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Displaying 216 - 220 of 2258Analysis of the Evolution of Land-Use Types in the Qilian Mountains from 1980 to 2020
The Qilian Mountains (QMs), located in the northeast part of the Qinghai–Tibetan Plateau in China, have a fragile ecological environment, complex and sensitive climate, and diverse land-cover types. It plays an important role in the “Qinghai–Tibetan Plateau Ecological Barrier” and “Northern Sand Control Belt” in China’s “two screens and three belts” ecological security strategy.
Soil Water Erosion Modeling in Tunisia Using RUSLE and GIS Integrated Approaches and Geospatial Data
Soil erosion is an important environmental problem that can have various negative consequences, such as land degradation, which affects sustainable development and agricultural production, especially in developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally.
Assessment of Water Yield and Water Purification Services in the Arid Zone of Northwest China: The Case of the Ebinur Lake Basin
Assessing how land-use changes will affect water-producing ecosystem services is particularly important for water resource management and ecosystem conservation. In this study, the InVEST model and geographical detector were used to assess the water ecosystem service functions of the Ebinur Lake Basin and analyze their relationship with land-use changes. The results show that in the past 25 years, the water yield of the study area showed a trend of a strong yield at first and then a weaker one; there was a relatively large water yield in the west and southeast regions of the basin.
Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China
Soil erosion often leads to land degradation, agricultural production reduction, and environmental deterioration, which seriously restricts the sustainable development of regions. Clarifying the driving factors of soil erosion is the premise of preventing soil erosion. Given the lack of current research on the driving factors/force changes of soil erosion in different regions or under different erosion intensity grades, this paper pioneered to use machine learning methods to address this problem.
A Prototype Machine Learning Tool Aiming to Support 3D Crowdsourced Cadastral Surveying of Self-Made Cities
Land administration and management systems (LAMSs) have already made progress in the field of 3D Cadastre and the visualization of complex urban properties to support property markets and provide geospatial information for the sustainable management of smart cities. However, in less developed economies, with informally developed urban areas—the so-called self-made cities—the 2D LAMSs are left behind. Usually, they are less effective and mainly incomplete since a large number of informal constructions remain unregistered.