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2023 | Buch

Advanced Remote Sensing for Urban and Landscape Ecology

herausgegeben von: Sk. Mustak, Dharmaveer Singh, Prashant Kumar Srivastava

Verlag: Springer Nature Singapore

Buchreihe : Advances in Geographical and Environmental Sciences

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Über dieses Buch

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).

Inhaltsverzeichnis

Frontmatter
Chapter 1. Data and Urban Poverty: Detecting and Characterising Slums and Deprived Urban Areas in Low- and Middle-Income Countries
Abstract
A multidimensional characterisation of urban areas is essential to provide relevant data for monitoring deprived urban areas (urban poverty) beyond the dollar threshold (World Bank) or household characterisation (UN-Habitat). We present a holistic characterisation of deprivation through a framework composed of domains and indicators for measuring urban poverty. It includes socio-economic and household characterisation (household-level) as well as the characterisation of physical and environmental conditions (area-level). In this chapter, we showcase the use of Earth Observation techniques to extract area-level data. The combination of Earth Observation and open geospatial data allows routine mapping and characterising essential aspects of urban deprivation related to the urban environment (e.g., contamination such as waste accumulations), urban morphology (e.g., unplanned urbanisation defined by built-up densities, street geometry, open/green spaces), and connectivity (e.g., the presence of infrastructures such as streetlights or road access). Such a mapping system provides meaningful information for classifying deprivation levels and discovering differences between and within deprived areas. Results are provided as an online tool for users to access information at the city and settlement scale in sub-Saharan African cities. The tool allows users to tailor information to support the improvement of living conditions for the rapidly growing number of urban inhabitants.
Monika Kuffer, Angela Abascal, Sabine Vanhuysse, Stefanos Georganos, Jon Wang, Dana R. Thomson, Anthony Boanada, Pere Roca
Chapter 2. Investigation of Ecological Sustainability Through the Landscape Approach of Geospatial Technology: Study from New Town Project in Eastern India
Abstract
The uncontrolled growth of urban population in developing nations has led to a situation of rapid alterations of peri-urban land. It immediately needs cost-effective monitoring and evaluates the policy for ecological sustainability. This study tries to investigate the spatio-temporal dynamics of land transformation patterns coupled with a holistic apprehension of landscape sustainability induced by different facets of ecological configurations of different land utilization, applying modern-day’s techniques from geospatial platform and landscape metrics within a multi-criteria framework of Analytical Hierarchy Process (AHP) in one of the new town project areas of Easter India. Computation of Landsat 5 TM and Landsat 8 OLI images for the years 1988, 2000, 2010 and 2020 reveals that there has been a steady growth in urban environment (1.35%/year) at a cost of altering natural resources. Use of different landscape metrics like Percentage of Landscape (PLAND), Largest Patch Index (LPI), Number of patches (NP) and Mean Euclidean Nearest Neighbour Distance (ENN_MN) within a fishnet grid space of 1 km × 1 km dimension reveals the areal extension and connectivity between vegetative landscape and water bodies has decreased with a steady increase of fragmentation until 2010, whereas the situation is completely reversed for builtscapes, especially in Action Areas I, II and III of New Town Rajarhat. These results certainly depict the chances of degradation of ecological sustainability which has also been observed using a land use-based Composite Ecological Sustainability Index (LUCESI). A steady decrement in LUCESI has been observed for Action Areas-I and II during 1988–2010. Contrarily, the state authority’s rapid greening and blueing programs have pertinently improved the situation in 2020. Therefore, this study certainly proves the role of authority in cityscape planning and calls for sustainable and radical policy interventions by different stakeholders in the future to accomplish a more ecologically sustainable township planning.
Anirban Kundu, Sk. Mafizul Haque
Chapter 3. Advanced Remote Sensing for Sustainable Decent Housing for the Economically Challenged Urban Households
Abstract
Future cities are viewed as environments that will provide opportunities for all populations (gender, age and persons with disability) with access to basic services, energy, housing and transportation. The Sustainable Development Goal (SDG) 11 is on sustainable cities and communities with a total of 10 targets and 15 indicators; with the first target concerned with urban households living in inadequate housing. This is aligned with the Africa Agenda 2063 whose first goal is on ensuring a sustainable environment for all citizens. UN-Habitat estimates that by 2030, 40% of the world’s population will need access to adequate housing with 100 million people globally being homeless and one in four people living in harmful conditions. Interventions aimed at reversing these trends should be supported by evidence. In this regard, this chapter explores the role of advanced remote sensing in providing relevant spatial information on economically challenged urban households using Kibera, Nairobi Kenya as a case study. Google Earth Engine (GEE) environment with two machine learning algorithms namely Random Forest (RF) and Support Vector Machines (SVM) were investigated with Sentinel 2A image data. From the results obtained, RF performed better with 86% accuracy compared to 74% with SVM in the classification process.
F. N. Karanja, P. W. Mwangi
Chapter 4. Impact of Uncontrolled Tourism Development on Landscape Ecology of Purba Medinipur Coastal Region, West Bengal: A 4-C Framework and SWOC Analysis
Abstract
Digha-Khadalgobra Census Town (Census of India, https://​censusindia.​gov.​in, 2011) area of Purba Medinipur district is one of the most popular beach destinations of West Bengal as well as India which has a low gradient and a shallow finest sand beach with gentle waves. Although this coastal tourism is the only major driving economy of this area, throughout time, it has been faced with the newer trend in urbanization transforming the rural coastal landscape. Consequently, the natural landscape gives way to concrete constructions in the name of upgraded coastal tourism planning and rurbanization (conversion from rural to urban). Destruction of dune ecology, the quick decline of the forest cover, deterioration of coastal wetlands, infrastructural sprawling, the decline of the coastal biodiversity, coastal erosion, illegal land use and encroachment, decline of sweet water resources, land pollution, soil degradation, plastic pollution, overfishing, increase in crime, traffic congestion, resort congestion, shops and vendor congestion, tourists harassment, declining of the coastal beauty, etc. are the few identified problems which ultimately violate the CRZ policies. Although this place has been enlightened in many research and project works, it is not emphasized as the rurban landscape featured by twin functional processes of man-nature interaction like tourism development and coastal urbanization till date. Under this backdrop, this research project has been done through the extensive literature survey, in-depth field observation, crisscross interviewing, extensive data collection, broadly viewed data compilation, and statistical and mapping analysis by proper GIS and statistical software, with 4-C Framework and SWOC analysis to provide a blueprint for the smart tourism and sustainable coastal urban development planning maintaining the coastal ecological footprint of this area.
Manishree Mondal, Rabin Das, Chayon Chakraborty, Puja Karmakar, Sk. Mustak
Chapter 5. Impact of Urban Heat Island: A Local-Level Urban Climate Phenomenon on Urban Ecology and Human Health
Abstract
With the rapid rate of urbanization in the last few decades, tremendous changes in the land use and land cover pattern of urban areas have occurred. These include the conversion of pervious surfaces to impervious surfaces, a decrease in the open and green spaces, and decreased sky-view factor that has led to the formation of Urban Heat Islands. These urban heat islands have implications for urban climate as it leads to elevated temperatures in the city centers and lower temperatures on the outskirts of urban areas. This further leads to increased energy consumption in cities besides having adverse effects on human health that get manifested in the form of distress as well as stroke due to high intensity of heat, fatigue, sapping of energy, irritation, and suicidal tendencies. With the ever-increasing size of urban areas by means of urban sprawl due to a greater influx of people from rural to urban areas in search of better amenities and opportunities, the problem of urban heat islands is bound to exacerbate in the coming years. Therefore, the present paper aims at critically assessing the spatio-temporal domain of Urban Heat Island in relation to urban ecology and human health using geospatial technology. A case study of Bathinda city has been described to assess the Impervious Surfaces and their impacts on Land Surface Temperature in Bathinda City of Punjab. Further, an attempt would be made to study the adaptation and mitigation measures for urban heat islands.
Sangita Singh, Priya Priyadarshni, Puneeta Pandey
Chapter 6. Identification of Environmental Epidemiology Through Advanced Remote Sensing Based on NDVI
Abstract
Advanced Remote Sensing (ARS) is a new scientific subject that combines high-performance computers and innovative spatial science techniques to extract knowledge from geographical large data to analyze Environmental Epidemiology (EE). Phenology of ecological landscapes (EL) is a cast-off approach to conduct EE to evaluate the hydrological scenarios based on the assumptions that Normalized Difference Vegetation Index (NDVI) time series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values. The application of ARS in the planning, implementation, and management of different water resources projects, is primarily concerned with the evaluation of ecological landscape response. When it comes to EE, ARS provides significant benefits, including the capacity to include massive volumes of vast geographical and temporal data in variability of forms; computational efficiency; workflows to accommodate crucial properties of spatial (environmental) processes, such as spatial non-stationarity; and scalability to EL with additional environmental exposures across multiple geographies. Key principles in geographic data science, data mining in EL with recent accessible spatial data applications in research, and future possibilities for phenology will be presented in this article.
Vibhanshu Kumar, Birendra Bharti, Harendra Prasad Singh, Himanshu Kumar, Sanjay Paul Kujur
Chapter 7. Assessment of Land Utilization Pattern and Their Relationship with Surface Temperature and Vegetation in Sikkim, India
Abstract
The land use/land cover change (LULC) is prominent in the hilly states of India. Population growth and consumerism have impacted the dynamics of LULCC. In this work, we have used satellite data to understand the NDVI and LST change over the period of 1995–2005–2021. The LULC maps were prepared and analysed to find out the change in different LULC classes. In contrast to land use classes like water bodies, agricultural land, rocky or barren, and scrubland or grassland found decreased whereas  dense forest cover and  snow or glaciers showed overall increased slightly from 1995–2021. The maximum change areal extent was changed from 1448.91 (1995) to 765.20 km2 (2021) into other categories. The LST and NDVI showed a drastic change over the studied period in the Sikkim state, India. The statistical analysis between NDVI and LST shows the relevant positive coefficient of determination for the years 1995 (R2 = 0.47), 2005 (R2 = 0.52), and 2021 (R2 = 0.46), respectively.
Shashi Sekhar, Nitu Singh, Sudhir Kumar Singh, Meenakshi Dhote, Kumar Rajnish
Chapter 8. Monitoring Land Use and Land Cover Change Over Bhiwani District Using Google Earth Engine
Abstract
Land use and land cover classes were mapped in the Bhiwani district of Haryana, India, from 1991 to 2021. Mapping and monitoring of land use and land cover are critical for government, industry, and human purposes. Landsat imagery was used for image classification due to its high spatial and radiometric resolution, as well as its historical availability beginning in 1972 with higher quality images. In the current study, a random forest classifier was used to classify the feature using Google Earth Engine (GEE). GEE is a cloud computing platform, and its advantages include the ability to preview data without downloading it, being free, and being simple to use. Random forest classification was used in GEE software with Python coding algorithms to categorise the images into five categories: cropland, fallow land, built-up area, waterbody, and open scrub. The results showed that 56.21%, 65.48%, 71.91%, and 74.34% of the land was classified as cropland in 1991, 2001, 2011, and 2021, respectively, followed by scrubland. It can also be concluded that fallow land has decreased over the year as cropping practises have increased. The accuracy assessment is a critical parameter for determining the accuracy of classified satellite images. Based on the findings, the classified maps exhibit an impressive overall accuracy exceeding 85%, demonstrating the reliability of the classification process. In contrast, water resources are depleting, and the Bhiwani district relies solely on the Dohan River to meet irrigation, domestic, industrial, and household demands. The study underscores the significance of addressing the threats posed by urban sprawl and natural phenomena to the natural environment. It highlights the crucial role of land and its services in benefiting humanity, emphasizing the need for continued efforts to protect and enhance its quality.
Suraj Kumar Singh, Shruti Kanga, Bhartendu Sajan, Sayali Madhukarrao Diwate, Gaurav Tripathi
Chapter 9. Image and Perception of Royal Heritage and Eco-space of the Medium Towns in India: Reflection from Burdwan Royal Heritage Site
Abstract
With the rampant and rapid growth of urbanization of the developing countries like India, especially from the last decade of the twentieth century, urban green spaces are rapidly vanishing. With this looming scenario of the defacement of urban green space, the urge for preservation, restoration, and recreation of urban green space has an integral part of urban planning. However, the older royal cities of Delhi, Mysore, Udaipur, Jaipur, Jodhpur, Burdwan, Jhargram, etc. for their heritage appeal are still offering scenic landscapes, deep green coverage interspersed with Royal architecture. Those heritage sites are practically the oasis in the jungle of concrete. Burdwan, a medium-sized town in West Bengal located in the central portion of Bengal is currently experiencing stupendous urban growth. However, the royal heritage site developed by the Maharajas of Burdwan with its appealing deep green eco-space still persists due to the authoritarian outlook of present stakeholders. This inquiry attempts to unfold this reality through qualitative analysis through narratives and word clouds and quantitative measures through factor analysis. The whole inquiry ultimately crops up that heritage site conservation is necessary to arrest the rampant urbanization and also it will help to develop a sensible attitude towards nature which is drastically sandwiched by relentless urbanization.
Koyel Sarkar, Sanat Kumar Guchhait
Chapter 10. Governance and Floodplain Extent Changes of Yamuna River Floodplain in Megacity Delhi
Abstract
Rivers across the globe are the most prosperous regions and loci of development of civilisations, e.g., New York on the Hudson, Paris on the Rhine, and Delhi on the bank of Yamuna River are some of the important million-plus cities located along the bank of rivers. Urban transformations of the 21st-century along the river bank create ecological problems in the natural riparian system. Delhi, a megacity, presents a complex case being the national capital of a developing nation with an ever-increasing population. In contrast, the planning of megacities is mainly rooted in the theories of the functioning of cities in the developed world. Delhi’s urban plan has divided Delhi into various planning zones, and the ecologically sensitive Yamuna River floodplain has been designated as Zone ‘O’. A land-hungry city and the artificial structures in the river’s floodplain obstruct, encroach and divert flow and reduce its natural evolution and extent. Such human interventions through casualness in planning for urban floodplains have necessitated the renewal of our understanding regarding the impact of recent urban transformations in the riparian environment and vice-versa and the role of governance. Remote sensing has been used to analyse these changes in the riverbed lying in Delhi and for understanding the planning and governing aspects of zone ‘O’.
Shobhika Bhadu, Milap Punia
Chapter 11. Assessing Urban Compactness Using Machine Learning and Earth Observation Datasets: A Case Study of Kolkata City
Abstract
The development of a compact city is an alternate sort of city development plan for dealing with a quickly urbanizing metropolitan area. City compactness is essential in analysing the current situation so the city can develop sustainably. Urban sustainability has widely been introduced in several countries to achieve sustainable development goals (e.g., SDGs-11) in terms of efficient land use, sustainable transportation, socially interactive environment, economic viability, and is environmentally protected. The measures of city compactness are crucial for assessing urban form over time. Long debates have been about the necessity of studying city compactness concerning a place that has already achieved a dense urban. The main objective of this study is to assess the compactness of urban footprints using machine learning and earth observation datasets. This study used sentinel-2 and Landsat TM data during 1990–2021 which were used to map the urban footprint using machine learning algorithms (e.g., SVM, RF, etc.). Urban compactness has been measured from the building footprint using spatial density, spatial matrices, spatial intensity, functional compactness index (FCI), diagnosing sprawl, mixed land use development, multicriteria decision making, and byes theorem. In this study, the compactness has been measured using spatial matrices. The result shows that the compactness of the built-up area in KMA is non-linear during different decades, as it was sometimes sprawling and sometimes compact. This type of growth pattern shows peri-urban sprawling and city center approaching towards compact development. This study would help policymakers, city planners, and local governments to improve their understanding of the urban form in terms of urban compactness to implement development plans in Kolkata urban agglomeration area.
Prosenjit Barman, Sk. Mustak
Chapter 12. Analysis of Ecological Vulnerability Behind the Land Conversion from Agriculture to Aquaculture of Purba Medinipur District in West Bengal, India
Abstract
The illegal, unplanned, and forceful conversion of fertile cultivable lands into brackish water aquaculture is now becoming a serious ecological threat at the cost of instant economic profit for the last decade in Bhagawanpur-II Block-, Purba Medinipur district, West Bengal. This study mainly focused on the impact of the mushrooming of these unwanted fishing ponds and ecological vulnerability on land and concerned people. It tried to unveil how short-term economic gain destroyed the long-term indigenous means of sustainable livelihood of the local residents. Extensive relevant-literature review, change detection of LULC using Rs-GIS-GPS techniques, ground truth verification, intensive perception survey using F-G-D and P-A-R approach, and ecological cost–benefit analysis techniques etc. were used to reach the goal of the research. The survey showed that the aquaculture area increased by 1.31 km2 (8.65%) from 2011 to 3.56 km2 (23.52%) in 2021. Mass reduction in cultivable and pastoral land, extinction of native species, changes in chemical characteristics of soil as well as water quality, economic stratification, vandalism, and social conflicts were identified. What people thought of as their economic strength was their ecological vulnerability. This research tried to set a blueprint for future micro-level planning and development so that, this vulnerability will be converted into their strength.
Manishree Mondal, Ramu Guchhait, Sk. Mustak
Chapter 13. Environmental Change Analysis Using Remote Sensing and GIS: A Study of Upper Baitarani Basin, Odisha
Abstract
Environmental change is directly associated with LU/LC changes and changes in vegetative cover. Therefore, Remote Sensing and Geographic Information Systems are commonly used for obtaining this kind of information. The present study focuses on the detection of environmental change in the upper Baitarani basin which is located in the Keonjhar district of Odisha state. In this study, LU/LC and NDVI (Normalized Difference Vegetation Index) are studied between 2000 and 2020 based on a Survey of India’s Topographic Map and temporal changes gathered from the Landsat 5 and 8 data and Sentinel 2 data. The study explores that the land under water bodies, agricultural activities, and irrigation reduces considerably due to mining activities and urbanization. On the other hand, the area under vegetative cover increased from 2010 to 2020 due to afforestation. Healthy vegetation accounts for minimum NDVI value. Therefore likewise the vegetative cover, and reclamation of water bodies is necessary to take necessary measures through local community participation. The experimental result indicates that over the specified period of study, the rate of increment and decrement in the urban built-up area, area of water bodies, vegetative cover, agricultural land, and other lands may have a significant impact on environmental sustainability.
Tapas Ranjan Patra, Priyanka Chakraborty, Diptimayee Naik, Ashis Chandra Pathy
Chapter 14. Mapping Urban Footprint Using Machine Learning and Public Domain Datasets
Abstract
The urban footprint is termed as the physical cover of the urban built-up. In the past several decades urbanization has been accelerated due to rural–urban migration, economic growth, globalization, etc., and it is observed that over half of the world’s population now living in cities. Mostly, the unintentional urbanization causes impermeable surface which triggers several environmental challenges such as trash disposal, groundwater scarcity, heat island effect, and so on which need to be managed to support urban sustainability. The main objective of this study is to map urban footprint of Kolkata metropolitan area using machine learning (ML) algorithms (e.g., SVM, Random Forest) and public domain dataset. Landsat TM satellite data, Night time light data, and census data were employed in this study. Satellite imagery was used for mapping Lulc and reclassifying the built-up area into rural and urban built up using socio-economic data like census data. The robustness of the ML algorithms was tested based on classification accuracy and transferability assessment. In Lulc analysis band and feature stacked images give the high accuracy than the normal image and PCA image in three ML algorithms. SVM-Linear gave the high accuracy comparatively to another ML algorithm. The building footprint of KMA was extracted from top three high accuracy LULC map of different ML algorithm. The built-up area of KMA was validated using the test sample and for the validation of test sample these test sample uses in GHSL images. This finding will aid in the categorization of rural and urban areas and gives the idea of urban extent in the Kolkata metropolitan area. This study will help urban planners, local governments, and policymakers for the urban policy improvement and sustainable urban development planning.
Prosenjit Barman, Sk. Mustak
Metadaten
Titel
Advanced Remote Sensing for Urban and Landscape Ecology
herausgegeben von
Sk. Mustak
Dharmaveer Singh
Prashant Kumar Srivastava
Copyright-Jahr
2023
Verlag
Springer Nature Singapore
Electronic ISBN
978-981-9930-06-7
Print ISBN
978-981-9930-05-0
DOI
https://doi.org/10.1007/978-981-99-3006-7