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The Shadow Effect on Surface Biophysical Variables Derived from Remote Sensing: A Review

Author

Listed:
  • Seyed Kazem Alavipanah

    (Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 14178-53933, Iran)

  • Mohammad Karimi Firozjaei

    (Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 14178-53933, Iran)

  • Amir Sedighi

    (Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 14178-53933, Iran)

  • Solmaz Fathololoumi

    (School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada)

  • Saeid Zare Naghadehi

    (Department of Civil, Environmental and Geomatics Engineering, College of Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL 33431, USA)

  • Samiraalsadat Saleh

    (Department of Geography and Environmental Science, North Texas University, Denton, TX 76203, USA)

  • Maryam Naghdizadegan

    (Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 14178-53933, Iran)

  • Zinat Gomeh

    (Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 14178-53933, Iran)

  • Jamal Jokar Arsanjani

    (Geoinformatics Research Group, Department of Planning and Development, Aalborg University Copenhagen, A.C. Meyers Vænge 15, DK-2450 Copenhagen, Denmark)

  • Mohsen Makki

    (Department of Geography, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany)

  • Salman Qureshi

    (Department of Geography, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany)

  • Qihao Weng

    (Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, 11 Yuk Choi Road Hung Hom, Kowloon, Hong Kong, China)

  • Dagmar Haase

    (Department of Geography, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany)

  • Biswajeet Pradhan

    (Center for Advanced Modeling and Geospatial Information Systema (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and IT, University of Technology Sydney, CB11.06.106, Building 11, 81 Broadway, Ultimo, NSW 2007, Australia)

  • Asim Biswas

    (School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada)

  • Peter M. Atkinson

    (Lancaster Environment Center, Faculty of Science and Technology, Lancaster University, Bailrigg, Lancaster LA1 4YR, UK)

Abstract

In remote sensing (RS), shadows play an important role, commonly affecting the quality of data recorded by remote sensors. It is, therefore, of the utmost importance to detect and model the shadow effect in RS data as well as the information that is obtained from them, particularly when the data are to be used in further environmental studies. Shadows can generally be categorized into four types based on their sources: cloud shadows, topographic shadows, urban shadows, and a combination of these. The main objective of this study was to review the recent literature on the shadow effect in remote sensing. A systematic literature review was employed to evaluate studies published since 1975. Various studies demonstrated that shadows influence significantly the estimation of various properties by remote sensing. These properties include vegetation, impervious surfaces, water, snow, albedo, soil moisture, evapotranspiration, and land surface temperature. It should be noted that shadows also affect the outputs of remote sensing processes such as spectral indices, urban heat islands, and land use/cover maps. The effect of shadows on the extracted information is a function of the sensor–target–solar geometry, overpass time, and the spatial resolution of the satellite sensor imagery. Meanwhile, modeling the effect of shadow and applying appropriate strategies to reduce its impacts on various environmental and surface biophysical variables is associated with many challenges. However, some studies have made use of shadows and extracted valuable information from them. An overview of the proposed methods for identifying and removing the shadow effect is presented.

Suggested Citation

  • Seyed Kazem Alavipanah & Mohammad Karimi Firozjaei & Amir Sedighi & Solmaz Fathololoumi & Saeid Zare Naghadehi & Samiraalsadat Saleh & Maryam Naghdizadegan & Zinat Gomeh & Jamal Jokar Arsanjani & Mohs, 2022. "The Shadow Effect on Surface Biophysical Variables Derived from Remote Sensing: A Review," Land, MDPI, vol. 11(11), pages 1-30, November.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:11:p:2025-:d:970721
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    References listed on IDEAS

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    1. Lei Zhao & Xuhui Lee & Ronald B. Smith & Keith Oleson, 2014. "Strong contributions of local background climate to urban heat islands," Nature, Nature, vol. 511(7508), pages 216-219, July.
    2. Jing Gao & Jianzhong Li & Yingshu Li, 2016. "Approximate event detection over multi-modal sensing data," Journal of Combinatorial Optimization, Springer, vol. 32(4), pages 1002-1016, November.
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