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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 361 - 365 of 1524

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.

Land Use Conflicts Assessment in Xiamen, China under Multiple Scenarios

Peer-reviewed publication
декабря, 2022
China

The accelerated urbanization process has resulted in increasingly prominent conflicts in land resource utilization and caused numerous ecological and environmental issues. Simulating the evolutionary patterns of land use conflicts (LUCs) is the foundation for promoting sustainable land use. The Markov and GeoSOS-FLUS models were used to predict the land use patterns under three different development scenarios, and to analyze the spatio-temporal characteristics of LUCs in Xiamen, China in 2030.

Analysis of the Evolution of Land-Use Types in the Qilian Mountains from 1980 to 2020

Peer-reviewed publication
декабря, 2022
China

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.

Assessment of Water Yield and Water Purification Services in the Arid Zone of Northwest China: The Case of the Ebinur Lake Basin

Peer-reviewed publication
декабря, 2022
Global

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.

Mapping and Monitoring Spatio-Temporal Patterns of Rainfed Agriculture Lands of North Darfur State, Sudan, Using Earth Observation Data

Peer-reviewed publication
декабря, 2022
Global

Rainfed agriculture in Northern Darfur is influenced by erratic seasonal and decadal rainfall patterns and frequent droughts. Understanding the spatio-temporal variation in rainfed agriculture is crucial for promoting food security, socio-economic stability and protecting the vulnerable ecosystem. This study aimed to investigate the spatio-temporal dynamics of rainfed agriculture in North Darfur State from 1984–2019 using multitemporal Landsat observation data.