Identifying urban growth patterns through land-use/land-cover spatio-temporal metrics: Simulation and analysis

[EN] The spatial pattern of urban growth determines how the physical, socio-economic and environmental characteristics of urban areas change over time. Monitoring urban areas for early identification of spatial patterns facilitates assuring their sustainable growth. In this paper, we assess the use of spatio-temporal metrics from land-use/land-cover (LULC) maps to identify growth patterns. We applied LULC change models to simulate different scenarios of urban growth spatial patterns (i.e., expansion, compact, dispersed, road-based and leapfrog) on various baseline urban forms (i.e., monocentric, polycentric, sprawl and linear). Then, we computed the spatio-temporal metrics for the simulated scenarios, selected the most informative metrics by applying discriminant analysis and classified the growth patterns using clustering methods. Two metrics, Weighted mean expansion and Weighted Euclidean distance, which account for the densification, compactness and concentration of urban growth, were the most efficient for classifying the five growth patterns, despite the influence of the baseline urban form. These metrics have the potential to identify growth patterns for monitoring and evaluating the management of developing urban areas.This work was supported by the the Spanish Ministerio de Economia y Competitividad and FEDER [CGL2016-80705-R].Sapena Moll, M.; Ruiz Fernández, LÁ. (2021). Identifying urban growth patterns through land-use/land-cover spatio-temporal metrics: Simulation and analysis. International Journal of Geographical Information Science. 35(2):375-396. https://doi.org/10.1080/13658816.2020.181746337539635

Linnade laienemine Eestis: seire, analüüs ja modelleerimine

Väitekirja elektrooniline versioon ei sisalda publikatsiooneLinnade laienemine, mida iseloomustab vähese tihedusega, ruumiliselt ebaühtlane ja hajutatud areng linna piiridest välja. Kuna linnade laienemine muudab põllumajandus- ja metsamaid ning väikesed muutused linnapiirkondades võivad pikaajaliselt mõjutada elurikkust ja maastikku, on hädavajalik seirata linnade ruumilist laienemist ning modelleerida tulevikku, saamaks ülevaadet suundumustest ja tagajärgedest pikemas perspektiivis. Eestis võeti pärast taasiseseisvumist 1991. aastal vastu maareformi seadus ning algas “maa” üleandmine riigilt eraomandisse. Sellest ajast peale on Eestis toimunud elamupiirkondade detsentraliseerimine, mis on mõjutanud Tallinna ümbruse põllumajandus- ja tööstuspiirkondade muutumist, inimeste elustiili muutusi ning jõukate inimeste elama asumist ühepereelamutesse Tallinna, Tartu ja Pärnu lähiümbruse. Selle aja jooksul on Eesti rahvaarv vähenenud 15,31%. Käesoleva doktoritöö eesmärgiks on "jälgida, analüüsida ja modelleerida Eesti linnade laienemist viimase 30 aasta jooksul ning modelleerida selle tulevikku", kasutades paljusid modelleerimismeetodeid, sealhulgas logistilist regressiooni, mitmekihilisi pertseptronnärvivõrke, rakkautomaate, Markovi ahelate analüüsi, mitme kriteeriumi. hindamist ja analüütilise hierarhia protsesse. Töö põhineb neljal originaalartiklil, milles uuriti linnade laienemist Eestis. Tegu on esimese põhjaliku uuringuga Eesti linnade laienemise modelleerimisel, kasutades erinevaid kaugseireandmeid, mõjutegureid, parameetreid ning modelleerimismeetodeid. Kokkuvõtteks võib öelda, et uusehitiste hajumismustrid laienevad jätkuvalt suuremate linnade ja olemasolevate elamupiirkondade läheduses ning põhimaanteede ümber.Urban expansion is characterized by the low–density, spatially discontinued, and scattered development of urban-related constructions beyond the city boundaries. Since urban expansion changes the agricultural and forest lands, and slight changes in urban areas can affect biodiversity and landscape on a regional scale in the long-term, spatiotemporal monitoring of urban expansion and modeling of the future are essential to provide insights into the long-term trends and consequences. In Estonia, after the regaining independence in 1991, the Land Reform Act was passed, and the transfer of “land” from the state to private ownership began. Since then, Estonia has experienced the decentralization of residential areas affecting the transformation of agricultural and industrial regions around Tallinn, changes in people's lifestyles, and the settling of wealthy people in single-family houses in the suburbs of Tallinn, Tartu, and Pärnu. During this period, Estonia's population has declined dramatically by 15.31%. Therefore, this dissertation aims to "monitor, analyze and model Estonian urban expansion over the last 30 years and simulate its future" using many modeling approaches including logistic regression, multi-layer perceptron neural networks, cellular automata, Markov chain Analysis, multi-criteria evaluation, and analytic hierarchy process. The thesis comprises four original research articles that studied urban expansion in Estonia. So far, this is the first comprehensive study of modeling Estonian urban expansion utilizing various sets of remotely sensed data, driving forces and predictors, and modeling approaches. The scattering patterns of new constructions are expected to continue as the infilling form, proximate to main cities and existing residential areas and taking advantage of main roads in future.https://www.ester.ee/record=b550782

Comparison of Ecological Risk among Different Urban Patterns Based on System Dynamics Modeling of Urban Development

In this study an urban development model was developed, based on system dynamics, in order to compare four urban layout patterns in terms of their effects on landscape ecology risk and environmental pollution. The four patterns are centralized urban model, green corridor urban model, decentralized urban model (satellite city model), and resource-based city model. Landscape ecology risk assessments based on simulation results show that the decentralized urban model is superior to the centralized urban model in terms of long-term landscape ecological development and environmental protection. The study also analyzed the relationships between the patch spacing index and the evaluation index

Geospatial approach using socio-economic and projected climate change information formodelling urban growth

Urban growth and climate change are two interwoven phenomena that are becoming global environmental issues. Using Niger Delta of Nigeria as a case study, this research investigated the historical and future patterns of urban growth using geospatialbased modelling approach. Specific objectives were to: (i) examine the climate change pattern and predict its impact on urban growth modelling; (ii) investigate the historical pattern of urban growth; (iii) embrace some selected parameters from United Nations Sustainable Development Goals (UN SDGs) and examine their impacts on future urban growth prediction; (iv) verify whether planning has controlled urban land use sprawl in the study area; and (v) propose standard operating procedure for urban sprawl in the area. A MAGICC model, developed by the Inter-Governmental Panel on Climate Change (IPCC), was used to predict future precipitation under RCP 4.5 and RCP 8.5 emission scenarios, which was utilized to evaluate the impact of climate change on the study area from 2016 to 2100. Observed precipitation records from 1972 to 2015 were analysed, and 2012 was selected as a water year, based on depth and frequency of rainfall. A relationship model derived using logistic regression from the observed precipitation and river width from Landsat imageries of 2012 was used to project the monthly river width variations over the projected climate change, considering the two emission scenarios. The areas that are prone to flooding were determined based on the projected precipitation anomalies and a suitability map was developed to accommodate the impact of climate change in the projection of future urban growth. Urban landscape changes between 1985 and 2015 were also analysed, which revealed a rapid urban growth in the region. A Cellular Automata/Markov Chain (CA-Markov) model was used to project the year 2030 land cover of the region considering two scenarios; normal projection without any constraint, and using some designed constraints (forest reserves, population and economy) based on some selected UN SDGs criteria and climate change. On validation, overall simulation accuracies of 89.25% and 91.22% were achieved based on scenarios one and two, respectively. The projection using the first scenario resulted to net loss and gains of - 7.37%, 11.84% and 50.88%, while that of second scenario produced net loss and gains of -4.72%, 7.43% and 48.37% in forest, farmland and built-up area between 2015 and 2030, respectively. The difference between the two scenarios showed that the UN SDGs have great influence on the urban growth prediction and strict adherence to the selected UN SDGs criteria can reduce tropical deforestation, and at the same time serve as resilience to climate change in the region

Towards a sustainable urban expansion: a case study of cities in Bangladesh

The economic growth of Bangladesh over the last several decades has subsequently been followed by the rapid expansion of urban areas. Unfortunately, this expansion of the urban footprint has mostly occurred in an unplanned and chaotic manner through the conversion of natural areas to urban landscape due to the lack of regulation and policies guiding the country’s urban planning. This has raised concerns about the sustainability and livability of these cities and urged the need for a robust planning framework targeted at promoting sustainable urban expansion. A well-x and enhancing the quality of life for everyone while minimizing environmental degradation and other potential adverse impacts of a growing number of city dwellers. This dissertation examines the extent of unevenness in urban growth patterns in Bangladesh and explores the application of Urban Growth Boundaries (UGB) as a mechanism to control and direct the growth of built-up urban areas to promote sustainable urban expansion of these cities. The first part of the dissertation examines the unevenness in the urban expansion in Bangladesh by comparing the urban footprint of the cities and municipalities in Bangladesh extracted using Google Earth Engine (GEE) and census population data for these areas. While a greater proportion of the population has been increasingly concentrated in the smaller and mid-sized cities over the last three decades, built-up urban areas, on the other hand, have been mostly clustered in the two largest cities— Dhaka and Chattogram—accounting for nearly 60 percent of the total built-up urban areas. These results shed light on the magnitude of continued spatial inequalities in urban development amongst cities and municipalities in Bangladesh despite there being an overall increase of evenness in the distribution of population over time. The second part of the dissertation explores the application of UGB delineation using Support Vector Machine (SVM) supervised machine learning algorithm as an urban growth restriction mechanism for the city of Chattogram, one of the world's largest port cities and the second-largest metropolitan areas in Bangladesh, as a case study. The application of the Support Vector Machine (SVM) supervised machine learning algorithm is a novel approach to the delineation of UGB and this model was used to simulate future built-up urban areas up to 2040 for Chattogram and to determine the UGB for the city. Although the delineation of the UGB is a crucial step for the adoption and implementation process of UGB for Chattogram, the overall success of the UGB policy is dependent on external factors that directly or indirectly impact the policy. The third part of the dissertation, thus, investigates the key considerations essential for the successful adoption and implementation of UGB for Chattogram. Through a systematic review of literature on UGB and planning policies on Chattogram, along with a web-based survey and unstructured interview with city officials, it examines the stakeholders’ perceptions on current growth patterns, the potential application of UGB as an urban growth containment strategy, and concerns and support regarding the application of UGB. While there has been an overall positive response regarding a potential adoption of UGB for Chattogram, this paper identifies five key concerns that would need to be addressed for the successful adoption and implementation of UGB for the city of Chattogram. These key challenges are namely: policy and regulatory consideration, civic engagement and stakeholder input, bureaucratic consensus and coordination, institutional capacity, and external influences. While distinct, these concerns are highly interrelated and can be expected to have a substantial influence on one another and need to be addressed for the successful adoption of UGB. These key challenges including policy and regulatory consideration, civic engagement and stakeholder input, bureaucratic consensus and coordination, institutional capacity, and external influences. While parts III and IV of this dissertation specifically focuses on the city of Chattogram as a testbed for the application of UGB, a similar methodological approach could potentially be implemented for other cities in Bangladesh with the goal to promote sustainable urban expansion

Urban Growth and Its Impact on Urban Heat Sink and Island Formation in the Desert City of Dubai.

The rapid pace of urban growth in Dubai has attracted the attention of economists, environmentalists and urban planners. This thesis quantifies the extent of urbanisation within the Emirate since the discovery of oil and investigates the impacts of such growth on urban temperatures. The study used remotely-sensed imagery in the absence of publicly available data on city growth and microclimate. The study used a hybrid classification method and landscape metrics to capture historical urban forms, rates and engines of growth in the Emirate. Stepwise multiple regression analysis techniques were subsequently used to investigate the relationship between the rate and form of urbanisation and the intensity of the urban heat sink between 1990 and 2011. Local Climate Zones were then developed to specifically investigate the impacts of urban geometry variables and proximity to water on both urban heat sinks during the day-time and urban heat islands during the night. The study revealed a significant increase in urban area over time (1972-2011) with accelerated phases of growth, linked to local and global economic conditions, occurring during specific periods. Physical urban growth has now outpaced population growth, indicating urban sprawl. This growth has occurred at the expense of sand and has included a significant increase in vegetation and water bodies unlike other desert cities in the Gulf region. The results demonstrated that urban growth has promoted a heat sink effect during daytime and that all urban land use types contributed to this effect. Urban albedo was not responsible for the daytime urban heat sink; other factors including the specific heat capacity of urban materials, urban geometry and proximity to the Gulf were mainly responsible. Furthermore, increases in vegetation cover and impervious surface cover over time have contributed to the daytime (morning) urban heat sink. At night-time, urban geometry and proximity to the Gulf were the major influences upon the formation of urban heat islands. This research contributes to better understanding of urbanisation in desert cities as demonstrated through Dubai, revealing previously unknown spatiotemporal variations in urban areas across the city through the use of a time-series of satellite images. The findings provide new insights into the impacts of land cover, land use, proximity to water and urban geometry on the formation of urban heat sinks and urban heat islands in the desert environment

Advancing large-scale analysis of human settlements and their dynamics

Due to the importance for a range of sustainability challenges, it is important to understand the spatial dynamics of human settlements. The rapid expansion of built-up land is among the most extensive global land changes, even though built-up land occupies only a small fraction of the terrestrial biosphere. Moreover, the different ways in which human settlements are manifested are crucially important for their environmental and socioeconomic impacts. Yet, current analysis of human settlements heavily relies on land cover datasets, which typically have only one class to represent human settlements. Consequently, the analysis of human settlements does often not account for the heterogeneity within urban environment or their subtle changes. This simplistic representation severely limits our understanding of change processes in human settlements, as well as our capacity to assess socioeconomic and environmental impacts. This thesis aims to advance large-scale analysis of human settlements and their dynamics through the lens of land systems, with a specific focus on the role of land-use intensity. Chapter 2 explores the use of human settlement systems as an approach to understanding their variation in space and changes over time. Results show that settlement systems exist along a density gradient, and their change trajectories are typically gradual and incremental. In addition, results indicate that the total increase in built-up land in village landscapes outweighs that of dense urban regions. This chapter suggests that we should characterize human settlements more comprehensively to advance the analysis of human settlements, going beyond the emergence of new built-up land in a few mega-cities only. In Chapter 3, urban land-use intensity is operationalized by the horizontal and vertical spatial patterns of buildings. Particularly, I trained three random forest models to estimate building footprint, height, and volume, respectively, at a 1-km resolution for Europe, the US, and China. The models yield R2 values of 0.90, 0.81, and 0.88 for building footprint, height, and volume, respectively. The correlation between building footprint and building height at a pixel level was 0.66, illustrating the relevance of mapping these properties independently. Chapter 4 builds on the methodological approach presented in chapter 3. Specifically, it presents an improved approach to mapping 3D built-up patterns (i.e., 3D building structure), and applies this to map building footprint, height, and volume at a global scale. The methodological improvement includes an optimized model structure, additional explanatory variables, and updated input data. I find distance decay functions from the centre of the city to its outskirts for all three properties for major cities in all continents. Yet, again, the height, footprint (density), and volume differ drastically across these cities. Chapter 5 uses built-up land per person as an operationalization for urban land-use intensity, in order to investigate its temporal dynamics at a global scale. Results suggest that the decrease of urban land-use intensity relates to 38.3%, 49.6%, and 37.5% of the built-up land expansion in the three periods during 1975-2015, but with large local variations. In the Global South, densification often happens in regions where human settlements are already used intensively, suggesting potential trade-offs with other living standards. These chapters represent the recent advancements in large-scale analysis of human settlements by revealing a large variation in urban fabric. Urban densification is widely acknowledged as one of the tangible solutions to satisfy the increased land demand for human settlement while conserving other land, suggesting the relevance of these findings to inform sustainable development. Nevertheless, local settlement trajectories towards intensive forms should also be guided in a large-scale context with broad considerations, including the quality of life for inhabitants, because these trade-offs and synergies remain largely unexplored in this analysis

産業革命以前の東アジアの都市における都市構造の複雑さに関する研究

The propose of this study intend to make a step forward the understanding of cities with their spatiotemporal dynamics and central-peripheral effects as the organism metabolism for the model-based built environment and socio-economic activities matching. Especially focus the self-organized formation process existed in pre-industrial East Asia cities with their historical form patterns as empirical evidence. And configuring the correlation between human action manifolded land consumption probability and statistical urban patterns quantity of non-fossil energy drives human settlement state. Additionally, the author purposed a simple mechanism to reproduce those cities expansion and growth of its organism evolution from historical order of relatively equilibrium to contemporary disorder of system complexity. The research approach is divided into two stages, namely, the pre-industrial city formation process simulates with East Asian cities model of their intact city boundaries and structure laws; the contemporary urban aggregation delineation with the system complex and boundary discreteness.北九州市立大

Remote Sensing of Earth Resources: A literature survey with indexes (1970 - 1973 supplement). Section 1: Abstracts

Abstracts of reports, articles, and other documents introduced into the NASA scientific and technical information system between March 1970 and December 1973 are presented in the following areas: agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis