With over 14 million hectares allocated, Vietnam’s forest and forestland allocation has been one of the largest natural resource decentralization programs in the developing world over the last three decades. Given this remarkable achievement, critics are concerned about the low rates of household tree planting investment and question the roles and effects of land institutions on investment.
The Mekong Delta region has been seriously affected by climate change, with increasing temperatures, sea-level rise, and salinization strongly impacting agricultural activities of the region. Recent studies have shown that groundwater exploitation also contributes significantly to land subsidence throughout the delta.
Spatial planning potential for reducing natural risks including wildfires is widely recognized.
How land is used is connected to some of the most important issues of our time: sustainable development, economic development, reducing territorial inequalities and the rights of future generations, to name but a few. There is growing recognition that a wide range of policies shape how land is used and managed beyond that of land use and environmental planning systems.
Identification of spatiotemporal changes in ecosystem service value and their drivers is the basis for ecosystem services management and decision making. This research selects Fujiang River Basin (FJRB) as the area of study, using the equivalent factor method to estimate the ecosystem service value (ESV) variation and characteristics of its spatial distribution.
Spatio-temporal changes in cultivated land have a profound impact on food security and sustainable development. However, existing studies on spatio-temporal changes in cultivated land mostly focus on single factors, for instance quantity, quality and ecology, that cannot comprehensively reflect the changes in total production capacity and the sustainability of cultivated land.
Malaysia deforested 6.3 million hectares since independence; 91% of which occurred before Malaysia pledged, at the Earth Summit in 1992, to maintain a minimum 50% of its terrestrial area under forest cover. However, under economic and population pressure, Sarawak—the largest contributing state to the country’s current forest cover of 54.8%—shows continuing deforestation even after 1992.
Accelerating land-use change (LUC) in the Nilgiri Hill Region (NHR) has caused its land to mortify. Although this deterioration has been documented, the destruction of buried gem soil has not been reported.
This paper addresses a forest harvesting problem with adjacency constraints, including additional environmental constraints to protect wildlife habitats and minimize infrastructure deployment costs. To this end, we propose an integer programming model to include those considerations during the optimization of the harvest regime of a Mexican forest.
In a digitalized era and with the rapid growth of computational skills and advancements, artificial intelligence and Machine Learning uses in various applications are gaining a rising interest from scholars and practitioners.