Analysis of land use/land cover spatio-temporal metrics and population dynamics for urban growth characterization

[EN] Promoting sustainable urbanization and limiting land consumption is a local and regional priority policy target in Europe. Monitoring and quantifying urban growth supports decision-making processes for the prevention of ecological and socio-economic consequences. In this work, we present a methodology based on spatio-temporal metrics and a new index (PUGI), that quantifies the inequality of growth between population and urban areas, to analyze and compare urban growth patterns at different levels. We computed an exhaustive set of spatio-temporal metrics at local level in a testing sample of six urban areas from the Urban Atlas database, then un-correlated metrics were selected and the data were interpreted at various levels. Results allow for a differentiation of growing patterns, discriminating between compact and sprawl trends. The index proposed complements the analysis by including demographic dynamics, being also useful for assessing the growing imbalance between the progression on residential areas and the population change at local level. The analysis at various levels contributes to a better understanding of urban growth patterns and its relation to sustainable policies not only within urban areas, but also for the comparison across Europe.This research has been funded by the Spanish Ministerio de Economia y Competitividad and FEDER, in the framework of the project CGL2016-80705-R and the Fondo de Garantia Juvenil contract PEJ-2014-A-45358.Sapena Moll, M.; Ruiz Fernández, LÁ. (2019). Analysis of land use/land cover spatio-temporal metrics and population dynamics for urban growth characterization. Computers Environment and Urban Systems. 73:27-39. https://doi.org/10.1016/j.compenvurbsys.2018.08.001S27397

Analyzing links between spatio-temporal metrics of built-up areas and socio-economic indicators on a semi-global scale

[EN] Manifold socio-economic processes shape the built and natural elements in urban areas. They thus influence both the living environment of urban dwellers and sustainability in many dimensions. Monitoring the development of the urban fabric and its relationships with socio-economic and environmental processes will help to elucidate their linkages and, thus, aid in the development of new strategies for more sustainable development. In this study, we identified empirical and significant relationships between income, inequality, GDP, air pollution and employment indicators and their change over time with the spatial organization of the built and natural elements in functional urban areas. We were able to demonstrate this in 32 countries using spatio-temporal metrics, using geoinformation from databases available worldwide. We employed random forest regression, and we were able to explain 32% to 68% of the variability of socio-economic variables. This confirms that spatial patterns and their change are linked to socio-economic indicators. We also identified the spatio-temporal metrics that were more relevant in the models: we found that urban compactness, concentration degree, the dispersion index, the densification of built-up growth, accessibility and land-use/land-cover density and change could be used as proxies for some socio-economic indicators. This study is a first and fundamental step for the identification of such relationships at a global scale. The proposed methodology is highly versatile, the inclusion of new datasets is straightforward, and the increasing availability of multi-temporal geospatial and socio-economic databases is expected to empirically boost the study of these relationships from a multi-temporal perspective in the near future.Sapena Moll, M.; Ruiz Fernández, LÁ.; Taubenböck, H. (2020). 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Spatio-temporal dynamics along the terrain gradient of diverse landscape

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth’s terrestrial surface according to its use and provides the intricate information for effective planning and management activities.  LULC changes are stated as local and location specifc, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the signifcant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identifed and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensifcation, deforestation, pasture expansion, and urbanization as the causal factors for LULC change

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

Defining the Peri-Urban: A Multidimensional Characterization of Spatio-Temporal Land Use along an Urban−Rural Gradient in Dar es Salaam, Tanzania

Highly dynamic peri-urban areas, particularly in the Global South, face many challenges including a lack of infrastructure, ownership conflicts, land degradation, and sustainable food production. This study aims to assess spatial land use characteristics and processes in peri-urban areas using the case of Dar es Salaam, Tanzania. A mixed-method approach was applied, consisting of expert interviews and spatial data analysis, on a local scale along an urban–rural gradient. Expert interviews were conducted during a field study and analyzed regarding the characteristics and processes of peri-urban land development. A GIS-based analysis of land use patterns was applied using satellite imagery and Open Street Map data to identify a number of variables, such as building density and proximity to environmental features. Results show specific patterns of land use indicators, which can be decreasing (e.g., house density), increasing (e.g., tree coverage), static (e.g., house size), or randomly distributed (e.g., distance to river), along a peri-urban gradient. Key findings identify lack of service structures and access to public transport as major challenges for the population of peri-urban areas. The combination of qualitative expert interviews and metrics-based quantitative spatial pattern analysis contributes to improved understanding of the patterns and processes in peri-urban land use changes.Peer Reviewe

PEMODELAN POLA DISPERSI SPASIAL PERTUMBUHAN KAWASAN METROPOLITAN SEMARANG

Dinamika Kawasan Metropolitan Semarang (KMS) yang merupakan salah satu Kawasan Metropolitan terbesar di Indonesia semakin sulit terkendali dan sangat erat kaitannya dengan fenomena urban sprawl. Perlu adanya pemantauan secara berkala secara cepat dan akurat sebagai upaya dalam menjaga kesesuaian arah perkembangan kota terhadap perencanaan tata ruang KMS. Tujuan dari penelitian ini adalah untuk melakukan pemodelan pola dispersi spasial pembangunan KMS tahun 2010-2020 melalui penggunaan Algoritma SVM. Penelitian ini menggunakan metode kuantitatif eksperimental dengan bantuan software QGIS 3.10 untuk melakukan deteksi perubahan tutupan lahan serta dengan bantuan software Terrset untuk melakukan analisis pola dispersi spasial KMS

Un panorama de la télédétection de l'étalement urbain

The objective of this review paper is to provide an overview of remote sensing based research tackling urban sprawl issue. 113 articles were indexed and analyzed after research on bibliographical databases. These 113 articles are presented in the form of summary table giving highlights of the listed publications. Articles are divided into 6 categories (F, A, B, C, D, E) according to whether they are articles of methodology, characterization, prospective modeling-simulation, retrospective modeling-simulation, analysis of impacts or monitoring of urban sprawl. The summary table is conceived as a tool which can help researchers interested by the measurement and the analysis of urban sprawl.Cette note rend compte d'une recherche bibliographique dont l'objectif est de fournir un panorama des recherches utilisant la télédétection pour aborder la problématique de l'étalement urbain. 113 articles ont été répertoriés et analysés à la suite de recherches dans des bases de données bibliographiques. Ces 113 articles sont présentés sous forme de tableau récapitulatif donnant un aperçu général des publications recensées. Les articles sont répartis en 6 catégories (F, A, B, C, D, E) suivant qu'il s'agit d'articles de méthodologie, de caractérisation, de modélisation-simulation prospective, de modélisation-simulation rétrospective, d'analyse d'impacts ou de monitorage de l'étalement urbain. Le panorama est conçu comme un outil d'aide aux chercheurs qui s'intéressent à la mesure et à l'analyse de l'étalement urbain

Spatio-temporal analysis of the urban–rural gradient structure: an application in a Mediterranean mountainous landscape (Serra San Bruno, Italy)

Abstract. The most recent and significant transformations of European landscapes have occurred as a consequence of a series of diffused, varied and often connected phenomena: urban growth and sprawl, agricultural intensification in the most suitable areas and agricultural abandonment in marginal areas. These phenomena can affect dramatically ecosystems' structure and functioning, since certain modifications cause landscape fragmentation while others tend to increase homogeneity. Thus, a thorough comprehension of the evolution trends of landscapes, in particular those linked to urban-rural relations, is crucial for a sustainable landscape planning. In this framework, the main objectives of the present paper are: (a) to investigate Land Use/Land Cover (LULC) transformations and dynamics that occurred over the period 1955–2006 in the municipality of Serra San Bruno (Calabria, Italy), an area particularly representative of the Mediterranean mountainous landscape; (b) to compare the settlement growth with the urban planning tools in charge in the study area; (c) to examine the relationship between urban–rural gradient, landscape metrics, demographic and physical variables; (d) to investigate the evolution of urban–rural gradient composition and configuration along significant axes of landscape changes. Data with a high level of detail (minimum mapping unit 0.2 ha) were obtained through the digitisation of historical aerial photographs and digital orthophotos identifying LULC classes according to the Corine Land Cover legend. The investigated period was divided into four significant time intervals, which were specifically analysed to detect LULC changes. Differently from previous studies, in the present research the spatio-temporal analysis of urban–rural gradient was performed through three subsequent steps: (1) kernel density analysis of settlements; (2) analysis of landscape structure by means of metrics calculated using a moving window method; (3) analysis of composition and configuration of the urban–rural gradient within three landscape profiles located along significant axes of LULC change. The use of thematic overlays and transition matrices enabled a precise identification of the LULC changes that had taken place over the examined period. As a result, a detailed description and mapping of the landscape dynamics were obtained. Furthermore, landscape profiling technique, using continuous data, allowed an innovative and valuable approach for analysing and interpreting urban–rural gradient structure over space and time

Analyzing spatial patterns and dynamics of landscapes and ecosystem services – Exploring fine-scale data and indicators

In den vergangenen Jahrzehnten hat der Einfluss des Menschen auf Ökosysteme stark zugenommen. Tendenzen der Landnutzungsänderung, darunter die Ausdehnung von Städten und die Intensivierung der Landwirtschaft als Folge des Bevölkerungsanstiegs und damit des Nahrungsmittel- und Energiebedarfs, führen zu Umweltproblemen wie dem Verlust von Lebensraum und biologischer Vielfalt. Die zunehmende Verfügbarkeit von Daten mit feiner räumlicher Auflösung kann die Analyse von Merkmalen und Prozessen in Landschaften mit Hilfe von räumlichen Metriken unterstützen. Das Ziel dieser Arbeit ist es, feinskalige Daten und räumliche Metriken zu integrieren, um Indikatoren zur Messung und Bewertung von Landnutzung, Ökosystemdienstleistungen und deren räumlichen Mustern zu entwickeln und folgende Fragen zu beantworten: Wie können Landnutzungsänderungen und Ökosystemleistungen einer Landschaft beschrieben und analysiert werden? Und, wie kann die Landschaftsperspektive zu unserem Verständnis von Landsystemen beitragen? In zwei verschiedenen Weltregionen werden Landschaften mit Hilfe von Hexagonen als räumliche Einheiten untersucht. Diese dienen zur Analyse von räumlichen Mustern und Beziehungen zwischen verschiedenen Indikatoren (z. B. Ökosystemdienstleistungen) und die Konzeptualisierung von Prozessen auf Landschaftsebene. Obwohl sich einige Phänomene auf feinen räumlichen Skalen manifestieren, ist es für die Operationalisierung und Überwachung dieser Prozesse notwendig, ‚herauszuzoomen‘. Der Landschaftsansatz im Zusammenhang mit Ökosystemleistungen bietet wichtige Perspektiven im Hinblick auf Umweltauswirkungen, die durch Landnutzungsänderungen verursacht werden. Dabei können Indikatoren, die die ökologische, ökonomische und soziale Dimension verknüpfen, dazu beitragen, regionalspezifisches Wissen über Landschaftsdynamiken zu erlangen und dieses Wissen an Entscheidungsträger weiterzugeben, um gezielte Maßnahmen für ein nachhaltiges Landmanagement zu entwickeln.Over the last decades, anthropogenic pressures on ecosystems have been increasing. Trends of land use change including urban expansion and agricultural intensification driven by population increase, and hence food and energy demand, cause environmental challenges including habitat and biodiversity loss. Analyzing major trends of land use change requires additional metrics to capture local processes on a landscape spatial scale. Increasing fine-scale data availability can support analyses of characteristics and processes of landscapes with the help of spatial metrics, e.g. distance or density measures. The aims of this thesis are to incorporate fine-scale data and spatial metrics to develop indicators to measure and assess land-use, ecosystem services (ESS) and their spatial patterns to answer the following questions: How can land use change and ecosystem services of landscapes be described and analyzed? And how can the landscape perspective contribute to our understanding of land systems? The thesis includes three case studies in two different world regions: 1) characteristics of land use within a peri-urban gradient in Dar es Salaam, Tanzania, 2) characteristics of agricultural landscapes in Brandenburg, Germany, and 3) ecosystem service relationships at different spatial units and scales. In both regions, landscapes are investigated with hexagons as spatial units for the analysis of spatial patterns and relationships among different indicators (i.e., ESS) and conceptualize processes on a landscape level. The landscape approach in context with ecosystem services offers important perspectives regarding environmental impacts caused by land use change. Thereby, metrics integrating the ecological, economic, and social dimensions can support obtaining region-specific knowledge on landscape dynamics and transferring this knowledge to decision-makers to design targeted measures towards sustainable land management