scholarly journals SPATIO-TEMPORAL ANALYSIS AND MODELING OF URBAN GROWTH OF BIRATNAGAR CITY, NEPAL

2019 ◽  
Vol IV-5/W2 ◽  
pp. 97-102
Author(s):  
S. Shrestha
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Urban Expansion ◽  
Urban Change ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Spatial Metrics ◽  
Land Cover Map ◽  
Spatio Temporal

Abstract. Increasing land use land cover changes, especially urban growth has put a negative impact on biodiversity and ecological process. As a consequences, they are creating a major impact on the global climate change. There is a recent concern on the necessity of exploring the cause of urban growth with its prediction in future and consequences caused by this for sustainable development. This can be achieved by using multitemporal remote sensing imagery analysis, spatial metrics, and modeling. In this study, spatio-temporal urban change analysis and modeling were performed for Biratnagar City and its surrounding area in Nepal. Land use land cover map of 2004, 2010, and 2016 were prepared using Landsat TM imagery using supervised classification based on support vector machine classifier. Urban change dynamics, in term of quantity, and pattern was measured and analyzed using selected spatial metrics and using Shannon’s entropy index. The result showed that there is increasing trend of urban sprawl and showed infill characteristics of urban expansion. Projected land use land cover map of 2020 was modeled using cellular automata-based approach. The predictive power of the model was validated using kappa statistics. Spatial distribution of urban expansion in projected land use land cover map showed that there is increasing threat of urban expansion on agricultural land.

Spatiotemporal Pattern Analysis of Rapid Urban Expansion Using GIS and Remote Sensing

2010 ◽  
Vol 1 (2) ◽  
pp. 55-70 ◽  
Author(s):  
Hyun Joong Kim
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Urban Areas ◽  
Temporal Dynamics ◽  
Urban Expansion ◽  
Local Scale ◽  
Spatiotemporal Pattern ◽  
Land Use Land Cover ◽  
Modeling Studies

Rapidly growing urban areas tend to reveal distinctive spatial and temporal variations of land use/land cover in a locally urbanized environment. In this article, the author analyzes urban growth phenomena at a local scale by employing Geographic Information Systems, remotely sensed image data from 1984, 1994, and 2004, and landscape shape index. Since spatial patterns of land use/land cover changes in small urban areas are not fully examined by the current GIS-based modeling studies or simulation applications, the major objective of this research is to identify and examine the spatial and temporal dynamics of land use changes of urban growth at a local scale. Analytical results demonstrate that sizes, locations, and shapes of new developments are spatio-temporally associated with their landscape variations and major transportation arteries. The key findings from this study contribute to GIS-based urban growth modeling studies and urban planning practices for local communities.

scholarly journals Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

2021 ◽  
Vol 13 (16) ◽  
pp. 3337
Author(s):  
Shaker Ul Din ◽  
Hugo Wai Leung Mak
Keyword(s):  
Land Use ◽  
Support Vector Machine ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

The dynamics of urban expansion and land use/land cover changes using remote sensing and spatial metrics: the case of Mekelle City of northern Ethiopia

2017 ◽  
Vol 38 (14) ◽  
pp. 4107-4129 ◽  
Author(s):  
Ayele Almaw Fenta ◽  
Hiroshi Yasuda ◽  
Nigussie Haregeweyn ◽  
Ashebir Sewale Belay ◽  
Zelalem Hadush ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Expansion ◽  
Land Cover Changes ◽  
Northern Ethiopia ◽  
Land Use Land Cover ◽  
Spatial Metrics ◽  
Mekelle City

scholarly journals Spatio-Temporal Analysis Of Urban Expansion And Future Growth Patterns Of Lahore, Pakistan

2021 ◽  
Vol 14 (3) ◽  
pp. 41-53
Author(s):  
Muhammad Nasar-u-Minallah ◽  
Sahar Zia ◽  
Atta-ur Rahman ◽  
Omer Riaz
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Population ◽  
Urban Expansion ◽  
Temporal Analysis ◽  
Growth Patterns ◽  
Land Use Land Cover ◽  
The Past ◽  
Spatio Temporal ◽  
Lahore City

Lahore, a metropolis and 2nd largest city of Pakistan, has been experiencing rapid urban expansion over the past five decades. The socio-economic development and growth of the urban population have caused the rapid increase of urban expansion. The increase in the built-up area of Lahore has seen remarkable growth during the past five decades. This study is aimed at detecting the Spatio-temporal changes in land use land cover and evaluating the urban expansion of Lahore since 1973. The conversion of land to other uses is primarily because of growth in urban population, whereas the increase in economic activities is the central reason for the land-use changes. In this study, temporal Landsat imageries were integrated with demographic data in the GIS environment to quantify the spatial and temporal dynamics of land use land cover (LULC) changes and urban expansion of Lahore city. The supervised image classification of maximum likelihood algorithm was applied on Landsat MSS (1973 and 1980), TM (1990), ETM+ (2000), TM (2010), and OLI/TIRs (2020) images, whereas a postclassification comparison technique was employed to detect changes over time. The spatial and temporal analysis revealed that during the past five decades, the built-up area of Lahore city has expanded by ~ 532 km2. It was found from the analysis that in Lahore city the urban expansion was primarily at the cost of loss of fertile agricultural land, vegetation, and other cultivable land use. The analysis further revealed that the structure and growth pattern of Lahore has mainly followed road network and linear expansion. The results indicate that this accretive urban expansion is attributed to socio-economic, demography, conversion of farmland, rural-urban migration, proximity to transportation routes, and commercial factors. This study envisions for decision-makers and urban planners to devise effective spatial urban planning strategies and check the growth trend of Lahore city.

scholarly journals Urban Growth Assessment of Chennai District by Remote Sensing and Gis Techniques

2020 ◽  
Vol 8 (6) ◽  
pp. 5119-5125
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Satellite Images ◽  
Remote Sensing And Gis ◽  
Land Use Land Cover ◽  
Gis Techniques ◽  
Land Cover Map ◽  
Landsat Satellite

Urban growth of Chennai district is exponential and heading towards extreme urbanisation. Hence this necessitates the study of urban growth in Chennai district. The recent advancement in Remote sensing and GIS has an excellent ability to derive various data from the satellite images obtained .This helps us to map, monitor and picturise various aspects of development with respect to their demands. The basic principle of remote sensing is followed as the methodology. By following the methodology correctly and by proper processing of the data acquired from the satellite images, the exact requirements of information can be obtained. The Change in the urban growth of the Chennai district for three decades from 1989 to 2019 have been found by using remote sensing and GIS techniques. The satellite images of various years are obtained from Landsat satellite from the USGS Earth Explorer .The Land use characteristics of Chennai district of each year can be obtained by preparing the land use land cover map of Chennai district by the use of landsat satellite images. The two software namely ArcGIS and ERDAS Imagine are used to create the Land use land cover map. From the Land use land cover map of Chennai district, the change detection and statistical analysis of three decades are done and these analysis clearly shows that the urban growth of Chennai district is constantly increasing and there is a huge decrease in other natural features such as vegetation, water body and barren land. By performing urban trend analysis the urban growth of Chennai district for the upcoming years are predicted to prove the urban agglomeration in Chennai district.

scholarly journals Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019

2021 ◽  
Vol 13 (16) ◽  
pp. 3331
Author(s):  
Han Zhai ◽  
Chaoqun Lv ◽  
Wanzeng Liu ◽  
Chao Yang ◽  
Dasheng Fan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Natural Habitat ◽  
Temporal Patterns ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Development Mode ◽  
Rapid Urbanization ◽  
Spatio Temporal ◽  
Landscape Dynamic

Exploring land use structure and dynamics is critical for urban planning and management. This study attempts to understand the Wuhan development mode since the beginning of the 21st century by profoundly investigating the spatio-temporal patterns of land use/land cover (LULC) change under urbanization in Wuhan, China, from 2000 to 2019, based on continuous time series mapping using Landsat observations with a support vector machine. The results indicated rapid urbanization, with large LULC changes triggered. The built-up area increased by 982.66 km2 (228%) at the expense of a reduction of 717.14 km2 (12%) for cropland, which threatens food security to some degree. In addition, the natural habitat shrank to some extent, with reductions of 182.52 km2, 23.92 km2 and 64.95 km2 for water, forest and grassland, respectively. Generally, Wuhan experienced a typical urbanization course that first sped up, then slowed down and then accelerated again, with an obvious internal imbalance between the 13 administrative districts. Hanyang, Hongshan and Dongxihu specifically presented more significant land dynamicity, with Hanyang being the active center. Over the past 19 years, Wuhan mainly developed toward the east and south, with the urban gravity center transferred from the northwest to the southeast of Jiang’an district. Lastly, based on the predicted land allocation of Wuhan in 2029 by the patch-generating land use simulation (PLUS) model, the future landscape dynamic pattern was further explored, and the result shows a rise in the northern suburbs, which provides meaningful guidance for urban planners and managers to promote urban sustainability.

scholarly journals Dynamics of Land Use and Land Cover Changes in Harare, Zimbabwe: A Case Study on the Linkage between Drivers and the Axis of Urban Expansion

Land ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 155 ◽  
Author(s):  
Andrew K. Marondedze ◽  
Brigitta Schütt
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Land Cover ◽  
Urban Growth ◽  
Vegetation Index ◽  
Urban Expansion ◽  
Binary Logistic Regression ◽  
Support Vector ◽  
Landsat 8 ◽  
Lulc Changes

With increasing population growth, the Harare Metropolitan Province has experienced accelerated land use and land cover (LULC) changes, influencing the city’s growth. This study aims to assess spatiotemporal urban LULC changes, the axis, and patterns of growth as well as drivers influencing urban growth over the past three decades in the Harare Metropolitan Province. The analysis was based on remotely sensed Landsat Thematic Mapper and Operational Land Imager data from 1984–2018, GIS application, and binary logistic regression. Supervised image classification using support vector machines was performed on Landsat 5 TM and Landsat 8 OLI data combined with the soil adjusted vegetation index, enhanced built-up and bareness index and modified difference water index. Statistical modelling was performed using binary logistic regression to identify the influence of the slope and the distance proximity characters as independent variables on urban growth. The overall mapping accuracy for all time periods was over 85%. Built-up areas extended from 279.5 km2 (1984) to 445 km2 (2018) with high-density residential areas growing dramatically from 51.2 km2 (1984) to 218.4 km2 (2018). The results suggest that urban growth was influenced mainly by the presence and density of road networks.

Sign in / Sign up

Export Citation Format

Share Document