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

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hot spot regions i n the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re - densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms

DIGITAL EARTH: QUANTIFYING URBAN LANDSCAPE CHANGES FOR IMPACT ANALYSIS

This study is to quantify land cover changes over time in order to analyze the impacts of human disturbances and climate factors on urban landscapes. The study area is Kansas City metropolitan area, USA. The study investigated both “dry-landscapes ” – urban impervious surface and “wet-landscapes ” – urban wetlands in order to fully understand the coupling effects of human built-up activities and precipitation variations. For the dynamics of drylandscapes, we classified multi-year Landsat images to map impervious surface change in relation to other land cover types at a metropolitan level. Based on the classified maps, we calculated relevant landscape metrics, including land patch density index and largest patch index of land covers, in order to better understand landscape change mechanism. The study reveals that in the recent decades urban built-up activities have greatly increased impervious surfaces and resulted in urban sprawling in the study area. To understand the variation of wetlandscapes, high-resolution SPOT images were classified to map urban wetlands and other relevant land cover types at finer scales. The mapped wetlands were analyzed in relation to precipitation conditions and impervious surface changes. The results suggest that urban wetland area changes were correlated with short-term precipitation conditions at a regional level, while the built-up activities have affected wetlands in some locations at fine scales

Decadal Land Surface Phenology and Water Quality in the Headwaters Illinois River Watershed

Over 25 percent of the world’s population either lives on or obtains water from karst aquifers. The complex interactions between subsurface karst geologic features, the constant motion of the plant life cycle, and significant water resource demand all suggest the need to better define those interactions. The relationship of historical land surface phenology and water quality in karst topography were investigated in the Headwaters Illinois River watershed in Northwest Arkansas (NWA). This area represents high vulnerability to surface water and groundwater contamination, with both natural and anthropogenic processes such as over application of broil litter for enhanced cattle browse, affecting groundwater quality. Land surface phenology patterns influenced by these processes were identified using Landsat satellite imagery and object-based image analysis (OBIA). A normalized difference vegetation index (NDVI) time series was produced using Google Earth Engine for all passes over the study area that meet atmospheric and data quality criteria over two decades from 1999 to 2018. Analysis of NDVI and ancillary data over time allowed insight into vegetation health norms, deviation from those norms, and human impact upon regional vegetation. OBIA techniques were used to segment vegetation index time series pixels into polygons based on adjacency and similarity. Resulting polygons were categorized using an unsupervised clustering approach, and were labeled based on visual and expert interpretation of the study area. The relation of the image analysis results to groundwater quality was determined using data organized by hydrologic catchments within the study area. Comparison of the decadal water quality data and NDVI image analysis resulted in meaningful temporal patterns within the datasets but showed a near 0 slope for NDVI and water quality metrics. Future LSP studies should consider areas with greater spatial and temporal availability of water quality metrics and variable surface/groundwater interactions

Role of Remote Sensing in Disaster Management

The objective of this report is to review the existing satellites monitoring Earth’s resources and natural disasters. Each satellite has different repeat pass frequency and spatial resolution (unless it belongs to the same series of satellites for the purpose of continuation of data flow with same specifications). Similarly, different satellites have different types of sensors on-board, such as, panchromatic, multispectral, infrared and thermal. All these sensors have applications in disaster mitigation, though depending on the electromagnetic characteristics of the objects on Earth and the nature of disaster itself. With a review of the satellites in orbit and their sensors the present work provides an insight to suitability of satellites and sensors to different natural disasters. For example, thermal sensors capture fire hazards, infrared sensors are more suitable for floods and microwave sensors can record soil moisture. Several kinds of disasters, such as, earthquake, volcano, tsunami, forest fire, hurricane and floods are considered for the purpose of disaster mitigation studies in this report. However, flood phenomenon has been emphasized upon in this study with more detailed account of remote sensing and GIS (Geographic Information Systems) applicability. Examples of flood forecasting and flood mapping presented in this report illustrate the capability of remote sensing and GIS technology in delineating flood risk areas and assessing the damages after the flood recedes. With the help of a case study of the Upper Thames River watershed the use of remote sensing and GIS has been illustrated for better understanding. The case study enables the professionals and planning authorities to realize the impact of urbanization on river flows. As the urban sprawl increases with the increase of population, the rainfall and snow melt reaches the river channels at a faster rate with higher intensity. In other words it can be inferred that through careful land use planning flood disasters can be mitigated.https://ir.lib.uwo.ca/wrrr/1002/thumbnail.jp

A Knowledge-based approach of satellite image classification for urban wetland detection

Title from PDF of title page, viewed on July 30, 2014Thesis advisor: Wei JiVitaIncludes bibliographical references (pages 85-93)Thesis (M. S.)--Dept. of Geosciences. University of Missouri--Kansas City, 2014It has been a technical challenge to accurately detect urban wetlands with remotely sensed data by means of pixel-based image classification. This is mainly caused by inadequate spatial resolutions of satellite imagery, spectral similarities between urban wetlands and adjacent land covers, and the spatial complexity of wetlands in human-transformed, heterogeneous urban landscapes. Knowledge-based classification, with great potential to overcome or reduce these technical impediments, has been applied to various image classifications focusing on urban land use/land cover and forest wetlands, but rarely to mapping the wetlands in urban landscapes. This study aims to improve the mapping accuracy of urban wetlands by integrating the pixel-based classification with the knowledge-based approach. The study area is the metropolitan area of Kansas City, USA. SPOT satellite images of 1992, 2008, and 2010 were classified into four classes -- wetland, farmland, built-up land, and forestland -- using the pixel-based supervised maximum likelihood classification method. The products of supervised classification are used as the comparative base maps. For our new classification approach, a knowledge base is developed to improve urban wetland detection, which includes a set of decision rules of identifying wetland cover in relation to its elevation, spatial adjacencies, habitat conditions, hydro-geomorphological characteristics, and relevant geostatistics. Using ERDAS Imagine software's knowledge classifier tool, the decision rules are applied to the base maps in order to identify wetlands that are not able to be detected based on the pixel-based classification. The results suggest that the knowledge-based image classification approach can enhance the urban wetland detection capabilities and classification accuracies with remotely sensed satellite imageryAbstract -- List of illustrations -- List of tables -- Acknowledgements -- Introduction -- Literature review -- Methodology -- Findings and analysis -- Discussion and conclusion -- Reference lis

Use of Earth observation for monitoring soil sealing trends in Flanders and Brussels between 1976 and 2013

The on-going growth of urban area in Flanders and in the Brussels Capital Region over the past decades has resulted in a highly sprawled urban tissue, consisting of large and smaller urban agglomerations, connected by a well-developed transportation network. The conversion of open land to urban area is accompanied by an increase in soil sealing, affecting the hydrological cycle and the urban climate. Despite a growing interest in monitoring the process of soil sealing in urban areas, to date no detailed information on the presence and evolution of sealed surfaces is available for Flanders. In this paper a linear regression unmixing approach is proposed to map and monitor changes of sealed surface cover at the regional scale, using medium as well as high resolution remote sensing data. Applied to Flanders and the Brussels Capital Region, a total sealed area of 2687 km² for 2013 is found, corresponding to an increase of 82% since 1976. Residential areas account for nearly half of the sealed area and show the largest increase in sealed surface cover over the past 37 years.De toenemende verstedelijking van Vlaanderen en het Brussels Hoofdstedelijk Gewest in de laatste decennia heeft geleid tot een sterk gefragmenteerde stedelijke ruimte die zich heeft ontwikkeld rond grote en kleinere bebouwingskernen en langs het dicht vertakte transportnetwerk dat deze kernen verbindt. De conversie van open ruimte naar stedelijk gebied gaat gepaard met een toenemende afdichting van de bodem met verharde oppervlakken. Deze afdichting heeft een impact heeft op de hydrologische cyclus en het klimaat van verstedelijkte zones. Ondanks de groeiende aandacht voor het opvolgen van bodemafdichting in verstedelijkte gebieden is op dit moment geen gedetailleerde informatie omtrent de evolutie van bodemverharding in Vlaanderen beschikbaar. In dit artikel wordt een methode voorgesteld om bodemverharding en veranderingen in verharding doorheen de tijd op regionale schaal in kaart te brengen, gebruik makend van satellietdata. De methode is gebaseerd op spectrale ontmenging van medium resolutie satellietdata, en gebruikt gedetailleerd, hoge resolutie beeldmateriaal om een op lineaire regressie gebaseerd ontmengingsmodel te calibreren en valideren. Toepassing van de methode op Vlaanderen en het Brussels Hoofdstedelijk Gewest resulteert voor 2013 in een totale verharde oppervlakte van 2687 km2, wat overeenstemt met een toename van 82% sinds 1976. Bijna de helft van de verharde oppervlakte situeert zich in residentiële gebieden, die vergeleken met andere landgebruiken ook de grootste toename in verharding kennen

A methodology to produce geographical information for land planning using very-high resolution images

Actualmente, os municípios são obrigados a produzir, no âmbito da elaboração dos instrumentos de gestão territorial, cartografia homologada pela autoridade nacional. O Plano Director Municipal (PDM) tem um período de vigência de 10 anos. Porém, no que diz respeito à cartografia para estes planos, principalmente em municípios onde a pressão urbanística é elevada, esta periodicidade não é compatível com a dinâmica de alteração de uso do solo. Emerge assim, a necessidade de um processo de produção mais eficaz, que permita a obtenção de uma nova cartografia de base e temática mais frequentemente. Em Portugal recorre-se à fotografia aérea como informação de base para a produção de cartografia de grande escala. Por um lado, embora este suporte de informação resulte em mapas bastante rigorosos e detalhados, a sua produção têm custos muito elevados e consomem muito tempo. As imagens de satélite de muito alta-resolução espacial podem constituir uma alternativa, mas sem substituir as fotografias aéreas na produção de cartografia temática, a grande escala. O tema da tese trata assim da satisfação das necessidades municipais em informação geográfica actualizada. Para melhor conhecer o valor e utilidade desta informação, realizou-se um inquérito aos municípios Portugueses. Este passo foi essencial para avaliar a pertinência e a utilidade da introdução de imagens de satélite de muito alta-resolução espacial na cadeia de procedimentos de actualização de alguns temas, quer na cartografia de base quer na cartografia temática. A abordagem proposta para solução do problema identificado baseia-se no uso de imagens de satélite e outros dados digitais em ambiente de Sistemas de Informação Geográfica. A experimentação teve como objectivo a extracção automática de elementos de interesse municipal a partir de imagens de muito alta-resolução espacial (fotografias aéreas ortorectificadas, imagem QuickBird, e imagem IKONOS), bem como de dados altimétricos (dados LiDAR). Avaliaram-se as potencialidades da informação geográfica extraídas das imagens para fins cartográficos e analíticos. Desenvolveram-se quatro casos de estudo que reflectem diferentes usos para os dados geográficos a nível municipal, e que traduzem aplicações com exigências diferentes. No primeiro caso de estudo, propõe-se uma metodologia para actualização periódica de cartografia a grande escala, que faz uso de fotografias aéreas vi ortorectificadas na área da Alta de Lisboa. Esta é uma aplicação quantitativa onde as qualidades posicionais e geométricas dos elementos extraídos são mais exigentes. No segundo caso de estudo, criou-se um sistema de alarme para áreas potencialmente alteradas, com recurso a uma imagem QuickBird e dados LiDAR, no Bairro da Madre de Deus, com objectivo de auxiliar a actualização de cartografia de grande escala. No terceiro caso de estudo avaliou-se o potencial solar de topos de edifícios nas Avenidas Novas, com recurso a dados LiDAR. No quarto caso de estudo, propõe-se uma série de indicadores municipais de monitorização territorial, obtidos pelo processamento de uma imagem IKONOS que cobre toda a área do concelho de Lisboa. Esta é uma aplicação com fins analíticos onde a qualidade temática da extracção é mais relevante.Currently, the Portuguese municipalities are required to produce homologated cartography, under the Territorial Management Instruments framework. The Municipal Master Plan (PDM) has to be revised every 10 years, as well as the topographic and thematic maps that describe the municipal territory. However, this period is inadequate for representing counties where urban pressure is high, and where the changes in the land use are very dynamic. Consequently, emerges the need for a more efficient mapping process, allowing obtaining recent geographic information more often. Several countries, including Portugal, continue to use aerial photography for large-scale mapping. Although this data enables highly accurate maps, its acquisition and visual interpretation are very costly and time consuming. Very-High Resolution (VHR) satellite imagery can be an alternative data source, without replacing the aerial images, for producing large-scale thematic cartography. The focus of the thesis is the demand for updated geographic information in the land planning process. To better understand the value and usefulness of this information, a survey of all Portuguese municipalities was carried out. This step was essential for assessing the relevance and usefulness of the introduction of VHR satellite imagery in the chain of procedures for updating land information. The proposed methodology is based on the use of VHR satellite imagery, and other digital data, in a Geographic Information Systems (GIS) environment. Different algorithms for feature extraction that take into account the variation in texture, color and shape of objects in the image, were tested. The trials aimed for automatic extraction of features of municipal interest, based on aerial and satellite high-resolution (orthophotos, QuickBird and IKONOS imagery) as well as elevation data (altimetric information and LiDAR data). To evaluate the potential of geographic information extracted from VHR images, two areas of application were identified: mapping and analytical purposes. Four case studies that reflect different uses of geographic data at the municipal level, with different accuracy requirements, were considered. The first case study presents a methodology for periodic updating of large-scale maps based on orthophotos, in the area of Alta de Lisboa. This is a situation where the positional and geometric accuracy of the extracted information are more demanding, since technical mapping standards must be complied. In the second case study, an alarm system that indicates the location of potential changes in building areas, using a QuickBird image and LiDAR data, was developed for the area of Bairro da Madre de Deus. The goal of the system is to assist the updating of large scale mapping, providing a layer that can be used by the municipal technicians as the basis for manual editing. In the third case study, the analysis of the most suitable roof-tops for installing solar systems, using LiDAR data, was performed in the area of Avenidas Novas. A set of urban environment indicators obtained from VHR imagery is presented. The concept is demonstrated for the entire city of Lisbon, through IKONOS imagery processing. In this analytical application, the positional quality issue of extraction is less relevant.GEOSAT – Methodologies to extract large scale GEOgraphical information from very high resolution SATellite images (PTDC/GEO/64826/2006), e-GEO – Centro de Estudos de Geografia e Planeamento Regional, da Faculdade de Ciências Sociais e Humanas, no quadro do Grupo de Investigação Modelação Geográfica, Cidades e Ordenamento do Territóri

Utilizing the Landsat spectral-temporal domain for improved mapping and monitoring of ecosystem state and dynamics

Just as the carbon dioxide observations that form the Keeling curve revolutionized the study of the global carbon cycle, free and open access to all available Landsat imagery is fundamentally changing how the Landsat record is being used to study ecosystems and ecological dynamics. This dissertation advances the use of Landsat time series for visualization, classification, and detection of changes in terrestrial ecological processes. More specifically, it includes new examples of how complex ecological patterns manifest in time series of Landsat observations, as well as novel approaches for detecting and quantifying these patterns. Exploration of the complexity of spectral-temporal patterns in the Landsat record reveals both seasonal variability and longer-term trajectories difficult to characterize using conventional bi-temporal or even annual observations. These examples provide empirical evidence of hypothetical ecosystem response functions proposed by Kennedy et al. (2014). Quantifying observed seasonal and phenological differences in the spectral reflectance of Massachusetts’ forest communities by combining existing harmonic curve fitting and phenology detection algorithms produces stable feature sets that consistently out-performed more traditional approaches for detailed forest type classification. This study addresses the current lack of species-level forest data at Landsat resolutions, demonstrating the advantages of spectral-temporal features as classification inputs. Development of a targeted change detection method using transformations of time series data improves spatial and temporal information on the occurrence of flood events in landscapes actively modified by recovering North American beaver (Castor canadensis) populations. These results indicate the utility of the Landsat record for the study of species-habitat relationships, even in complex wetland environments. Overall, this dissertation confirms the value of the Landsat archive as a continuous record of terrestrial ecosystem state and dynamics. Given the global coverage of remote sensing datasets, the time series visualization and analysis approaches presented here can be extended to other areas. These approaches will also be improved by more frequent collection of moderate resolution imagery, as planned by the Landsat and Sentinel-2 programs. In the modern era of global environmental change, use of the Landsat spectral-temporal domain presents new and exciting opportunities for the long-term large-scale study of ecosystem extent, composition, condition, and change

Impact of land use change on urban surface temperature and urban green space planning; case study of the island of Bali, Indonesia

Land use and surface temperature were monitored from 1995 to 2013 to examine green space development in Bali using Landsat and ASTER imageries. Urban areas were formed by conversion of vegetation and paddy fields. Heat islands with surface temperature of over 29 ºC were found and influenced by urban area types. High priority, low priority and not a priority zones for green space were resulted by weighted overlay of LST, NDVI and urban area types