<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Vegetation of Cameroon includes a variety of landscape types with high biodiversity. Ecological monitoring of Yaoundé requires visualization of vegetation types in context of climate change. Vegetation Indices (VIs) derived from Sentinel-2 multispectral satellite image were analyzed in SAGA GIS to separate wetland biomes, as well as savannah and tropical rainforests. The methodology includes computing 6 VIs: NDVI, DVI, SAVI, RVI, TTVI, CTVI. The VIs shown correlation of data with vegetation distribution rising from wetlands, grassland, savanna, and shrub land towards tropical rainforests, increasing values along with canopy greenness, while also being inversely proportional to soils, urban spaces and Sanaga River. The study contributed to the environmental studies of Cameroon and demonstration of the satellite image processing.</p></abstract>

Vegetation of Cameroon includes a variety of landscape types with high biodiversity. Ecological monitoring of Yaoundé requires visualization of vegetation types in context of climate change. Vegetation Indices (VIs) derived from Sentinel-2 multispectral satellite image were analyzed in SAGA GIS to separate wetland biomes, as well as savannah and tropical rainforests. The methodology includes computing 6 VIs: NDVI, DVI, SAVI, RVI, TTVI, CTVI. The VIs shown correlation of data with vegetation distribution rising from wetlands, grassland, savanna, and shrub land towards tropical rainforests, increasing values along with canopy greenness, while also being inversely proportional to soils, urban spaces and Sanaga River. The study contributed to the environmental studies of Cameroon and demonstration of the satellite image processing.

Sentinel-2 for High Resolution Mapping of Slope-Based Vegetation Indices Using Machine Learning By SAGA GIS

Laboratory of Regional Geophysics and Natural Disasters

Transylvanian Review of Systematical and Ecological Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Vegetation of Cameroon includes a variety of landscape types with high biodiversity. Ecological monitoring of Yaoundé requires visualization of vegetation...

Sentinel-2 for High Resolution Mapping of Slope-Based Vegetation Indices Using Machine Learning By SAGA GIS

Pubblicato online: 18 mar 2021

Pagine: 17 - 34

DOI: https://doi.org/10.2478/trser-2020-0015

Parole chiave
Sentinel-2, SAGA GIS, Cameroon, remote sensing, vegetation

© 2020 Polina Lemenkova, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Sentinel-2 for High Resolution Mapping of Slope-Based Vegetation Indices Using Machine Learning By SAGA GIS

Pubblicato online: 18 mar 2021

Pagine: 17 - 34

DOI: https://doi.org/10.2478/trser-2020-0015

Parole chiaveSentinel-2, SAGA GIS, Cameroon, remote sensing, vegetation

© 2020 Polina Lemenkova, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Sentinel-2, SAGA GIS, Cameroon, remote sensing, vegetation