Abstract – Remotesensing and geographic information system techniques are significant and popular approaches that have been used in recent years to measure and map urbangrowthpatterns. This paper primarily aims to provide a basis for a literature review of urbangrowth measurement and mapping by using different methods. For this purpose, the general characteristics of measuring and mappingurbangrowthpatterns are described and classified. The strengths and weaknesses of the various methods have been identified from an analysis and discussion of the characteristics of the techniques. Results of reviews confirm that combining quantitative and qualitative techniques, such as Shannon approach and change detection, to measure and map urbangrowthpatterns will improve understanding of the phenomenon of urbangrowth. Moreover, using social and economic data such as population and income data will improve understanding of the relationships between causes and effects. The integration of social and economic factors with quantitative and qualitative techniques will contribute to a perfect evaluation of urbangrowthpatterns and land use changes, taking technical, social, economic, spatial, and temporal factors into account.
The important of seagrass and plankton ar that they are often correlated to the fish breeding grounds, hence, measuring these two factors can assists in identifying both fish breeding and fishing grounds. In this paper, both ocean colour and seagrass mapping from satellite remotesensing data off eastern coast of Malaysia comprising clustered island priorily gazette by the Malaysian Government as one of the five national marine parks.
A map provides the visual aspect from which studies on urban sprawl can begin in relation to urbangrowth. A Geographic Information System is useful for mapping the spatial distribution of urban areas. Unlike traditional cartographic methods, GIS allows for the manipulation of different types of data in one map frame. Mappingurban phenomena is a crucial part of quantifying urban sprawl. While many layers of data are used to create a map of urbangrowth, ultimately it is the map that tells the story about the level of urban sprawl over a given landscape. This type of mapping involves a temporal signature in which two or more time periods are used for comparing amounts of urbanization. One base map shows urban or built-up land in a starting year and another map shows the developed land from the end year. Therefore, mapping the extent of urbanization over a given period of time is an essential part of understanding urban sprawl.
The RemoteSensing and GIS application appears to be an alternative for urban sprawl mapping and monitor- ing effectively . That is why, time series imagery of Peshawar was acquired and classified into various lan- duse classes including built up land, vegetation, soil, rock and water. It is clearly seen that, huge sprawl in term of aerial shown in different themes is observed by segregation and calculation of areas of these classes. Area covered under built up in 1978 is 195.4 Sq. Km (Figure 9). In Figure 10, area expansion has been shown after 1992. It is extended up to 305.16 Sq. Km in 2011 (Figure 11). To find changed area, change detection map has been drawn in Figure 12. These figure points out that about 56% urban area extensions in the span of 1978-2011 were witnessed which is certainly an alarming number for any city of the world. Hence, it supports the census figure and goes side by side which reveals rapid urbangrowth in Peshawar and its outskirts.
2.2 Land use/Land cover: The Dulung watershed area was extensively forested with seasoned trees in the recent past. The watershed region is also extensively drained by number of 1st order, 2nd order, 3rd order and 4th order streams form source to mouth. The remaining areas of newer alluvium tracts were potential for cultivation and settlement with available surface and groundwater resource. Thus as a whole the watershed is now modified with the alteration of land cover by expansion of settlements in different corner of the watershed. Almost 500 km 2 areas of the basin are now still under forest tracts in different forms of dense forest (82.9 km 2 ), mixed forest (125.40km 2 ), and open land/blank forest (60.98 km 2 ). Other areas of the watershed are mostly altered by extension cultivation land and settlements and different road ways and railway tracks (Fig: 03). On the basis of the alteration of land cover areas some urban centers have coming up on the margin of road ways and railway track of the Dulung watershed.
Fig. 1 ). Mansoura (the capital of Daqahlia governorate) and Talkha are the most important cities in Daqahlia gov- ernorate; the area of investigation covers 670 km 2 (159,541 feddan). Regionally, the studied area is located in the cen- tral Daqahlia governorate and has been chosen because of the fast rate of urbanization and little studies were made on it. Urbangrowth is one of the main problems that reduces the limited highly fertile land in these cities. In this context, Mansoura and Talkha are experiencing various urban envi- ronmental problems. For sustainability of urban systems a balanced land use/land cover is to be planned.
2. Role of GIS, RemoteSensing and GPS in Land-use/cover Mapping Viewing the earth from space has become essential to comprehend the cumulative influence of human activities on its natural resource base. In a time of rapid and often unrecorded land-use change, observations from space provide objective information of human utilization of landscape. Over the past two decades, data from earth sensing satellites have become important in mapping the earth’s features, infrastructure managing, managing natural resources and studying environmental change. Remotesensing and GIS are providing new tools for advanced ecosystem management. The collection of remotely sensed data facilitates the synoptic analysis of earth-system functions, patterns and change at local, regional and global scales over time. Such data also provide vital links between intense localized ecological researches and the regional, national and international conservation and management of biological diversity (Wilkie and Finn, 1996). Allocating and managing earth’s resource requires knowing its distribution in space. Maps help us measure the extent and distribution of resources, analyze resource interactions and identify suitable locations for specific action (eg. development or preservation) and plan future events. GIS helps in performing varied analysis on the data thus obtained from remotesensing. Boolean algebraic operations such as overlay analysis could bring out the interim characteristics of the land-use. GPS helps in the in-situ (ground truth verification) of the land-use represented by these technologies.
Urbanization indicates to the process by which rural areas become urbanized due to economic development and industrialization. Urbanization is a shift of population from rural areas to urban areas and slight increase in the proportion of people living in urban areas(Aswathy et al.,).Urbangrowth is a global phenomena and one of the important reforming processes affecting both natural and human environment through many ecological and socio-economic processes (Mandela’s et al., 2007). Urbanization is one factor that leads to landscape degradation. It involves transformation of various land uses into urban areas wherein unplanned urban expansion leads to environmental degradation causing shortages of housing, worsening water quality, excessive air pollution (Ramachandra et al., 2012, Uttara et al., 2012).Urban landscape analysis provides the spatial properties and configuration of the area at a particular time (Galster et al., 2001). The urbanpatterns mainly deal with the physical structure and the spatial characteristics of the urban processes that vary over time (Aguilera et al., 2011). Urbanpatterns have been analysed using various spatial metrics (Jiang et al., 2007, Angel et al., 2007, Bharath et al., 2012, Ramachandra et al., 2012). Landscape degradation reduces the ability of the land to perform many biophysical and chemical functions. Over exploitation of environmental resources by humans and by grazing animals, non scientific political decisions or economic policies add external impetus to landscape degradation.Long term detecting of changes in land degradation is accomplished by spatially comparing different multi temporal satellite images. It involves looking for difference between two surface models that are obtained at different times Areas affected by degradation can be identified and mapped from Land sat Thematic Mapper(TM) images. This paper describes urban landscape analysis usingRemotesensing and GIS in Kollam district.
Guzman et al'.(2002) in their project Multi-Scale and Multi- Temporal Poverty Mapping made an attempt on poverty mapping and developed Poverty Alleviation Decision Support System (PADSS) in which forms, patterns and structures of poverty at various scales and years were analyzed through RemoteSensing and Geographic Information Systems (RS- GIS). Location motivation behind informal settlements within Metro-Manila and in Ivluntinlupa include vacant lots and easements, major transport routes, water bodies, sites for vegetable gardens and job attractors, like commercial and industrial areas and informal livelihood sources. Clustering around socio economic attractors is evident from large and smaller pockets of slums. The results of National-scale' and multi-temporal mapping of poverty indices are indicative of movement of migration. A useful application of RS—GIS is also land suitability mapping like Existing land use and land cover, slope, water availability. distance to employment, development costs, Natural hazards and risks influence the appropriateness of a site for a specific or multiple purpose, especially socialized housing. These suitability maps are important inputs to Comprehensive and Sustainable Land Use Plans (CSLUP), especially towards the better integration of the marginalized into the urban system.
Limited training samples to mapping land cover over large areas is one of the challenging problems that limit the capability of the classifier to make generalization to the patterns that located in sampled areas. There are two significant challenges always faced analysts when conduct to map rubber trees growth. Firstly, the confusing that occurs between mature rubber trees and tropical evergreen vegetation and that because the similarity in the spectral reflectance characteristics. Mature rubber trees areas are often overestimated by misclassifying with forests as rubber trees. Secondly, mixed scrub and bare ground, or intercropped that occurred with economic crops like cassava and pineapple are revealed in young rubber trees areas. Rubber tree growth canopies even after (3- 4) years has a small fraction of overall planted area in the land cover scale. Thirdly, the small area that covers with rubber trees very small if compared with the features in surrounding area. Fourthly, the high different of intra class – variability between the rubber trees at different age levels. All these conditions make it mapping rubber trees very difficult . Nowadays machine learning techniques  like neural networks and decision tress  have been widely used in remotesensing imageries classification because they demonstrate many benefits over other conventional classifiers  .
planners have begun to evaluate the resources in a multi-disciplinary approach for timely results and with less preparation cost and manpower support. Remotesensing data has been widely used in preparation of perspectives plan and development plan. It includes mapping of present land use, infrastructure network (roads, railways and settlements), hydrological features (river/stream, lakes), etc., useful for preparation of regional level landscape, updating of base maps, urban sprawl, land use change and population growth and master plan proposals.
Yue et al. (2003) developed models for landscape change detection in newly created wetland of yellow river delta for the conservation of the newly created delta. Four models were employed in the landscape change detection of the newly created wetland. The models included ones for patch connectivity, ecological diversity, human impact intensity and mean center of land cover. Alados et al. (2004) study aimed to analyze the main processes that determine changes in landscape patterns and vegetation cover from 1957-1994 of semiarid and Mediterranean, to develop a model for land cover dynamics. Land cover and landscape patterns were assessed and compared using aerial photographs taken in 1957, 1985, and 1994. They used scanned toposheet and the aerial photographs of the different year and conducted the overlay analysis with the help of GIS software. They also conducted the ground check to verify the results obtained by the analysis. Ye qui et al. (2004) study characterized and analyzed the dynamics of a rapidly expanding urban landscape of Beijing Municipality, based on the Hierarchical Regional Space (HRS) model. Kayhko and Skanes (2005) performed retrospective landscape change trajectory analysis with the help of available spatio-temporal data of different time era and verify it with the help of the field data, all the collected landscape information taken to the GIS environment and compiled to detect the path of change of trajectory analysis.
Google Earth has been used in several research in- cluding disaster and crisis-management support , the influence of land use on the urbanization , the use of crowd sourcing to improve global land cover , land- scape cover-type modeling using a MultiScene Thematic Mapper mosaic , Water Harvesting siting in the Jor- danian Badia , and mapping the appropriate sites for the cultivation of forage in the Jordanian Badia . Also, Google Earth has been used for the recent valida- tion of remotesensing derived products e.g., the Euro- pean forest cover map .
The thematic maps derived through the interpretation of satellite data i.e., geology, geomorphology, lineament, drainage patterns and soil were digitized, edited and saved as shape files in GIS software. The lineament and drainage maps were digitized as line coverage whereas geological and geomorphological maps were digitized and saved as polygon coverage, assigning unique polygon to each geological /geomorphological unit. The maps were then projected to a common UTM projection system so as to subsequently superimpose in ArcGIS using to weighted overlay sub-module to demarcate groundwater prospect zones based on above themes. Integration of thematic maps led to the demarcation of groundwater potential map which qualitatively defines the prospect zones for future groundwater development in and around Bengaluru urban district. Thus, the groundwater prospective zones are obtained for the study area was represented in the figure 10.
tion and pollution of water, soil and air are taken in to consideration . Understanding this urban systems and addressing questions regarding changes in the spatio tem- poral patterns of urban form are of paramount impor- tance in urban research. Land use information can be used to develop solutions for natural resource manage- ment issues. Remotesensing, although challenged by the spatial and spectral heterogeneity of urban environments, seems to be a suitable source of reliable information about the multiple facets of urban environment [14,15]. GIS can generate a two or three dimensional images of an area, usingGIS images as models, making precise measurements, gathering data, and testing ideas with the help of computer .
Urbangrowth and land use changes in the FCT was investigated usingremotesensingtechniques. The remotely sensed Landsat data from 1990 to 2015 and Sentinel 2 of 2018 were used for the study. The image pre-processing and processing was carried out using ArcGIS 10.1 and QGIS 2.3.18. The stacked composite images were classified into Built-up, rivers, rock surface, vegetation, Thick vege- tation, developing land, and bare land. The classified images for the various years were compared to investigate urban sprawl and land use change dynamics within FCT. Cross-tabulation was used to estimate the degree of the urban sprawl, and land use changes in FCT. And it was noticed that urban sprawl has completely change land use pattern within the FCT most especially Abuja municipal area council which has replaced agricultural land with built-up. More also, there s considerably more changes noticed across the remaining five area council. However, the degree of urban sprawl and land use changes has affected the natural surfaces, weather, and climatic condition and geological foundation within the FCT. Slums settlement and un-pattern Built-up area have claimed 90% of greenery in the FCT which has resulted to UHI in the FCT. Conclusively, this study will help town planners to monitor development such that, it will favor living condition within the FCT. The results from the study show that if urbangrowth is not monitored, there will be unplanned and indecent built-up in cities area and the ecosystem would not be preserve thereby resulting in UHI. UHI can lead to fatalities (16). Town planners must therefore, take the preservation of the ecosystem into consideration by allowing land for greenery to ensure energy balance in the cities when they design a layout for a city or town.
Urbangrowth is a dynamic process and understanding the relationship between growth and its driving factors, is a primary objective in the urban research agenda. Increase in urbangrowth is usually associated with the population concentration in an area which drives the change in land use land cover pattern. Analysis of urbangrowth pattern is a continuous process that involves scientists, resource managers and planners (Pathan et al., 1989; Pathan et al., 1991; Barnes et al., 2001; Angel et al., 2007; Kumar et al., 2007). The conventional surveying and mappingtechniques are expensive and time consuming for the estimation of urban sprawl and such information is not available for most of the urban centers, especially in developing countries. As a result, increased research interest is being directed to the mapping and monitoring of urban sprawl/growthusingGIS and remotesensingtechniques (Epstein et al., 2002, Tiwari & Dixit., 2015).
Urban areas are rapidly expanding in both developed and developing nations [1, 2]. However, urban land expansion is placing a formidable challenge in many countries around the globe, especially in terms of deforestation and land degradation . Presently, more people dwell in urban areas than rural areas , and about 40 percent of the world’s people lives in dry lands accounting for about 20 percent of the earth’s surface . In spite of the fact that urbanization remains a key to modernization, economic growth and development, it equally has some reverberations on the environment [6, 7]. Looking at the influence of urbangrowth on deforestation, it becomes imperative to understand how urban areas are developing and the impacts of their development on the physical environment especially in terms of biodiversity and land degradation.
patterns and relationships that characterize real-world planning and policy problems. Visualization of spatial patterns also supports modify investigation, which is significant in monitoring of communal indicators. This in turn should result in improving need assessment. The progressive satellite based used in geomatic techniques of land surface mapping give a batter opportunity for making of more accurate and detailed maps of our cities. These maps can gives urban planners with a better understanding of city growth, dynamics of the urban rural boundary, monitoring of stress on the existing civic amenities and urban infrastructure. They may also help in taking remedial measures and future developmental planning.
The high rate of increase in the urban population has created many problems in the urban areas of Indian cities. Doubling and tripling of urban population practically in all major cities and towns and the consequent strain on the existing system manifested in an environmental chaos. Every major city of India faces the same prolifer- ating problems of urban expansion, inadequate housing, poor transportation system, poor sewerage, erratic elec- tric supply, insufficient drinking water supplies etc. An increasing number of trucks, buses, cars, three-wheelers and motorcycles all spewing uncontrolled fumes, surge in sometimes-haphazard patterns over city streets jamm- ed with jaywalking pedestrians, rickshaw, cattle, and goats. The phenomena of accelerated urbanization is the main culprit, wherein besides bringing higher standard of living has also brought problems of growth of dense and unplanned residential areas, environmental pollution, non-availability of services and amenities and solid waste generation and growth of slums. The rapid growth of Delhi in past decades has resulted in significant de- crease in the quality of environment. Rise in population and growth in economic activity has led to environ- mental degradation in Delhi. Emerging future of Delhi in the light of its past experiences, current trends, and de- velopment initiatives is one of the important issue which shows different social and physical factors affecting the housing and quality of life in Delhi . After independ- ence, when Delhi witnessed a large influx of migrants, within a very short time, the population of Delhi in- creased more than two folds. To house such a large mi- grant people city has to expand but the rate of expansion is very fast, unplanned, uncontrolled and most of them are illegal .