Agricultural Land-Use Change (ALUC) is a major driver of global environmental change, not least via its direct impact on the sustainability and resilience of the rural economy. Its drivers are complex and have remained contentious, necessitating further empirical study.
Agricultural Land-Use Change (ALUC) is a major driver of global environmental change, not least via its direct impact on the sustainability and resilience of the rural economy. Its drivers are complex and have remained contentious, necessitating further empirical study.
Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe.
Water quality models are useful tools to understand and mitigate eutrophication processes. However, gaining access to high-resolution data and fitting models to local conditions can interfere with their implementation.
Despite the economic and social costs of national and international efforts to restore millions of hectares of deforested and degraded landscapes, results have not met expectations due to land tenure conflicts, land-use transformation, and top-down decision-making policies.
In Ethiopia, expropriation and compensation measures have become a great concern due to horizontal urban expansion and development induced projects. Especially in peri-urban areas, the livelihood of farmers is affected by expropriation without fair and comparable compensation.
Neoliberal urbanism land planning has led to the development of public–private coalitions associating common interest with lucrative private enterprise projects. In Castilla–La Mancha (Spain), this regional growth coalition was backed by a spatial planning instrument, known as Projects of Special Interest (PSI).
The Yushu Tibetan Autonomous Prefecture is a typical Tibetan plateau area, and its ecological environment is very fragile. It is necessary to explore the terrain and cultural factors for the protection of the local ecological environment.
Effective management decisions regarding greenhouse gas (GHG) emissions may be hampered by the lack of scientific tools for modeling future land use change. This study addresses methodological principles for land use development scenario modeling assumed for use in processes of GHG accounting and management. Associated land use policy implications in Lithuania are also discussed.
In the last few decades, land use/land cover (LULC) has changed significantly under the influence of local planning and policy implementation, and this has had a profound impact on the regional ecological environment.
The purpose of this study is to reveal the spatial-temporal change and driving factors of green space in coastal cities of southeast China over the past 20 years. A supervised classification method combining support vector machines (SVMs) and visual interpretation was used to extract the green space from Landsat TM/OLI imageries from 2000–2020.
Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes.