Microwave remote sensing of soil moisture with vegetation effect

被引:0
|
作者
Tsegaye, T [1 ]
Inguva, R [1 ]
Lang, RH [1 ]
O'Neill, PE [1 ]
Fahsi, A [1 ]
Coleman, TL [1 ]
Tadesse, W [1 ]
Rajbhandari, N [1 ]
Aburemie, SA [1 ]
de Matthaeis, P [1 ]
机构
[1] Alabama A&M Univ, Ctr Hydrol Soil Climatol & Remote Sensing, Normal, AL 35762 USA
关键词
modeling; soil moisture; backscatter; brightnness temperature; radiative transfer model (RTM); discrete backscatter approach;
D O I
10.1117/12.373132
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
The objectives of this study were: to examine the sensitivity of radar backscatter, to estimate soil moisture under a corn plot and to evaluate the effectiveness and sensitivity of a Radiative Transfer Model (RTM), adapted from the earlier work of Njoku and Kong, (1977) in predicting brightness temperature from a grass plot. Microwave radar measurements were collected from plots of different vegetation cover types, vegetation density, and moisture conditions during the Huntsville 1998 field experiment. A large amount of ground data on brightness temperatures, soil moisture, and vegetation characteristics (e.g., biomass, and water content) were collected. The experiments were conducted at Alabama A&M University's, Winfred Thomas Agricultural Research Station, located near Hazel Green, Alabama. Six plots, one 50 X 60 m smooth bare plot, one 50 X 60 m grass plot, and four 30 X 50 m corn plots at full, 2/3, In, and 1/3 densities were used. Radar backscatter data were obtained from a ground based truck mounted radar operating at L, C, and X bands (1.6, 4.75, and 10 GHz) with four linear polarization HH, HV, VV, and VH and two incidence angles (15 and 45 degrees). Soil moisture values were determined using Water Content Reflectometry (WCR). Three types of soil temperature sensors (Infrared Thermometer, Thermistor, and a 4-sensor averaging thermocouple probes) were used. A discrete backscatter approach model and RTM were evaluated. Comparisons between model prediction and experimental observation for HH polarization indicated good agreement for a corn full plot. The direct-reflected scattering coefficient is found to be the most dominant term for both polarization and the backscatter is also highly sensitive to soil moisture. The trends in time variation of brightness temperature are in agreement with the experimental results and the numerical results are within a few percent of the experimental results. The vegetation corrections as estimated by the Jackson and Schmugge method are very small. Detailed examination of the vegetation canopy contribution including the geometry of the canopy, the various absorption and scattering mechanisms are necessary.
引用
收藏
页码:36 / 47
页数:12
相关论文
共 50 条
  • [31] Passive Microwave Remote Sensing of Soil Moisture Based on Dynamic Vegetation Scattering Properties for AMSR-E
    Du, Jinyang
    Kimball, John S.
    Jones, Lucas A.
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2016, 54 (01): : 597 - 608
  • [32] PASSIVE MICROWAVE SENSING OF SOIL-MOISTURE UNDER VEGETATION CANOPIES
    JACKSON, TJ
    SCHMUGGE, TJ
    WANG, JR
    [J]. WATER RESOURCES RESEARCH, 1982, 18 (04) : 1137 - 1142
  • [33] Effect of soil moisture and crop cover in remote sensing
    Singh, D
    Mukherjee, PK
    Sharma, SK
    Singh, KP
    [J]. SATELLITE DATA FOR ATMOSPHERE, CONTINENT AND OCEAN RESEARCH, 1996, 18 (07): : 63 - 66
  • [34] Study on the retrieval of soil moisture by active and passive microwave remote sensing
    Wu, Qian
    Zhang, Chengming
    Yu, Fan
    Zhang, Chao
    Gong, Wenwen
    [J]. 2016 FIFTH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS), 2016, : 359 - 362
  • [35] STATUS OF MICROWAVE SOIL-MOISTURE MEASUREMENTS WITH REMOTE-SENSING
    ENGMAN, ET
    CHAUHAN, N
    [J]. REMOTE SENSING OF ENVIRONMENT, 1995, 51 (01) : 189 - 198
  • [36] Retrieving Surface and Rootzone Soil Moisture Using Microwave Remote Sensing
    Thaggahalli Nagaraju, Santhosh Kumar
    Pathak, Abhishek A.
    [J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2024, 52 (07) : 1415 - 1430
  • [37] Multispectral and Microwave Remote Sensing Models to Survey Soil Moisture and Salinity
    Periasamy, Shoba
    Shanmugam, Ramakrishnan S.
    [J]. LAND DEGRADATION & DEVELOPMENT, 2017, 28 (04) : 1412 - 1425
  • [38] Operational readiness of microwave remote sensing of soil moisture for hydrologic applications
    Wagner, Wolfgang
    Bloeschl, Guenter
    Pampaloni, Paolo
    Calvet, Jean-Christophe
    Bizzarri, Bizzarro
    Wigneron, Jean-Pierre
    Kerr, Yann
    [J]. NORDIC HYDROLOGY, 2007, 38 (01) : 1 - 20
  • [39] Multifrequency ground-based microwave remote sensing of soil moisture
    Laymon, CA
    Crosson, WL
    Soman, VV
    Jackson, TJ
    Manu, A
    Tsegaye, TD
    [J]. IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, : 2420 - 2422
  • [40] Soil Moisture Retrieval by Active/Passive Microwave Remote Sensing Data
    Wu, Shengli
    Yang, Lijuan
    [J]. REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XIV, 2012, 8531