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Community Organizations MDPI Online, Open Access Journals
MDPI Online, Open Access Journals
MDPI Online, Open Access Journals
Acronym
MDPI
Publishing Company
Phone number
+41 61 683 77 34

Location

St. Alban-Anlage 66
Basel
Basel-Stadt
Switzerland
Working languages
English

MDPI AG, a publisher of open-access scientific journals, was spun off from the Molecular Diversity Preservation International organization. It was formally registered by Shu-Kun Lin and Dietrich Rordorf in May 2010 in Basel, Switzerland, and maintains editorial offices in China, Spain and Serbia. MDPI relies primarily on article processing charges to cover the costs of editorial quality control and production of articles. Over 280 universities and institutes have joined the MDPI Institutional Open Access Program; authors from these organizations pay reduced article processing charges. MDPI is a member of the Committee on Publication Ethics, the International Association of Scientific, Technical, and Medical Publishers, and the Open Access Scholarly Publishers Association (OASPA).

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Resources

Displaying 371 - 375 of 1524

Development of a Methodology and Model for Land Administration Data Dissemination Processes

Peer-reviewed publication
декабря, 2022
Global

Land administration (LA) is concerned with processes. Simply put, LA cannot be understood, built, or improved unless the processes associated with it are understood. When it comes to the processes involved in LA, two general processes can be identified, namely registration and dissemination. Nowadays, processes are implemented electronically; however, paper-based thinking is still present, and the performance of processes is impeded by siloed data management. These issues could be addressed through the employment of standards such as the Land Administration Domain Model.

Assessing Land-Use Conflict Potential and Its Correlation with LULC Based on the Perspective of Multi-Functionality and Landscape Complexity: The Case of Chengdu, China

Peer-reviewed publication
декабря, 2022
Global

The rapid development of megacities has greatly impacted land use in the urban–rural fringe area. The Western Protected Area defined by Chengdu’s Master Plan (2016–2035) to end the unrestrained urban sprawl, where locates the most superior agricultural and ecological resources, namely Mount Qingcheng and the Dujiangyan Essence Irrigation District, is facing great challenges when implementing protective strategies, related to huge land use competition caused by land multi-functionality.

Soil Water Erosion Modeling in Tunisia Using RUSLE and GIS Integrated Approaches and Geospatial Data

Peer-reviewed publication
декабря, 2022
Tunisia

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.

Land Use Transition and Its Ecosystem Resilience Response in China during 1990–2020

Peer-reviewed publication
декабря, 2022
China

Land use transition and its eco-environmental effects are important research topics. Its essence is the process that human activities exert interference to the ecological environment in the process of social and economic development, and the ecosystem resists interference and recovers and adapts to interference. The article starts from the transition of land use dominant morphology and takes ecological resilience as the breakthrough point.

Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China

Peer-reviewed publication
декабря, 2022
Global

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.