Assessing ecological impacts of urban forest conversion using Sentinel-2 NDVI-based canopy cover analysis: A systematic review and bibliometric analysis
คำสำคัญ:
Canopy cover analysis, GIS, Remote sensing, Systematic review, Urban forest conversionบทคัดย่อ
Importance of the work: The lack of integration of canopy cover assessment with ecological
indicators constrains effective monitoring and conservation of small tropical urban forests.
Objectives: To identify research trends, evaluate geographic information system and remote- sensing
techniques for canopy cover assessment and determine relevant ecological indicators for the Shah
Alam Community Forest (SACF), Selangor, Malaysia.
Materials and Methods: A systematic review was undertaken using: Preferred Reporting Items
for Systematic reviews and Meta-Analyses (PRISMA) on Scopus-indexed studies (2020–2025);
bibliometric analysis via VOSviewer; and inclusion criteria limited to peer-reviewed English articles
on urban forest conversion, canopy cover, GIS and remote sensing.
Results: From 1,697 initial records, 465 passed screening and 15 studies underwent full analysis.
Research growth peaked in 2024 (110 articles). Four thematic clusters emerged: remote sensing
methods, urban forest ecology, canopy change/land use/land cover and conservation policy. China
ranked 1st, with Malaysia ranking 10th in publication output. Major gaps were: limited integration of
canopy metrics with biodiversity data; few studies on small-scale tropical forests such as SACF; and
minimal fragmentation analysis in urban contexts.
Main finding: The conceptual framework of urban forest research, the key research milestones of the
Urban Forest Ecological Assessment; the gaps analisis and justification that calls for the research; and
the framework for preserving urban forest with geospatial methods that enable the multidimensional
canopy cover analysis with ecological indicators can enhance monitoring and conservation strategies
for small tropical urban forests.
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ประเภทบทความ
สัญญาอนุญาต
ลิขสิทธิ์ (c) 2026 online 2452-316X print 2468-1458/Copyright © 2026. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/), production and hosting by Kasetsart University Research and Development Institute on behalf of Kasetsart University.online 2452-316X print 2468-1458/Copyright © 2022. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/),
production and hosting by Kasetsart University of Research and Development Institute on behalf of Kasetsart University.

