引用本文:彭 婕,于 婧※,陈唐冰莹,聂 艳.阿克苏流域表层土壤湿度指数反演研究[J].中国农业信息,2019,31(3):79-88
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阿克苏流域表层土壤湿度指数反演研究
彭 婕1, 于 婧※1, 陈唐冰莹1, 聂 艳2
1.湖北大学资源环境学院,武汉430062;2.华中师范大学地理过程分析与模拟湖北省重点实验室,武汉430079
摘要:
【目的】为研究国产高分一号(GF-1)遥感影像在绿洲地区农情基础数据有效采集的可行性,对土壤湿度实施大范围区域监测。【方法】以新疆阿克苏流域为研究区,基于GF-1 WFV 影像以及研究区63 个土壤表层湿度的实测样点数据,对垂直干旱指数(PDI)和植被调整垂直干旱指数(VAPDI)的土壤湿度监测效果进行比较和验证。【结果】(1)PDI和VAPDI 与土壤湿度实测值的决定系数分别为0.589 和0.735,各模型满足监测精度要求;(2)在植被覆盖较高的阿克苏绿洲,VAPDI 指数模型监测精度高于PDI;(3)从反演的土壤湿度空间分布格局来看,VAPDI 对土壤湿度变化更敏感,更能反映出不同植被覆盖程度下土壤湿度的实际水平。【结论】基于GF-1 WFV 影像进行流域尺度的土壤湿度监测具有可行性。相比PDI 指数模型,VAPDI 通过对遥感影像中混合像元进行不同程度的分解,监测精度更高。研究结果能为阿克苏流域表层土壤湿度数据快速有效地采集和动态监测提供理论支持和验证。
关键词:  高分一号  土壤湿度  PDI  VAPDI  阿克苏流域
DOI:10.12105/j.issn.1672-0423.20190308
分类号:
基金项目:农业农村部农业遥感重点实验室开放课题(2016002);华中师范大学重要高校基本科研业务费(CCNU18TS002)
Research on surface soil moisture index inversion in Aksu River
Peng Jie1, Yu Jing※1, Chen Tangbingying1, Nie Yan2
1.College of Resources and Environment,Hubei University,Wuhan 430062,China;2.Hubei Provincial Key Laboratory for Geographical Process Analysis and Simulation,Central China Normal University,Wuhan 430062,China
Abstract:
[Purpose]Soil moisture remote sensing monitoring plays an important role in agricultural production. The wide-area regional monitoring of soil moisture was carried out by using the domestic Gaofen 1(GF-1)remote sensing data,and the applicability of different index inversion models in the rapid acquisition of agricultural parameters in the oasis area was discussed.[ Method]The Xinjiang Aksu Basin was adopted as the study area. Based on the GF-1 WFV image and the measured sampling point data of 63 soil surface moisture in the study area,the effects of soil moisture monitoring on vertical drought index(PDI)and vegetation adjusted vertical drought index(VAPDI)were compared and verified.[ Result](1)The determination coefficients of PDI and VAPDI for soil moisture measured values are 0.589 and 0.735,respectively,and each model can meet the monitoring accuracy requirements.( 2)In the Aksu Oasis with high vegetation coverage,the VAPDI index model has higher monitoring accuracy than PDI(. 3)From the spatial distribution pattern of soil moisture inversion,VAPDI is more sensitive to soil moisture changes,and more reflects the actual level of soil moisture under different vegetation coverage.[ Conclusion]It is feasible to carry out soil moisture monitoring at the basin scale based on GF-1 WFV image. Compared with the PDI index model,VAPDI has higher monitoring accuracy by differently decomposing mixed pixels in remote sensing images. The research results can provide theoretical basis and practical reference for the rapid acquisition and dynamic monitoring of surface soil moisture in the Aksu Basin.
Key words:  GF-1  soil moisture  PDI  VAPDI  Aksu River Basin