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In this study, a knowledge-based fuzzy classification method was used to classify possible soil-landforms in urban areas based on analysis of morphometric parameters (terrain attributes) derived from digital elevation models (DEMs).
The recent decades have witnessed a significant increase in the population in peri-urban areas which led to a progressive transformation of peri-urban landscapes, and the reduced ability of agriculture to provide ecosystem services.
Drastic growth of urban populations has caused expansion of peri-urban areas—the transitional zone between a city and its hinterland.
Street trees, native plantings, bioswales, and other forms of green infrastructure alleviate urban air and water pollution, diminish flooding vulnerability, support pollinators, and provide other benefits critical to human well-being.
In West Africa, where the majority of the population relies on natural resources and rain-fed agriculture, regionally adapted agricultural land-use planning is increasingly important to cope with growing demand for land-use products and intensifying climate variability.
The contemporary urbanization and its implication to land use dynamics especially in the peri-urban areas are emerging as a cross-cutting theme in policy debates and scientific discourse.
The purpose of this research is to better conserve biodiversity by improving land allocation modeling software. Here we introduce a planning support framework designed to be understood by and useful to land managers, stakeholders, and other decision-makers.
Spain is a global hotspot of transformations of agri-food land systems due to changing production intensity, diets, urbanization, market integration, and climate change.
Existing studies on blockchain within land administration have focused mainly on replacing or complementing the technology for land registration and titling.
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