scholarly journals Assessment of Land Cover Dynamics and Drivers of Urban Expansion Using Geospatial and Logistic Regression Approach in Wa Municipality, Ghana

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1251
Author(s):  
Mawuli Asempah ◽  
Wahib Sahwan ◽  
Brigitta Schütt
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Land Cover ◽  
Temporal Dynamics ◽  
Driving Forces ◽  
Urban Expansion ◽  
Thematic Mapper ◽  
Land Use Dynamics ◽  
Spatio Temporal ◽  
Wa Municipality

The current trends of land use dynamics have revealed a significant transformation of settlement spaces. In the Wa Municipality of Ghana, the changes in land use and land cover are inspired by a plethora of driving forces. In this study, we assessed the geo-physical drivers of settlement expansion under land use dynamics in the Wa Municipality of Ghana. The study employed geospatial and remote sensing tools to map and analyse the spatio-temporal dynamics of the landscape, using Landsat satellite imageries: thematic mapper (TM), enhanced thematic mapper (ETM) and operational land imager (OLI) from 1990 to 2020. The study employed a binomial logistic regression model to statistically assess the geo-physical drivers of settlement expansion. Random forest (RF)–supervised classification based on spatio-temporal analyses generated relatively higher classification accuracies, with overall accuracy ranging from 89.33% to 93.3%. Urban expansion for the last three decades was prominent, as the period from 1990 to 2001 gained 11.44 km2 landmass of settlement, while there was 11.30 km2 gained from 2001 to 2010, and 29.44 km2 gained from 2010 to 2020. Out of the independent variables assessed, the distance to existing settlements, distance to river, and distance to primary, tertiary and unclassified roads were responsible for urban expansion.

Spatio-temporal dynamics of land use/land cover and its driving forces in Nanjing from 1995 to 2008

2013 ◽  
Vol 33 (18) ◽  
pp. 5848-5857
Author(s):  
贾宝全 JIA Baoquan ◽  
王成 WANG Cheng ◽  
邱尔发 QIU Erfa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Temporal Dynamics ◽  
Driving Forces ◽  
Land Use Land Cover ◽  
Spatio Temporal

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 Application of Geospatial Techniques and Logistic Regression Model for Urban Growth Analysis in Limbe, Cameroon

2020 ◽  
Vol 4 (1) ◽  
pp. 138-151
Author(s):  
E. A. Adzandeh ◽  
D. Alaigba ◽  
C. N. Nkemasong
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Land Cover ◽  
Regression Model ◽  
Urban Growth ◽  
Land Use Planning ◽  
Logistic Regression Model ◽  
Transition Probability ◽  
Thematic Mapper ◽  
Geospatial Techniques

Little is known about the nature of ecosystem loss, rampant changes in land use and land cover (LULC) and urban growth taking place in Limbe. The aim of this study is to analyze urban growth in Limbe, Cameroon from 1986-2019 using geospatial techniques and Logistic Regression Model (LRM). Landsat Thematic Mapper (1986), Enhanced Thematic Mapper+ (2002) and Operational Land Imagery/Thermal Infrared Sensor (2019) were utilized in this study. The images were classified into land cover classes using supervised image classification algorithm in ENVI software. The classification output was subjected to LRM application to evaluate urban growth. Image difference of urban growth between 1986 and 2019 was calculated as dependent variable and the independent variables were produced by calculating the Euclidean distance and Buffer of built-up, waterbody, road and farmland as driving factor for urban growth. Future urban growth was determined for 2035 using the Land Change Modeler in IDRISI Selva. Classification overall accuracy for the three date were not less than 99%. LRM results show a good fit with relative operation characteristic of 0.8344 and Pseudo R2 of 0.21. Analysis of LULC shows that built-up increased from 3.5% (1986) to 17.6% (2019). An urban land expansion rate of about 23% was observed for 2035. Transition probability matrix revealed high probability (0.6345) of build-up to remaining build-up by 2035, while the probability for it changing to waterbody, bare land, farm land and vegetation are 0.1099, 0.0459, 0.1939 and 0.1221, respectively. This study successfully demonstrates the application of geo-spatial techniques and LRM for land use/land cover change detection and in understanding the urban growth dynamics. It also identifies the potential areas of future urban growth, which can help land use policy planners for making optimum decisions of land use planning and investment.

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.

scholarly journals Contribution à l’étude de la vulnérabilité des terres de cultures de la région de Thiès (Sénégal) à l’aide de la télédétection et des systèmes d’information géographique (SIG)

2019 ◽  
pp. 6731-6746 ◽  
Author(s):  
Amadou SALL ◽  
Assize TOURE ◽  
Alioune KANE ◽  
Awa Niang Fall
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Temporal Dynamics ◽  
Remote Sensing And Gis ◽  
Cultivated Land ◽  
Landsat Images ◽  
Systèmes D’Information Géographique ◽  
Spatio Temporal ◽  
Systèmes D’Information

L’objectif de cette étude est d’établir à partir de la télédétection et des SIG, la dynamique spatio-temporelle des terres de cultures et d’explorer les futurs possibles de l’occupation du sol dans trois communes rurales de la région de Thiès (Fandène, Notto Diobass et Taiba Ndiaye). Une classification multidate des images landsat (1988, 2002 et 2014) a permis de quantifier les changements d’occupation des terres. Les résultats montrent que les zones de culture de Fandène sont passées entre 1988 et 2014 de 62% à 52% de la superficie totale de la commune. A l’opposée la commune de Taiba Ndiaye connait une expansion des zones de culture entre ces deux dates. Les changements enregistrés à Notto sont négligeables. Les simulations, faites sur la base des probabilités pour que la valeur d’une cellule i reste inchangée ou prenne la valeur d’une autre cellule j à l’horizon 2035, révèlent que les terres de culture de Fandène ont 69% de probabilité d’évoluer vers d’autres classes d’occupation du sol. ABSTRACT The objective of this study is to quantify from remote sensing and GIS the spatio temporal dynamics of cultivated land and explore possible futures of land use in three rural municipalities of Thies (Fandene, Notto Diobass, and Taiba Ndiaye). A multidate classification Landsat images (1988, 2002 et 2014) was used to quantify change in land cover. The results show that between 1988 and 2014 Fandene cropping areas have passed from 62% to 52% of the total area. At the opposite the commune of Taiba Ndiaye has known an expansion of cropping areas between these two dates. Minor changes are noted in Notto district. Simulations carried out on the basis of probabilities for a unit i to stay in the same cell or to be converted to another unit j in 2035, reveals that the probability for a cultivated land unit to be transformed into a another land cover category is high in Fandene (69 %).

scholarly journals DYNAMICS OF SPATIO-TEMPORAL URBAN EXPANSION IN SOUTH WEST DELHI REGION: A GEO-SPATIAL APPROACH FOR URBAN DISASTER MANAGEMENT

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 373-379
Author(s):  
N. Sharma ◽  
A. Kaur ◽  
P. Bose
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Natural Resources ◽  
Land Cover Change ◽  
Rural Areas ◽  
Urban Areas ◽  
Urban Expansion ◽  
Urban Disaster ◽  
Spatio Temporal ◽  
The Impact

<p><strong>Abstract.</strong> Constantly increasing population and up-scaling economic growth has certainly contributed to fast-paced urban expansion, but simultaneously, as a result, has developed immense pressure on our natural resources. Among other unfavorable consequences, this has led to significant changes in the land use and land cover patterns in megacities all across the globe. As the impact of uncontrolled and unplanned development continues to alter life patterns, it has become imperative to study severe problems resulting from rapid development and leading to environmental pollution, disruptions in ecological structures, ever increasing pressure on natural resources and recurring urban disasters This paper presents an approach to address these challenges using geospatial data to study the land use and land cover change and the patterns and processes of urban growth. Spatio-temporal changes in land-use/land-cover were assessed over the years using multi-date high resolution satellite data. The land use classification was conducted using visual image interpretation technique wherein, study area was categorized into five different classes based on NRSC classification system namely agricultural, built-up, urban green (forest), and fallow land and water bodies. Post-classification change detection technique was used for the assessment of land-cover change and transition matrices of urban expansion were developed to quantify the changes. The results show that the city has been expanding majorly in its borders, where land masses have been converted from agriculture based rural areas to urban structures. An increase in the built-up category was observed with the transformation of agricultural and marginal land with an approximate change of 8.62% in the peri-urban areas. Urban areas are becoming more densely populated and open barren lands are converted into urban areas due to over population and migration from the rural areas of Delhi and thus increasing threat towards urban disaster. Conservation and sustainable management of various natural resources is recommended in order to minimize the impact of potential urban disasters.</p>

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 A Spatio-temporal Study of Land Use Land Cover Change Detection Using GIS and Remote Sensing Techniques

2021 ◽  
Vol 12 (1) ◽  
pp. 026-031
Author(s):  
Snehalata Chaware ◽  
◽  
Nitin Patil ◽  
Gajanan Satpute ◽  
M. R. Meshram ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Planning ◽  
Water Body ◽  
Temporal Dynamics ◽  
Kappa Coefficient ◽  
Population Pressure ◽  
Land Use Land Cover ◽  
Spatio Temporal

Land resources in India are under severe pressure and it is widely believed that marginal lands are being brought under cultivation. The extent of such changes needs to be known for better land use planning decisions. The present study illustrates the spatio-temporal dynamics of land use land cover of Nagjhari watershed in Bhatkuli block of Amravati, Maharashtra. Multi-temporal high resolution of Sentinel and Landsat satellite data were used to identify the significant positive and negative Land use land cover changes over a decade of 2007 to 2017. From 2007 to 2017, the ‘habitation’ class increased by 34% due to increasing population pressure. There was a decrease in ‘wasteland’ by 10.3%, while the area under ‘agriculture’ decreased by approximately 4.7% because of the increased area under ‘habitation’ and ‘water body’ at Nagjhari watershed. The biggest change occurred in land use class ‘water body’ increased sharply from 2013-17 by 62.7 per cent due to consequence of state policy of watershed development that was implemented after 2014. The forest class recorded maximum loss (18.3%) due to increasing population maximum land converted into habitation. The study shows overall classification accuracy as 85.46% and kappa coefficient (K) of 0.85. Kappa coefficient indicated that land use land cover assessment from remote sensing data show the best accuracy. These finding will help in deciding land use policy for future and its impact on land management of the watershed.

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