(1):148-154.
[20]季国华,胡德勇,王兴玲,等.基于Landsat 8数据和温度-植被指数的干旱监测[J].自然灾害学报,2016,25(2):43-52.
[21]张雅梅,熊康宁,安裕伦,等.花江喀斯特峡谷示范区土壤侵蚀调查[J].水土保持通报,2003,23(2):19-22.
[22]喻阳华,秦仕忆,钟欣平.喀斯特干热河谷花椒林母岩化学组成与元素含量随海拔的分异[J].贵州师范大学学报:自然科学版,2018,36(2):9-14.
[23]徐涵秋.Landsat 8热红外数据定标参数的变化及其对地表温度反演的影响[J].遥感学报,2016,20(2):229-235.
[24]田涟祎,周忠发,闫利会.人为干预下喀斯特峡谷区不同土地利用类型对土壤理化性质的影响[J].水土保持通报,2015,35(6):92-96.
[25]田涟祎.石漠化地区土壤性质对不同土地利用方式的响应研究[D].贵阳:贵州师范大学,2016.
[26]Carlson T,Gillies R,Perry E.A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover[J].Remote Sensing Reviews,1994,9(1):161-173.
[27]范辽生,姜纪红,盛晖,等.利用温度植被干旱指数(TVDI)方法反演杭州伏旱期土壤水分[J].中国农业气象,2009,30(2):230-234.
[28]覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004,16(3):28-32.
[29]Sobrino J A,Jiménez-Mu1oz J C,Paolini L.Land surface temperature retrieval from LANDSAT TM 5[J].Remote Sensing of Environment,2004,90(4):434-440.
[30]李小文.遥感原理及其应用[M].北京:科学出版社,2008:109-115.
[31]丁凤,徐涵秋.TM热波段图像的地表温度反演算法与实验分析[J].地球信息科学学报,2006,8(3):125-130.
[32]齐述华,王长耀,牛铮.利用温度植被旱情指数(TVDI)进行全国旱情监测研究[J].遥感学报,2003,7(5):420-427.
[33]李丹,刘丹丹,赵金祥.基于DEM的山区土地利用变化分析[J].水土保持研究,2014,21(1):66-70.
[34]黎景良,后斌,危双峰,等.基于DEM的广东省山区土地利用变化分析[J].测绘通报,2007(6):53-57.
[35]熊康宁,黎平,周忠发.喀斯特石漠化的遥感:GIS典型研究[M].北京:地质出版社,2002.
[36]国家质量监督检验检疫总局,国家标准化管理委员会.土地利用现状分类,中华人民共和国国家标准GB/T21010-2017[S].北京:中国标准出版社,2017.
[37]盈斌.岩溶地区土地利用、石漠化与治理工程设计[D].贵阳:贵州师范大学,2009.
[2]白力改,燕琴,张丽,等.MODIS干旱指数对华北干旱的敏感性分析[J].干旱区地理,2012,35(5):708-716.
[3]李强子,闫娜娜,张飞飞,等.2010年春季西南地区干旱遥感监测及其影响评估[J].地理学报,2010,65(7):771-780.
[4]Wang Wei,Wang Wenjie,Li Junsheng,et al.The impact of sustained drought on vegetation ecosystem in Southwest China based on remote sensing[J].Procedia Environmental Sciences,2010,2(6):1679-1691.
[5]赵志平,吴晓莆,李果,等.2009-2011年我国西南地区旱灾程度及其对植被净初级生产力的影响[J].生态学报,2015,35(2):350-360.
[6]李阳兵,王世杰,李瑞玲,等.花江喀斯特峡谷地区石漠化成因初探[J].水文地质工程地质,2004,31(6):37-42.
[7]覃换勋.喀斯特石漠化地区水利水保措施优化配套与极度干旱应急调控技术示范[D].贵阳:贵州师范大学,2016.
[8]林巧,王鹏新,张树誉,等.不同时间尺度条件植被温度指数干旱监测方法的适用性分析[J].干旱区研究,2016,33(1):186-192.
[9]Yu Xiaolei,Guo Xulin,Wu Zhaocong.Land surface temperature retrieval from landsat 8 TIRS:Comparison between radiative transfer equation-based method,split window algorithm and single channel method[J].Remote Sensing,2014,6(10):9829-9852.
[10]李兴华,李云鹏,杨丽萍.内蒙古干旱监测评估方法综合应用研究[J].干旱区资源与环境,2014,28(3):162-166.
[11]Price J C.Using spatial context in satellite data to infer regional scale evapotranspiration[J].Ieee Transa-Ctions on Geoscience&Remote Sensing,1990,28(5):940-948.
[12]Carlson T N,Gillies R R,Schmugge T J.An interpretation of methodologies for indirect measurement of soilwater content[J].Agricultural&Forest Meteorology,1995,77(3):191-205.
[13]Sandholt I,Rasmussen K,Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J].Remote Sensing of Environment,2002,79(2):213-224.
[14]荣祁远,何祺胜,刘宝柱.基于Landsat 8数据的干旱监测研究[J].科学技术与工程,2015,15(31):205-211.
[15]姚春生,张增祥,汪潇.使用温度植被干旱指数法(TVDI)反演新疆土壤湿度[J].遥感技术与应用,2004,19(6):473-479.
[16]薛天翼,白建军.基于TVDI和气象数据的陕西省春季旱情时空分析[J].水土保持研究,2017,24(4):240-246.
[17]刘立文,张吴平,段永红,等.TVDI模型的农业旱情时空变化遥感应用[J].生态学报,2014,34(13):3704-3711.
[18]闫娜,李登科,杜继稳,等.基于MODIS产品LST/NDVI/EVI的陕西旱情监测[J].自然灾害学报,2010,19(4):178-182.
[19]伍漫春,丁建丽,王高峰.基于地表温度-植被指数特征空间的区域土壤水分反演[J].中国沙漠,2012,32(1):148-154.
[20]季国华,胡德勇,王兴玲,等.基于Landsat 8数据和温度-植被指数的干旱监测[J].自然灾害学报,2016,25(2):43-52.
[21]张雅梅,熊康宁,安裕伦,等.花江喀斯特峡谷示范区土壤侵蚀调查[J].水土保持通报,2003,23(2):19-22.
[22]喻阳华,秦仕忆,钟欣平.喀斯特干热河谷花椒林母岩化学组成与元素含量随海拔的分异[J].贵州师范大学学报:自然科学版,2018,36(2):9-14.
[23]徐涵秋.Landsat 8热红外数据定标参数的变化及其对地表温度反演的影响[J].遥感学报,2016,20(2):229-235.
[24]田涟祎,周忠发,闫利会.人为干预下喀斯特峡谷区不同土地利用类型对土壤理化性质的影响[J].水土保持通报,2015,35(6):92-96.
[25]田涟祎.石漠化地区土壤性质对不同土地利用方式的响应研究[D].贵阳:贵州师范大学,2016.
[26]Carlson T,Gillies R,Perry E.A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover[J].Remote Sensing Reviews,1994,9(1):161-173.
[27]范辽生,姜纪红,盛晖,等.利用温度植被干旱指数(TVDI)方法反演杭州伏旱期土壤水分[J].中国农业气象,2009,30(2):230-234.
[28]覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004,16(3):28-32.
[29]Sobrino J A,Jiménez-Mu1oz J C,Paolini L.Land surface temperature retrieval from LANDSAT TM 5[J].Remote Sensing of Environment,2004,90(4):434-440.
[30]李小文.遥感原理及其应用[M].北京:科学出版社,2008:109-115.
[31]丁凤,徐涵秋.TM热波段图像的地表温度反演算法与实验分析[J].地球信息科学学报,2006,8(3):125-130.
[32]齐述华,王长耀,牛铮.利用温度植被旱情指数(TVDI)进行全国旱情监测研究[J].遥感学报,2003,7(5):420-427.
[33]李丹,刘丹丹,赵金祥.基于DEM的山区土地利用变化分析[J].水土保持研究,2014,21(1):66-70.
[34]黎景良,后斌,危双峰,等.基于DEM的广东省山区土地利用变化分析[J].测绘通报,2007(6):53-57.
[35]熊康宁,黎平,周忠发.喀斯特石漠化的遥感:GIS典型研究[M].北京:地质出版社,2002.
[36]国家质量监督检验检疫总局,国家标准化管理委员会.土地利用现状分类,中华人民共和国国家标准GB/T21010-2017[S].北京:中国标准出版社,2017.
[37]盈斌.岩溶地区土地利用、石漠化与治理工程设计[D].贵阳:贵州师范大学,2009.