Topographic Correction of Optical Remote Sensing Images in Mountainous Areas: A systematic review

Chen, Rui; Yin, Gaofei; Zhao, Wei; Yan, Kai; Wu, Shengbiao; Hao, Dalei; Liu, Guoxiang

doi:10.1109/mgrs.2023.3311100

Title: Topographic Correction of Optical Remote Sensing Images in Mountainous Areas: A systematic review

Journal Article · 27 September 2023 · IEEE Geoscience and Remote Sensing Magazine

DOI: https://doi.org/10.1109/mgrs.2023.3311100 · OSTI ID:2305452

^[1];

^[2]; Yan, Kai ^[3];

^[4]; Hao, Dalei ^[5];

^[1]

Southwest Jiaotong University, Chengdu (China)
Chinese Academy of Sciences, Chengdu (China)
Beijing Normal University, Beijing (China)
University of Hong Kong (China)
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Rugged terrain distorts optical remote sensing observations and subsequently impacts land cover classification and biophysical and biochemical parameter retrieval over mountainous areas. Therefore, topographic correction (TC) is a prerequisite for many remote sensing applications. Although various TC methods have been explored over the past four decades to mitigate topographic effects, a systematic and global review of these studies is still lacking. Using a multicomponent bibliometric approach, we extracted bibliometric metadata from 426 publications identified by searching titles, keywords, and abstracts for research on “topographic correction” and “topographic effects” in Scopus and Web of Science (WoS) from 1980 to 2022. Here this systematic review revealed a rapid growth in the number of TC studies since the 1980s, primarily driven by the availability of decametric-resolution remote sensing observations and digital elevation models (DEMs). Most of the research has focused on relatively low-elevation regions, with increasing attention beyond American and European regions, particularly in China. The seasonal distribution of satellite acquisition for TC showed considerable imbalance, mainly concentrated in months with favorable solar illumination conditions (e.g., May to October). Important themes emerged from the keyword analysis, including satellite sensors, DEMs, TC methods, evaluation criteria, and applications.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC); National Natural Science Foundation of China (NSFC); Sichuan Science and Technology Program

Grant/Contract Number:: AC05-76RL01830; 41971282; 42271323; 2021JDJQ0007

OSTI ID:: 2305452

Report Number(s):: PNNL-SA-190887

Journal Information:: IEEE Geoscience and Remote Sensing Magazine, Vol. 11, Issue 4; ISSN 2473-2397

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments Wen, Jianguang; Liu, Qiang; Xiao, Qing Remote Sensing, Vol. 10, Issue 3 https://doi.org/10.3390/rs10030370	journal	February 2018
Application of three‐dimensional solar radiative transfer to mountains Chen, Y.; Hall, A.; Liou, K. N. Journal of Geophysical Research: Atmospheres, Vol. 111, Issue D21 https://doi.org/10.1029/2006jd007163	journal	November 2006
Comparison of Topographic Correction Methods Richter, Rudolf; Kellenberger, Tobias; Kaufmann, Hermann Remote Sensing, Vol. 1, Issue 3 https://doi.org/10.3390/rs1030184	journal	July 2009
PLC: A simple and semi-physical topographic correction method for vegetation canopies based on path length correction Yin, Gaofei; Li, Ainong; Wu, Shengbiao Remote Sensing of Environment, Vol. 215 https://doi.org/10.1016/j.rse.2018.06.009	journal	September 2018
Assessing the spatial, spectral, and temporal consistency of topographically corrected Landsat time series composites across the mountainous forests of Nepal Hurni, Kaspar; Van Den Hoek, Jamon; Fox, Jefferson Remote Sensing of Environment, Vol. 231 https://doi.org/10.1016/j.rse.2019.111225	journal	September 2019
Fast and Robust Topographic Correction Method for Medium Resolution Satellite Imagery Using a Stratified Approach Szantoi, Zoltan; Simonetti, Dario IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, Issue 4 https://doi.org/10.1109/jstars.2012.2229260	journal	August 2013
Humboldt’s enigma: What causes global patterns of mountain biodiversity? Rahbek, Carsten; Borregaard, Michael K.; Colwell, Robert K. Science, Vol. 365, Issue 6458 https://doi.org/10.1126/science.aax0149	journal	September 2019
Canopy near-infrared reflectance and terrestrial photosynthesis Badgley, Grayson; Field, Christopher B.; Berry, Joseph A. Science Advances, Vol. 3, Issue 3 https://doi.org/10.1126/sciadv.1602244	journal	March 2017
Scale effect and scale correction of land-surface albedo in rugged terrain Wen, Jianguang; Liu, Qiang; Liu, Qinhuo International Journal of Remote Sensing, Vol. 30, Issue 20 https://doi.org/10.1080/01431160903130903	journal	September 2009
C-correction of optical satellite data over alpine vegetation areas: A comparison of sampling strategies for determining the empirical c-parameter Reese, Heather; Olsson, Håkan Remote Sensing of Environment, Vol. 115, Issue 6 https://doi.org/10.1016/j.rse.2011.01.019	journal	June 2011
Topographic Correction for Landsat 8 OLI Vegetation Reflectances Through Path Length Correction: A Comparison Between Explicit and Implicit Methods Yin, Gaofei; Ma, Lei; Zhao, Wei IEEE Transactions on Geoscience and Remote Sensing, Vol. 58, Issue 12 https://doi.org/10.1109/tgrs.2020.2987985	journal	December 2020
Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstration Ganguly, Sangram; Nemani, Ramakrishna R.; Zhang, Gong Remote Sensing of Environment, Vol. 122 https://doi.org/10.1016/j.rse.2011.10.032	journal	July 2012
Global high-resolution mountain green cover index mapping based on Landsat images and Google Earth Engine Bian, Jinhu; Li, Ainong; Lei, Guangbin ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 162 https://doi.org/10.1016/j.isprsjprs.2020.02.011	journal	April 2020
An improved topographic correction model based on Minnaert Gao, Mingliang; Gong, Huili; Zhao, Wenji GIScience & Remote Sensing, Vol. 53, Issue 2 https://doi.org/10.1080/15481603.2015.1118976	journal	December 2015
An Introduction to the Chinese High-Resolution Earth Observation System: Gaofen-1~7 Civilian Satellites Chen, Liangfu; Letu, Husi; Fan, Meng Journal of Remote Sensing, Vol. 2022 https://doi.org/10.34133/2022/9769536	journal	January 2022
Evaluation of Topographic Correction Models Based on 3-D Radiative Transfer Simulation Chi, Haojing; Yan, Kai; Yang, Kai IEEE Geoscience and Remote Sensing Letters, Vol. 19 https://doi.org/10.1109/lgrs.2021.3110907	journal	January 2022