Communities worldwide need data to compensate for and adapt to current growth while planning for expected further change and its impact on infrastructure, as well as the surrounding environment 5 . This study has demonstrated the potential of using remote sensing data to obtain accurate and detailed information on urbanlanduse/land cover changes through the use of spatial data analysis and arrive at a prediction model to depict how the entire landscape would change in the future. The overall aim of the study was to investigate the spatial extent of urbanlandusechanges in Chennaicity, Tamil Nadu, taking into consideration the nature and dynamics. The Chennaiurbanchanges during the past 23 years are mainly due to the population growth and commercial and industrial activities . The present studies indicate that in Chennaicityurbansprawl is very active. It is estimated that 20698.2 hectare lands have been converted into built-up lands over the past 23 years between 1991 and 2014. The multi date landuse and land cover maps show the major changes in the landuse, i.e., increase in residential urban, commercial urban and reduction of vegetation and water bodies. The multi-temporal satellite data and model analysis predict the future status of landuseland cover in Chennaicity which is presented as: (1) the category of residential urban will be increased from 35564 hectare to 51059 hectare between 2014 and 2020 and (2) the category of commercial urban will increase from 3527.3 hectare to 4246.7 hectare between 2014 and 2020. The field observation conducted thereafter also proves the fact that drastic changes in the Chennaiurban is because of commercial, industrial and entertainment tourism activities.
The spatial and physical characteristics of urban features, urban patterns and its forms may be quantified usingspatial metrics . These indices can be obtained directly from thematic maps derived from remote sensing data . The availability of remotely sensed data from multiple dates enables us to carry out studies on urban modeling , urban landscape pattern analysis , and urban growth studies [13,16]. Globally, different studies on urban growth and model analysis have been carried out [8,9,12,15,17]. However, with a few exceptions, such studies are scarce for India [16,18–20]. The city of Chennai, India has been one of the fastest growing urban areas in the country in the last three decades. This has resulted in traffic congestion, air and water pollution, uncontrolled increase of population, encroachment, water and land scarcity, the growth of slums, and the degradation of vegetation within and in the peripheral areas of the city . Thus, such a study would benefit urban planners that need to understand the spatiotemporal changes of urban areas to better address these environmental problems and, at the same time, to ensure the provision of basic infrastructures and facilities without disturbing ecosystems. This study (1) studies land- use and land-cover changes from 1991 to 2016; (2) examines the spatiotemporal urban growth pattern using entropy and spatial metrics; and (3) predicts the urban growth and the urbansprawl for the year 2027.
Centre for Environmental Science and Technology, Banaras Hindu University, Varanasi, India Abstract: Urban growth identification, quantification, and the knowledge of rate and trends of growth helps in determining the changes associated with landuse and land cover properties and in regional planning with better infrastructure in environmentally sound way. Spatial and temporal technologies such as Remote Sensing, Geographic Information System (GIS) and Global Positioning System (GPS) are very helpful in such type of studies. This paper focuses on urban growth pattern analyses being carried out for urbansprawl in Varanasi city. Various GIS layers such as built-up area; agricultural land; vegetation/forest land; water bodies/wet land; brick kiln; rivers; DLW (industrial area); BHU (educational area), road network, city boundary etc. were generated using data such as the Survey of India toposheet and Remote sensing imagery. Spatialchanges in built-up area and the pattern of sprawl were studied using GIS. This study revealed that in Varanasi there is remarkable decrease in agricultural areas and tremendous growth in Built-ups. About 37.57% of agricultural land is transformed to other landuse features. Rate of change agricultural land to other landuse is observed 210.80ha/yr. There is no brick kiln in city area during the 2010 while in 1976; it covered the total area of 143.14ha. Built-ups increased by 7325.72ha, with change rate of 215.46 ha/yr. Study showed decreased in water bodies by 15.13 ha. There is no change in the area of BHU, DLW, River Ganga and Varuna.
of the land. So characteristics of land cover define the information for activities like thematic mapping and change detection analysis. Landuse–shows the activity, economic purpose, intended use, strategy placed on the land cover type by humans. Management practice constitutes landuse change. When used together, LandUse / Land Cover shows the classification of different elements on the landscape within a specific time frame based on established methods of analysis of appropriate source data. Land cover is the physical data at the surface of the earth. Landuse refers to how people utilize the land for the socio-economic activity, urbanuse and agricultural land uses are two of the most common high-level classes of use. At any one point or place, there may be a multiple land uses, the specification of which may have a great value. Hence, Landuse is the activity for which land is used by the humans. RS & GIS provide efficient methods for systematic analysis of landuse and land cover aspects and tools for LandUse/Cover planning and modelling. Satellite data is usually the most used and updated resource available for study the LandUse and land cover which helps in detection of change. Especially with developing towns and cities in India, it is finest method that can show up the urban growth/sprawl. With geographical information system flexible geo- database can be generated for the landuse/cover issues. Hence this tool is helpful to bring out the results along with socio–Economic Survey. Knowledge of both landuse/cover is important, for planning information on both the above aspects.
This paper presents landuse features and coastline changes on the Kepez Delta between 1962 and 2005 by using remote sensing, aerial photograph interpretations and field observations. Rapid increase of population of the Kepez town from 1935 to 2000 fits with a growth of 24 times, resulting in continual expansion (~23 times) of residential areas on fertile farming lands. The sprawling of summer houses in the Dardanos area to the south threatens agricultural lands and the coastal ecosystem on a large scale. Coastline changes occurred as result of natural morpho-dynamic processes and human involvement in the past 43 years. These changes are characterized by seaward progradation (sediment accumulation) of about 40 m and coastal retrogradation (marine erosion) of 20 m at various parts of the coastline.
1980 The Lagos State Regional Plan (1980–2000) Doxiadis Associates, 1980 National Population Census 1963, 1991, 2006 NPC 1991, 2006 Data on built-up urban areas were extracted from ISODATA classified rasters by coding built-up pixels as black and other land cover types as white. The classified images were subsequently analysed for their fractal dimensions using the software package Fractalyse (version 2.3.2). The software uses numerous methods to measure fractal dimensions; these include box counting, radius mass, dilation, and correlation. For this study, the radial mass measure was employed, which analyses by the iteration principle whereby the total number of built-up pixels are counted within the circle from a specified point (the counting centre).
Various studies (Frank 1989; Duncan 1989; Burchell and Listokin1995; Bank of America 1995) look at the relationship between landuse patterns and infrastructure costs (i.e. local and county roads, water, sewers, and schools). They estimate that for eighteen communities in Southeast Michigan, managing growth (relative to unmanaged growth) can produce annual savings of over $5 million (Burchell 1997). Burchell also finds in a New Jersey study that managed growth is 2% less costly than unmanaged growth for both municipalities and school districts (Burchell 1992). The implication is that current, unmanaged, low-density development demands more community costs than they provide communal benefits over time. The solution to this dilemma of increasing communal costs and decreasing benefits has traditionally been growth; incorporating adjacent lands to increase the tax base and take advantage of typically low impact land uses (agricultural property taxes are a small fraction of urbanlanduse taxes) and newly developed urbanland uses. Alternative solutions, a higher tax rate per capita, or a permanent and early switch to more compact and sustainable development patterns are rarely considered. The inherent feedback loops in the sprawl paradigm are generally self- reinforcing and favor fringe development, instead of self-correcting as they are in equilibrium models.
regions further cluster analysis was performed to classify each of the cities and finally it has been observed that urban concentrations are more compact than their counterparts in either Europe or North America. initiated the development of LandUse Geospatial Indices which included segregated landuse, development planning consistency, urban density, strip and leapfrog development and the results stated that segregated landuse and leapfrog development were salient indicators for strategic planning zone for alpha cities in Kuala Lumpur Metropolitan and these can be adopted for landuse planning and strategic development. states that urbansprawl is typically more of a planned sprawl where the urban development in the city of Shanghai has increased by 125% more than double the population, from 2000 to 2015 and proposing the use of Geo-detector, the analysis affirm that the detailed plan of the city has a pivotal role in the urbansprawl expansion. Indicators such as density and centrality (by using Moran’s I coefficient of developed land) reveal that there has been a decreased land consumption therefore increased urbansprawl. Besides, Moran’s coefficient showed that the urban lands intended to form clusters. A reversed U shape pattern was formed for both land consumption and Moran’s I coefficient. Researches have been conducted on a global scale comparing cities from different geographical atmospheres having different economic situations. These cities were analyzed and categorized into high growth cities, low growth cities, expansive growth and frantic growth cities. Cities tend to expand in an unpredictable manner
7.5.1. Use of stormwater best management practices (BMPs)
There were number of BMPs used to make sure the land development complied with the WSUD and the guidelines of the local authorities. Rainfall runoff on the front and backyards of lots (garden areas) was modeled to either infiltrate directly at- source or, in larger rainfall events (i.e. > 1 year 1 hour ARI event), it was assumed that a portion of the runoff may discharge to the road network. The runoff from roof areas was directed to soakwells, which will infiltrate into the sandy soil and ultimately the groundwater. The soil of the area has a good infiltration rate and can facilitate the expected soakage. During modeling, the stormwater runoff from the 1 year 1 hour ARI rainfall event was retained as close to source as practicably possible; only rainfall events greater than this event were allowed to discharge from the source area. The retention storage within the model was provided through a treatment train which included soakwells, sub-surface storage cells and vegetated retention areas (located either immediately adjacent to road pavement or within downstream POS areas). The vegetation and the infiltration processes within the soil column were expected to remove a large portion of the contaminants (nutrients, gross pollutants, suspended sediments, etc.) contained within the stormwater runoff. Bio-retention areas were modeled as offline storage areas. Rainfall events greater than the 1 year 1 hour ARI event were modeled to bypass the infiltration or bio- retention areas and conveyed by overland flow or the concrete pipe network to end- of-catchment retention storage areas. Another type of 1 year 1 hour attenuating method used was the swales. They were modeled to provide both conveyance of stormwater and retention/detention storage. It was proposed to utilize swales within road reserve adjacent to POS areas. Stormwater would be directed into the swale via flush kerbing or the concrete pipe network. The swales were modeled in the same way as the bio–retention areas and were approximately 300 mm deep and 4 m wide. The use of swales provided a large surface area for the stormwater to infiltrate into the underlying sandy soil. Swales ensure that the 1 year 1 hour ARI rainfall event is retained at or near the source. For larger rainfall events, swales were used to convey or divert the runoff into the nearest end-of-catchment retention storage areas.
Contrary to population decrease in the historic city core, important growth is verified in the towns located nearby the railway stations and the road network. This growth reaches 33.8%, 22.3%, and 21% in agglomerations situated on the northeast axis that links La Plata with the Federal Capital (Villa Elisa, City Bell and Gonnet) with a population of 21,800; 26,210, and 22,859 respectively. Other population centres which register a growth of 10%, are located, on the one hand, on the southwest periphery (Los Hornos), traditional settlement where extractive activities related to the construction of the city are located, and on the other hand, on the southeast periphery (Villa Elvira), where the growth is connected with the low value of the land, in comparison with the values in the rest of the district. These tendencies respond to the market dynamics, but not to a city project designed from the regulation, or to sustainability criteria.
Golmohammadi et.al, (2009) had conducted research in the city of Hamadan with the ultimate objective of setting up a traffic noise model based on the traffic conditions of Iranian cities . Noise levels and other variables have been measured in 282 samples to develop a statistical regression model based on A-weighted equivalent noise level for Iranian road condition. The results revealed that the average Leq in all stations was 69.04±4.25 dB (A), the average speed of vehicles was 44.57±11.46 km/h and average traffic load was 1231.9 ± 910.2 V/h. The suggested road traffic noise model can be effectively used as a decision support tool for predicting equivalent sound pressure level index in the cities of Iran. Kluijver et.al. (2003) had said that noise caused by industry and infrastructure is a major source of dissatisfaction with the environment in residential areas . Policies on noise control have been developed in most European countries. Noise effect studies are carried out to support these policies. The integration of GIS and noise models makes it possible to increase the quality of noise effect studies by automating the modeling process, by dealing with uncertainties and by applying standardized methods to study and quantify noise effects.
2000, 2010 and 2015) on scale 1:50,000 and ENVI software has been used for classification of geometrically and radiometrically images. Resampling method has been used to transform the images so that the original pixel value can be retained. For assessing the patterns of sprawl in Jodhpur city, landscape metrics are calculated using Fragstats software. In this study, selected landscape metrics i.e. Mean Fractal Dimension Index (FRAC_MN), Area Weighted Mean Patch Fractal Dimension (AWMPFD), Euclidean Mean est Neighbor (ENN_MN) and Core Area Percentage of are calculated to analyze the change in urban landscape. These indexes are a collection of metrics that quantify and analyze landscape patches on the basis of and compactness. Methodology adopted for this study is given in Fig.2.
have subsequently initiated strategies to evolve a participatory approach to the development and management of urban environment hinged on the principle of sustainable development [Ogu 2000]. Popular among this is the Sustainable City Pro- gramme (SCP) which promotes a positive vision where all humans have adequate shelter, healthy and safe environment, basic services and freely chosen employment. It also places strong em- phasis on gender equality, partnership and good urban governance. In Nigeria, the Sustainable City Project (SCP) was first applied in Ibadan, i.e. Sustainable Ibadan City Project (SICP) in 1992; and subsequently replicated in Kano and Enugu while the Sustainable Ibadan City Project had been abandoned due to non-readiness of the major stakeholders (Oyo state government and the local government council authorities) to con- tribute their counterpart funding and the projects at Enugu and Kano have only started with skel- etal ground works. Ever before the introduction of Sustainable City Project in Nigeria, significant efforts had been made at redressing urban decay, particularly at the core area in Nigerian cities in a form of urban renewal programme but this was not extended to the urbansprawl at the peripher- ies of the Nigerian cities. This is because urbansprawl had not been seen as physical development problem that needs special focus except in a form of preparing a master plan for the existing settle- ment, a project that is believed to take care of the sprawling growth of the settlement in question. Besides the fact that not many cities and towns can boast of having master plan, the few cities and towns with master plan had become obsolete without any significant efforts to get them re- viewed. Disappointedly, the few cities and towns with current master plan suffer the non-political will to implement/effect the development control measures that could check urbansprawl [Olujimi and Fashuyi, 2004].
Methods: A survey of 7510 individuals aged . = 15 years was undertaken covering Chennaicity (urban), Ambattur (semi- urban) and Sriperumbudur (rural) taluk. Details on tobacco use were collected using a questionnaire adapted from both Global Youth Tobacco Survey and Global Adults Tobacco Survey.
Results: The overall prevalence of tobacco use was significantly higher in the rural (23.7%) compared to semi-urban (20.9%) and urban (19.4%) areas (P value ,0.001) Tobacco smoking prevalence was 14.3%, 13.9% and 12.4% in rural, semi-urban and urban areas respectively. The corresponding values for smokeless tobacco use were 9.5%, 7.0% and 7.0% respectively. Logistic regression analysis showed that the odds of using tobacco (with smoke or smokeless forms) was significantly higher among males, older individuals, alcoholics, in rural areas and slum localities. Behavioural pattern analysis of current tobacco users led to three groups (1) those who were not reached by family or friends to advice on harmful effects (2) those who were well aware of harmful effects of tobacco and even want to quit and (3) those are exposed to second hand/passive smoking at home and outside.
The design of water supply network for water demand purposes is based on the population projection of a particular city or town, which is estimated for the design period. Any underestimated value will make the system incompetent for the purpose intended; likewise, overestimated value will make it costly. Population change in the city over the years will take place; hence, the system should be designed considering the population at the end of the design period . Factors affecting changes in population include increase due to births, decrease due to deaths, migration increase/decrease, and increase due to annexation . The present and past population record for the city was acquired from the census population records. After collecting these population figures, the population at the end of the design period was predicted using various methods that is suitable considering the growth pattern of the city. Population forecasting can be estimated using the following methods:
Moreover, exhaustive use of land and change of land-cover and its patterns vulnerable to soil and land degradation. This leads to increasing poverty and migration, failure of land productivity, damage of biodiversity and natural resources, deterioration of groundwater recharge and carbon storage capacity, and change in population size; and spatial distribution (Abate, 2011). Land-use and land-cover changes also have consequences of soil and land degradation, soil erosion, salinization and desertification. Soil and land degradation results in soil erosion, salinization, compaction, acidification, nutrient impoverishment, waterlogging and dehumification. Desertification is also another effect of extreme land-use and land-cover. It increases the concentration of carbon-di-oxide in the atmosphere and brings wildfire. Therefore, incidences of forest fire related to land-use and land-cover degradation/change increase the emission of toxic gases (GHG) such as carbon monoxide and nitric oxide which alter the chemistry of the atmosphere causing air pollution, affecting energy balance and climate and global warming. Land- use and land-cover change have impacts on hydrology. It changes the quality of water and water flows, cause surface water pollution, depletion of groundwater aquifers. Land-use and land-cover changes also increase the frequency and severity of flooding which is due to continuous and serious deforestation.
Iran. Accordingly, in this study, the effort was concentrated on analyzing urbansprawl as one of the phenomena that arise from the increase in urbanization. For that, the theoretical foundations encompassing definitions, causes, and impacts and manifestations of sprawl were examined. Accordingly, in this study sprawl was defined as: “unplanned, far from the center and automobile-dependent growth that influences the environment, the economy and the social structure of the city, and can be characterized as having low concentration, segregation of land uses and limited accessibility”. Then, Iranian and international research, which measured this phenomenon by using different methods and indicators, were studied. In the end, 13 indicators were selected for this research and data values attributed to each of them were collected. Finally, by performing two stages of factor analysis and removing one of the indicators (percentage of population within 500-meter distance of educational landuse) because of weak correlation with other variables, the remaining indicators were classified into four factors: “density”, “configuration”, “landuse” and “accessibility.” The analysis, which has been performed in the case of Qazvin City, shows that these factors explain the variance of sprawl by 27.8, 21.6, 11.3 and 9.5 percent respectively. The explanatory power of “configuration factor” (21.6%) indicates that the “shape index” and “fractal dimension” indicators introduced by Frenkel & Ashkenazi (2007) have a high impact on urbansprawl and should be considered when measuring this phenomenon. The results of this study (Table 7) show that the districts 17, 28, 38 and 39 of Qazvin City have been very dense and districts 4, 5, 7,
Data acquired for the study includes information from Google images, GIS and remote sensing. The data for this study was collected via primary and secondary sources. Primary data was gathered through the use of the satellite images, GIS and Remote sensing soft ware. Five (5) districts were purposively selected for the study mainly due to high rate of physical development of these areas. These areas are Bolori districts, Dala Alamderi districts, Maisandari districts, Galtimari districts and Mairi district respectively. Data collected for the study was presented using maps, charts, and the frequency distribution table.
In the present study, detailed investigations have been carried out in Petroleum, Chem- icals and Petrochemical Investment Region (PCPIR) area in Vygra and Bharuch Talu- kas in Bharuch district of Gujarat State using Indian Remote Sensing satellite digital data. The changes in landuse/land cover PCPIR area have monitored using the multi- date IRS LISS-III and Cartosat-1 data of 2011, 2012 and 2013 periods. Various thematic landuse/land cover maps were prepared and GIS database for various thematic layers have been generated using satellite and ground based information.
Various studies were conducted to understand the effect of SUHI across the world [45,46]; these attempts also elaborated solutions to counteract SUHI effects by applying necessary mitigation and adaptation practices. Enhancing vegetated spaces in urban areas or the concept of the land-use mixture (a mixture of impervious surfaces and green spaces) was identified as an appropriate mitigation approach, which our results also proved. The green forest located close to the city center called Udawaththakele (460,700.48 m north (N), 806,816.30 m east (E)) was categorized as a comparatively low-temperature class (24–26 °C) in 2007, as shown in Figure 2c. In addition to that, Figures 5e and 6e show the power of vegetated land that behaves as a heatsink. Vegetated land can regulate the SUHI effect, as past research also proved, even in Sri Lanka . Planting trees around parks, residential areas, and along roads leads to shaded IS, and it encourages air circulation in the urban area to make the environment more livable. It also lowers albedo and increases evapotranspiration. Vegetated land can cool and circulate polluted air , which is primarily essential for making urban life more comfortable by preventing heat stress and respiratory diseases . In addition, green walls and green roofs are proposed for high-rise buildings that are not covered with trees .