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

Seyed Kazem Alavipanah, Mohammad Karimi Firozjaei, Amir Sedighi, Solmaz Fathololoumi, Saeid Zare Naghadehi, Samiraalsadat Saleh, Maryam Naghdizadegan, Zinat Gomeh, Jamal Jokar Arsanjani, Mohsen Makki, Salman Qureshi, Qihao Weng, Dagmar Haase, Biswajeet Pradhan, Asim Biswas, Peter M. Atkinson

Research output: Journal article publicationReview articleAcademic researchpeer-review

6 Citations (Scopus)


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.

Original languageEnglish
Article number2025
Issue number11
Publication statusPublished - 12 Nov 2022


  • de-shadowing
  • remote sensing
  • shadow
  • shadow detection
  • surface biophysical variables

ASJC Scopus subject areas

  • Global and Planetary Change
  • Ecology
  • Nature and Landscape Conservation


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