GIS / Remote Sensing Tag

GIS / Remote Sensing is one of more than 16 discipline tags that we use to categorize and aggregate our interdisciplinary information within and across CZOs. Much of our information has been tagged with 2-3 disciplines.

NATIONAL GIS / Remote Sensing >

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  • IML People - GIS / Remote Sensing

    7 People

    Donald Keefer

    INVESTIGATOR

    .(JavaScript must be enabled to view this email address), 217-244-2786

    Heterogeneities in Geologic Systems, Hydrogeology of Glacial Sediments, Uncertainty in Geologic Data

    Quinn Lewis

    GRAD STUDENT

    .(JavaScript must be enabled to view this email address)
    Univ of Illinois
    Geography and Geographic Information Science

    Yu-Feng Lin

    INVESTIGATOR

    .(JavaScript must be enabled to view this email address), 217-333-0235

    Hydrogeology and Geophysics

    Joshua Peschel

    INVESTIGATOR

    .(JavaScript must be enabled to view this email address), 217-419-2571

    Soil and water engineering, geographical information systems, and robotics

    Andrew Stumpf

    INVESTIGATOR

    .(JavaScript must be enabled to view this email address), 217-244-6462
    ISGS
    Quaternary and Engineering Geology

    Kunxuan Wang

    GRAD STUDENT

    PhD student, University of Illinois, Civil and Environmental Engineering


    Univ of Illinois
    Engineering and remote sensing, hydrology

    Mingjing Yu

    GRAD STUDENT

    .(JavaScript must be enabled to view this email address)
    Univ of Illinois
    Geography and Geographic Information Science

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  • IML Research Groups - GIS / Remote Sensing


    Multiple Disciplines >

  • IML Data - GIS / Remote Sensing

    No datasets with this discipline tag have been entered yet

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  • IML Models - GIS / Remote Sensing

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  • IML Publications - GIS / Remote Sensing

    2016

    Characterizing Vegetation Canopy Structure Using Airborne Remote Sensing Data. Dutta, D., Wang, K., Lee, E., Goodwell, A., Woo, D.K., Wagner, D., and Kumar, P. (2016): IEEE Transactions on Geoscience and Remote Sensing

    2015

    Using field and remotely sensed hyperspectral data to quantify water quality parameters in the Wabash River and its tributary, Indiana. Tan, J., K.A. Cherkauer, and I. Chaubey (2015): International Journal of Remote Sensing 36 (21): 5466-5484

    2014

    Prediction of Saturated Hydraulic Conductivity Dynamics in an Iowan Agriculture Watershed. Elhakeem, M., Papanicolaou, A.N., Wilson, C., and Chang, Y. (2014): International Journal of Biological, Veterinary, Agricultural, and Food Engineering

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  • IML Events - GIS / Remote Sensing

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