Geodata Science and Spatial Analysis with Remote Sensing 11

Global warming and climate change have become indisputable facts. The Earth has entered the Anthropocene phase. A series of resource, environment, and ecology issues have arisen due to continuous anthropic activities, especially industrialization and urbanization. For example, air pollutants and toxic metals have significantly negative effects on public health and the environment.  Sustainable development has been severely influenced by a variety of issues such as air contamination, water pollution, heavy metal pollution, greenhouse gas emissions, organic pollution, and microplastic pollution.

To address the above issues, it is necessary to observe the environmental parameters and resource conditions, analyze the dynamics of each parameter and resource, identify the main ecological and environmental issues on a regional and global scale, and predict the trends of environmental elements. The outcomes can supply scientific support for achieving the Sustainable Development Goals (SDG) of the United Nations.

Remote sensing technology supplies a new perspective for environmental parameters and resource monitoring due to its fast detection capacity, wide spatial coverage, and multiple spectral characteristics. Notably, the limited ground monitoring stations for environmental issues can be effectively compensated for with remote sensing technology. Remote sensing technology has been widely used to retrieve ecological parameters. Meanwhile, previous studies have also used nighttime light remote sensing images as a proxy to predict social–economic parameters such as population density, GDP, and electricity consumption. Furthermore, some previous studies took advantage of hyperspectral remote sensing to retrieve pollutant concentrations in soils, the air, vegetation, and water bodies. Obviously, remote sensing technology plays an important role in data collection and further spatial analysis. With more and more fine-resolution sensors launched, the role of remote sensing will be more significant in the future.

Hence, it is urgent to conduct related research in the field of geodata science and spatial analysis with remote sensing. The objective of this Special Issue is to publish papers from new perspectives and viewpoints on using remote sensing techniques in the field of geodata science and spatial analysis. This Special Issue mainly seeks to utilize remote sensing techniques, spatial analysis methods, models, and numerical simulation in addressing complicated social, economic, resource, ecology, and environmental issues. Articles are not limited to the above-mentioned topics, as other topics related to remote sensing are also desired.

Dr. Bin Guo
Dr. Sergio Bernardes
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• • air pollutants • heavy metals • nighttime light remote sensing • data-driven models • hyperspectral remote sensing • coupled CFD-GIS