Pasar al contenido principal

page search

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
inglés

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).

Members:

Resources

Displaying 826 - 830 of 1524

Forests to the Foreigners: Large-Scale Land Acquisitions in Gabon

Peer-reviewed publication
Diciembre, 2020
Gabon

For the past decade, the land rush discourse has analyzed foreign investment in land and agriculture around the world, with Africa being a continent of particular focus due to the scale of acquisitions that have taken place. Gabon, a largely forested state in Central Africa, has been neglected in the land rush conversations, despite having over half of its land allocated to forestry, agriculture, and mining concessions. This paper draws on existing evidence and contributes new empirical data through expert interviews to fill this critical knowledge gap.

Assessing Matching Characteristics and Spatial Differences between Supply and Demand of Ecosystem Services: A Case Study in Hangzhou, China

Peer-reviewed publication
Diciembre, 2020
China

Ecosystem services (ESs) is a term used to describe the foundations of the well-being of human society, and several relevant studies have been carried out in this area. However, given the fact that the complex trade-offs/synergy relationships of ESs are a challenging area, studies on matching mechanisms for ES supply and demand are still rare.

Agricultural Land Transition in the “Groundnut Basin” of Senegal: 2009 to 2018

Peer-reviewed publication
Diciembre, 2020
Senegal

The study aims to reveal the transition features of agricultural land use in the Groundnut Basin of Senegal from 2009 to 2018, especially the impact of urbanization on agricultural land and the viewpoint of farmland spatiotemporal evolution. Integrated data of time series MCD12Q1 land-use images of 2009, 2012, 2015, and 2018 were used to provide a land transition in agricultural and urban areas through the synergistic methodology. Socio-economic data was also used to serve as a basis for the argument.

Analyzing the Effects of Institutional Merger: Case of Cadastral Information Registration and Landholding Right Providing Institutions in Ethiopia

Peer-reviewed publication
Diciembre, 2020
Ethiopia

Strong national institutional arrangements in the geospatial information management are essential for successful implementation of sustainable land administration system. However, it is not only the existence of institutions but also their effectiveness that leads to the intended goals and reaching of objectives.

Delineating Urban Functional Zones Using U-Net Deep Learning: Case Study of Kuancheng District, Changchun, China

Peer-reviewed publication
Diciembre, 2020
Global

Scientific functional zone planning is the key to achieving long-term development goals for cities. The rapid development of remote sensing technology allows for the identification of urban functional zones, which is important since they serve as basic spatial units for urban planning and functioning. The accuracy of three methods—kernel density estimation, term frequency-inverse document frequency, and deep learning—for detecting urban functional zones was investigated using the Gaode points of interest, high-resolution satellite images, and OpenStreetMap.