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The purpose of this paper is to present a spatial decision support system (SDSS) to be used by the local authorities of a city in the planning and response phase of a disaster. The SDSS focuses on the management of public spaces as a resource to increase a vulnerable population’s accessibility to essential goods and services. Using a web-based platform, the SDSS would support data-driven decisions, especially for cases such as the COVID-19 pandemic which requires special care in quarantine situations (which imply walking access instead of by other means of transport).

This paper proposes a methodology to create a web-SDSS to manage public spaces in the planning and response phase of a disaster to increase the access to essential goods and services. Using a regular polygon grid, a city is partitioned into spatial units that aggregate spatial data from open and proprietary sources. The polygon grid is then used to compute accessibility, vulnerability and population density indicators using spatial analysis. Finally, a facility location problem is formulated and solved to provide decision-makers with an adaptive selection of public spaces given their indicators of choice.

The design and implementation of the methodology resulted in a granular representation of the city of Lima, Peru, in terms of population density, accessibility and vulnerability. Using these indicators, the SDSS was deployed as a web application that allowed decision-makers to explore different solutions to a facility location model within their districts, as well as visualizing the indicators computed for the hexagons that covered the district’s area. By performing tests with different local authorities, improvements were suggested to support a more general set of decisions and the key indicators to use in the SDSS were determined.

This paper, following the literature gap, is the first of its kind that presents an SDSS focused on increasing access to essential goods and services using public spaces and has had a successful response from local authorities with different backgrounds regarding the integration into their decision-making process.

Despite significant progress in schooling, social and spatial inequalities in access to education remain important in Algeria. In the present article, taking into account the geographic dimension makes it possible to identify the links existing between spatial location and disparities in the field of education in Algeria. Also, three types of education indicators (quantity, quality and inequality) are used in the study. The study’s sample includes 48 Algerian provinces, studied between 2008 and 2018.

In this study, the authors used data from the 2008 and 2018 General Census of Population and Housing (GCPH) for 48 provinces. Indeed, the two censuses of 2008 and 2018 (sources of data for this study) were based on questionnaires intended for different categories of the population (households, non-household populations, transit population, etc.). Therefore, the no response rate is assumed to be close to 0. Using spatial econometric techniques.

Results indicate that the indicator used is strong spatial disparity in education in Algeria. The development of a spatial synthetic index (SI) makes it possible to measure more precisely the extent and nature of spatial disparities in the field of education in Algeria. The results also confirm the hypothesis of β-convergence of the performance of the Algerian education system. Consequently, the need for policies to reduce the unfair inequalities between different areas is apparent.

Works that analyze education indicators in a classical perspective (educational performances between different sexes and between rural and urban areas) are abundant (Amaghouss and Ibourk, 2013a). However, very few studies proceed to the analysis of educational variables in a spatial perspective (Catin and Hazem, 2012). To the best of the authors’ knowledge, no work has tried to analyze spatial disparities in the field of education in Algeria.

Uncontrolled and unsustainable urban development has a significant impact on the overall quality of the environment. Contemporary spatial management does not take into account the non-economic conditions of ecosystem functions and their biophysical limits, which results in a deterioration of the environment. Furthermore, urban development continues all over the world, which is associated with a projected population increase, particularly in cities. Therefore, there is need to include analyses in the field of environmental carrying capacity (ECC) for more sustainable spatial management and development. The ECC concept is a tool for sustainable development of human settlements. It could be defined as threshold level of anthropopressure, which the environment is able to balance and withstand without serious degradation and irreversible changes. The use of ECC assessment will help ensure the needs of the city’s residents, which are conditioned by the environment. The paper aims to discuss this issue.

This review study presents an overview of the ECC concept and its potential for use in spatial management at local level, especially for cities. The content analysis introduces definitions of spatial management and others main actions of spatial economy as well as the definitions of ECC. The overview of existing ECC models is a part of presented review.

The paper shows the ECC approach from global to local level on Poland as an example country.

The literature review identified that the idea of ECC could be a useful concept and tool for sustainable spatial development and management. This concept allows for verification of the resources and environmental state of given territory unit. Therefore, the assessment of ECC allows to verify if development of given area, for instance country, region or even city, is conducted within the framework of sustainable principles. Despite this, the assessment of ECC is not taken into account when future spatial management is defined. Thus, this circumstance could be a reason for this research area development.

This study uses computer-aided design to improve the ecological and environmental sustainability of early-stage landscape designs. Urban expansion on open land and natural habitats has led to a decline in biodiversity and increased climate change impacts, affecting urban inhabitants' quality of life and well-being. While sustainability indicators have been employed to assess the performance of buildings and neighbourhoods, landscape designs' ecological and environmental sustainability has received comparatively less attention, particularly in early-design stages where applying sustainability approaches is impactful.

The authors propose a computation framework for evaluating key landscape sustainability indicators and providing real-time feedback to designers. The method integrates spatial indicators with widely recognized sustainability rating system credits. A specialized tool was developed for measuring biomass optimization, precipitation management and urban heat mitigation, and a proof-of-concept experiment tested the tool's effectiveness on three Mediterranean neighbourhood-level designs.

The results show a clear connection between the applied design strategy to the indicator behaviour. This connection enhances the ability to establish sustainability benchmarks for different types of landscape developments using parametric design.

The study allows non-expert designers to measure and embed landscape sustainability early in the design stages, thus lowering the entry level for incorporating biodiversity enhancement and climate mitigation approaches.

This study expands the parametric vocabulary for measuring landscape sustainability by introducing spatial ecosystem services and architectural sustainability indicators on a unified platform, enabling the integration of critical climate and biodiversity-loss solutions earlier in the development process.

This research aims to develop sustainable development scores at districts level based on weights of thirteen sub-indicators using a spatial information system.

The empirical study was conducted at seven districts in the state of Terengganu Malaysia. The evaluation was implemented using a spatial information system combined with weights of sub-indicators that were computed from the analytic hierarchy process (AHP) method.

In this study the sub-indicators layers overlaid into one raster layer to produce a sustainability development score from 1 to 3 for every district. The one raster layer shows that Marang district received the highest sustainable development score of 2.284. On the other hand, Kemaman district received the poorest sustainable development score of 1.686.

In this study the weights that obtained from the AHP method are verified and validated using a sensitivity analysis. The scores at districts level perhaps may not be accurate due to difficulties in differentiating the variability of indicators and sub-indicators. These are among the unsettled issues that could be explored as future research direction.

The results would have greatly benefited the policy makers and stakeholders, particularly in planning for future development without compromising the significance of environment, social and economic indicators.

Sustainable development is one of the key elements that needs to be considered seriously in assessing development of a country. The assessment may include proposing indices for environment, social, economic indicators and related sub-indicators of sustainable development. Instead of considering specific indices for indicators, this approach departs more formally from the concept of unweighted indices at country level.

This paper aims to contribute to the approaches based on traditional industry concentration statistics for identifying clusters by complementing them with the techniques of exploratory spatial data analysis (ESDA).

Using a sample with 34,500 observations retrieved from the social information annual report released by Brazil Ministry of Labor and Employment, the methodology was designed to make a comparison between the application of industry concentration statistics and ESDA statistics.

As the results show, the geographic distribution measures proved to be fundamental for longitudinal studies on regional dynamics and industrial agglomerations, and the local indicator of spatial association statistic tends to overcome the limitation of the industry concentration approach.

In the period considered, due to economic, structural and circumstantial questions, activities linked to the transformation industry have been losing ground in the value creation process in Brazil. In this sense, the study of other industries may generate other types of insights that should be considered in the process of regional development.

This paper offers a critical analysis of empirical approaches and methodological advances with an emphasis on the treatment of special effects: spatial dependence, spatial heterogeneity and spatial scale. However, the regional dynamic presents a temporal dimension and a spatial dimension. The role of space has increasingly attracted attention in the analysis of economic changes. This work has identified opportunities for incorporating spatial effects in regional analysis over time.

This study assesses the Laguna District's spatial qualities in Gazimagusa. Gazimagusa is a coastal settlement that possesses long golden beaches. However, almost all sea fronts are closed to the public. There is both a physical and a visual barrier along the sea-shore. The Laguna District is the only area in the city, where the sea-shore is open to the public. Therefore, this district is an important area. In this study, three indicators and eleven determinants are used to assess the spatial qualities of the Laguna District. The indicators are natural and physical aspects as well as existing functions and activities in the district. In this research, the determinants are used in question form for assessing the spatial qualities of the Laguna District. The first part of this paper discusses some theoretical issues related to the significance of sea fronts in respect of coastal settlements and the spatial qualities of the coastal districts. Observation and physical analysis methods are used for assessing the spatial qualities. According to findings, some recommendations are given for improving the spatial qualities of the Laguna District.

Does the standard of living vary from region to region in Portugal and are spatial units in Portugal converging in income? We observe spatial error dependence between municipalities and estimate spatial econometric models to test convergence. For conditional convergence we conclude that primary sector employment, activity rate, and percentage of active population with higher education are important to distinguish the “steady state” of the regional economies, reflecting the labor market at regional level.

This study investigates the economic outcomes of organic farming controlling for the four major aspects of a cropping system, including climate, genotypes, management and soil. Considering possible variations in treatment responses, this study also presents empirical evidence of heterogeneous treatment effects associated with spatial agglomeration or farm covariates.

Rice farm households data taken from the 2015 Agriculture Census is merged with township-level seasonal weather data, crop suitability index and average income per capita in Taiwan. To address the selection bias problem, the authors apply the Probit-2SLS instrumental variable (IV) method in the binary treatment model under homogeneous and heterogeneous assumptions.

It is found that organic farming leads to a significantly positive effect on rice farms' economic performances in terms of cost reduction and profit growth. This positive treatment effect is more sizable with spatial agglomeration. Furthermore, the treatment effect of organic farming is found to vary with the farm characteristics such as farmland area and the number of hired workers.

Two important implications for the promotion of sustainable agri-food production are inferred: (1) establishing organic agriculture specialized zones may benefit rural development; (2) providing economic incentives to small farms to expand their scale may be a more effective policy means to promote sustainable agri-food production.

The findings in this study complement the body of knowledge by drawing insights from the agriculture census data and providing profound evidence of the heterogeneous outcomes of organic farming due to spatial clustering and farm covariates.