Spatio-temporal Assessment of Landscape Ecological Risk and Associated Drivers: A Case Study of Delhi

2021 ◽  
Vol 12 (1_suppl) ◽  
pp. S85-S106
Author(s):  
Biswajit Mondal ◽  
Pragya Sharma ◽  
Debolina Kundu ◽  
Sarita Bansal
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Ecological Risk ◽  
Urban Expansion ◽  
Landscape Fragmentation ◽  
Lulc Changes ◽  
Risk Areas ◽  
Key Drivers ◽  
Spatio Temporal ◽  
Vulnerability Score

Urbanization is considered as the key driver for land use and land cover (LULC) changes across the globe and Delhi is no exception to this phenomenon. The population of Delhi has almost doubled from 8.4 million in 1991 to 16.3 million in 2011. Correspondingly, the built-up area has also increased from 336.82 to 598.22 km 2 during 1999–2018. This urban expansion has led to emergence of serious ecological risk and fragmentation of the landscape. In this context, it is imperative to analyse the level of risks induced by such urban expansion and its underlying associations with other factors. This article quantifies the LULC changes in Delhi during 1999–2018 using Landsat 5 (TM) and Landsat 8 (OLI) data. A spatio-temporal sprawl induced risk assessment index has been developed by combining landscape fragmentation score and land use land cover vulnerability score. The landscape fragmentation score was based on four landscape metrics, whereas the vulnerability score was computed from LULC data. The article also assesses the association between risk areas and economic activities, environmental and infrastructural amenities that are considered key drivers of urban expansion in Delhi. To estimate spatio-temporal variability between risk areas and key drivers, ordinary least square regression and geographical weighted regression (GWR) were used. The GWR results reveal that sprawl-induced ecological risk in Delhi is strongly associated with economic activity, infrastructural accessibility and environmental amenities. This spatial empirical assessment also shows that urban growth incentives or services such as roads, metro rail, schools and hospitals can also create pressure on the landscape if local authorities arbitrarily provide these services across space without considering the associated risks.

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 Influence of Land Use and Land Cover Change on Land surface temperature

2021 ◽  
Vol 283 ◽  
pp. 01038
Author(s):  
Jing Sun ◽  
Jing He
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Rapid Urbanization ◽  
Lulc Changes ◽  
The Mean ◽  
The Relationship

The rapid urbanization process has recently led to significant land use and land cover (LULC) changes, thereby affecting the climate and the environment. The purpose of this study is to analyze the LULC changes in Hefei City, Anhui Province, and their relationship with land surface temperature (LST). To achieve this goal, multitemporal Landsat data were used to monitor the LULC and LST between 2005 and 2015. The study also used correlation analysis to analyze the relationship between LST, LULC, and other spectral indices (NDVI, NDBI, and NDWI). The results show that the built-up land has expanded significantly, transforming from 488.26 km2 in 2005 to 575.64 km2 in 2015. It further shows that the mean LST in Hefei city has increased from 284.0 K in 2005 to 285.86 K in 2015. The results also indicate that there is a positive correlation between LST and NDVI and NDBI, while there is a negative correlation between LST and NDWI. This means that urban expansion and reduced water bodies will lead to an increase in LST.

scholarly journals Identification of Ecological Risk Zoning on Qinghai-Tibet Plateau from the Perspective of Ecosystem Service Supply and Demand

2021 ◽  
Vol 13 (10) ◽  
pp. 5366
Author(s):  
Wei Shi ◽  
Fuwei Qiao ◽  
Liang Zhou
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
High Risk ◽  
Ecological Risk ◽  
Temporal Pattern ◽  
Supply And Demand ◽  
Tibet Plateau ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Qinghai Tibet Plateau

With the interaction of global change and human activities, the contradistinction between supply and demand of ecosystem services in the Qinghai-Tibet Plateau is becoming increasingly tense, which will have a profound impact on the ecological security of China and even Asia. Based on land cover data on the Qinghai-Tibet Plateau in 1990, 2005, and 2015, this paper estimated the supply capacity of ecosystem services using the value equivalent method, calculated the demand for ecosystem services using population density and economic density, established an ecosystem risk index based on the idea of an ecosystem service matrix to reveal the spatio-temporal pattern of the supply and demand of ecosystem services in the Qinghai-Tibet Plateau, and identified the potential ecological risk areas arising from the imbalance between supply and demand. The results showed that: (1) In terms of the spatio-temporal pattern of land use change, the desert area of the Qinghai-Tibet Plateau decreased the most with 26,238.9 km2, and other types of land use increased, of which construction land increased by 131.7%; (2) In terms of the supply and demand of ecosystem services, the Qinghai-Tibet Plateau was mainly dominated by low-level surplus areas, accounting for 64.0%, and the deficit in some areas has worsened significantly; and (3) In terms of division pattern of ecological risk areas, the Qinghai-Tibet Plateau presented characteristics of high risk in the east and low risk in the west. The high-risk area accounted for 1.1%, mainly distributed in the Huangshui Valley and the “One River and Two Tributaries” (Yarlung Zangbo River, Lhasa River, Nianchu River). The research results can provide reference for ecosystem management and policy formulation of the Qinghai-Tibet Plateau and have important significance for realizing the coupling and coordinated development of human–land relationship in Qinghai-Tibet Plateau.

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 Park in the periphery: Land use and land cover change and forest fragmentation in and around Yangoupokpi Lokchao Wildlife Sanctuary, Manipur, India

2020 ◽  
Vol 93 (1) ◽  
pp. 107-120 ◽  
Author(s):  
Khangsembou Bungnamei ◽  
Anup Saikia
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Geographical Area ◽  
Landscape Fragmentation ◽  
Wildlife Sanctuary ◽  
Dense Forest ◽  
Land Cover Dynamics ◽  
Total Geographical Area ◽  
Spatio Temporal ◽  
Supervised Image Classification

This study documents the spatio-temporal land use and land cover dynamics of Yangoupokpi Lokchao Wildlife Sanctuary (YLWLS) in Manipur, India. Landsat imageries at three points of time spanning 38 years (1978, 2000 and 2016) were taken into account. Supervised image classification techniques were employed. Fragstats software was used to derive five landscape metrics, namely, class area (CA), number of patches (NP), largest patch index (LPI), percentage of landscape (PLAND) and mean patch size (MPS), to quantitatively assess the level of landscape fragmentation in the YLWLS. Dense and moderately dense forests decreased markedly during 1978-2000 from 46.5% to 40% and 38% to 28% of the total geographical area, respectively. However, between 2000 and 2016, the sanctuary managed to gain 840 ha of dense forest through various afforestation activities. The overall change in YLWLS during 1978-2016 indicates a substantial transition of dense and moderately dense forests.

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 Characterizing the Up-To-Date Land-Use and Land-Cover Change in Xiong’an New Area from 2017 to 2020 Using the Multi-Temporal Sentinel-2 Images on Google Earth Engine

2021 ◽  
Vol 10 (7) ◽  
pp. 464
Author(s):  
Jiansong Luo ◽  
Xinwen Ma ◽  
Qifeng Chu ◽  
Min Xie ◽  
Yujia Cao
Keyword(s):  
Land Use ◽  
Land Cover ◽  
State Level ◽  
Google Earth ◽  
Lulc Changes ◽  
Classification Framework ◽  
Multi Temporal ◽  
Google Earth Engine ◽  
Spatio Temporal ◽  
Sentinel 2

Land use and land cover (LULC) are fundamental units of human activities. Therefore, it is of significance to accurately and in a timely manner obtain the LULC maps where dramatic LULC changes are undergoing. Since 2017 April, a new state-level area, Xiong’an New Area, was established in China. In order to better characterize the LULC changes in Xiong’an New Area, this study makes full use of the multi-temporal 10-m Sentinel-2 images, the cloud-computing Google Earth Engine (GEE) platform, and the powerful classification capability of random forest (RF) models to generate the continuous LULC maps from 2017 to 2020. To do so, a novel multiple RF-based classification framework is adopted by outputting the classification probability based on each monthly composite and aggregating the multiple probability maps to generate the final classification map. Based on the obtained LULC maps, this study analyzes the spatio-temporal changes of LULC types in the last four years and the different change patterns in three counties. Experimental results indicate that the derived LULC maps achieve high accuracy for each year, with the overall accuracy and Kappa values no less than 0.95. It is also found that the changed areas account for nearly 36%, and the dry farmland, impervious surface, and other land-cover types have changed dramatically and present varying change patterns in three counties, which might be caused by the latest planning of Xiong’an New Area. The obtained 10-m four-year LULC maps in this study are supposed to provide some valuable information on the monitoring and understanding of what kinds of LULC changes have taken place in Xiong’an New Area.

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.

Analysis of Urban Expansion and Modeling of LULC Changes Using Geospatial Techniques: The Case of Adama City

2020 ◽  
Vol 4 (1-2) ◽  
pp. 40-58
Author(s):  
Bedasa Regassa ◽  
Mikir Kassaw ◽  
Murugesan Bagyaraj
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
Spatiotemporal Variability ◽  
Kappa Statistics ◽  
Geospatial Techniques ◽  
Lulc Changes ◽  
The Right

In the last decades, Adama city has experienced drastic changes in its shape, not just in its vast geographical expansion, but also by internal transformations. Subsequently, understanding and evaluating the spatiotemporal variability of urban land use and land cover (LULC) shifts, and it is important to bring forth the right strategies and processes to track population development in decision-making. The goal of this analysis was therefore to examine LULC changes that have taken place over 37 years, forecast the long-term urban development in Adama City using geospatial techniques. To attain this, satellite data of Landsat 1973, 2000 and 2010 was downloaded from USGS Earth Explorer and processed using Arc GIS 10.5, Erdas 9.2, and Idrisi 32. A supervised classification technique has been used to prepare the base maps with six land cover classes that are accustomed to generate LULC maps. The maps are cross-tabulated to measure LULC changes, to look at land-use transfers between the land cover classes, to spot increases and declines in built-up areas in comparison to other land cover classes, and to determine the spatial changes in built-up areas. Finally, Markov Chain and CA-Markov techniques were used to model the LULC changes in the Adama district and to forecast possible changes in urban land use. The model was verified by the Kappa statistics and also by the application of other validation techniques. The growth of built-up areas in the last 37 years has risen from 2% in 1973, 10% in 2000 and 23% in 2010 and estimated about 60% over the next 30 years (2040).

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