Vegetation cover change and classification-based zonation of Fanjing Mountain using google earth engine
- 1College of Geography and Environmental Science, Guizhou Normal University, Guiyang, China
- 2Guizhou Mountain Resources and Environmental Remote Sensing Application Laboratory, Guiyang, China
Abstract
This study utilizes the Google Earth Engine (GEE) platform, integrating Landsat and Sentinel-2 imagery from 1987 to 2022 alongside terrain data to develop a technical system for “vegetation cover inversion–classification–vertical belt spectrum analysis.” The Fractional Vegetation Cover (FVC) is estimated using a pixel dichotomy model, while spatiotemporal changes are evaluated through Theil-Sen trend analysis and Mann-Kendall tests. A multi-feature combination scheme has been designed, employing random forest models to enhance forest classification and analyze altitude zoning characteristics. The findings indicate that: (1) Over nearly 36 years, FVC in Fanjing Mountain has demonstrated a pattern of “fluctuating decline–adjustment–jump increase,” with 2007 serving as a pivotal turning point; notably, 41.65% of the area exhibited significant improvement, particularly in the southern region; (2) The classification model that integrates terrain features, red-edge index, and texture attributes (T9 scheme) achieves an overall accuracy of 77.88%, with terrain factors being the most influential in significantly enhancing the identification of shrub meadows and evergreen broadleaf forests; (3) Distinct vertical zoning of vegetation is observed: evergreen broadleaf forests dominate lower to mid-elevations (750–1550 m), deciduous broadleaf forests and coniferous forests are found at mid-to-high elevations, while shrub meadows are concentrated above 2400 m, forming a gradient succession sequence. This study provides methodological support and scientific evidence for ecological conservation efforts in subtropical mountain regions.
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BibTeX
@article{wang2026vegetation,
title = {{Vegetation cover change and classification-based zonation of Fanjing Mountain using google earth engine}},
author = {Rongrong Wang and Wengang Cui and Suihua Liu and Ting Yu and Fei Ning and Qingsong Xu and Dan Hu},
journal = {PLOS One},
year = {2026},
month = oct,
doi = {10.1371/journal.pone.0359961},
url = {https://doi.org/10.1371/journal.pone.0359961},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Vegetation cover change and classification-based zonation of Fanjing Mountain using google earth engine
AU - Rongrong Wang
AU - Wengang Cui
AU - Suihua Liu
AU - Ting Yu
AU - Fei Ning
AU - Qingsong Xu
AU - Dan Hu
PY - 2026
DA - 2026/10/07
JO - PLOS One
DO - 10.1371/journal.pone.0359961
UR - https://doi.org/10.1371/journal.pone.0359961
AB - This study utilizes the Google Earth Engine (GEE) platform, integrating Landsat and Sentinel-2 imagery from 1987 to 2022 alongside terrain data to develop a technical system for “vegetation cover inversion–classification–vertical belt spectrum analysis.” The Fractional Vegetation Cover (FVC) is estimated using a pixel dichotomy model, while spatiotemporal changes are evaluated through Theil-Sen trend analysis and Mann-Kendall tests. A multi-feature combination scheme has been designed, employing random forest models to enhance forest classification and analyze altitude zoning characteristics. The findings indicate that: (1) Over nearly 36 years, FVC in Fanjing Mountain has demonstrated a pattern of “fluctuating decline–adjustment–jump increase,” with 2007 serving as a pivotal turning point; notably, 41.65% of the area exhibited significant improvement, particularly in the southern region; (2) The classification model that integrates terrain features, red-edge index, and texture attributes (T9 scheme) achieves an overall accuracy of 77.88%, with terrain factors being the most influential in significantly enhancing the identification of shrub meadows and evergreen broadleaf forests; (3) Distinct vertical zoning of vegetation is observed: evergreen broadleaf forests dominate lower to mid-elevations (750–1550 m), deciduous broadleaf forests and coniferous forests are found at mid-to-high elevations, while shrub meadows are concentrated above 2400 m, forming a gradient succession sequence. This study provides methodological support and scientific evidence for ecological conservation efforts in subtropical mountain regions.
SN - 1932-6203
ER -