NIR-red spectra space based new method for soil moisture monitoring

被引:52
|
作者
Zhan ZhiMing
Qin QiMing [1 ]
Ghulan Abduwasit
Wang DongDong
机构
[1] Peking Univ, Inst Remote Sensing & GIS, Beijing 100871, Peoples R China
[2] Environm Protect Bur Dongcheng Dist, Beijing 100007, Peoples R China
来源
关键词
NIR-red spectral space; soil moisture; quantitative remote sensing; soil drought; remote monitoring of soil moisture;
D O I
10.1007/s11430-007-2004-6
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Drought is a complex natural disaster that occurs frequently. Soil moisture has been the main issue in remote monitoring of drought events as the most direct and important variable describing the drought. Spatio-temporal distribution and variation of soil moisture evidently affect surface evapotranspiration, agricultural water demand, etc. In this paper, a new simple method for soil moisture monitoring is developed using near-infrared versus red (NIR-red) spectral reflectance space. First, NIR-red spectral reflectance space is established using atmospheric and geometric corrected ETM+ data, which is manifested by a triangle shape, in which different surface covers have similar spatial distribution rules. Next, the model of soil moisture monitoring by remote sensing (SMMRS) is developed on the basis of the distribution characteristics of soil moisture in the NIR-red spectral reflectance space. Then, the SMMRS model is validated by comparison with field measured soil moisture data at different depths. The results showed that satellite estimated soil moisture by SMMRS is highly accordant with field measured data at 5 cm soil depth and average soil moisture at 0-20 cm soil depths, correlation coefficients are 0.80 and 0.87, respectively. This paper concludes that, being simple and effective, the SMMRS model has great potential to estimate surface moisture conditions.
引用
收藏
页码:283 / 289
页数:7
相关论文
共 50 条
  • [21] Study on the Mobile PHS Method for Soil Moisture Monitoring Based on Thermal Effect
    He, Fengfei
    Zhang, Chanqing
    Chen, Jiang
    Xiong, Feng
    IEEE SENSORS JOURNAL, 2021, 21 (13) : 15209 - 15217
  • [22] A New Non-parametric Bayesian Based Space Upscaling Method for In-situ Soil Moisture Sampling
    Zhu, Lu
    Yue, Chaozheng
    Liu, Yuanyuan
    Xiong, Guang
    2017 PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM - FALL (PIERS - FALL), 2017, : 2629 - 2634
  • [23] MONITORING OF SOIL MOISTURE USING THE BALANCE METHOD AND GIS
    Craciun, A. I.
    GEOGRAPHIA TECHNICA, 2008, 3 (02): : 8 - 15
  • [24] A New Method for Predicting Soil Moisture Based on UAV Hyperspectral Image
    Ge Xiang-yu
    Ding Jian-li
    Wang Jing-zhe
    Sun Hui-lan
    Zhu Zhi-qiang
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40 (02) : 602 - 609
  • [25] Determining the dry boundary of the LST/FVC space for soil moisture monitoring: a semi-empirical method
    Sun, Hao
    Ma, Liru
    Wang, Yanmei
    Zhou, Baichi
    Liu, Weihan
    Cai, Chuangchuang
    Zhou, Wei
    Chen, Wei
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2020, 41 (10) : 3723 - 3739
  • [26] New Index for Soil Moisture Monitoring Based on ΔTs-Albedo Spectral Information
    Yao Yun-jun
    Qin Qi-ming
    Zhao Shao-hua
    Shen Xin-yi
    Sui Xin-xin
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31 (06) : 1557 - 1561
  • [27] OLCI-based NIR-red models for estimating chlorophyll-aconcentration in productive coastal waters-a preliminary evaluation
    Moses, Wesley J.
    Saprygin, Vladislav
    Gerasyuk, Victoria
    Povazhnyy, Vasiliy
    Berdnikov, Sergey
    Gitelson, Anatoly A.
    ENVIRONMENTAL RESEARCH COMMUNICATIONS, 2019, 1 (01):
  • [28] An IoT Based Soil Moisture Monitoring on Losant Platform
    Kodali, Ravi Kishore
    Sahu, Archana
    PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING AND INFORMATICS (IC3I), 2016, : 764 - 768
  • [29] Ground-Based GPS for Soil Moisture Monitoring
    Zhao, Guisheng
    Zhang, Shuangcheng
    Zhang, Qin
    Zhang, Jingjiang
    Wang, Lifu
    Wang, Tao
    CHINA SATELLITE NAVIGATION CONFERENCE (CSNC) 2019 PROCEEDINGS, VOL I, 2019, 562 : 14 - 22
  • [30] IMPROVED SOIL MOISTURE MONITORING BASED ON EVAPOTRANSPIRATION AND NDVI
    Zhao, Long
    Xing, Xuguang
    Chen, Chaofei
    Zhang, Kun
    Ma, Xiaoyi
    FRESENIUS ENVIRONMENTAL BULLETIN, 2018, 27 (10): : 6640 - 6652