Resources
Displaying 1086 - 1090 of 2258In the Search of an Assessment Method for Urban Landscape Objects (ULOs): Tangible and Intangible Values, Public Participation Geographic Information Systems (PPGIS), and Ranking Approach
The effective assessment of urban space must link subjective and objective approaches. The main aim of the paper was to develop and test such a method of assessment in relation to one of the elements of the urban landscape called urban landscape objects (ULOs). The tested method fulfils the following requirements: (1) merges social and expert opinions, (2) analyzes diverse characteristics of urban space, (3) quantitatively presents the results of values assessments, and (4) features the simplicity of structure and ease of public understanding.
Effects of Land Cover Changes on Net Primary Productivity in the Terrestrial Ecosystems of China from 2001 to 2012
The 2001–2012 MODIS MCD12Q1 land cover data and MOD17A3 NPP data were used to calculate changes in land cover in China and annual changes in net primary productivity (NPP) during a 12-year period and to quantitatively analyze the effects of land cover change on the NPP of China’s terrestrial ecosystems. The results revealed that during the study period, no changes in land cover type occurred in 7447.31 thousand km2 of China, while the area of vegetation cover increased by 160.97 thousand km2 in the rest of the country.
Identifying Land Use Change Trajectories in Brazil’s Agricultural Frontier
Many of the world’s agricultural frontiers are located in the tropics. Crop and cattle expansion in these regions has a strong environmental impact. This paper examines land use and land cover transformations in Brazil, where large swaths of natural vegetation are being removed to make way for agricultural production. In Brazil, the land use dynamics are of great interest regarding the country’s sustainable development and climate mitigation actions, leading to the formulation and implantation of public policies and supply chain interventions to reduce deforestation.
Using Machine Learning Algorithms to Estimate Soil Organic Carbon Variability with Environmental Variables and Soil Nutrient Indicators in an Alluvial Soil
Soil organic carbon (SOC) is an important indicator of soil quality and directly determines soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary for efficient and sustainable soil nutrient management. In this study, machine learning algorithms including artificial neural network (ANN), support vector machine (SVM), cubist regression, random forests (RF), and multiple linear regression (MLR) were chosen for advancing the prediction of SOC.
Study on the Spatial Restructuring of the Village System at the County Level Oriented toward the Rural Revitalization Strategy: A Case of Jintan District, Jiangsu Province
The spatial restructuring of village systems is an important means by which to promote rural revitalization. A large number of villages with small average areas bring great challenges to the implementation of the Rural Revitalization Strategy (RRS) in China. To promote the implementation of the RRS, it is necessary to restructure the village system. This paper proposes a method of spatial restructuring for the village system at the county level, oriented toward the RRS. This study proposes a village classification system with central villages, characteristic villages, and merged villages.