scholarly journals Impact Quantification of Decentralization in Urban Growth by Extracting Impervious Surfaces Using ISEI in Model Maker

2020 ◽  
Vol 12 (1) ◽  
pp. 380
Author(s):  
Nana Yaw Danquah Twumasi ◽  
Chikondi Chisenga ◽  
Nayyer Saleem ◽  
Neema Nicodemus Lyimo ◽  
Orhan Altan
Keyword(s):  
Urban Growth ◽  
Public Investment ◽  
Good Method ◽  
Impervious Surface ◽  
Computational Time ◽  
Impervious Surfaces ◽  
Landsat Images ◽  
Target Feature ◽  
Surface Areas ◽  
Decentralization Policy

Decentralization problems in Africa have caused some infrastructure disparity between country capitals and distant districts. In Ghana, less public investment has created a gap between implementation results and theoretical benefits. Spectral indices are a good approach to extracting impervious surfaces, which is a good method of measuring urbanization. These are restricted by complexity, sensor limitation, threshold values, and high computational time. In this study, we measure the urbanization dynamics of Wa District in Ghana by applying a proposed method of impervious surface extraction index (ISEI), to evaluate the decentralization policy using Landsat images from 1984–2018 and a single S2A data. Comparing our proposed method with five other existing indexes, ISEI provided good discriminated results between target feature and background, with pixel values ranging between 0 and +1. Other indexes produced negative values. ISEI accuracy varied from 84.62–94.00% while existing indexes varied from 73.85–90.00%. Our results also showed increased impervious surface areas of 83.26 km2, which is about 7.72% of total area while the average annual urban growth was recorded as 4.42%. These figures proved that the quantification of decentralization is very positive. The study provides a foundation for urban environment research in the context of decentralization policy.

scholarly journals Spatio-Temporal Analysis of Impervious Surface Expansion in the Qinhuai River Basin, China, 1988–2017

2021 ◽  
Vol 13 (22) ◽  
pp. 4494
Author(s):  
Shanshan Wang ◽  
Yingxia Pu ◽  
Shengfeng Li ◽  
Runjie Li ◽  
Maohua Li
Keyword(s):  
River Basin ◽  
Spatial Scales ◽  
Impervious Surface ◽  
Temporal Analysis ◽  
Impervious Surfaces ◽  
Continuous Change ◽  
Landsat Images ◽  
Rapid Urbanization ◽  
Spatio Temporal ◽  
Qinhuai River

Impervious surfaces are key indicators for urbanization monitoring and watershed degradation assessment over space and time. However, most empirical studies only extracted impervious surface from spatial, temporal or spectral perspectives, paying less attention to integrating multiple dimensions in acquiring continuous changes in impervious surfaces. In this study, we proposed a neighborhood-based spatio-temporal filter (NSTF) to obtain the continuous change information of impervious surfaces from multi-temporal Landsat images in the Qinhuai River Basin (QRB), Jiangsu, China from 1988–2017, based on the results from semi-automatic decision tree classification. Moreover, we used the expansion intensity index (EII) and the landscape extension index (LEI) to further characterize the spatio-temporal characteristics of impervious surfaces on different spatial scales. The preliminary results showed that the overall accuracies of the final classification were about 95%, with the kappa coefficients ranging between 0.9 and 0.96. The QRB underwent rapid urbanization with the percentage of the impervious surfaces increasing from 2.72% in 1988 to 25.6% in 2017. Since 2006, the center of urbanization expansion was shaped from the urban built-up areas of Nanjing and Jiangning to non-urban built-up areas of the Jiangning, Lishui, and Jurong districts. The edge expansion occupied 73% on average among the different landscape expansion types, greatly beyond outlying (12%) and infilling (15%). The window size in the NSTF has a direct impact on the subsequent analysis. Our research could provide decision-making references for future urban planning and development in the similar basins.

scholarly journals THE USAGE OF RUSBOOST BOOSTING METHOD FOR CLASSIFICATION OF IMPERVIOUS SURFACES

2016 ◽  
Vol XLI-B7 ◽  
pp. 981-985 ◽  
Author(s):  
M. H. Kesikoglu ◽  
U. H. Atasever ◽  
C. Ozkan ◽  
E. Besdok
Keyword(s):  
Decision Tree ◽  
Classification Tree ◽  
Satellite Image ◽  
Impervious Surface ◽  
Landsat 8 ◽  
Impervious Surfaces ◽  
Classification Methods ◽  
Surface Areas ◽  
Tree Algorithms ◽  
Boosting Method

Impervious surface areas are artificial structures covered by materials such as asphalt, stone, brick, rooftops and concrete. Buildings, parking lots, roads, driveways and sidewalks are shown as impervious surfaces. They increase depending on the population growth. The spatial development of impervious surface expansion is necessary for better understanding of the urbanization status and its effect on environment. There are different impervious surface determining approaches met in literature. In this paper, it is aimed to extract the impervious surface areas of Kayseri city, Turkey by using remote sensing techniques. It is possible to group these techniques under a few main topics as V-I-S (vegetation-impervious surface-soil) model, based on spectral mixture analysis or decision tree algorithms or impervious surface indices. According to these techniques, we proposed a new technique by using RUSBoost algorithm based on decision tree in this study. In this scope, Landsat 8 LDCM image belonging to July, 2013 was used. Determining of impervious surface areas accurately depends on accuracy of image classification methods. Therefore, satellite image was classified separately by using Classification Tree and RUSBoost boosting method which increases accuracy of the classification method based on decision tree. Classification accuracies of these supervised classification methods were compared and it was observed that the best overall accuracy was obtained with RUSBoost method. For this reason, RUSBoost method was preferred to determine impervious surface areas. The overall accuracies were obtained 95 % with Classification Tree and 97 % with RUSBoost boosting method.

scholarly journals Expansion of Impervious Surfaces and Their Driving Forces in Highly Urbanized Cities in Kyrgyzstan

2020 ◽  
Vol 17 (1) ◽  
pp. 362 ◽  
Author(s):  
Gulkaiyr Omurakunova ◽  
Anming Bao ◽  
Wenqiang Xu ◽  
Eldiiar Duulatov ◽  
Liangliang Jiang ◽  
...  
Keyword(s):  
Natural Resources ◽  
Urban Areas ◽  
Driving Forces ◽  
Land Use Changes ◽  
Impervious Surface ◽  
Good Evidence ◽  
Sustainable Urban Development ◽  
Population Increase ◽  
Impervious Surfaces ◽  
Landsat Images

The expansion of urban areas due to population increase and economic expansion creates demand and depletes natural resources, thereby causing land use changes in the main cities. This study focuses on land cover datasets to characterize impervious surface (urban area) expansion in select cities from 1993 to 2017, using supervised classification maximum likelihood techniques and by quantifying impervious surfaces. The results indicate an increasing trend in the impervious surface area by 35% in Bishkek, 75% in Osh, and 15% in Jalal-Abad. The overall accuracy (OA) for the image classification of two different datasets for the three cities was between 82% and 93%, and the kappa coefficients (KCs) were approximately 77% and 91%. The Landsat images with other supplementary data showed positive urban growth in all of the cities. The GDP, industrial growth, and urban population growth were driving factors of impervious surface sprawl in these cities from 1993 to 2017.Landscape Expansion Index (LEI) results also provided good evidence for the change of impervious surfaces during the study period. The results emphasize the idea of applying future planning and sustainable urban development procedures for sustainable use of natural resources and their management, which will increase life quality in urban areas and environments.

scholarly journals Spatiotemporal Variance Assessment of Urban Rainstorm Waterlogging Affected by Impervious Surface Expansion: A Case Study of Guangzhou, China

2018 ◽  
Vol 10 (10) ◽  
pp. 3761 ◽  
Author(s):  
Huafei Yu ◽  
Yaolong Zhao ◽  
Yingchun Fu ◽  
Le Li
Keyword(s):  
Spatial Pattern ◽  
Urban Renewal ◽  
Impervious Surface ◽  
City Centre ◽  
Impervious Surfaces ◽  
Surface Expansion ◽  
The Impact ◽  
Gwr Model ◽  
Runoff Plots

Urban rainstorm waterlogging has become a typical “city disease” in China. It can result in a huge loss of social economy and personal property, accordingly hindering the sustainable development of a city. Impervious surface expansion, especially the irregular spatial pattern of impervious surfaces, derived from rapid urbanization processes has been proven to be one of the main influential factors behind urban waterlogging. Therefore, optimizing the spatial pattern of impervious surfaces through urban renewal is an effective channel through which to attenuate urban waterlogging risk for developed urban areas. However, the most important step for the optimization of the spatial pattern of impervious surfaces is to understand the mechanism of the impact of urbanization processes, especially the spatiotemporal pattern of impervious surfaces, on urban waterlogging. This research aims to elucidate the mechanism of urbanization’s impact on waterlogging by analysing the spatiotemporal characteristics and variance of urban waterlogging affected by urban impervious surfaces in a case study of Guangzhou in China. First, the study area was divided into runoff plots by means of the hydrologic analysis method, based on which the analysis of spatiotemporal variance was carried out. Then, due to the heterogeneity of urban impervious surface effects on waterlogging, a geographically weighted regression (GWR) model was utilized to assess the spatiotemporal variance of the impact of impervious surface expansion on urban rainstorm waterlogging during the period from the 1990s to the 2010s. The results reveal that urban rainstorm waterlogging significantly expanded in a dense and circular layer surrounding the city centre, similar to the impervious surface expansion affected by urbanization policies. Taking the urban runoff plot as the research unit, GWR has achieved a good modelling effect for urban storm waterlogging. The results show that the impervious surfaces in the runoff plots of the southeastern part of Yuexiu, the southern part of Tianhe and the western part of Haizhu, which have experienced major urban engineering construction, have the strongest correlation with urban rainstorm waterlogging. However, for different runoff plots, the impact of impervious surfaces on urban waterlogging is quite different, as there exist other influence factors in the various runoff plots, although the impervious surface is one of the main factors. This result means that urban renewal strategy to optimize the spatial pattern of impervious surfaces for urban rainstorm waterlogging prevention and control should be different for different runoff plots. The results of the GWR model analysis can provide useful information for urban renewal strategy-making.

scholarly journals A Novel Index for Impervious Surface Area Mapping: Development and Validation

2018 ◽  
Vol 10 (10) ◽  
pp. 1521 ◽  
Author(s):  
Yugang Tian ◽  
Hui Chen ◽  
Qingju Song ◽  
Kun Zheng
Keyword(s):  
Near Infrared ◽  
Thermal Emission ◽  
Impervious Surface ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Remotely Sensed Data ◽  
Capital Cities ◽  
Heat Islands ◽  
Surface Areas ◽  
Hydrological Cycles

The distribution and dynamic changes in impervious surface areas (ISAs) are crucial to understanding urbanization and its impact on urban heat islands, earth surface energy balance, hydrological cycles, and biodiversity. Remotely sensed data play an essential role in ISA mapping, and numerous methods have been developed and successfully applied for ISA extraction. However, the heterogeneity of ISA spectra and the high similarity of the spectra between ISA and soil have not been effectively addressed. In this study, we selected data from the US Geological Survey (USGS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral libraries as samples and used blue and near-infrared bands as characteristic bands based on spectral analysis to propose a novel index, the perpendicular impervious surface index (PISI). Landsat 8 operational land imager data in four provincial capital cities of China (Wuhan, Shenyang, Guangzhou, and Xining) were selected as test data to examine the performance of the proposed PISI in four different environments. Threshold analysis results show that there is a significant positive correlation between PISI and the proportion of ISA, and threshold can be adjusted according to different needs with different accuracy. Furthermore, comparative analyses, which involved separability analysis and extraction precision analysis, were conducted among PISI, biophysical composition index (BCI), and normalized difference built-up index (NDBI). Results indicate that PISI is more accurate and has better separability for ISA and soil as well as ISA and vegetation in the ISA extraction than the BCI and NDBI under different conditions. The accuracy of PISI in the four cities is 94.13%, 96.50%, 89.51%, and 93.46% respectively, while BCI and NDBI showed accuracy of 77.53%, 93.49%, 78.02%, and 84.03% and 58.25%, 57.53%, 77.77%, and 64.83%, respectively. In general, the proposed PISI is a convenient index to extract ISA with higher accuracy and better separability for ISA and soil as well as ISA and vegetation. Meanwhile, as PISI only uses blue and near-infrared bands, it can be used in a wider variety of remote sensing images.

scholarly journals URBAN IMPERVIOUS SURFACE EXTRACTION BASED ON REMOTE SENSING IMAGES

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 357-360
Author(s):  
X. Y. Long ◽  
Z. F. Shao ◽  
X. X. Feng
Keyword(s):  
Rapid Development ◽  
Impervious Surface ◽  
Support Vector ◽  
Impervious Surfaces ◽  
Surface Distribution ◽  
Human Environment ◽  
Important Indicator ◽  
Urbanization Level ◽  
Urban Impervious Surfaces

Abstract. Urban planning and constructions affect spatial patterns of urban impervious surfaces, which in turn modify the urban environment and affect human-environment interactions. Impervious surfaces can redistribute precipitation patterns, and the perviousness–imperviousness ratio is considered as one important indicator for assessing the degree of urbanization and the quality of urban eco-environment. The spatial distribution and dynamics of impervious surfaces contribute to better understand urbanization and its impacts on regional or urban hydrological environment, surface temperature balance and biodiversity, etc. Hengqin new area is located in Hengqin island, south of Zhuhai city, adjacent to Hong Kong and Macao. It was officially established as a free trade zone in 2009. Due to the rapid development of Hengqin in recent years, this paper discusses Landsat8 imagery of time series in mapping impervious surfaces, and analysis the changes of impervious surface in Hengqin from 2013 to 2018. Support vector machine (SVM) is a classical classifier that is supervised learning models and that use related learning algorithms to analyze data for classification and regression analysis (Vapnik, 1995). In this paper, we obtain the impervious surface distribution via SVM and get good accuracy. The impervious surface distribution of Hengqin in six years show that the quickly improve of urbanization level. However, with the development of urbanization, the impervious surface has not changed dramatically, which shows that the decision-making of urban managers is correct. After the urbanization construction in Hengqin, it is still an ecological island.

scholarly journals Land Use Dynamics and Variations in Sprawl across Municipalities in the Bamenda Urban-scape from 1996-2018

2020 ◽  
Vol 13 (4) ◽  
pp. 224
Author(s):  
Fombe Lawrence F. ◽  
Acha Mildred E.
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Urban Areas ◽  
Agricultural Land ◽  
Pearson Correlation ◽  
Town Planning ◽  
Land Values ◽  
Landsat Images ◽  
Land Use Dynamics ◽  
Spatiotemporal Analyses

Worldwide urban areas are having increasing influence over the surrounding landscape. Peri-urban regions of the world are facing challenges which results from sprawl with increasing problems of social segregation, wasted land and greater distance to work. This study seeks to examine the trends in land use dynamics, urban sprawl and associated development implications in the Bamenda Municipalities from 1996 to 2018. The study made use of the survey, historical and correlational research designs. The purposive and snowball techniques were used to collect data. Spatiotemporal analyses were carried out on Landsat Images for 1996, 2008, and 2018 obtained from Earth Explorer, Erdas Image 2014 and changes detected from the maps digitized. The SPSS version 21 and MS Excel 2016 were used to analyze quantitative and qualitative data. The former employed the Pearson correlation analysis. Analysis of land use/land cover change detection reveals that built-up area has increased significantly from 1996 to 2018 at the detriment of forest, wetland and agricultural land at different rates within each municipality. These changes have led to invasion of risk zones, high land values, uncoordinated, uncontrolled and unplanned urban growth. The study suggests that proactive planning, use of GIS to monitor land use activities, effective implementation of existing town planning norms and building regulations, are invaluable strategies to sustainably manage urban growth in Bamenda.

Detection of Urban Expansion by Using DMSP-OLS, Landsat Data and Linear Spectral Unmixing Method

2019 ◽  
pp. 1372-1382
Author(s):  
Cihan Uysal ◽  
Derya Maktav
Keyword(s):  
Urban Growth ◽  
Urban Areas ◽  
Urban Expansion ◽  
Dynamic Structure ◽  
Spectral Unmixing ◽  
Landsat Images ◽  
Green Vegetation ◽  
Linear Mixture Model ◽  
Linear Spectral Unmixing ◽  
Spectral Mixture

Urbanization has been increasingly continuing in Turkey and in the world for the last 30 years. Especially for the developing countries, urbanization is a necessary fact for the sustainability of the urban growth. Yet, this growth should be controlled and planned; otherwise, many environmental problems might occur. Therefore, the urban areas having dynamic structure should be monitored periodically. Monitoring the changes in urban environment can be provided with land cover land use (LCLU) maps produced by the pixel based classification methods using ‘maximum likelihood' and ‘isodata' techniques. However, these thematic maps might bring about inaccurate classification results in heterogeneous areas especially where low spatial resolution satellite data is used since, in these approaches, each pixel is represented with only one class value. In this study, considering the spectral mixture analysis (SMA) each pixel is represented by endmember fractions. The earth is represented more accurately using 'substrate (S)', ‘green vegetation (V)' and ‘dark surfaces (D)' spectral endmember reflectances with this analysis based on linear mixture model. Here, the surrounding of Izmit Gulf, one of the most industrialized areas of Turkey, has been chosen as the study area. SMA has been applied to LANDSAT images of the years of 1984, 1999 and 2009. In addition, DMSP-OLS data of 1992, 1999 and 2009 has been used to detect urban areas. According to the results, the changes in LCLU and especially the urban growth areas have been detected accurately using the SMA method.

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