资助项目:国家自然科学基金(U1612441,41661088); 贵州高层次创新型人才培养计划——“百”层次人才(黔科合平台人才〔2016〕5674)
第一作者:李永柳(1996—),女,重庆南川人,硕士研究生,研究方向为地理信息系统与遥感。E-mail:1141481344@qq.com 通信作者:周忠发(1969—),男,贵州遵义人,教授,博导,主要从事喀斯特生态环境、地理信息系统与遥感研究。E-mail:fa6897@163.com
为了获取黔中水利工程区土壤含水量的变化情况,基于2013—2018年的Landsat 8地表温度产品数据(LST)和植被指数产品数据(NDVI),采用植被供水指数(VSWI)法,反演研究区不同年份土壤含水量,结合实测数据进行精度验证,探讨了研究区土壤含水量分布的时空异质性及主要影响因素。结果 表明:(1)基于Landsat 8影像反演的土壤含水量和实测数据具有较好的正相关性,表明Landsat 8影像适于研究区土壤含水量反演;(2)2013—2018年研究区土壤含水量在时间上表现出波动升高的趋势,年平均增速为0.91%,在空间上呈现出西南部高、东北部低的趋势,以湿润为主;(3)6年来研究区平均土壤含水量类型发生明显的变化,其面积变化幅度以增加为主;(4)研究区土壤含水量与温度均呈中度负相关,而与降雨量在毕节等部分地区呈高度正相关,在其余地区则呈中度正相关。利用Landsat 8遥感影像数据和植被供水指数(VSWI)可以实现研究区的土壤含水量反演,研究结果可为该地区土壤含水量动态监测和改善区域生态环境提供科学依据。
In order to obtain the changes of soil moisture in the zone of Qianzhong Water Diversion Project area, based on Landsat 8 surface temperature data(LST)and vegetation index data(NDVI)from 2013 to 2018, the inversion analysis on the soil moisture contents in different years in the Qianzhong Water Diversion Project area was carried out based on the vegetation water supply index(VSWI), and the accuracy of inversion was verified with measured soil moisture data, the space-time heterogeneity of soil moisture distribution and the main influencing factors in the study area were discussed. The results showed that:(1)correlation between soil moisture resulted from Landsat 8 data inversion and the measured soil moisture was significant, suggesting that Landsat 8 data is suitable for soil moisture inversion in the study area;(2)the soil moisture content in the study area showed the tendency of fluctuating increase in the period from 2013 to 2018, the average annual growth rate was 0.91%, showing the trend of high soil moisture in the southwest and the lower soil moisture in the northeast in terms of the spatial distribution;(3)the types of average soil water contents in the study area had changed significantly in the last six years, the area with the change of soil water content mainly increased;(4)in the period 2013—2018, the soil moisture in the study area was moderately negatively correlated with temperature, significantly positively correlated with rainfall in parts of Bijie area, and moderately positively correlated with rainfall in the rest of the regions. The soil moisture inversion of the study area can be realized by Landsat 8 data and VSWI, and the results can provide the reference for soil moisture monitoring in this area.