Impact of Land Cover Variability Indices on Land Surface Temperature Using Multi-Temporal Landsat Data in Greater Accra, Ghana
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Due to the increased anthropogenic activities, vegetated and green spaces are decreasing and are getting replaced by impervious surfaces, especially in cities. This leads to the increase in the surface temperature of urban areas when compared to the rural regions leading to the formation of urban heat island. Due to the higher rate of population increase and a lack of infrastructural facilities and regulations to mitigate the negative consequences of urbanisation, it is critical in developing countries to obtain timely and accurate information on the urban trend and its development. The current study examines the urban development of Greater Accra, Ghana using Landsat 7 dataset acquired during 2002, 2013, and 2020. Further, the influence of urban growth on the land surface temperature (LST) and land cover variability (LCV) indices including NDVI (Normalized Difference Vegetation Index), NDBI (Normalized Difference Built-Up Index), and NDWI (Normalized Difference Water Index) is identified during the study periods. According to the findings, the built-up area in the study region quadrupled between 2002 and 2020. According to Shannon's entropy analysis, the region's urban development is heterogeneous or dispersive. Furthermore, the regression analysis reveals a strong positive relationship between LST and NDBI (0.755), as well as a negative relationship between LST and NDVI (0.4417) and LST and NDWI (0.4417). (0.76). The study's findings could be used to develop sustainable urban socioeconomic and environmental planning policies in the study region.Keywords:
Impervious surface
Land Cover
Impervious surfaces have become the most intuitive indicator in the process of urbanization. Timely and accurate information on impervious surfaces from remote sensing images is essential. It not only helps us understand the process of land use/cover change, but also the influences on human society and the environment. In this study, convolutional neural network (CNN) was used to extract the impervious surface in Chengdu city, Sichuan province, China. The overall accuracy in 2009 and 2017 were 98.75% and 99.76% respectively. From the results for 2009 and 2017, the impervious surface increased by 51.24 km2, Growth rate is 13.8%. During the process of urban expansion, suburban farmland was replaced by impervious surfaces and the area of impervious surface gradually increased.
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Due to increasing impervious surfaces resulting from urbanization and industrialization which are directly linked to urban inundation and non-point pollutants runoff, there is a need to manage them systematically. A management over urban impervious surfaces calls for pervious/impervious maps, which enable viewing the distribution of impervious surfaces. Nevertheless, relevant data are absent as now. In this respect, despite the diversity of proposed methods, pilot implementation and accuracy verification have never been conducted. Therefore, this study is aimed to produce a pilot pervious/impervious map based on previously proposed methods and to elucidate its pros and cons with a view to proposing a method for producing a GIS-based optimal pervious/impervious map. Following previously proposed methods, a pervious/impervious map of Bupyeong-gu, Incheon was produced. Then, a method of producing optimal pervious/impervious maps applicable to urban areas was proposed through the comparison of pros and cons of relevant spatial data. As a result, the map had been confirmed 99.2% of classification accuracy. Based on the present findings, future studies should establish a standardized method for producing. Also, this method should be used to produce pervious/impervious maps of other regions so that it can be applied to managing impervious surfaces in major urban areas nationwide.
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Urban impervious surface in the form of rooftops, street pavement, parking lots, etc. is an important contributor to water pollution, urban heat island, flash floods and other environmental degradations. While studies on the extent of impervious surface are common in advanced countries, few have been carried out in developing countries. This paper discusses a study on the nature of impervious surface coverage in a southern city in Malaysia. The study focuses on impervious surface in several residential areas, looking at the relationship between impervious surface and housing density as well as the source of the surface. Remote sensing images combined with some GIS techniques were employed for this purpose. The percentage o[ impervious surface measured ranged from 40-95%, well above the values indicated from similar studies overseas. While density was a factor in the amount of impervious surface, it was not the only factor. Other factors such as policies on impervious surface control were also important as illustrated by comparison of the results of this study to similar studies reported in the USA. Based on these findings, the paper offersseveral steps towards reduction of impervious sw'face in residential areas.
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Simulated results from many urban runoff models are sensitive to the value used for impervious area. This paper explores the use of effective impervious area versus total impervious area for input to these models. Total impervious areas may be appropriate for black-box models but not for deterministic models. Potential problems of using total impervious area in deterministic models include that (1) runoff volumes and peak flows may be substantially overestimated for ungaged watersheds, (2) simulated changes in runoff due to increasing intensity of land use are likely to be smaller if total impervious area is used rather than effective impervious area, and (3) overestimates of infiltration parameters are likely if the model is calibrated using total impervious area and measured runoff data. Impervious-area data collected from 19 urban watersheds in the Denver metropolitan area showed strong relationships between effective impervious area, total impervious area, and land use.
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In estimating runoff from urban catchments, 3 separate types of surfaces are generally recognised: (i) impervious areas (e.g. roofs and paved areas) which are directly connected to the drainage system (ii) additional impervious areas which are not directly connected, runoff from which flows over pervious surfaces before reaching the drainage system (e.g. a roof that discharges onto a lawn); (iii) Pervious areas consisting of lawns, gardens and parkland. The identification of directly connected impervious areas and indirectly connected impervious areas in urban areas is a key issue that informs any modelling assessment of runoff in urban catchments. Key questions to be resolved in this regard are: - Whether the ratio of directly connected impervious area to total impervious area is broadly constant, irrespective of catchment location and age; or - if it is a factor of the age of a catchment, whether this may be an indicator of the historical versus current drainage practices An analysis of seven gauged urban catchments across Australia has been undertaken to establish if directly connected impervious areas are the same as effective impervious areas or if effective impervious areas reflect runoff responses from connected impervious areas and indirectly connected impervious areas draining onto pervious areas. These analysis comprised a statistical analysis of rainfall and streamflow, and a desktop GIS analysis using mainly aerial photography. The analysis of rainfall and streamflow indicated that across the study catchments, the Effective Impervious Area is approximately 30% - 40% of the urbanised area, and is around 75%-85% of the Directly Connected Impervious Area estimated using a desktop GIS analysis method. It is concluded that the GIS procedure overestimates DCIA and that impervious areas are less connected than assumed to date by hydrologists.
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Land cover change monitoring is important for climate and environmental research. An automated approach for updating land cover maps derived from Landsat-like data is urgently needed to process large amounts of data. Change detection is an important part of the updating approach; however, pseudo-changes commonly occur because satellite images acquired in different seasons can capture phenological differences. Change detection based on normalized difference vegetation index (NDVI) time series data could avoid this problem; nevertheless it suffers from the much lower spatial resolution of the NDVI data. To address the resolution issue, this study improves an automated land cover updating approach by integrating downscaled NDVI time series data. First, Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data at 250-m resolution are downscaled to 30 m using the NDVI linear mixing growth model. Then, the NDVI-based change detection method is used to detect the changed/unchanged areas, and the unchanged areas are removed from the changed areas that were detected using the original land cover updating approach. A case study shows that the NDVI-based change detection module sufficiently removed the pseudo-change caused by seasonal differences and improved the land cover updating result, with an increase in overall accuracy from 76.6% to 89.6%.
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Urban impervious surface in the form of rooftops, street pavement, parking lots, etc. is an important contributor to water pollution, urban heat island, flash floods and other environmental degradations. While studies on the extent of impervious surface are common in advanced countries, few have been carried out in developing countries. This paper discusses a study on the nature of impervious surface coverage in a southern city in Malaysia. The study focuses on impervious surface in several residential areas, looking at the relationship between impervious surface and housing density as well as the source of the surface. Remote sensing images combined with some GIS techniques were employed for this purpose. The percentage o[ impervious surface measured ranged from 40-95%, well above the values indicated from similar studies overseas. While density was a factor in the amount of impervious surface, it was not the only factor. Other factors such as policies on impervious surface control were also important as illustrated by comparison of the results of this study to similar studies reported in the USA. Based on these findings, the paper offersseveral steps towards reduction of impervious sw'face in residential areas.
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Urban area
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With increasing urbanization and population pressure, the barren ground is altered from undisturbed soils to disturbed soils, which multiplies fast growth of impervious areas in cities. An impervious area is a modified surface that prevents water from infiltrating into the soil. Hydraulically connected impervious areas are denoted as effective impervious area (EIA) and hydraulically disconnected are denoted as non-effective impervious area (NEIA). The summation of above two impervious covers amounts to the total impervious area (TIA). Impervious surface data is important for urban planning and environmental and resources management. Therefore, remote sensing of impervious surfaces in the urban areas has recently attracted unprecedented attention. The estimation of TIA is comparatively simple as compared to the estimation of EIA, despite the fact that later is viewed as more proper for hydrologic studies. In this paper, emphasis was given on the estimation of impervious area (TIA) for the year 2000 and 2014 to scrutinize urbanization growth of Ahmedabad city in India using medium resolution satellite imageries by using geospatial techniques under the ArcGIS 10.1 platform. The more hydraulically relevant EIA is estimated using two indirect methods, i.e. empirical equations derived from the whole basin or sub-basin parameters from the estimated TIA and using an annual hydrograph methodology. A graphical demonstration of the estimated EIA and TIA for different years is illustrated to analyze the rate of urban expansion.
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