Analysis of Urban Expansion and Modeling of LULC Changes Using Geospatial Techniques: The Case of Adama City

2020 ◽  
Vol 4 (1-2) ◽  
pp. 40-58
Author(s):  
Bedasa Regassa ◽  
Mikir Kassaw ◽  
Murugesan Bagyaraj
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
Spatiotemporal Variability ◽  
Kappa Statistics ◽  
Geospatial Techniques ◽  
Lulc Changes ◽  
The Right

In the last decades, Adama city has experienced drastic changes in its shape, not just in its vast geographical expansion, but also by internal transformations. Subsequently, understanding and evaluating the spatiotemporal variability of urban land use and land cover (LULC) shifts, and it is important to bring forth the right strategies and processes to track population development in decision-making. The goal of this analysis was therefore to examine LULC changes that have taken place over 37 years, forecast the long-term urban development in Adama City using geospatial techniques. To attain this, satellite data of Landsat 1973, 2000 and 2010 was downloaded from USGS Earth Explorer and processed using Arc GIS 10.5, Erdas 9.2, and Idrisi 32. A supervised classification technique has been used to prepare the base maps with six land cover classes that are accustomed to generate LULC maps. The maps are cross-tabulated to measure LULC changes, to look at land-use transfers between the land cover classes, to spot increases and declines in built-up areas in comparison to other land cover classes, and to determine the spatial changes in built-up areas. Finally, Markov Chain and CA-Markov techniques were used to model the LULC changes in the Adama district and to forecast possible changes in urban land use. The model was verified by the Kappa statistics and also by the application of other validation techniques. The growth of built-up areas in the last 37 years has risen from 2% in 1973, 10% in 2000 and 23% in 2010 and estimated about 60% over the next 30 years (2040).

scholarly journals An Analysis of Urban Land Use/Land Cover Changes in Blantyre City, Southern Malawi (1994–2018)

2020 ◽  
Vol 12 (6) ◽  
pp. 2377 ◽  
Author(s):  
John Mawenda ◽  
Teiji Watanabe ◽  
Ram Avtar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Land ◽  
Urban Land Use ◽  
Sustainable Growth ◽  
Sub Saharan Africa ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Lulc Changes ◽  
Bare Land

Rapid and unplanned urban growth has adverse environmental and social consequences. This is prominent in sub-Saharan Africa where the urbanisation rate is high and characterised by the proliferation of informal settlements. It is, therefore, crucial that urban land use/land cover (LULC) changes be investigated in order to enhance effective planning and sustainable growth. In this paper, the spatial and temporal LULC changes in Blantyre city were studied using the integration of remotely sensed Landsat imageries of 1994, 2007 and 2018, and a geographic information system (GIS). The supervised classification method using the support vector machine algorithm was applied to generate the LULC maps. The study also analysed the transition matrices derived from the classified map to identify prominent processes of changes for planning prioritisation. The results showed that the built-up class, which included urban structures such as residential, industrial, commercial and public installations, increased in the 24-year study period. On the contrary, bare land, which included vacant lands, open spaces with little or no vegetation, hilly clear-cut areas and other fallow land, declined over the study period. This was also the case with the vegetation class (i.e., forests, parks, permanent tree-covered areas and shrubs). The post-classification results revealed that the LULC changes during the second period (2007–2018) were faster compared to the first period (1994–2007). Furthermore, the results revealed that the increase in built-up areas systematically targeted the bare land and avoided the vegetated areas, and that the vegetated areas were systematically cleared to bare land during the study period (1994–2018). The findings of this study have revealed the pressure of human activities on the land and natural environment in Blantyre and provided the basis for sustainable urban planning and development in Blantyre city.

scholarly journals Geospatial analysis of wetlands based on land use/land cover dynamics using remote sensing and GIS in Sindh, Pakistan

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110261
Author(s):  
Hamza Islam ◽  
Habibuulah Abbasi ◽  
Ahmed Karam ◽  
Ali Hassan Chughtai ◽  
Mansoor Ahmed Jiskani
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Kappa Statistics ◽  
Natural Ecosystem ◽  
Land Use Land Cover ◽  
Dry Land ◽  
Lulc Changes ◽  
Manchar Lake

In this study, the Land Use/Land Cover (LULC) change has been observed in wetlands comprises of Manchar Lake, Keenjhar Lake, and Chotiari Reservoir in Pakistan over the last four decades from 1972 to 2020. Each wetland has been categorized into four LULC classes; water, natural vegetation, agriculture land, and dry land. Multitemporal Landsat satellite data including; Multi-Spectral Scanner (MSS), Thematic Mapper (TM), and Operational Land Imager (OLI) images were used for LULC changes evaluation. The Supervised Maximum-likelihood classifier method is used to acquire satellite imagery for detecting the LULC changes during the whole study period. Soil adjusted vegetation index technique (SAVI) was also used to reduce the effects of soil brightness values for estimating the actual vegetation cover of each study site. Results have shown the significant impact of human activities on freshwater resources by changing the natural ecosystem of wetlands. Change detection analysis showed that the impacts on the land cover affect the landscape of the study area by about 40% from 1972 to 2020. The vegetation cover of Manchar Lake and Keenjhar Lake has been decreased by 6,337.17 and 558.18 ha, respectively. SAVI analysis showed that soil profile is continuously degrading which vigorously affects vegetation cover within the study area. The overall classification accuracy and Kappa statistics showed an accuracy of >90% for all LULC mapping studies. This work demonstrates the LULC changes as a critical monitoring basis for ongoing analyses of changes in land management to enable decision-makers to establish strategies for effectively using land resources.

scholarly journals Urban Land-Use Dynamics in the Niger Delta: The Case of Greater Port Harcourt Watershed

Urban Science ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 108 ◽  
Author(s):  
Nimi Dan-Jumbo ◽  
Marc Metzger ◽  
Andrew Clark
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Niger Delta ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
Hard Copy ◽  
Land Use Classification ◽  
Depth Analysis

Cities in developing countries are urbanising at a rapid rate, resulting in substantial pressures on environmental systems. Among the main factors that lead to flooding, controlling land-use change offers the greatest scope for the management of risk. However, traditional analysis of a “from–to” change matrix is not adequate to provide information of all the land-use changes that occur in a watershed. In this study, an in-depth analysis of land-use change enabled us to quantify the bulk of the changes accumulating from swap changes in a tropical watershed. This study assessed the historical and future land-use/land-cover (LULC) dynamics in the River State region of the Niger Delta. Land-use classification and change detection analysis was conducted using multi-source (Landsat TM, ETM, polygon map, and hard copy) data of the study area for 1986, 1995, and 2003, and projected conditions in 2060. The key findings indicate that historical urbanisation was rapid; urban expansion could increase by 80% in 2060 due to planned urban development; and 95% of the conversions to urban land occurred chiefly at the expense of agricultural land. Urban land was dominated by net changes rather than swap changes, which in the future could amplify flood risk and have other severe implications for the watershed.

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