Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

Ahmed, Bayes; Kamruzzaman, Md.; Zhu, Xuan; Rahman, Md. Shahinoor; Choi, Keechoo

doi:10.3390/rs5115969

Cited by 287 publications

(214 citation statements)

References 56 publications

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“…In this study, the C factor was derived from the Normalized Difference Vegetation Index (NDVI) interpreted using image data from ETM+ and OLI sensors (Figure 5g,h). The equation to calculate the spectral indices of NDVI is as follows [113,114]:…”

Section: Slope Length and Steepness (Ls) Factormentioning

confidence: 99%

Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia

Woldemariam

Iguala

Tekalign

et al. 2018

Land

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Abstract:Soil erosion by water has accelerated over recent decades due to non-sustainable land use practices resulting in substantial land degradation processes. Spatially explicit information on soil erosion is critical for the development and implementation of appropriate Soil and Water Conservation (SWC) measures.The objectives of this study were to estimate the magnitude of soil loss rate, assess the change of erosion risk, and elucidate their implication for SWC planning in the Gobele Watershed, East Hararghe Zone, Ethiopia. Applying remote sensing data, the study first derived the Revised Universal Soil Loss Equation (RUSLE) model parameters in an ArcGIS environment and estimated the soil loss rates. The estimated total soil loss in the watershed was 1,390,130.48 tons in 2000 and 1,022,445.09 tons in 2016 with a mean erosion rate of 51.04 t ha −1 y −1 and 34.26 t ha −1 y −1 , respectively. The study area was divided into eight erosion risk classes ranging from very low to extremely high. We established a change detection matrix of the soil erosion risk classes between 2000 and 2016. The change analysis results have revealed that about 70.80% of the soil erosion risk areas remained unchanged, 19.67% increased in total area, and 9.53% decreased, showing an overall worsening of the situation. We identified and mapped areas with a higher and increasing erosion risk as SWC priority areas using a Multi-criteria Decision Rules (MCDR) method. The top three priority levels marked for the emergency SWC measures account for about 0.04%, 0.49%, and 0.83%, respectively. These priority levels are situated along the steep slope areas in the north, northwest, south, and southeast of the Gobele Watershed. It is, thus, very critical to undertake proper intervention measures in upslope areas based on the priority levels to establish sustainable watershed management in the study area.

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Section: Slope Length and Steepness (Ls) Factormentioning

confidence: 99%

Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia

Woldemariam

Iguala

Tekalign

et al. 2018

Land

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“…To access the reliability of the resulting LULC maps, an accuracy assessment was performed [35,36]. The accuracy of the land-use classification was checked with 500 random sample points for Built-up, Cropland, Grass, Forest and Water [37].…”

Section: Assessing the Accuracy Of Lulc Mapsmentioning

confidence: 99%

Change of Land Use/Cover in Tianjin City Based on the Markov and Cellular Automata Models

Wang

Murayama

2017

IJGI

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Abstract:In recent years, urban areas have been expanding rapidly in the world, especially in developing countries. With this rapid urban growth, several environmental and social problems have appeared. Better understanding of land use and land cover (LULC) change will facilitate urban planning and constrain these potential problems. As one of the four municipalities in China, Tianjin has experienced rapid urbanization and such trend is expected to continue. Relying on remote sensing (RS) and geographical information system (GIS) tools, this study investigates LULC change in Tianjin city. First, we used RS to generate classification maps for 1995, 2005, and 2015. Then, simulation models were applied to evaluate the LULC changes. Analysis of the 1995, 2005, and 2015 LULC maps shows that more than 10% of the cropland areas were transformed into built-up areas. Finally, by employing the Markov model and cellular automata (CA) model, the LULC in 2025 and 2035 were simulated and forecasted. Our analysis contributes to the understanding of the development process in the Tianjin area, which will facilitate future planning, as well as constraining the potential negative consequences brought by future LULC changes.

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“…Ahmed and Kamruzzaman predicted land use/cover changes in the capital city of Bangladesh and analyzed their interactions with land surface temperature in 2019 and 2029 [38]. Deilami and Kamruzzaman forecasted the urban heat island and its impact on land use/cover changes under three policy scenarios [39].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

2018

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Abstract:Simulating future land use/cover changes is of great importance for urban planners and decision-makers, especially in metropolitan areas, to maintain a sustainable environment. This study examines the changes in land use/cover in the Tokyo metropolitan area (TMA) from 2007 to 2017 as a first step in using supervised classification. Second, based on the map results, we predicted the expected patterns of change in 2027 and 2037 by employing a hybrid model composed of cellular automata and the Markov model. The next step was to decide the model inputs consisting of the modeling variables affecting the distribution of land use/cover in the study area, for instance distance to central business district (CBD) and distance to railways, in addition to the classified maps of 2007 and 2017. Finally, we considered three scenarios for simulating land use/cover changes: spontaneous, sub-region development, and green space improvement. Simulation results show varied patterns of change according to the different scenarios. The sub-region development scenario is the most promising because it balances between urban areas, resources, and green spaces. This study provides significant insight for planners about change trends in the TMA and future challenges that might be encountered to maintain a sustainable region.

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Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

Cited by 287 publications

References 56 publications

Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia

Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia

Change of Land Use/Cover in Tianjin City Based on the Markov and Cellular Automata Models

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

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