HIGH-RESOLUTION SOIL MOISTURE MAPPING IN AFGHANISTAN

被引:3
|
作者
Hendrickx, Jan M. H. [1 ]
Harrison, J. Bruce J. [1 ]
Borchers, Brian [1 ]
Kelley, Julie R. [2 ]
Howington, Stacy [2 ]
Ballard, Jerry [2 ]
机构
[1] New Mexico Inst Min & Technol, Socorro, NM 87801 USA
[2] Engineer Res & Dev Ctr Army Corps Engineers, Coastal & Hydraul Lab, Vicksburg, MS 39180 USA
关键词
soil moisture; Landsat; QuickBird; IED; Helmand; Afghanistan; ENERGY BALANCE ALGORITHM; MODEL; EVAPOTRANSPIRATION; ZONE; ASSIMILATION; VARIABILITY; CALIBRATION; SIGNATURES; LANDMINES; FLUXES;
D O I
10.1117/12.887255
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1-4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations
    Fan, Lei
    Xiao, Qing
    Wen, Jianguang
    Liu, Qiang
    Jin, Rui
    You, Dongqing
    Li, Xiaowen
    REMOTE SENSING, 2015, 7 (10): : 13273 - 13297
  • [42] HIGH RESOLUTION MAPPING OF SOIL MOISTURE BY SAR: DATA INTEGRATION AND EXPLOITATION OF PRIOR INFORMATION
    Pierdicca, N.
    Pulvirenti, L.
    Bignami, C.
    Ticconi, F.
    Laurenti, M.
    2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 3340 - +
  • [43] Soil Moisture Estimation Using High-Resolution Spotlight TerraSAR-X Data
    Kseneman, Matej
    Gleich, Dusan
    Cucej, Zarko
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2011, 8 (04) : 686 - 690
  • [44] GLEMOK - NOVEL METHOD FOR CATCHMENT MOISTURE DETERMINATION USING HIGH-RESOLUTION SOIL MAP
    Baziak, B.
    Gadek, W.
    Szczepanek, R.
    APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2019, 17 (06): : 12667 - 12681
  • [45] Synergistic Effects of High-Resolution Factors for Improving Soil Moisture Simulations Over China
    Ji, Peng
    Yuan, Xing
    Jiao, Yang
    WATER RESOURCES RESEARCH, 2023, 59 (12)
  • [46] High-resolution European daily soil moisture derived with machine learning (2003–2020)
    Sungmin O
    Rene Orth
    Ulrich Weber
    Seon Ki Park
    Scientific Data, 9
  • [47] Combining Proximal and Penetrating Soil Electrical Conductivity Sensors for High-Resolution Digital Soil Mapping
    Myers, D. B.
    Kitchen, N. R.
    Sudduth, K. A.
    Grunwald, S.
    Miles, R. J.
    Sadler, E. J.
    Udawatta, R. P.
    PROXIMAL SOIL SENSING, 2010, : 233 - +
  • [48] Intercomparison of very high-resolution surface soil moisture products over Catalonia (Spain)
    Ouaadi, Nadia
    Jarlan, Lionel
    Le Page, Michel
    Zribi, Mehrez
    Paolini, Giovani
    Hssaine, Bouchra Ait
    Escorihuela, Maria Jose
    Fanise, Pascal
    Merlin, Olivier
    Baghdadi, Nicolas
    Boone, Aaron
    REMOTE SENSING OF ENVIRONMENT, 2024, 309
  • [49] High-resolution digital soil mapping of multiple soil properties: an alternative to the traditional field survey?
    Flynn, Trevan
    de Clercq, Willem
    Rozanov, Andrei
    Clarke, Cathy
    SOUTH AFRICAN JOURNAL OF PLANT AND SOIL, 2019, 36 (04) : 237 - 247
  • [50] A Bayesian Deep Image Prior Downscaling Approach for High-Resolution Soil Moisture Estimation
    Fang, Yuan
    Xu, Linlin
    Chen, Yuhao
    Zhou, Wei
    Wong, Alexander
    Clausi, David A.
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2022, 15 : 4571 - 4582