CHEN Mingxing,ZHANG Yuhu.Retrieval of Soil Moisture in Sanjiang Plain Based on TVDI Model with Four Vegetation Indices[J].Research of Soil and Water Conservation,2019,26(03):93-100,107.
基于4种植被指数TVDI模型的三江平原土壤湿度反演
- Title:
- Retrieval of Soil Moisture in Sanjiang Plain Based on TVDI Model with Four Vegetation Indices
- Keywords:
- TVDI; vegetation Index; soil moisture; precipitation; Sanjiang Plain
- 分类号:
- TP79
- 摘要:
- 利用遥感手段监测土壤湿度有利于分析大尺度区域的土壤干湿状况。比对分析不同植被指数计算的温度植被干旱指数（TVDI）的精度能够提高TVDI反演土壤湿度的实际应用价值。以三江平原为研究区，基于2013年5—9月的四期MODIS影像，利用归一化植被指数（NDVI）、增强型植被指数（EVI）、修正土壤调节植被指数（MSAVI）、比值植被指数（RVI）分别计算TVDI，并以地面实测土壤湿度数据及降水数据进行精度验证。结果表明：（1）4种植被指数计算的TVDI与土壤湿度数据均具有一定的负相关关系，即TVDI值越高，土壤湿度值越低；（2）不同植被指数计算的TVDI在5月、6月、9月与土壤湿度回归分析的R2数值相近，均适合用来反演这3个时间段的土壤湿度，在7月份，相较于NDVI和RVI计算的TVDI结果（R2均在0.15左右），基于EVI和MSAVI计算的TVDI （R2均在0.35左右）更适合反演该时期的土壤湿度；（3）5—9月期间，干旱现象主要发生在三江平原的中部及西南部，干旱程度主要为轻旱，东部及东北部在不同时期基本保持在正常或轻微湿润状态。
- Abstract:
- The use of remote sensing to monitor soil moisture is conducive to the analysis of soil moisture conditions in large-scale areas. Comparing and analyzing the accuracy of the Temperature Vegetation Dryness Index (TVDI) calculated under different vegetation indices can increase the practical value of TVDI on retrieval of soil moisture. There are four vegetation indices, including NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), MSAVI (Modified Soil Adjusted Vegetation Index), RVI(Ratio Vegetation Index), were respectively used to construct LST-Ⅵ feature space and calculate TVDI by combining with land surface temperature data. The results indicated that:(1) all the TVDIs calculated by different vegetation indices presented the negative correlations with soil moisture data, that is, the higher the TVDI value, the lower the soil moisture value; (2) the values of R2 of regression analysis between soil moisture data and TVDI based on different vegetation indices were similar in May, June and September, and they were all suitable for retrieving soil moisture in these three periods; in July, compared to the TVDI results calculated by NDVI and RVI (R2 is around 0.15), TVDI based on EVI and MSAVI (R2 is around 0.35) was more suitable for retrieving soil moisture in this period; (3) from May to September, the drought mainly occurred in the central and southwest parts of the Sanjiang Plain, and the degree of drought was mainly mild drought. The eastern and northeastern parts remained basically normal or slightly humid in different periods.
参考文献/References:
[1] 郭广猛,赵冰茹.使用MODIS数据监测土壤湿度[J].土壤,2004,36(2):219-221.
[2] Martínez-Fernández J, González-Zamora A, Sánchez N, et al. Satellite soil moisture for agricultural drought monitoring:Assessment of the SMOS derived Soil Water Deficit Index[J]. Remote Sensing of Environment, 2016,177:277-286.
[3] 安雪丽,武建军,周洪奎,等.土壤相对湿度在东北地区农业干旱监测中的适用性分析[J].地理研究,2017,35(5):837-849.
[4] Carrão H, Russo S, Sepulcre-Canto G, et al. An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data[J]. International Journal of Applied Earth Observation and Geoinformation, 2016,48:74-84.
[5] 张喆,丁建丽,李鑫,等. TVDI用于干旱区农业旱情监测的适宜性[J].中国沙漠,2015,35(1):220-227.
[6] 于健,杨国范,王颖,等.基于MODIS数据反演阜新地区土壤水分的研究[J].遥感技术与应用,2011,26(4):413-419.
[7] Qin J, Yang K, Lu N, et al. Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia[J]. Remote Sensing of Environment, 2013,138:1-9.
[8] Holzman M E, Rivas R, Piccolo M C. Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index[J]. International Journal of Applied Earth Observation and Geoinformation, 2014,28:181-192.
[9] 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.
[10] Zhou L, Zhang J, Wu J, et al. Comparison of remotely sensed and meteorological data-derived drought indices in mid-eastern China[J]. International Journal of Remote Sensing, 2012,33(6):1755-1779.
[11] 倪波顺,高阳华,李月臣,等.基于FY-3A/VIRR数据的重庆市干旱监测研究[J].西南大学学报:自然科学版,2014,36(7):143-148.
[12] 高炜,安如,王喆.基于微波遥感技术的干旱监测指数及其应用研究:以三江源区为例[J].干旱区研究,2017,34(3):541-550.
[13] 黄对,王文.基于粗糙度定标的IEM模型的土壤含水率反演[J].农业工程学报,2014,30(19):182-190.
[14] 王学,刘全明,屈忠义,等.盐渍化土壤水分微波雷达反演与验证[J].农业工程学报,2017,33(11):108-114.
[15] 闫峰,覃志豪,李茂松,等.农业旱灾监测中土壤水分遥感反演研究进展[J].自然灾害学报,2006,16(6):114-121.
[16] 郭茜,李国春.用表观热惯量法计算土壤含水量探讨[J].中国农业气象,2005,26(4):13-17.
[17] 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.
[18] 曹雷,丁建丽,牛增懿.基于TVDI的艾比湖地区土壤水分时空变化分析[J].水土保持研究,2016,23(3):43-47.
[19] Chen J, Wang C, Jiang H, et al. Estimating soil moisture using Temperature-Vegetation Dryness Index(TVDI)in the Huang huai-hai(HHH)plain[J]. International Journal of Remote Sensing, 2011,32(4):1165-1177.
[20] Li Z, Wang Y, Zhou Q, et al. Spatiotemporal variability of land surface moisture based on vegetation and temperature characteristics in Northern Shaanxi Loess Plateau, China[J]. Journal of Arid Environments, 2008,72(6):974-985.
[21] Son N T, Chen C F, Chen C R, et al. Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data[J]. International Journal of Applied Earth Observation and Geoinformation, 2012,18:417-427.
[22] Patel N R, Anapashsha R, Kumar S, et al. Assessing potential of MODIS derived temperature/vegetation condition index(TVDI)to infer soil moisture status[J]. International Journal of Remote Sensing, 2009,30(1):23-39.
[23] 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.
[24] 杨玲,杨艳昭.基于TVDI的西辽河流域土壤湿度时空格局及其影响因素[J].干旱区资源与环境,2016,30(2):76-81.
[25] 朱明宇.基于MODIS数据对辽宁地区农业干旱的监测研究[D].沈阳:沈阳农业大学,2017.
[26] 李海霞,杨井,陈亚宁,等.基于MODIS数据的新疆地区土壤湿度反演[J].草业学报,2017,26(6):16-27.
[27] 胡屾,刘骏,毛学刚.中国东北地区2007—2010年植被覆盖度及其变化[J].东北林业大学学报,2017,45(7):45-50.
[28] 李新辉,宋小宁,周霞.半干旱区土壤湿度遥感监测方法研究[J].地理与地理信息科学,2010,26(1):90-93.
[29] 陈斌,张学霞,华开,等.温度植被干旱指数(TVDI)在草原干旱监测中的应用研究[J].干旱区地理,2013,36(5):930-937.
[30] 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.
[31] 王丹,南瑞,韩俊杰,等.黑龙江省土壤湿度及其对气温和降水的敏感性分析[J].气象与环境学报,2012,28(2):49-53.
[32] Liyang L, Jishan L, Xiuzhi C, et al. The Microwave Temperature Vegetation Drought Index(MTVDI)based on AMSR-E brightness temperatures for long-term drought assessment across China(2003—2010)[J]. Remote Sensing of Environment, 2017,199:302-320.
[33] 薛飞.利用风云卫星数据的东北地区土地覆盖监测研究[D].成都:电子科技大学,2017.
[34] 孙舒婷.大兴安岭森林地表温度的遥感估算及分析研究[D].哈尔滨:东北林业大学,2015.
相似文献/References:
[1]杨勤科,罗万勤,马宏斌,等.区域水土流失植被因子的遥感提取[J].水土保持研究,2006,13(05):267.
YANG Qing-ke,LUO Wan-qin,MA Hong-bin,et al.NDVI Extraction of Regional Soil Erosion Based on Remate Sensing[J].Research of Soil and Water Conservation,2006,13(03):267.
[2]马驰,卢玉东.重庆南部TM图像植被指数与植被覆盖度信息的关系研究[J].水土保持研究,2008,15(06):136.
MA Chi,LU Yu-dong.The Correlation Between Percentage of Vegetation Cover and Normalized Difference Vegetation Index in the South of Chongqing City[J].Research of Soil and Water Conservation,2008,15(03):136.
[3]张佳,温仲明,杨尚斌.基于自然植被的延河流域生物量空间分布格局评估[J].水土保持研究,2010,17(03):35.
ZHANG Jia,WEN Zhong-ming,YANG Shang-bin.Spatial Distribution Evaluation of Biomass in Yanhe River Catchment Using Natural Ecosystem as a Reference[J].Research of Soil and Water Conservation,2010,17(03):35.
[4]马延辉,林辉,孙华.湖南省主要森林类型植被指数动态变化分析[J].水土保持研究,2010,17(03):217.
MA Yan-hui,LIN Hui,SUN Hua.Variation Analysis of Different Forest Types Vegetation Index in HU’nan Province[J].Research of Soil and Water Conservation,2010,17(03):217.
[5]赵广敏,李晓燕,李宝毅.基于地表温度和植被指数特征空间的农业干旱遥感监测方法研究综述[J].水土保持研究,2010,17(05):245.
ZHAO Guang-min,LI Xiao-yan,LI Bao-yi.An Overview on Agricultural Drought Montoring Methods Based on Land Surface Temperature and Vegetation Index Feature Space[J].Research of Soil and Water Conservation,2010,17(03):245.
[6]陆广勇,杨勤科,王海江.基于MODIS-NDVI时序数据的黄土丘陵区土地覆盖分类研究[J].水土保持研究,2011,18(02):112.
LU Guang-yong,YANG Qin-ke,WANG Hai-jiang.Land Cover Classification in Loess Hilly and Gully Region Using Multi-temporal MODIS-NDVI Data[J].Research of Soil and Water Conservation,2011,18(03):112.
[7]何磊,唐姝娅,苗放,等.岷江上游典型流域叶面积指数的遥感模型及反演[J].水土保持研究,2010,17(01):218.
HE Lei,TANG Shu-ya,MIAO Fang,et al.Remote Sensing Model and Inversion of Leaf Area Index in the Typical Area of Minjiang Valley Upriver[J].Research of Soil and Water Conservation,2010,17(03):218.
[8]刘倩楠,欧阳志云,李爱农,等.重庆市森林植被生物量和碳储量的空间分布特征研究[J].水土保持研究,2016,23(06):221.
LIU Qiannan,OUYANG Zhiyun,LI Ainong,et al.Study on Spatial Differentiation Characteristics of Forest Vegetation Biomass and Carbon Stock in Chongqing City[J].Research of Soil and Water Conservation,2016,23(03):221.
[9]王蕾钦,王飞,李朋飞.相似降水年组下黄土高原植被恢复与土壤水分变化过程与空间特征分析[J].水土保持研究,2017,24(06):179.
WANG Leiqin,WANG Fei,LI Pengfei.Relationships Between Vegetation Restoration and Soil Moisture on the Loess Plateau[J].Research of Soil and Water Conservation,2017,24(03):179.
[10]张巧凤,刘桂香,于红博,等.锡林郭勒草原蒸散发月季动态及相关因子分析[J].水土保持研究,2017,24(03):164.
ZHANG Qiaofeng,LIU Guixiang,YU Hongbo,et al.Monthly and Seasonal Dynamics of ET in Xilingol Steppe and Related Factors Analysis[J].Research of Soil and Water Conservation,2017,24(03):164.
备注/Memo
收稿日期:2018-06-01;改回日期:2018-07-20。
基金项目:国家重点研发计划项目大面积农业灌溉的地表水与地下水联合调控（2017YFC0406002）
作者简介:陈明星(1995-),男,湖北武汉人,硕士研究生,主要从事农业干旱遥感监测研究。E-mail:Chen_mingxing0126@163.com
通讯作者:张玉虎(1975-),男,江苏徐州人,副教授,主要从事环境系统分析及风险评估研究。E-mail:zhang_yuhu@163.com