Literature DB >> 33688308

Analysis of the Current and Future Prediction of Land Use/Land Cover Change Using Remote Sensing and the CA-Markov Model in Majang Forest Biosphere Reserves of Gambella, Southwestern Ethiopia.

Semegnew Tadese1, Teshome Soromessa1, Tesefaye Bekele2.   

Abstract

This study aimed to evaluate land use/land cover changes (1987-2017), prediction (2032-2047), and identify the drivers of Majang Forest Biosphere Reserves. Landsat image (TM, ETM+, and OLI-TIRS) and socioeconomy data were used for the LU/LC analysis and its drivers of change. The supervised classification was also employed to classify LU/LC. The CA-Markov model was used to predict future LU/LC change using IDRISI software. Data were collected from 240 households from eight kebeles in two districts to identify LU/LC change drivers. Five LU/LC classes were identified: forestland, farmland, grassland, settlement, and waterbody. Farmland and settlement increased by 17.4% and 3.4%, respectively; while, forestland and grassland were reduced by 77.8% and 1.4%, respectively, from 1987 to 2017. The predicted results indicated that farmland and settlement increased by 26.3% and 6.4%, respectively, while forestland and grassland decreased by 66.5% and 0.8%, respectively, from 2032 to 2047. Eventually, agricultural expansion, population growth, shifting cultivation, fuel wood extraction, and fire risk were identified as the main drivers of LU/LC change. Generally, substantial LU/LC changes were observed and will continue in the future. Hence, land use plan should be proposed to sustain resource of Majang Forest Biosphere Reserves, and local communities' livelihood improvement strategies are required to halt land conversion.
Copyright © 2021 Semegnew Tadese et al.

Entities:  

Year:  2021        PMID: 33688308      PMCID: PMC7925022          DOI: 10.1155/2021/6685045

Source DB:  PubMed          Journal:  ScientificWorldJournal        ISSN: 1537-744X


  1 in total

1.  Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis.

Authors:  Laju Gandharum; Djoko Mulyo Hartono; Asep Karsidi; Mubariq Ahmad
Journal:  ScientificWorldJournal       Date:  2022-01-12
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.