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Jin, Y., Liu, X., Chen, Y. and Liang, X. (2018) Land-Cover Mapping Using Random Forest Classification and Incorporating NDVI Time-Series and Texture: A Case Study of Central Shandong. International Journal of Remote Sensing, 39, 8703-8723.
https://doi.org/10.1080/01431161.2018.1490976

has been cited by the following article:

• TITLE: Modelling Land Use/Land Cover Change of River Rwizi Catchment, South-Western Uganda Using GIS and Markov Chain Model

  AUTHORS: Lauben Muhangane, Morgan Andama

  KEYWORDS: Land Cover, River Catchment, Geographic Information System, Markov Model, Sustainable Land Management

  JOURNAL NAME: Journal of Water Resource and Protection, Vol.16 No.2, February 26, 2024

  ABSTRACT: Analysis of catchment Land use/Land cover (LULC) change is a vital tool in ensuring sustainable catchment management. The study analyzed land use/land cover changes in the Rwizi catchment, south western Uganda from 1989-2019 and projected the trend by 2040. Landsat images, field observations, key informant interviews and focus group discussions were used to collect data. Changes in cropland, forestland, built up area, grazing land, wetland and open water bodies were analyzed in ArcGIS version 10.2.2 and ERDAS IMAGINE 14 software and a Markov chain model. All the LULC classes increased in area except grazing land. Forest land and builtup area between 2009-2019 increased by 370.03% and 229.53% respectively. Projections revealed an increase in forest land and builtup area by 2030 and only built up area by 2040. LULCC in the catchment results from population pressure, reduced soil fertility and high value of agricultural products.