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Advanced remote sensing for urban and landscape ecology

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced remote sensing for urban and landscape ecologyedited by Sk. Mustak, Dharmaveer Singh, Prashant Kumar Srivastava.
其他作者:	Mustak, Sk.
出版者:	Singapore :Springer Nature Singapore :2023.
面頁冊數:	xiii, 317 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Urban ecology (Biology)Remote sensing.
電子資源:	https://doi.org/10.1007/978-981-99-3006-7
ISBN:	9789819930067$q(electronic bk.)

Advanced remote sensing for urban and landscape ecology
Advanced remote sensing for urban and landscape ecology[electronic resource] /edited by Sk. Mustak, Dharmaveer Singh, Prashant Kumar Srivastava. - Singapore :Springer Nature Singapore :2023. - xiii, 317 p. :ill. (some col.), digital ;24 cm. - Advances in geographical and environmental sciences,2198-3550. - Advances in geographical and environmental sciences..

Data And Urban Poverty: Detecting And Characterising Slums And Deprived Urban Areas In Low-And Middle-Income Countries -- Investigation Of Ecological Sustainability Through The Landscape Approach Of Geospatial Technology: Study From New Town Project In Eastern India -- Advanced Remote Sensing For Sustainable Decent Housing For The Economically Challenged Urban Households -- Impact Of Uncontrolled Tourism Development On Landscape Ecology Of Purba Medinipur Coastal Region, West Bengal: A 4-C Framework And Swoc Analysis -- Impact Of Urban Heat Island: A Local-Level Urban Climate Phenomenon On Urban Ecology And Human Health -- Identification Of Environmental Epidemiology Through Advanced Remote Sensing Based On Ndvi -- Assessment Of Land Utilization Pattern And Their Relationship With Surface Temperature And Vegetation In Sikkim, India -- Monitoring Land Use And Land Cover Change Over Bhiwani District Using Google Earth Engine -- Image And Perception Of Royal Heritage And Eco-Space Of The Medium Towns In India: Reflection From Burdwan Royal Heritage Site -- Governance And Floodplain Extent Changes Of Yamuna River Floodplain In Megacity Delhi -- Assessing Urban Compactness Using Machine Learning And Earth Observation Datasets: A Case Study Of Kolkata City -- Analysis Of Ecological Vulnerability Behind The Land Conversion From Agriculture To Aquaculture Of Purba Medinipur District In West Bengal, India -- Environmental Change Analysis Using Remote Sensing And Gis: A Study Of Upper Baitarani Basin, Odisha -- Mapping Urban Footprint Using Machine Learning And Public Domain Datasets.

This book introduces the use of various remote sensing data such as microwave, hyperspectral and very high-resolution (VHR) satellite imagery; mapping techniques including pixel and object-based machine learning; and geostatistical modelling techniques including cellular automation, entropy and land fragmentation. Remote sensing plays a vital role in solving urban and environmental challenges at the landscape level. Globally, more than half of the urban population is facing severe environmental and social challenges, especially those relating to climate change, agricultural land encroachment, green infrastructure and environmental degradation, mobility due to rapid rural-urban transformation and anthropogenic interventions. Mapping and quantification of such threats at the landscape level are challenging for experts using traditional techniques; however, remote sensing technology provides diverse spatial data at a varying scale, volume and accessibility for mapping and modelling, and it also analyses challenges at urban and landscape levels. Together, they address challenges at urban and landscape levels to support the Sustainable Development Goals (SDGs)

ISBN: 9789819930067$q(electronic bk.)

Standard No.: 10.1007/978-981-99-3006-7doiSubjects--Topical Terms:

950080
Urban ecology (Biology)
--Remote sensing.

LC Class. No.: QH541.5.C6

Dewey Class. No.: 577.560285

Advanced remote sensing for urban and landscape ecology
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520 $a This book introduces the use of various remote sensing data such as microwave, hyperspectral and very high-resolution (VHR) satellite imagery; mapping techniques including pixel and object-based machine learning; and geostatistical modelling techniques including cellular automation, entropy and land fragmentation. Remote sensing plays a vital role in solving urban and environmental challenges at the landscape level. Globally, more than half of the urban population is facing severe environmental and social challenges, especially those relating to climate change, agricultural land encroachment, green infrastructure and environmental degradation, mobility due to rapid rural-urban transformation and anthropogenic interventions. Mapping and quantification of such threats at the landscape level are challenging for experts using traditional techniques; however, remote sensing technology provides diverse spatial data at a varying scale, volume and accessibility for mapping and modelling, and it also analyses challenges at urban and landscape levels. Together, they address challenges at urban and landscape levels to support the Sustainable Development Goals (SDGs)
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