Urban growth pattern identification : a case study in Siem Reap, Cambodia

The main purpose of this paper is to identify the pattern of urban growth from 1993 to 2011 in Siem reap town, Cambodia. Land use and land cover maps were generated from Landsat TM imageries from different years in order to extract the information related to urban sprawl. The settlement pattern theory, geographic pattern analysis and visualisation interpretation were used to detect the pattern of urban growth in Siem Reap. Result shows that from 1993 to 2011 the urban area grew significantly, about 102.51%. The development of core settlement areas in Siem Reap revealed to be concentrated along main roads and along the river in the past and still keeping the same trend in the present. The current pattern of urban settlement in Siem Reap was classified as clustered and linear, following the roads network

Advances in remote sensing applications for urban sustainability

Abstract: It is essential to monitor urban evolution at spatial and temporal scales to improve our understanding of the changes in cities and their impact on natural resources and environmental systems. Various aspects of remote sensing are routinely used to detect and map features and changes on land and sea surfaces, and in the atmosphere that affect urban sustainability. We provide a critical and comprehensive review of the characteristics of remote sensing systems, and in particular the trade-offs between various system parameters, as well as their use in two key research areas: (a) issues resulting from the expansion of urban environments, and (b) sustainable urban development. The analysis identifies three key trends in the existing literature: (a) the integration of heterogeneous remote sensing data, primarily for investigating or modelling urban environments as a complex system, (b) the development of new algorithms for effective extraction of urban features, and (c) the improvement in the accuracy of traditional spectral-based classification algorithms for addressing the spectral heterogeneity within urban areas. Growing interests in renewable energy have also resulted in the increased use of remote sensing—for planning, operation, and maintenance of energy infrastructures, in particular the ones with spatial variability, such as solar, wind, and geothermal energy. The proliferation of sustainability thinking in all facets of urban development and management also acts as a catalyst for the increased use of, and advances in, remote sensing for urban applications

Monitoring urban sustainability based on an integrated indicator model using geospatial technique and multiple data sources: a case study in the city of Saskatoon, Saskatchewan, Canada

A comprehensive understanding of urban development is critical for moving towards the goal of sustainability. Despite a collection of urban sustainability indicator (USI) conceptual frameworks proposed and explored in practical urban sustainability assessment, establishing an integrated, well-quantified, spatially characterized USI model is still a challenging task. Therefore, based on a manuscript-style format this thesis develops a subjectively weighted integrated USI model and then applies it to the city of Saskatoon, SK, Canada, as a case study, based on quantifying a hierarchical index system. In addition, urban environmental sustainability is spatiotemporally investigated for an improved understanding of Urban Heat Island (UHI) effect. Results show that the proposed integrated USI model improved urban sustainability measurement by overcoming the shortages in existing USI models. Geospatial statistics demonstrated disparity in urban sustainability across residential neighbourhoods for Saskatoon in 2006 based on the significant clusters and outliers. It also found that population increases can possibly improve intellectual and economic well-being and promote urbanization, but may cause environmental degradation and lead to a decline in overall urban sustainability. This research also demonstrates that satellite imagery can be used to study environmental sustainability at different spatiotemporal scales. This research reveals that both urban water and green spaces had significant cooling effects on the surrounding urban LST within specific ranges. Urban surface temperature can be estimated based on a multiple linear regression model with sustainable traveling mode index and land use information as input variables. The overall significance of this research has three folds. First, it lays a preliminary theoretical foundation for a comprehensive understanding of urban sustainability based on a well-quantified integrated USI model. Second, it is relatively original with respect to improving urban sustainability measurements through the incorporation of subjective information into objective data. Third, this research has explored spatiotemporal analysis to detect urban sustainability patterns based on compiling multiple data sources using geospatial techniques. The proposed USI model is highly suitable for comparison analysis at different spatial scales as well as continuously tracking the dynamic changes. Therefore, this research can be a good practice of applying the spatiotemporal philosophy to urban geographical problems

Farmland Allocation along the Rural-Urban Gradient: The Impacts of Urbanization and Urban Sprawl

In the vicinity of a city, farmers are confronted with increasing agricultural land prices and rents along the rural-urban gradient, but they concurrently enjoy the advantages associated with proximity to a larger and wealthier consumer base. We hypothesize that farmers transition from low-value, land-intensive \traditional" crops to high-value, labor-intensive \specialized" crops on parcels located closer to urban centers. Once returns to development of a parcel exceed the profits associated with farming, exurban farmers may sell their land for conversion to urban use. Urban pressure in the rural-urban fringe intensifies as cities expand. We differentiate between a gradual process of urban growth (or urbanization) and urban sprawl. Utilizing farmland fragmentation measures as indicators of sprawl, we hypothesize that urban sprawl burdens \traditional" farms to the extent that they accelerate the transition to specialized crops or convert farmland to urban use. We use crop-specific land cover data at the level of grid cells and a state-of-the-art system of spatially correlated simultaneous equations with data for the metropolitan area of Indianapolis, IN and its immediate hinterland. Our initial empirical results corroborate that accelerated urban development around Indianapolis in the 1990s is associated with land uses characterized by fewer field crops and more idle land.land use, urban sprawl, agriculture, specialized crops, spatial econometrics, Community/Rural/Urban Development, Land Economics/Use, C31, O13, Q15, R14,

Cityscape, poverty and crime: a quantitative assessment using VHR imagery

[EN] The first part of this work reviews the potential applications of satellite remote sensing to regional science research in urban settings. The availability of satellite remote sensing data has increased significantly in the last two decades. The increasing spatial resolution of commercial satellite imagery has influenced the emergence of new research and applications of regional science in urban settlements because it is now possible to identify individual objects of the urban fabric. The most common applications found in the literature are the detection of urban deprivation hot spots, quality of life index assessment, urban growth analysis, house value estimation, urban population estimation, urban social vulnerability assessment, and the variability of intra-urban crime rates. The satellite remote sensing imagery used in these applications has medium, high or very high spatial resolution (Landsat MSS, Landsat TM and ETM+, SPOT, ASTER, IRS, Ikonos and QuickBird). Consistent relationships between socio-economic variables derived from censuses and field surveys and proxy variables of vegetation coverage measured from satellite remote sensing data have been found in several cities in the US. Different approaches and techniques have been applied successfully around the world, but local research is always needed to account for the unique elements of each place. Spectral mixture analysis, object-oriented classifications and image texture measures are some of the techniques of image processing that have been implemented with good results. This work contributes empirical evidence about the usefulness of remote sensing imagery to quantify the degree of poverty at the intra-urban scale. This concept is based on two premises: first, that the physical appearance of an urban settlement is a reflection of the society; and second, that the people who reside in urban areas with similar physical housing conditions have similar social and demo- graphic characteristics. We evaluate the potential of the image-derived urban fabric descriptors to explain a measure of poverty known as the Slum Index. We found that these variables explain up to 59% of the variability in the Slum Index. Similar approaches could be used to lower the cost of socioeconomic surveys by developing an econometric model from a sample and applying that model to the rest of the city and to perform intercensal or intersurvey estimates of intra-urban Slum Index maps. The last part of this work analyzes the relation between the urban layout and crime. The link between place and crime is at the base of social ecology theories of crime that focus in the relationship of the characteristics of geographical areas and crime rates. The broken windows theory states that visible cues of physical and social disorder in a neighborhood can lead to an increase in more serious crime. Based on the premise that a settlement's appearance is a reflection of the society, we ask whether a neighbor- hood's design has a quantifiable imprint when seen from space using urban fabric descriptors computed from VHR imagery. The percentage of impervious surfaces other than clay roofs, the fraction of clay roofs to impervious surfaces, two structure descriptors related to the homogeneity of the urban layout, and the uniformity texture descriptor were all statistically significant. Areas with higher homicide rates tended to have higher local variation and less general homogeneity; that is, the urban layouts were more crowded and cluttered, with small dwellings with different roofing materials located in close proximity to one another, and these regions often lacked other homogeneous surfaces such as open green spaces, wide roads, or large facilities. These results seem to be in agreement with the broken windows theory and CPTED in the sense that more heterogeneous and disordered urban layouts are associated with higher homicide rates.[ES] La primera parte aporta una revisión de las aplicaciones de la teledetección satelital en la investigación de ciencia regional en entornos urbanos. La disponibilidad de imágenes satelitales se ha incrementado significativamente en las dos últimas décadas, al tiempo que la resolución espacial ha venido aumentando, lo que ha influenciado el surgimiento de investigaciones y aplicaciones de ciencia regional en zonas urbanas. Las aplicaciones más comunes son la detección de hot spots de pobreza urbana, la evaluación de índices de calidad de vida, el análisis del crecimiento urbano, la estimación de valores de vivienda, la estimación de población urbana, la evaluación de la vulnerabilidad social y las variaciones intra-urbanas en tasas de crimen. Las imágenes satelitales usadas tienen resolución espacial media, alta o muy alta (Landsat MSS, Landsat TM y ETM+, SPOT, ASTER, IRS, Ikonos y Quickbird). Se han encontrado relaciones consistentes entre variables socio-económicas obtenidas de censos y encuestas y variables de la cobertura de vegetación en varias ciudades de Estados Unidos. Algunas de las técnicas que se han implementado y obtenido buenos resultados son el análisis de mezcla espectral, las clasificaciones orientadas a objetos y las medidas de textura de la imagen. Se aporta evidencia empírica acerca de la utilidad de las imágenes satelitales para cuantificar el grado de pobreza a escala intra-urbana. Se basa en dos premisas: primero, que la apariencia física de un asentamiento urbano es un reflejo de la sociedad que lo habita; y segundo, que la población de áreas urbanas con condiciones físicas de vivienda parecidas tiene características sociales y demográficas similares. Evaluamos el potencial de los descriptores del tejido urbano extraídos de la imagen para explicar una medida de pobreza conocida como el índice Slum. Encontramos que esas variables explican hasta un 59% de la variabilidad en el índice Slum. Aproximaciones similares a esta podrían usarse para disminuir el costo de encuestas socioeconómicas por medio del desarrollo de un modelo econométrico usando una muestra y luego aplicando el modelo al resto de la ciudad, y para elaborar estimaciones inter-censales o inter-encuestas de mapas intra-urbanos del índice Slum. La última parte analiza la relación entre el trazado urbano y crimen. El enlace entre el lugar y el crimen está en la base de las teorías socio-ecológicas de crimen que se enfocan en la relación de las características de las áreas geográficas y las tasas de crimen. La teoría de las ventanas rotas afirma que las evidencias visibles de desorden físico y social en un barrio pueden llevar al incremento de crímenes más serios. Con base en la premisa de que la apariencia de un asentamiento es un reflejo de la sociedad, nos preguntamos si el diseño del barrio tiene un impacto cuantificable cuando se observa desde el espacio usando descriptores del tejido urbano obtenidos de imágenes de muy alta resolución. El porcentaje de superficies impermeables diferentes a los techos de arcilla, la fracción de techos de arcilla sobre las superficies impermeables, dos variables de estructura relacionadas con la homogeneidad del trazado urbano y la variable de textura uniformidad resultaron estadísticamente significativas. Las áreas con tasas de homicidio más altas tienden a tener mayor variación local y menor homogeneidad general; esto es, los trazados urbanos son más desordenados y hacinados, con pequeñas viviendas que tienen materiales diferentes en sus techos localizadas muy cerca unas de otras, y estas áreas carecen a menudo de otras superficies homogéneas tales como espacios verdes abiertos, vías amplias y grandes construcciones industriales o institucionales. Estos resultados parecen estar en acuerdo con la teoría de las ventanas rotas y CPTED en el sentido de que los trazados urbanos más desordenados y heterogéneos están asociados con tasas de homicid[CA] La primera part aporta una revisió de les potencials aplicacions de la teledetecció espacial a la investigació en ciència regional en entorns urbans. La disponibilitat de dades de percepció remota des de satèl·lits s'ha incrementat significativament a les dues últimes dècades. La resolució espacial de les imatges de satèl·lit comercials també han anat augmentant i això, ha influït en l'aparició de investigacions i aplicacions a la ciència regional en assentaments urbans. Les aplicacions més comunes trobades a la literatura són la detecció de punts calents de pobresa urbana, l'avaluació dels índex de qualitat de vida, les anàlisis de creixement urbà, l'avaluació de la vulnerabilitat social i les variacions intraurbanes de les taxes de crims. Les imatges de satèl·lit emprades tenen resolució espacial mitjana, alta o molt alta (Landsat MSS, Landsat TM i ETM+, SPOT, ASTER, IRS, Ikonos y Quickbird). S'han torbat relacions consistents entre variables socioeconòmiques obtingudes de censos i enquestes i variables de la cobertura de vegetació en varies ciutats del Estats Units. Algunes de les tècniques que s'han implementat i han donat bons resultats són l'anàlisi de mescla espectral, les classificacions orientades a objecte i les mesures de textura de les imatges. Es aporta evidència empírica sobre la utilitat de les imatges de satèl·lit per quantificar el grau de pobresa a escala intraurbana. Es bassa en dues premisses: primer, que l'aparença física d'un assentament urbà n'és un reflex de la societat que l'habita; i segon, que les persones que resideixen en àrees urbanes amb condicions físiques de vivenda paregudes tenen també característiques socials i demogràfiques similars. Avaluem el potencial dels descriptors del teixit urbà extrets de la imatge per explicar una mesura de pobresa coneguda com index Slum. Trobem que aquestes variables expliquen fins un 59% de la variabilitat de l'índex Slum. Aproximacions semblants a aquesta es podrien emprar per a disminuir el cost de les enquestes socioeconòmiques mitjançant el desenvolupament d'un model economètric utilitzant una mostra i després aplicant el model a la resta de la ciutat, i per elaborar estimacions inter-censals o inter-enquestes de mapes intraurbans de l'índex Slum. La darrera part analitza la relació entre el traçat urbà i el crim. L'enllaç entre el lloc i el crim està a la base de les teories socio-ecològiques del crim que es centren en la relació de les característiques de les àrees geogràfiques i les taxes de crims. La teoria de les finestres trencades afirma que les evidències visibles de desordre físic i social d'un barri pot portar a l'augment de crims més greus. Basant-se en la premissa de que l'aparença d'un assentament n'és el reflex de la societat, ens hi preguntem si el disseny del barri té un impacte quantificable quan s'observa des de el espai, utilitzant descriptors del teixit urbà obtinguts de imatges de molt alta resolució. Han resultat estadísticament significatius el percentatge de superfícies impermeables diferents a les teulades de argila, la fracció de teulades d'argila sobre les superfícies impermeables, dues variables d'estructura relacionades amb la homogeneïtat del traçat urbà i la variable de textura de uniformitat. Les àrees amb taxes d'homicidi més altes tendeixen a presentar una major variació local i una menor homogeneïtat general; és a dir, el traçats urbans són més desordenats i amuntonats, amb petites vivendes que tenen materials diferents a les seues teulades localitzades molt prop unes d'altres, i aquestes àrees manquen sovint d'altres superfícies homogènies, com ara espais verds oberts, vies amplies i grans construccions industrials o institucionals. Aquests resultats pareixen estar-hi d'acord amb la teoria de les finestres trencades i CPTED en el sentit de que els traçats urbans més desordenats i heterogenis estan associats amb taxes d'homicides mPatiño Quinchía, JE. (2015). Cityscape, poverty and crime: a quantitative assessment using VHR imagery [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59453TESI

Landscape metrics and indices : an overview of their use in landscape research

The aim of this overview paper is to analyze the use of various landscape metrics and landscape indices for the characterization of landscape structure and various processes at both landscape and ecosystem level. We analyzed the appearance of the terms landscape metrics/indexes/indices in combination with seven main categories in the field of landscape ecology [1) use/selection and misuse of metrics, 2) biodiversity and habitat analysis; 3) water quality; 4) evaluation of the landscape pattern and its change; 5) urban landscape pattern, road network; 6) aesthetics of landscape; 7) management, planning and monitoring] in the titles, abstracts and/or key words of research papers published in international peer-reviewed scientific journals indexed by the Institute of Science Information (ISI) Web of Science (WoS) from 1994 to October 2008. Most of the landscape metrics and indices are used concerning biodiversity and habitat analysis, and also the evaluation of landscape pattern and its change (up to 25 articles per year). There are only a few articles on the relationships of landscape metrics/indices/indexes to social aspects and landscape perception

Urban sprawl in the state of Missouri : current trends, driving forces, and predicted growth on Missouri's natural landscape

Title from PDF of title page (University of Missouri--Columbia, viewed on March 5, 2013).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Hong S. HeIncludes bibliographical references.Vita.Ph.D. University of Missouri--Columbia 2012."December 2012"Missouri reflects a full range of sprawl characteristics that include large metropolitan centers, which led growth in 1980s, and smaller metropolitan and rural areas, which led growth in 1990s. In order to study the historical patterns of sprawl, there is a need to quantitatively and geographically depict the extent and density of impervious surface for three time periods of 1980, 1990, and 2000 for the entire state of Missouri. Mapped impervious surface is the best candidate of ancillary data for dasymetric mapping of population in several comparison studies. The current research examines the performances of dasymetric mapping of population with imperviousness as ancillary data and regression analysis of population using imperviousness as a predictor Results from this work can be aggregated to any geographical unit (hydrologic boundaries, administrative boundaries, etc.). A pilot future urban growth study for the two decades of 1980s and 1990s was done in Missouri. The historical urban growth of the two decades were analyzed then coupled with various predictor variables to investigate the influence of each predictor variables towards the process of urban growth. The knowledge learned from the process is then used to build an urban growth simulation model that is GIS-based with open framework for ease of management and improvement. Pixel level urban growth was simulated for year 2010, 2020 and 2030. This model framework is developed with the ultimate goal of simulating urban growth for the entire state of Missouri.Includes bibliographical reference

SPATIAL ANALYSES AND REMOTE SENSING FOR LAND COVER CHANGE DYNAMICS: ASSESSING IN A SPATIAL PLANNING

ABSTRACT (EN) Spatial planning is a crucial discipline for the identification and implementation of sustainable development strategies that take into account the environmental impacts on the soil. In recent years, the significant development of technology, like remote sensing and GIS software, has significantly increased the understanding of environmental components, highlighting their peculiarities and criticalities. Geographically referenced information on environmental and socio-economic components represents a fundamental database for identifying and monitoring vulnerable areas, also distinguishing different levels of vulnerability. This is even more relevant considering the increasingly significant impact of land transformation processes, consisting of rapid and frequent changes in land use patterns. In order to achieve some of the Sustainable Development Goals of the 2030 Agenda, the role of environmental planning is crucial in addressing spatial problems, such as agricultural land abandonment and land take, which cause negative impacts on ecosystems. Remote sensing, and in general all Earth Observation techniques, play a key role in achieving SDG 11.3 and 15.3 of Agenda 2030. Through a series of applications and investigations in different areas of Basilicata, it has been demonstrated how the extensive use of remote sensing and spatial analysis in a GIS environment provide a substantial contribution to the results of the SDGs, enabling an informed decisionmaking process and enabling monitoring of the results expected, ensuring data reliability and directly contributing to the calculation of SDG objectives and indicators by facilitating local administrations approaches to work in different development and sustainability sectors. In this thesis have been analyse the dynamics of land transformation in terms of land take and soil erosion in sample areas of the Basilicata Region, which represents an interesting case example for the study of land use land cover change (LULCC). The socio-demographic evolutionary trends and the study of marginality and territorial fragility are fundamental aspects in the context of territorial planning, since they are important drivers of the LULCC and territorial transformation processes. In fact, in Basilicata, settlement dynamics over the years have occurred in an uncontrolled and unregulated manner, leading to a constant consumption of land not accompanied by adequate demographic and economic growth. To better understand the evolution and dynamics of the LULCCs and provide useful tools for formulating territorial planning policies and strategies aimed at a sustainable use of the territory, the socio-economic aspects of the Region were investigated. A first phase involved the creation of a database and the study and identification of essential services in the area as a fundamental parameter against which to evaluate the quality of life in a specific area. The supply of essential services can be understood as an assessment of the lack of minimum requirements with reference to the urban functions exercised by each territorial unit. From a territorial point of view, the level of peripherality of the territories with respect to the network of urban centres profoundly influences the quality of life of citizens and the level of social inclusion. In these, the presence of essential services can act as an attractor capable of generating discrete catchment areas. The purpose of this first part of the work was above all to create a dataset of data useful for the calculation of various socio-economic indicators, in order to frame the demographic evolution and the evolution of the stock of public and private services. The first methodological approach was to reconstruct the offer of essential services through the use of open data in a GIS environment and subsequently estimate the peripherality of each municipality by estimating the accessibility to essential services. The study envisaged the use of territorial analysis techniques aimed at describing the distribution of essential services on the regional territory. It is essential to understand the role of demographic dynamics as a driver of urban land use change such as, for example, the increase in demand for artificial surfaces that occurs locally. Social and economic analyses are important in the spatial planning process. Comparison of socio-economic analyses with land use and land cover change can highlight the need to modify existing policies or implement new ones. A particular land use can degrade and thereby destroy other land resources. If the economic analysis shows that the use is beneficial from the point of view of the land user, it is likely to continue, regardless of whether the process is environmentally friendly. It is important to understand and investigate which drivers have been and will be in the future the most decisive in these dynamics that intrinsically contribute to land take, agricultural abandonment and the consequent processes of land degradation and to define policies or thresholds to mitigate and monitor the effects of these processes. Subsequently, the issues of land take and abandonment of agricultural land were analysed by applying models and techniques of remote sensing, GIS and territorial analysis for the identification and monitoring of abandoned agricultural areas and sealed areas. The classic remote sensing methods have also been integrated by some geostatistical analyses which have provided more information on the investigated phenomenon. The aim was the creation of a quick methodology that would allow to describe the monitoring and analysis activities of the development trends of soil consumption and the monitoring and identification of degraded areas. The first methodology proposed allowed the automatic and rapid detection of detailed LULCC and Land Take maps with an overall accuracy of more than 90%, reducing costs and processing times. The identification of abandoned agricultural areas in degradation is among the most complicated LULCC and Land Degradation processes to identify and monitor as it is driven by a multiplicity of anthropic and natural factors. The model used to estimate soil erosion as a degradation phenomenon is the Revised Universal Soil Loss Equation (RUSLE). To identify potentially degraded areas, two factors of the RUSLE have been correlated: Factor C which describes the vegetation cover of the soil and Factor A which represents the amount of potential soil erosion. Through statistical correlation analysis with the RUSLE factors, on the basis of the deviations from the average RUSLE values and mapping of the areas of vegetation degradation, relating to arable land, through statistical correlation with the vegetation factor C, the areas were identified and mapped that are susceptible to soil degradation. The results obtained allowed the creation of a database and a map of the degraded areas to be paid attention to

Urban Image Classification: Per-Pixel Classifiers, Sub-Pixel Analysis, Object-Based Image Analysis, and Geospatial Methods

Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post-classification steps. Within this chapter, each of the four approaches is described in terms of scale and accuracy classifying urban land use and urban land cover; and for its range of urban applications. We demonstrate the overview of four main classification groups in Figure 1 while Table 1 details the approaches with respect to classification requirements and procedures (e.g., reflectance conversion, steps before training sample selection, training samples, spatial approaches commonly used, classifiers, primary inputs for classification, output structures, number of output layers, and accuracy assessment). The chapter concludes with a brief summary of the methods reviewed and the challenges that remain in developing new classification methods for improving the efficiency and accuracy of mapping urban areas

Current Assessment and Future Prediction of Forest Cover Change in Cumberland and Morgan Counties, Tennessee: A Modeling Technique

Determining the relationship between human disturbance of the environment and natural forest change is critical for sound natural resource planning. Improved land cover modeling techniques that incorporate geographic information systems and statistical models are needed to assist in this analysis. Continued forest fragmentation due to increasing population and urbanization has created a growing interest in forest protection for the Cumberland Plateau of Tennessee. Specifically, Cumberland and Morgan Counties have seen unprecedented population growth over the last two decades, resulting in fragmentation of forestland. This study developed a model to determine the probability of exurbia development and its resulting forest fragmentation. Geographic data used in the research included satellite imagery from 1992 and 2000, U.S. Census population and demographic estimates, and road and water coverages for the two counties. The first objective of this study was to develop an accurate and efficient procedure for the development of a land cover map for use in a forest change detection system for Cumberland and Morgan Counties, Tennessee. A unique method was developed to generate this procedure by combining post-classification and image differencing. The second objective of the study was to determine the relationship between urbanization and forest loss in Cumberland and Morgan Counties, Tennessee, and to predict current and future land cover patterns. Logistic regression analysis suggested that demographic variables such as education and population along with spatial factors such as slope, distance to water, distance to interstate junctions, and gravity index factors of nearby urban retail centers, significantly influenced the transition of forest to urban cover. Of these parameters, a high gravity index, a suburban designation, and unsloped terrain had the greatest impact on forest to urban conversion. In addition, spatial factors such as parcel distance to water, and parcel distance to interstate junctions significantly influenced the probability of development. Finally, using population density predictions, the model identified the probability that forest land would be urbanized by 2010