scholarly journals Exploring the Relationship between Urbanization and the Eco-Environment: A Case Study of Beijing

2019 ◽  
Vol 11 (22) ◽  
pp. 6298 ◽  
Author(s):  
Yi Huang ◽  
Qianqian Qiu ◽  
Yehua Sheng ◽  
Xiangqiang Min ◽  
Yuwei Cao
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Local Development ◽  
Coupling Model ◽  
Spatiotemporal Analysis ◽  
Landsat Images ◽  
Major Function ◽  
Stage Of Development ◽  
Land Cover Data ◽  
Functional Zones

Beijing is one of the most developed cities in China and has experienced a series of environmental problems. In accordance with the Major Function Zone planning, Beijing is divided into four zones in an attempt to coordinate development between urban areas and the eco-environment. Classic coupling model uses statistical data to evaluate the interactions of these two subsystems; however, it lacks the capability to express dynamic changes to land cover. Thus, we extracted land cover data from Landsat images and examined the urbanization and eco-environment level as well as the coupling coordination in Beijing and its functional zones. The main conclusions are as follows. (1) Between 2001 and 2011, both urbanization and the eco-environment level in Beijing and its functional zones grew steadily. Different zones coordinated together according to their own characteristics, and the overall coupling coordination of the city transformed from the “basically balanced” to the “superiorly balanced” stage of development. (2) After 2011, the condition of the eco-environment worsened in Beijing and in most of the function zones, while the coordination between increased urbanization and the worsened eco-environment may be a result of environmental lag. This study integrated land cover data into the coupling mode and fully utilized the advantages of spatiotemporal analysis and the coupling model. In other words, the spatiotemporal analysis explains the land cover changes visually over the research period, while the coupling model explores the interaction mechanisms between urbanization and the eco-environment. The land cover data enriches the coupling theory and provides a reference for evaluating the effectiveness of local development policy.

scholarly journals Spatial and Temporal Dynamics of Urban Wetlands in an Indian Megacity over the Past 50 Years

2020 ◽  
Vol 12 (4) ◽  
pp. 662 ◽  
Author(s):  
Katja Brinkmann ◽  
Ellen Hoffmann ◽  
Andreas Buerkert
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Temporal Dynamics ◽  
Open Water ◽  
Water Bodies ◽  
Annual Rainfall ◽  
Urban Wetlands ◽  
Landsat Images ◽  
Urban District ◽  
Wetland Area

Asian megacities have attracted much scientific attention in the context of global urbanization, but few quantitative studies analyze wetland transformation in the rural–urban interface. With its rampant growth and transformation from a tree-lined “Garden City” to a busy megalopolis with often-blocked highways and large built-up areas, Bengaluru (Karnataka, S-India) is a good example for assessing how urbanization has led to the acute degradation of wetlands. We therefore investigated long-term land cover and wetland changes from 1965 to 2018 based on an object-based classification of multi-temporal Corona and Landsat images. To quantify and compare the dynamics of open water surfaces and vegetation, we defined the potential wetland areas (PWA) along the rural–urban gradient and linked our analyses to an index describing the degree of urbanization (survey stratification index (SSI)). During the five decades studied, built-up areas in the Bengaluru Urban district increased ten-fold, with the highest growth rate from 2014 to 2018 (+ 8% annual change). Patches of lake wetlands were highly dynamic in space and time, partly reflecting highly variable annual rainfall patterns ranging from 501 mm in 1965 to 1374 mm in 2005 and monsoon-driven alterations in the hydrologic regime. While water bodies and flooded areas shrunk from 64 km2 in 1965 to 55 km2 in 2018, in 1965, the total rural wetland area with an SSI > 0.5 was twice as high as in 2018. The rural–urban land cover pattern within potential wetland areas changed drastically during this period. This is reflected, for example, by a four-fold increase in the wetland area with an SSI of 0.3, as compared to a decline by 43% in wetland area with an SSI of 0.8. While, in urban areas, wetlands were mostly lost to construction, in areas with a rural character, open water bodies were mainly transformed into green space. The detected changes in urban wetlands were likely accompanied by ecological regime changes, triggering deteriorations in ecosystem services (ESS) which merit further research.

scholarly journals Regionalisation of asset values for risk analyses

2006 ◽  
Vol 6 (2) ◽  
pp. 167-178 ◽  
Author(s):  
A. H. Thieken ◽  
M. Müller ◽  
L. Kleist ◽  
I. Seifert ◽  
D. Borst ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Large Scale ◽  
Census Data ◽  
Population Data ◽  
Dasymetric Mapping ◽  
Unit Value ◽  
Land Cover Data ◽  
Mapping Techniques ◽  
Asset Data

Abstract. In risk analysis there is a spatial mismatch of hazard data that are commonly modelled on an explicit raster level and exposure data that are often only available for aggregated units, e.g. communities. Dasymetric mapping techniques that use ancillary information to disaggregate data within a spatial unit help to bridge this gap. This paper presents dasymetric maps showing the population density and a unit value of residential assets for whole Germany. A dasymetric mapping approach, which uses land cover data (CORINE Land Cover) as ancillary variable, was adapted and applied to regionalize aggregated census data that are provided for all communities in Germany. The results were validated by two approaches. First, it was ascertained whether population data disaggregated at the community level can be used to estimate population in postcodes. Secondly, disaggregated population and asset data were used for a loss evaluation of two flood events that occurred in 1999 and 2002, respectively. It must be concluded that the algorithm tends to underestimate the population in urban areas and to overestimate population in other land cover classes. Nevertheless, flood loss evaluations demonstrate that the approach is capable of providing realistic estimates of the number of exposed people and assets. Thus, the maps are sufficient for applications in large-scale risk assessments such as the estimation of population and assets exposed to natural and man-made hazards.

scholarly journals An Assessment of Changes the Land Use Land Cover and Impact of the It Park at Talwade Pune On the Nearby Villages

2020 ◽  
pp. 172-179
Author(s):  
Ujjwala Khare ◽  
Prajakta Thakur
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rapid Growth ◽  
Urban Areas ◽  
Satellite Images ◽  
Ground Truth ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Tertiary Sector ◽  
Land Cover Maps

<p>The expansion of urban areas is common in metropolitan cities in India. Pune also has experienced rapid growth in the fringe areas of the city. This is mainly on account of the development of the Information Technology (IT) Parks. These IT Parks have been established in different parts of Pune city. They include Hinjewadi, Kharadi, Talwade and others like the IT parks in Magarpatta area. The IT part at Talwade is located to close to Pune Nashik Highway has had an impact on the villages located around it. The surrounding area includes the villages of Talwade, Chikhli, Nighoje, Mahalunge, Khalumbre and Sudumbre.</p> <p>The changes in the land use that have occurred in areas surrounding Talwade IT parks during the last three decades have been studied by analyzing the LANDSAT images of different time periods. The satellite images of the 1992, 2001 and 2011 were analyzed to detect the temporal changes in the land use and land cover.</p> <p>This paper attempts to study the changes in land use / land cover which has taken place in these villages in the last two decades. Such a study can be done effectively with the help of remote sensing and GIS techniques. The tertiary sector has experienced a rapid growth especially during the last decade near the IT Park. The occupation structure of these villages is also related to the changes due to the development of the IT Park.</p> <p>The land use of study area has been analysed using the ground truth applied to the satellite images at decadal interval. Using the digital image processing techniques, the satellite images were then classified and land use / land cover maps were derived. The results show that the area under built-up land has increased by around 14 per cent in the last 20 years. On the contrary, the land under agriculture, barren, pasture has decreased significantly.</p>

scholarly journals ASSESSMENT OF LAND USE AND LAND COVER CHANGE DETECTION BY USING REMOTE SENSING AND GIS TECHNIQUES IN THE COASTAL DESERTS, SOUTH OF IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 489-492
Author(s):  
S. A. R. Hosseini ◽  
H. Gholami ◽  
Y. Esmaeilpoor
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Urban Areas ◽  
Ground Truth ◽  
Landsat Images ◽  
Ground Truth Data ◽  
Sensing Technology ◽  
Time Period

Abstract. Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Due to the large expanse of land change detection by the traditional methods is not sufficient and efficient; therefore, using of new methods such as remote sensing technology is necessary and vital This study evaluates LULC change in chabahar and konarak Coastal deserts, located in south of sistan and baluchestan province from 1988 to 2018 using Landsat images. Maximum likelihood classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. Then, taking ground truth data, the classified maps accuracy were assessed by calculating the Kappa coefficient and overall accuracy. The results for the time period of 1988–2018 are presented. Based on the results of the 30-year time period, vegetation has been decreased in area while urban areas have been developed. The area of saline and sandy lands has also increased.

scholarly journals A GEOBIA Approach for Multitemporal Land-Cover and Land-Use Change Analysis in a Tropical Watershed in the Southeastern Amazon

2018 ◽  
Vol 10 (11) ◽  
pp. 1683 ◽  
Author(s):  
Pedro Souza-Filho ◽  
Wilson Nascimento ◽  
Diogo Santos ◽  
Eliseu Weber ◽  
Renato Silva ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Urban Areas ◽  
Landsat Images ◽  
Change Analysis ◽  
Human Settlements ◽  
Object Based ◽  
Detection Approach ◽  
Tropical Watershed

The southeastern Amazon region has been intensively occupied by human settlements over the past three decades. To evaluate the effects of human settlements on land-cover and land-use (LCLU) changes over time in the study site, we evaluated multitemporal Landsat images from the years 1984, 1994, 2004, 2013 and Sentinel to the year 2017. Then, we defined the LCLU classes, and a detailed “from-to” change detection approach based on a geographic object-based image analysis (GEOBIA) was employed to determine the trajectories of the LCLU changes. Three land-cover (forest, montane savanna and water bodies) and three land-use types (pasturelands, mining and urban areas) were mapped. The overall accuracies and kappa values of the classification were higher than 0.91 for each of the classified images. Throughout the change detection period, ~47% (19,320 km2) of the forest was preserved mainly within protected areas, while almost 42% (17,398 km2) of the area was converted from forests to pasturelands. An intrinsic connection between the increase in mining activity and the expansion of urban areas also exists. The direct impacts of mining activities were more significant throughout the montane savanna areas. We concluded that the GEOBIA approach adopted in this study combines the advantages of quality human interpretation and the capacities of quantitative computing.

scholarly journals Impacts of Urbanization on Land Cover Pattern in Bangladesh: A Downscaled Approach for Chuadanga District

2021 ◽  
Vol 12 (1-2) ◽  
pp. 37-42
Author(s):  
S Mahfuza ◽  
MS Hossain ◽  
M Islam
Keyword(s):  
Land Cover ◽  
Water Body ◽  
Urban Areas ◽  
Urban Expansion ◽  
Bare Soil ◽  
Strongly Correlated ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Development Goals ◽  
Remote Sensing Techniques

Bangladesh has been facing rapid and unplanned urbanization for last several years resulting devastating change to vegetation, fresh water body and bare soil in this area. This integrated study aimed to find out the trend of urbanization and land cover changes in Chuandanga, a western district of Bangladesh. This downscaled approach used GIS and remote sensing techniques for supervised land cover classification of Landsat images for last five years (2014-2018). The study has portrayed an increasing trend in built up area and bare soil whereas a decreasing trend in vegetation and water body. Meanwhile, it has been found that change in built up area and vegetation cover is strongly correlated whilst built area is increased by 1.28% (14.84 sq.km) and vegetation decreased by 16.54% (191.96 sq.km) during this period. Moreover, it is also observed that rapid growth of urban areas has a considerable influence on decreasing water body and bare soil as well as the changing pattern showing the forthcoming urbanization in this city. This study shows the importance of urban expansion for achieving Sustainable Development Goals (SDG) in particular Goal 11, Sustainable Cities. Environ. Sci. & Natural Resources, 12(1&2): 37-42, 2019

scholarly journals PRODUCING INFORMATION FOR CORINE DATABASE BY USING CLASSIFICATION METHOD: A CASE STUDY OF SAZLIDERE BASIN, ISTANBUL

2017 ◽  
Vol IV-4/W4 ◽  
pp. 357-362
Author(s):  
F. B. Sarıyılmaz ◽  
N. Musaoğlu ◽  
N. Uluğtekin
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landsat Images ◽  
Mapping Unit ◽  
Corine Land Cover ◽  
Land Cover Data ◽  
Image Pixels ◽  
Analysis Of The Images ◽  
Agricultural Areas

The Sazlidere Basin is located on the European side of Istanbul within the borders of Arnavutkoy and Basaksehir districts. The total area of the basin, which is largely located within the province of Arnavutkoy, is approximately 177 km2. The Sazlidere Basin is faced with intense urbanization pressures and land use / cover change due to the Northern Marmara Motorway, 3rd airport and Channel Istanbul Projects, which are planned to be realized in the Arnavutkoy region. Due to the mentioned projects, intense land use /cover changes occur in the basin. In this study, 2000 and 2012 dated LANDSAT images were supervised classified based on CORINE Land Cover first level to determine the land use/cover classes. As a result, four information classes were identified. These classes are water bodies, forest and semi-natural areas, agricultural areas and artificial surfaces. Accuracy analysis of the images were performed following the classification process. The supervised classified images that have the smallest mapping units 0.09 ha and 0.64 ha were generalized to be compatible with the CORINE Land Cover data. The image pixels have been rearranged by using the thematic pixel aggregation method as the smallest mapping unit is 25&amp;thinsp;ha. These results were compared with CORINE Land Cover 2000 and CORINE Land Cover 2012, which were obtained by digitizing land cover and land use classes on satellite images. It has been determined that the compared results are compatible with each other in terms of quality and quantity.

scholarly journals Spatiotemporal Analysis of Land Cover Changes in the Chemoga Basin, Ethiopia, Using Landsat and Google Earth Images

2020 ◽  
Vol 12 (9) ◽  
pp. 3607 ◽  
Author(s):  
Wubeshet Damtea ◽  
Dongyeob Kim ◽  
Sangjun Im
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
Environmental Concern ◽  
Kappa Statistic ◽  
Spatiotemporal Analysis ◽  
Google Earth ◽  
Agricultural Lands ◽  
Landsat Images ◽  
The Past ◽  
Land Cover Maps

Land cover change is a major environmental concern in the northwestern highlands of Ethiopia. This study detected land cover transitions over the past 30 years in the Chemoga basin (total area = 118,359 ha). Land cover maps were generated via the supervised classification of Landsat images with the help of the Google Earth (GE) images. A total of 218 unchanged land features sampled from GE images were used as the training datasets. Classification accuracy was evaluated by comparing classified images with 165 field observations during the 2017 field visit. The overall accuracy was 85.4% and the kappa statistic was 0.81, implying that the land classification was satisfactory. Agricultural land is the dominant land cover in the study basin, and increased in extent by 2,337 ha from 1987 to 2017. The second and third most dominant land cover types, grassland and woodland, decreased by 1.9% and 3.6%, respectively, over the past 30 years. The increase in agricultural lands was mostly due to the conversion of grasslands and woodlands, although some agricultural lands changed to Eucalyptus plantations and human settlements. The results revealed that the expansion of built-up space and agricultural lands was the major driver of fragmentation of the landscape, and degradation of natural resources in the Chemoga basin, Ethiopia.

scholarly journals Land-Use/Land-Cover Change Analysis and Urban Growth Modelling in the Greater Accra Metropolitan Area (GAMA), Ghana

Urban Science ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 26 ◽  
Author(s):  
Bright Addae ◽  
Natascha Oppelt
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Urban Growth ◽  
Urban Areas ◽  
City Planning ◽  
Land Use Land Cover ◽  
Vegetative Cover ◽  
Landsat Images ◽  
Urban Extent

A rapid increase in the world’s population over the last century has triggered the transformation of the earth surface, especially in urban areas, where more than half of the global population live. Ghana is no exception and a high population growth rate, coupled with economic development over the last three decades, has transformed the Greater Accra region into a hotspot for massive urban growth. The urban extent of the region has expanded extensively, mainly at the expense of the vegetative cover in the region. Although urbanization presents several opportunities, the environmental and social problems cannot be underestimated. Therefore, the need to estimate the rate and extent of land use/land cover changes in the region and the main drivers of these changes is imperative. Geographic Information Systems (GIS) and remote sensing techniques provide effective tools in studying and monitoring land-use/land-cover change over space and time. A post classification change detection of multiple Landsat images was conducted to map and analyse the extent and rate of land use/land cover change in the region between 1991 and 2015. Subsequently, the urban extent of the region was forecasted for the year 2025 using the Markov Chain and the Multi-Layer Perceptron neural network, together with drivers representing proximity, biophysical, and socio-economic variables. The results from the research revealed that built-up areas increased by 277% over the 24-year study period. However, forest areas experienced massive reduction, diminishing from 34% in 1991 to 6.5% in 2015. The 2025 projected land use map revealed that the urban extent will massively increase to cover 70% of the study area, as compared to 44% in 2015. The urban extent is also anticipated to spill into the adjoining districts mainly on the western and eastern sides of the region. The success of this research in generating a future land-use map for 2025, together with the other significant findings, demonstrates the usefulness of spatial models as tools for sustainable city planning and environmental management, especially for urban planners in developing countries.

scholarly journals Monitoring of Changes in Land Use/Land Cover in Syria from 2010 to 2018 Using Multitemporal Landsat Imagery and GIS

Land ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 226 ◽  
Author(s):  
Mohamed Mohamed ◽  
Julian Anders ◽  
Christoph Schneider
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Large Scale ◽  
Management Practices ◽  
Landsat Imagery ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Climate Trend ◽  
Lulc Change

Understanding the effects of socio-ecological shocks on land use/land cover (LULC) change is essential for developing land management strategies and for reducing adverse environmental pressures. Our study examines the impacts of the armed conflict in Syria, which began in mid-2011, and the related social and economic crisis on LULC between 2010 and 2018. We used remote sensing for change detection by applying a supervised maximum likelihood classification to Landsat images of the three target years 2010, 2014, and 2018. Based on the computed extent of our LULC classes and accuracy assessment, we calculated area-adjusted estimates and 95% confidence intervals. Our classification achieved an overall accuracy of 86.4%. Compared to 2010, we found an increase in spatial extent for bare areas (40,011 km2), forests (2576 km2), and urban and peri-urban areas (3560 km2), whereas rangelands (37,005 km2) and cultivated areas (9425 km2) decreased by 2018. It is not possible to determine whether the changes in LULC in Syria will be permanent or temporary. Natural conditions such as climate fluctuations had an impact on the uses of the natural environment and cultivated areas during the study period, especially in regions suffering from water stress. Although seasonal precipitation patterns and temperature affect LULC change, however, we could not identify a prevailing climate trend towards more drought-prone conditions. Our analysis focuses on (potential) direct and indirect implications of the Syrian conflict on LULC change, which most notably occurred between 2014 and 2018. Conflict-related main drivers were human activities and demographic changes, which are mainly attributable to large-scale population displacement, military operations, concomitant socio-economic status, and control of local resources. As the study provides quantitative and qualitative information on the dynamics of LULC changes in Syria, it may serve as a framework for further relevant conflict-related research and support planning, management practices, and sustainable development.

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