Urban Landscape Dynamics for Quantifying the Changing Pattern of Urbanisation in Delhi

Tiwari, Anuj; Merugu, Suresh; Jain, Kamal; Shoab, Mohd; Dixit, Abhilasha; Pandey, Akshay

doi:10.25175/jrd/2018/v37/i2/129706

Cited by 8 publications

(5 citation statements)

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“…Remote sensing and Geographic Information Systems has emerged as the most accurate technologies in various elds for planning, mapping, assessing and evaluating spatial data on natural resources. (Tiwari et al, 2018;Bauer et al, 2005 ;Jamal, 2022). Using computational models and satellite data from remote sensing, researchers have been able to analyze LULC and nd out how it has changed over time and how it might change in the future (Li et al,2014;Mourya et al,2022) The development of new technologies in the elds of space exploration and optics has improved the accuracy of RS data enabling the collection of useful spatiotemporal data on LULC (Jensen, 2015).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Analysis Land Use Land cover changes in South Kashmir Region of North-western Himalayas Using Landsat data

Mushtaq,

Saleem,

Ahmed

et al. 2024

Preprint

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This paper presents a comprehensive analysis of land use changes in South Kashmir from 2000 to 2022, revealing significant transformations in various land cover classes. Leveraging remote sensing and geographic information systems (GIS), the study examines the spatial patterns and temporal dynamics of land use and land cover, offering valuable insights into the region's landscape dynamics. Using supervised classification techniques, satellite imagery was analyzed to identify 10 major land use classes. The findings demonstrate notable increases in horticulture and built-up areas, accompanied by declines in agricultural land, glaciers and snow, exposed rock, and water bodies. The expansion of horticultural lands, covering approximately 7% of the study area, has been attributed to the conversion of agricultural lands. This shift, coupled with the encroachment of settlements to accommodate the growing human population, has resulted in a substantial loss of approximately 757 km2 of farmland agriculture, representing a total percentage change of about 13% during the study period. The implications of these changes extend beyond the local region, highlighting the urgent need for comprehensive and sustainable solutions to address human-induced challenges at a global scale. Furthermore, the study underscores the cost-effectiveness and efficacy of geospatial technologies in conducting spatiotemporal analyses and formulating evidence-based policies for the sustainable management of natural resources. The insights gained from this study offer a solid foundation for informed decision-making and the development of targeted land management strategies in South Kashmir and other similar regions facing similar challenges.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal Analysis Land Use Land cover changes in South Kashmir Region of North-western Himalayas Using Landsat data

Mushtaq,

Saleem,

Ahmed

et al. 2024

Preprint

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“…An increase in migration [14] and improved life expectancy due to better opportunities and healthcare frameworks in urban localities have contributed to the exponential population growth at a higher rate than in rural settlements leading to unplanned development of cities, particularly in emerging nations. The expected population growth forecasts that 6.3 billion people, or 70% of the predicted 9.1 billion globally by 2050, will live in urban areas [15,16]. Urban populations have presented a snowball scenario in Africa and Asia during the past 70 years, outnumbering Europe, North, and Latin America.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Land Surface Temperature from the Indian Cities of Ranchi and Dhanbad during COVID-19 Lockdown: Implications on the Urban Climatology

Qadri,

Hamdan,

Raj

et al. 2023

Sustainability

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An apparent increase in average global temperature is evident globally, and India is no exception. With the recent decade (2011–2020) arguably being the warmest, significant challenges due to rapid climate change have gained attention. However, notable spatial-temporal changes, especially with regard to land surface temperature (LST), were observed during the COVID-19 pandemic lockdown period, when a comparatively cooler climate was experienced in many urban centers. Assessment of LST, crucial in many heat-balance, land use, and climate change models research studies, depicts the near-surface hotness of the Earth’s temperature at a given location. Thus, this study utilizes satellite remote-sensing data to investigate the spatial-temporal variations of LST pre and post-lockdown imposed during the COVID-19 outbreak. Unlike many existing research studies on the metropolitans of India, the study considers developing Indian cities, Ranchi and Dhanbad, as its study area. Accurate LST computation was performed using existing LANDSAT-8 OLI/TIRS images and judged using other parameters (NDVI, LSE) obtained directly from the thermal infrared bands. The LST assessment successfully estimated temperature variations in Ranchi and Dhanbad, depicting a significant drop in temperature coinciding with the lockdown period and subsequent increase in urban temperature post-pandemic, indicating a meaningful relationship between human activities and urban surface temperature.

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“…Hence, change detection can be defined as "the process of identifying the difference in the state of a phenomenon or object by observing it at different times" (Singh, 1989). To assess urban growth, timely and accurate change detection of Land use and land cover (LULC) features is extremely important (Tiwari et al, 2018). LULC change (LUCC) is one of the most appropriate indications to monitor the impact of human being on the environment.…”

Section: Introductionmentioning

confidence: 99%

“…Remote sensing and GIS are extensively used for detecting LULC changes (Tiwari et al, 2018). There has been a growing trend in the development of change detection techniques using remote sensing data.…”

Section: Introductionmentioning

confidence: 99%

Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India

Saini¹,

Aswal²,

Tanzeem³

et al. 2019

IJCA

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Ecosystems in urban areas are strongly influenced by anthropogenic activities. Spatial-temporal transformations that occur in different classes of land use/cover like Built-up, Vegetation and Water are the key drivers of global change that reflects the territorial and socio-economic progress of an area and have significant implications for many policy issues.The current study uses a maximum likelihood classification method to map five different land use land cover classes in the openly available Landsat satellite images of 2008 and 2016 for selected urban boundaries of Srinagar, India. Pixel to pixel change detection strategy is implemented to find out the changes occurred in individual land use land cover class. The results are compared and illustrated in the form of graph and maps for providing an interactive visual representation for administrators and policymakers.

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Urban Landscape Dynamics for Quantifying the Changing Pattern of Urbanisation in Delhi

Cited by 8 publications

References 0 publications

Spatiotemporal Analysis Land Use Land cover changes in South Kashmir Region of North-western Himalayas Using Landsat data

Spatiotemporal Analysis Land Use Land cover changes in South Kashmir Region of North-western Himalayas Using Landsat data

Assessment of Land Surface Temperature from the Indian Cities of Ranchi and Dhanbad during COVID-19 Lockdown: Implications on the Urban Climatology

Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India

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