Use of Landsat Thematic Mapper for urban land use/land cover mapping

1989 ◽  
Vol 17 (3) ◽  
pp. 85-99 ◽  
Author(s):  
A. P. Subudhi ◽  
N. D. Sharma ◽  
Debajit Mishra
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Land ◽  
Urban Land Use ◽  
Thematic Mapper ◽  
Land Cover Mapping ◽  
Landsat Thematic Mapper ◽  
Land Use Land Cover

Employing Spatial Metrics in Urban Land-use/Land-cover Mapping

2007 ◽  
Vol 73 (12) ◽  
pp. 1403-1415 ◽  
Author(s):  
Soe W. Myint ◽  
Elizabeth A. Wentz ◽  
Sam J. Purkis
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Cover Mapping ◽  
Land Use Land Cover ◽  
Spatial Metrics

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.

Reviewing the Pertinence of Sentinel-1 SAR for Urban Land Use Land Cover Classification

2020 ◽  
Vol 11 (5) ◽  
pp. 529-535
Author(s):  
Dan Abudu ◽  
Nigar Sultana Parvin ◽  
Geoffrey Andogah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Cover Classification ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Sensing Technology

Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets.

scholarly journals Improved simulation of very heavy rainfall events by incorporating WUDAPT urban land use/land cover in WRF

Urban Climate ◽  
2020 ◽  
Vol 32 ◽  
pp. 100616
Author(s):  
Pratiman Patel ◽  
Subhankar Karmakar ◽  
Subimal Ghosh ◽  
Dev Niyogi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Heavy Rainfall ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Rainfall Events ◽  
Heavy Rainfall Events

scholarly journals A Study of Diffusion Equation-Based Land-Use/Land-Cover Change Simulation

2021 ◽  
Vol 10 (6) ◽  
pp. 383
Author(s):  
Min Jin ◽  
Ruyi Feng ◽  
Lizhe Wang ◽  
Jining Yan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Diffusion Equation ◽  
Land Cover Change ◽  
Change Process ◽  
Urban Land ◽  
Urban Land Use ◽  
Series Data ◽  
Land Cover Changes ◽  
Land Use Land Cover

Simulating and predicting the development and changes in urban land change can provide valuable references for the sustainable development of cities. However, the change process of urban land-use/land-cover is a complex process involving multiple factors and multiple relationships. This dilemma makes it very challenging to accurately simulate the results and to make predictions. In response to this problem, we started with the physical characteristics of the land-use/land-cover change process and constructed a diffusion equation to simulate and predict urban land-use/land-cover changes. The diffusion equation is used to describe the diffusion characteristics of the land-use/land-cover change process, which helps to understand the urban land-use/land-cover change process. The experimental results show that (1) the diffusion equation we constructed can simulate urban land-use/land-cover changes, (2) the simulation process of the model is not limited by the time interval of the time series data itself, and (3) the model only requires one parameter without other constraints.

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