Maik Netzband

Monitoring Urban Sprawl Using Remote Sensing and GIS Techniques of a Fast Growing Urban Centre, India

Indias urban population has grown tremendously in the last four decades from 79 million in 1961 to 285 million in 2001. This fast rate of increase in urban population is mainly due to large scale migration of people from rural and smaller towns to bigger cities in search of better employment opportunities and good life style. This rapid population pressure has resulted in unplanned growth in the urban areas to accommodate these migrant people which in turn leads to urban sprawl. It is a growing problematic aspect of metropolitan and bigger citys growth and development in recent years in India. Urban sprawl has resulted in loss of productive agricultural lands, open green spaces, loss of surface water bodies and depletion of ground water. Therefore, there is a need to study, understand and quantify the urban sprawl. In this paper an attempt has been made to use Shannons entropy model to assess urban sprawl using IRS P-6 data and topographic sheet in GIS environment for one of the fastest growing city of South India and its surrounding area. The built-up area of the city has increased from 135 km2 in 1971 to 370 km2 in 2005. The study shows that there is a remarkable urban sprawl in and around the twin city between 1971 and 2005 because 215 km2 of agricultural land has lost to built-up land during this period. As a result the urban ecosystem has changed in the last four decades.

Applied remote sensing for urban planning, governance and sustainability

Remote Sensing as a Tool for Urban Planning and Sustainability.- Automatic Land-Cover Classification Derived from High-Resolution IKONOS Satellite Imagery in the Urban Atlantic Forest of Rio de Janeiro, Brazil, by Means of an Object-Oriented Approach.- Advances in Urban Remote Sensing: Examples From Berlin (Germany).- Spatial Analysis of Urban Vegetation Scale and Abundance.- Urban Environmental Monitoring in Buenos Aires - Determining Green Areas.- Challenges in Characterizing and Mitigating Urban Heat Islands - A Role for Integrated Approaches Including Remote Sensing.- Phoenix, Arizona, USA: Applications of Remote Sensing in a Rapidly Urbanizing Desert Region.- Application of Remote Sensing and GIS Technique for Urban Environmental Management and Sustainable Development of Delhi, India.- Berlin (Germany) Urban and Environmental Information System: Application of Remote Sensing for Planning and Governance - Potentials and Problems.- Views of Chiang Mai: The Contributions of Remote-Sensing to Urban Governance and Sustainability.- 20 Years After Reforms: Challenges to Planning and Development in Chinas City-Regions and Opportunities for Remote Sensing.

Remote sensing as a tool for urban planning and sustainability

In coming decades, the rapid increase of large cities in the developing world and the transformation of urban landscapes in the developed world will be among the greatest challenges to human welfare and a viable global environment. Although cities occupy only 5% of the Earth’s terrestrial surface, they are home to almost half the global population, who consume 75% of the world’s natural resources and generate an equivalent proportion of pollution and waste. The United Nations estimates that virtually all net population growth over the next 30 years will occur in cities, doubling their population. This anticipated population growth will transform urban landscapes, create undreamed-of challenges and opportunities for political and social institutions, and require an unprecedented investment in infrastructure.

Urban and Suburban Areas as a Research Topic for Remote Sensing

This chapter provides an introduction into the book’s theme, its relevance for the scientific community as well as for instructors and practitioners. It tries to give an umbrella for the topics that have been chosen to bridge the gap between remote sensing and urban studies through a better understanding of the science that underlies both fields. In so doing, in the second half this first chapter introduces the following 16 chapters written by leading international experts in respected fields to provide a balanced coverage of fundamental issues in both remote sensing and urban studies.

Phoenix, Arizona, USA: Applications of Remote Sensing in a Rapidly Urbanizing Desert Region

The Phoenix metropolitan agglomeration (Fig. 7.1) is one of the fastest-growing conurbations in the United States, and is the focus of the Central Arizona-Phoenix Long-Term Ecological Research Project (CAP LTER) (Grimm et al. 2000, Grimm and Redman 2004). This project has been the locus of significant remote sensing investigation and characterization of the Phoenix urban and peri-urban areas (Stefanov 2002), combined with ground truthing and allied studies (Hope et al. 2003). The information derived from these and other studies is increasingly being used by local governments and regional planners (GP2100 2003). As an example, the City of Scottsdale, Arizona has used high-resolution, airborne, multispectral data to assess impervious and pervious land-cover percentages for surface water runoff studies. This use of remotely sensed information, rather than traditional ground-based surveys, produced estimated cost savings of eight to fifteen million dollars for the city (W. Erickson 1999). Construction of an advanced visualization and modeling environment (a “decision theater”) that integrates remotely sensed and other geospatial data for the Phoenix metropolitan region was completed in 2005 at Arizona State University (J. Fink 2005). Use of such an advanced system enables near real-time modeling of the impact of planning and development decisions. Remotely sensed data acquired at a variety of spatial, spectral, and temporal resolutions provides the basic biophysical information necessary to initialize models of urban resilience and sustainability.

Physical characterisation of deprivation in cities: How can remote sensing help to profile poverty (slum dwellers) in the megacity of Delhi/India?)

Addressing the question ‘Is the world urbanizing in a context of poverty?’ has been so far based on limited information. There is only poor scientific and operational knowledge of this process. Urban growth & land consumption patterns are poorly understood (i.e. coastal cities are growing faster; they are disproportionately urban and with higher densities). Thus, the available information is inadequate for policy & planning. Due to their microstructure, irregularity and direct adaptation to local conditions and the terrain, a generically applicable mapping of these settlements is difficult. The focus of the proposed paper will be laid on experiences in identifying slums and informal settlements in the Megacity of Delhi/India by means of high resolution remote sensing in order to help spatially profile poverty in very complex (cluttered) and partly hard to control giant and fast growing urbanized regions. An integrated approach using ASTER satellite data and GIS is applied in conjunction with socio-economic data collected from different government offices for assessing such urban issues.

Synthesizing urban remote sensing through application, scale, data and case studies

This article describes the outcomes of an international workshop on urban remote sensing. The workshop synthesized the needs of remote sensing scientists to better monitor and analyse urban physical and social dynamics. The workshop was held with urban land use forecasting workshop in April 2011 in Arizona. The four major themes of the jointly held workshops were application, data, scale and case studies. Application refers to how data are used to address urban problems. Data refers to the sources and types of raw data available. Scale is the ever-present concern over data reduction and resolution. Case studies examine a single urban area, typically based on one or two primary themes. One outcome was to integrate multiple case studies to form an urban typology. To respond to this need, this article integrates two case studies on the urban heat island in Atlanta, GA and Phoenix, AZ based on the four themes.

Urban growth in last three decades in Kuala Lumpur, Malaysia

This paper empirically examines an integrated study of urbanization in Kuala Lumpur City, Malaysia, by using Geographical Information Systems (GIS) and remote sensing. The study explores a multi buffer ring method to investigate the spatial and temporal dynamics of urban growth between 1989 - 2014. We classified Landsat images from 1989, 2001 and 2014 with a Maximum Likelihood classification scheme to produce land-cover maps and find four types of land cover: Settlement, Agriculture, Forest and Water. Then, the area coverage for all the land use types at different points in time were measured and coupled with the distance from the city center. Later on urbanization density from city center to outside for every 1 km distance is derived from 1 to 50 km. When comparing the time cuts of 1989 and 2014 at the distances of 5, 8, 15, 20 and 30 km, the city density is found as being increased at very high pace. Temporally urban expansion show fast and slow growth stages with high speed growth shifting to the east side of the city. In general, the population, traffic conditions, industrialization, and policy are the major factors that influenced the urban expansion.

Monitoring and modeling of urban sprawl through remote sensing and GIS in Kuala Lumpur, Malaysia

IntroductionKuala Lumpur is currently experiencing a large-scale urban transformation. This study explores a multi-buffer ring method to investigate the spatial and temporal dynamics of urban growth in the Kuala Lumpur metropolitan area by using Geographical Information Systems (GIS) and remote sensing imageries from1989 to 2014.MethodsThe first Landsat images from 1989, 2001, and 2014 were classified with maximum likelihood classification to produce land cover maps and identify four types of land cover: urban/built-up, agriculture, forest, and water. Then, the area coverage for all the land use types at different points in time were measured and combined with distance from the city center. Later on, urbanization densities from the city center to the outside for every 1-km distance from 1 to 50 km are calculated.ResultsCity density on the distance of 5, 8, 15, 20, and 30 km was very high in the years 1989 and 2014. Temporally, urban expansion shows fast and slow growth stages with high-speed growth shifting to the east side of the city.ConclusionsIn general, the population, traffic conditions, industrialization, and policy are the major factors thatinfluenced the urban expansion

Characterization and Monitoring of Urban/Peri-urban Ecological Function and Landscape Structure Using Satellite Data

This chapter utilizes a case study from Phoenix, Arizona to examine the relationships between ecological variables and landscape structure in cities. The relationships are assessed using ASTER and MODIS data; and through the techniques of expert system land cover classification and grid-based landscape metric analysis.