Greening the Urban Environment Using Geospatial Techniques, A Case Study of Bangkok, Thailand

Abstract

Urbanization is one of human induced activities causing land use changes. In recent years, various land usetransformationsin Bangkok influenced the city's ecological sustainability in all means, i.e., diminishing the city's cultivated land and greenery. This study investigates lack of green spaces due to extreme urban growth in the mega city. To do so, first, land use transitions are modelled through two different images; one from Landsat 5Thematic Mapper for the year 1994, and second fromHJ-1A CCD for the year 2012. Next, theMulti-Layer Perceptron Markov Model (MLP-Markov) is applied to predict land usechange for the year 2030. The MLP neural network is trained to modelland usetransitionsthrough creating transition maps. Markov Chain predictive model is applied with sufficient accuracy to process the transition maps for the prediction process. The results indicate that 348km²of green areas are transformed into built-up areas for the period 1994-2012,witha considerable loss of greenery (42%). The MLP model predictions show 4% increase in built-up and 6% decrease in greenery for the period 2012-2030. The study highly recommends conservation of green spaces and green corridors in the city. Future research can includeanalysing greenplot ratio for suitablegreen patches in vulnerable sites. The research output will benefit urban planners to implement long term planning strategies forsecuring natural environment in mega cities.