To evaluate future wetland degradation at wami ruvu river basin from 2020 to 2050 using remote sensing imagery and hybrid ca- markov model
DOI:
https://doi.org/10.48346/IMIST.PRSM/ajlp-gs.v7i1.42616Keywords:
Land Change Modeler, Markov chain, Wetland, Cellular Automata (CA), Remote SensingAbstract
Context and background:
In current industrialized world, extremely increase of urbanization, Agriculture land expansion and climate change have led to increase of degradation of wetland in many basins and coastal area, which result to the malfunction of its ecosystem services. However, there are few studies have been conducted to analyze how the historical degradation of wetland will continue in the future especially in most of the developing countries.
Goal and objectives:
The overall objective of the study intents to provide an integrated method which includes GIS, remote sensing and CA-Markov Chain modelling to analyse the influence of LULC dynamic into wetland degradation. Specifically, is to use historical land use/cover maps of 2000,2010 and 2020 to develop land use simulation model to predict the spatial degradation of wetland for three decades.
Methodology:
In this study will use historical land use/cover maps of 2000,2010 and 2020 to develop land use simulation model to predict the spatial degradation of wetland in Wami-Ruvu river basin for coming 30 years (2020-2050) under different scenarios using land change modeler (LCM) in Idris-TerrSet. Future land use/cover map of the study area was developed using Markov chain and artificial neural network (ANN) Analysis in LCM modeler.
Results:
The study found of about 1209.0753Km2 (2%), 949Km2 (1.4%), 521.33Km2 (0.78%) and 213 (0.32%) of wetland was decreasing, which was equal to 1339999, 1055066, 578584and 237199 for the year 2000, 2010, 2020 and 2050 for the individual pixel values respectively, which made a half of the total simulated wetland to have been lost that is 50% of the land in the study region.
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