Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Multi-temporal Satellite Images Analysis for Assessing and Mapping Deforestation in Um Hataba Forest, South Kordofan, Sudan

Domaine:

geospatialenvironment and energy
Créateur:
BudEmaOm
Éditeur:
Uni
Hôte:
. Sudan is a hot spot for deforestation, despite the increasing awareness of deforestation and its consequences. Consequences are related to increased emissions of greenhouse gases, water pollution, and loss of biodiversity. However, precise information on its forests' current state is very limited. Therefore, to intervene support of existing resources effectively, it is important to have a better understanding of the process to take place in the country and impact those resources. The objective of this study is assess and map Land use Land cover (LULC) change and analyze the anthropogenic factors causing it in Um Hataba forest, South Kordofan State. The study utilized two-free cloud images (TM 2000 and Sentinel-2 in 2018), field surveys, and questionnaires to analyze the decrease in forest cover. The results indicated there were a decrease in vegetation cover on wadis (clay soil) from 20.98% in 2000 to 15.85% in 2018 and vegetation on sandy soil decreased from 30.29% in 2000 to 30.13% in 2018. While mixed shrubs and grassland increased from 28.60% in 2000 to 33.20% in 2018 of the total area under study and the rainfed agricultural area increased from 20.13% in 2000 to 20.82% in 2018. The main factors of degradation and fragmentation as the expansion of mechanized are rain-fed agriculture, felling of trees and woodcutting, worse grazing activities, and construction of infrastructure. Information garnered from this study can provide a good basis for forest rehabilitation programs and can also be used for developing proper management plans that consider the needs of the communities utilizing the forest.

Visit

doi.org

Languages

El Hugeirat

Licenses

https://creativecommons.org/licenses/by-nc/4.0

Similaires

Assessment of Sentinel-2 Satellite Images and Random Forest Classifier for Rainforest Mapping in GabonAppropriate Methods for Monitoring and Mapping Land Cover Changes in Semi-arid Areas in North Kordofan (Sudan) by Using Satellite Imagery and Spectral Mixture AnalysisMulti-Temporal and Multi-Frequency SAR Analysis for Forest Land Cover Mapping of the Mai-Ndombe District (Democratic Republic of Congo)Mapping forests and deforestation activities in Madagascar using satellite imageryMapping Natural Forest Remnants with Multi-Source and Multi-Temporal Remote Sensing Data for More Informed Management of Global Biodiversity HotspotsComparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

Assessment of Sentinel-2 Satellite Images and Random Forest Classifier for Rainforest Mapping in Gabon

This study is focused on the assessment of the potential of Sentinel-2 satellite images and the Rand

Appropriate Methods for Monitoring and Mapping Land Cover Changes in Semi-arid Areas in North Kordofan (Sudan) by Using Satellite Imagery and Spectral Mixture Analysis

Multi-Temporal and Multi-Frequency SAR Analysis for Forest Land Cover Mapping of the Mai-Ndombe District (Democratic Republic of Congo)

The European Space Agency’s (ESA) “SAR for REDD” project aims to support complementing optical remot

Mapping forests and deforestation activities in Madagascar using satellite imagery

This dataset includes output data from the following article: Oladimeji Mudele, Marissa Childs, J

Mapping Natural Forest Remnants with Multi-Source and Multi-Temporal Remote Sensing Data for More Informed Management of Global Biodiversity Hotspots

Global terrestrial biodiversity hotspots (GBH) represent areas featuring exceptional concentrations

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, G