Using GHSL to Analyze Urbanization and Land-Use Efficiency in the Philippines from 1975-2020: Trends and Implications for Sustainable Development

This study analyzed the trends and patterns of urbanization and changes in land-use efficiency in the Philippines from 1975-2020 using the Global Human Settlement Layers (GHSL). Utilizing the GHS-BUILT-S, GHS POP, and GHS-SMOD raster datasets from the GHSL Data Package 2023, we examined the spatiotemporal expansion of built-up areas and the growth of population in urban and rural regions of the country. Using the same datasets, we also measured the country's achievement of Sustainable Development Goal (SDG)11.3, particularly on inclusive and sustainable urbanization through efficient land utilization, by computing the ratio of land consumption rate (LCR) to the population growth rate (PGR), also known as LCRPGR. The results of our analysis revealed an increasing trend in the overall built-up area and population of the Philippines within the examined period. Built-up areas and population in urban regions more than tripled in size from 1975 to 2020, demonstrating a notable shift towards more urbanized regions over time. In addition to presenting evidence of the Philippines' developmental progress and urbanization, our analysis of GHSL data shows a decline in land consumption, a deceleration in population growth, and an overall enhancement in land-use efficiency within the country. These findings suggest a shift towards more controlled and sustainable land development practices, supporting the country's goal of sustainable urbanization and land management. The implications of these findings are crucial for policymakers and urban planners in the Philippines, offering valuable insights to guide the formulation of effective and comprehensive land management strategies. Further work includes conducting localized analyses at the city or municipality level to provide valuable insights into the unique urbanization patterns and land-use dynamics across different islands and regions, enabling tailored policy interventions and spatial planning strategies to promote sustainable development

Integration of geospatial information in sustainable development indicators

Internship report presented as partial requirement for obtaining the Master’s degree in Geographical Information Systems and ScienceThis report aims to introduce, discuss, detail and describe the internship I have accomplished at Directorate-General for Territory (DGT), the Portuguese national mapping and cadastre agency. As a geographic information systems intern, the nature of my work was focused into the United Nations Sustainable Development Goals (SDG) indicators with a geospatial component. My main duty was to hold the functionality of aspects regarding SDG matters that could emerge to DGT in an operational perspective. I have researched about the indicators metadata and the benefits that the integration of geospatial information delivers to measure and monitor the progress towards sustainable development. In a practical working context, two SDG indicators in articulation with Statistics Portugal were produced and calculated: 11.3.1 – ratio of land consumption rate to population growth rate; 15.4.2 – mountain green cover index. The principal outcomes of this internship were appealing for my academic path: the production of a manuscript entitled “Ratio of Land Consumption Rate to Population Growth Rate—Analysis of Different Formulations Applied to Mainland Portugal” published at ISPRS International Journal of Geo-Information, and, a presentation delivered in the first United Nations World Geospatial Information Congress held in China. Therefore, I have considerably improved my GIS capabilities, learning and applying geospatial methodologies such as the dasymetric mapping technique. Additionally, as part of the internship workflow, I followed and collaborated with UN-GGIM: Europe Work Group on Data Integration subgroup 2 activities.O presente relatório tem como objetivo central introduzir, discutir, detalhar, e descrever o período de estágio realizado na Direção-Geral do Território (DGT). Como estagiário de sistemas de informação geográfica (SIG), a natureza do meu trabalho focou-se nos Objetivos de Desenvolvimento Sustentável (ODS) das Nações Unidas. A minha principal responsabilidade foi exatamente garantir o funcionamento da pasta ODS de acordo com as tarefas e trabalhos operacionais em que a DGT ter-se-ia de envolver e desenvolver. Assim, investiguei sobre os metadados dos indicadores ODS e tudo aquilo que eles representam para sua correta aplicação. Do mesmo modo, investiguei sobre a necessidade e os benefícios provenientes da integração de informação geográfica nesses mesmos indicadores, com o intuito de medir e monitorizar o progresso rumo a um desenvolvimento desejavelmente sustentável. Numa perspetiva de operacionalização, dois indicadores ODS foram calculados e produzidos numa articulação com o Instituto Nacional de Estatística: 11.3.1 – Rácio entre a taxa de consumo do solo e a taxa de crescimento da população; 15.4.2 – Coberto vegetal nas regiões de montanha. Os resultados deste estágio foram proveitosos tendo em conta o meu percurso académico: a produção do artigo “Ratio of Land Consumption Rate to Population Growth Rate—Analysis of Different Formulations Applied to Mainland Portugal” recentemente publicado na revista ISPRS International Journal of Geo-Information assim como uma apresentação dos resultados do trabalho de estágio no congresso das Nações Unidas, United Nations World Geospatial Information Congress, decorrido na China. Concluindo, melhorei substancialmente as minhas capacidades em SIG com a aprendizagem levada a cabo na DGT, e com aplicação de metodologias como a técnica do mapeamento dasimétrico. Ainda no âmbito do meu estágio, acompanhei e colaborei com o grupo de trabalho UN-GGIM: Europe Work Group on Data Integration subgroup 2 activities

Ratio of land consumption rate to population growth rate - analysis of different formulations applied to mainland Portugal

ArticleThis paper presents a methodological approach for the assessment of the indicator 11.3.1: “Ratio of Land Consumption Rate to Population Growth Rate” proposed by the United Nations (UN), discussing the definitions and assumptions that support the indicator quantification, and analysing the results provided by different formulations applied to mainland Portugal, at the municipality level. Due to specific limitations related to the actual formula proposed by the UN (LCRPGR) for the computation of the indicator, an alternative formulation derived from Land Use Efficiency (LUE) was explored. Considering that the land to which the indicator refers may be described by specific classes represented in Land Cover Land Use (LCLU) maps, in the estimation of the land consumption rate we tested two LCLU datasets: Corine Land Cover and COS—the Portuguese LCLU reference map. For the estimation of the population growth rate, prior allocation of inhabitants to the areas where people are most likely to reside was deemed necessary, using a dasymetric mapping technique based on LCLU information. The results obtained for 2007–2011 and 2011–2015 showed, in most municipalities, an increase in the urban area and a decrease in urban population, leading to negative values both in LCRPGR and LUE in most of the territory. Clearly, LUE performed better than LCRPGR in what urban development monitoring and urban area dynamics trends are concerned. Furthermore, LUE was much easier to interpretinfo:eu-repo/semantics/publishedVersio

USING GHSL TO ANALYZE URBANIZATION AND LAND-USE EFFICIENCY IN THE PHILIPPINES FROM 1975–2020: TRENDS AND IMPLICATIONS FOR SUSTAINABLE DEVELOPMENT

This study analyzed the trends and patterns of urbanization and changes in land-use efficiency in the Philippines from 1975–2020 using the Global Human Settlement Layers (GHSL). Utilizing the GHS-BUILT-S, GHS POP, and GHS-SMOD raster datasets from the GHSL Data Package 2023, we examined the spatiotemporal expansion of built-up areas and the growth of population in urban and rural regions of the country. Using the same datasets, we also measured the country's achievement of Sustainable Development Goal (SDG)11.3, particularly on inclusive and sustainable urbanization through efficient land utilization, by computing the ratio of land consumption rate (LCR) to the population growth rate (PGR), also known as LCRPGR. The results of our analysis revealed an increasing trend in the overall built-up area and population of the Philippines within the examined period. Built-up areas and population in urban regions more than tripled in size from 1975 to 2020, demonstrating a notable shift towards more urbanized regions over time. In addition to presenting evidence of the Philippines' developmental progress and urbanization, our analysis of GHSL data shows a decline in land consumption, a deceleration in population growth, and an overall enhancement in land-use efficiency within the country. These findings suggest a shift towards more controlled and sustainable land development practices, supporting the country's goal of sustainable urbanization and land management. The implications of these findings are crucial for policymakers and urban planners in the Philippines, offering valuable insights to guide the formulation of effective and comprehensive land management strategies. Further work includes conducting localized analyses at the city or municipality level to provide valuable insights into the unique urbanization patterns and land-use dynamics across different islands and regions, enabling tailored policy interventions and spatial planning strategies to promote sustainable development

Atlas of the Human Planet 2019

The Atlas of the Human Planet 2019 presents key human settlements and urbanisation statistics for 239 countries based on the progress made towards the development of a people-based global harmonised definition of cities and rural areas. Figures and statistics presented in the Atlas 2019 are the result of massive automatic big data processing carried out at the European Commission Directorate General Joint Research Centre in the framework of the Global Human Settlement Layer (GHSL) combining satellite imagery and census information to map settlements, understand their characteristics, and report about their changes over 40 years’ time (1975 – 2015). The Atlas explains the fundamentals of the GHSL, and the service it provides to upscale to the globe the Degree of Urbanisation method (currently adopted as European Union Regulation). Based on the global application of the method the Atlas presents a global urbanisation brief, a commented series of highlights on global human settlement development trajectories, supported by 239 urbanisation briefs, which form the knowledge base for the next generation of urban and territorial policy, development and cooperation action, and global reporting on progress made towards meeting the Sustainable Development Goals and the 2030 Development Agenda as a whole.JRC.E.1-Disaster Risk Managemen

Urbanization and urban land use efficiency: Evidence from regional and Addis Ababa satellite cities, Ethiopia

Ethiopia has experienced rapid urbanization over the past three decades. Several cities expanded rapidly and many satellite towns sprung up around the major cities. The high rate of urbanization and urban growth resulted in high demand for urban land, mainly for industrial, commercial, and residential purposes. In order to meet the demand, an enormous amount of land has been made available for urban use, mainly through land conversion. However, we know very little about how efficiently cities use urban land. This paper investigated the urban land use efficiency (ULUE) of sixteen cities in Ethiopia. Remote sensing data (Landsat 7/8) was analysed with ArcGIS to assess spatiotemporal land use changes between 2007 and 2019. Built-up environment footprints were computed from Google Earth imagery. The ratio of land consumption to population growth rate, and the rate of urban infill were assessed. The findings revealed a prevalence of urban land use inefficiencies in all cities. In most cities, the rate of land consumption far exceeds the population growth rate. Densification (urban infill) is low and slow. A considerable part of the converted agricultural land sits idle within the built-up area for many years. Low ULUE is what fuels urban sprawl, fragmentation and informal settlements. This study emphasised the need to implement urban policies and practices aimed at improving ULUE. Improving ULUE is imperative to achieve the Sustainable Development Goals; ensuring sustainable urban land use; addressing land prices and housing shortages; protecting farmland and ecosystems; tackling land hoarding, urban sprawl and informal settlement

Description of the GHS Urban Centre Database 2015

The Global Human Settlement Layer Urban Centres Database (GHS-UCDB) is the most complete database on cities to date, publicly released as an open and free dataset - GHS STAT UCDB2015MT GLOBE R2019A V1.0. The database represents the global status on Urban Centres in 2015 by offering cities location, their extent (surface, shape), and describing each city with a set of geographical, socio-economic and environmental attributes, many of them going back 25 or even 40 years in time. Urban Centres are defined in a consistent way across geographical locations and over time, applying the “Global Definition of Cities and Settlements” developed by the European Union to the Global Human Settlement Layer Built-up (GHS-BUILT) areas and Population (GHS-POP) grids. This report contains the description of the dimensions and the derived attributes that characterise the Urban Centres in the database. The document includes notes about methodology and sources. The GHS-UCDB contains information for more than 10,000 Urban Centres and it is the baseline data of the analytical results presented in the Atlas of the Human Planet 2018.JRC.E.1-Disaster Risk Managemen

Atlas of the Human Planet 2018

The Atlas of the Human Planet 2018 describes the Urban Centre Database, which was produced in the framework of the Global Human Settlement Layer (GHSL) project by applying a global definition of cities and settlements to the GHSL data. The Atlas presents the key findings of the analysis of geographic, environmental and socio-economic variables that were gathered from free and open sources for each urban centre in the world.JRC.E.1-Disaster Risk Managemen