Population density as the attractor of business to the place.

Firm location studies traditionally assume that this is business that attracts other business to a given location. They focus on knowledge transfers between the most productive and innovative firms and analyse agglomeration economies arising from matching, learning and sharing mechanisms. We argue that the population density also attracts firms to the place.

Mapping urban well-being with Quality Of Life Index (QOLI) at the fine-scale of grid data.

Accessibility of transport infrastructure, commercial amenities, recreational facilities, and green spaces is widely recognised as crucial to the well-being of urban residents. However, these features are often unevenly distributed across the geographical boundaries of a city, leading to disparities in the local quality of life. This study focuses on the city of Warsaw, Poland, and uses the aforementioned characteristics and the framework of the '15-min city' concept to construct a grid-level urban Quality of Life Index (QOLI) that facilitates comparisons between the city's districts and local neighbourhoods.

Fresh air in the city: the impact of air pollution on the pricing of real estate.

This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter (PM, PM and PM) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact.

Natural spatial pattern-When mutual socio-geo distances between cities follow Benford's law.

Benford's law states that the first digits of numbers in any natural dataset appear with defined frequencies. Pioneering, we use Benford distribution to analyse the geo-location of cities and their population in the majority of countries. We use distances in three dimensions: 1D between the population values, 2D between the cities, based on geo-coordinates of location, 3D between cities' location and population, which jointly reflects separation and mass of urban locations.

Spatial and Machine Learning Approach to Model Childhood Stunting in Pakistan: Role of Socio-Economic and Environmental Factors.

This study presents the determinants of childhood stunting as the consequence of child malnutrition. We checked two groups of factors-the socio-economic situation and climate vulnerability-using disaggregated sub-regional data in the spatial context. Data related to the percentage of stunted children in Pakistan for 2017 were retrieved from MICS 2017-18 along with other features.

Decoding Rocks: An Assessment of Geomaterial Microstructure Using X-ray Microtomography, Image Analysis and Multivariate Statistics.

An understanding of the microstructure of geomaterials such as rocks is fundamental in the evaluation of their functional properties, as well as the decryption of their geological history. We present a semi-automated statistical protocol for a complex 3D characterization of the microstructure of granular materials, including the clustering of grains and a description of their chemical composition, size, shape, and spatial properties with 44 unique parameters. The approach consists of an X-ray microtomographic image processing procedure, followed by measurements using image analysis and statistical multivariate analysis of its results utilizing freeware and widely available software.