Using remote sensing images and markov chain to forecast land-use change in Cai Rang district, Can Tho city

Abstract

Land-use change management is essential for land monitoring, especially land-use planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. This study applied GIS technology and remote sensing coupled with Markov chain to assess land-use changes, and forecast land-use change towards 2025 in Cai Rang district, Can Tho city. The results showed that the land-use change in 2010-2015 was up to 18,92% and in 2015-2020 it was up to 11,5% of the total area. The results of verifying the accuracy of the Markov model with the current land use status in 2020 reached 95,85%. Forecast results by 2025 are: water body is 1119,14 ha, perennial cropland is 2851,04 ha, annual cropland is 471,88 ha, urban residential land is 2287,77 ha and vacant land is 29,53 ha. Therefore, applying the remote sensing image and Markov model to evaluate land-use change and forecast land use provides realizable outcomes according to the fluctuation of the common ones in the period 2010- 2020.