Special Issue "Advances to GIS for Sensing of Earth and Human Interaction"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editors

Dr. Tao Pei
E-Mail Website
Guest Editor
Institute of Geographic Sciences and Natural Resources Research, the Chinese Academy of Sciences, Beijing 100101, China
Interests: big geodata mining; geostatistics; urban computation
Prof. Dr. Piotr A. Werner
E-Mail Website
Guest Editor
Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warsaw, Poland
Interests: application of information and communication technologies; information society development; GIS and remote sensing; methodology and applications of geoinformation systems; analysis, modeling, and simulation of spatial data; monitoring and land use changes; urbanization issues; natural hazard issues
Prof. Dr. Ling Yin
E-Mail Website
Guest Editor
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Interests: spatiotemporal data analysis; geographically computational epidemiology; GIS for transportation
Special Issues and Collections in MDPI journals
Dr. Xi Gong
E-Mail Website
Guest Editor
Department of Geography & Environmental Studies, UNM Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM 87131, USA
Interests: big data science and analytics; health and environment; spatially integrated social science; GIS-based modeling
Dr. Johannes H. Uhl
E-Mail Website
Guest Editor
University of Colorado Population Center (CUPC), Institute of Behavioral Science & Earth Lab, Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO 80309, USA
Interests: urban analysis; long-term land change, built environment, time series analysis in remote sensing; integrative approaches using remotely sensed data and other geospatial datasets

Special Issue Information

Dear Colleagues,

Advances in GIS for Sensing of Earth and Human Interactions

Earth and human interaction is one of the core issues in geography. Remotely sensed data and associated analytical methods are essential for detecting changes in the Earth’s surface. Although changes derived from remote sensing data can be used as a proxy to infer the intensity of human activity, the observation of human activities from remote sensing is indirect. With the development of location-aware technologies, alternative data sources measuring human activities have emerged, and social sensing techniques have been developed to reveal human behavior patterns. The combination of remote sensing data and human behavior data provides a new perspective on coupled human-natural systems. For this reason, we have launched this special issue on sensing the interactions between Earth and humans with both types of data. The topics of this issue include but are not limited to:

  1. Multisource big data processing (e.g., social media data, cellular signaling data, vehicle trajectories, and other VGIs);
  2. Urban function identification with remote sensed data and human behavior data;
  3. Simulation models of human–Earth system interactions;
  4. Urban environment evaluation with multisource data;
  5. Urban renewal detection based on remote sensing and VGI data;
  6. Human activity and its environmental effects;
  7. Evolution of urban systems and populated places based on alternative (non-remote sensing) data.
Dr. Tao Pei
Prof. Dr. Piotr A. Werner
Prof. Dr. Ling Yin
Dr. Xi Gong
Dr. Johannes H. Uhl
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 papers will be 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 2400 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.

Keywords

  • Coupled human-natural systems
  • Social sensing
  • Human-environmental interactions
  • Human behavior
  • Geospatial big data
  • Urban analysis

Published Papers (2 papers)

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Research

Article
Impact of Urban Expansion on Rain Island Effect in Jinan City, North China
Remote Sens. 2021, 13(15), 2989; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13152989 - 29 Jul 2021
Viewed by 477
Abstract
Rapid urbanization leads to changes in urban micro meteorology, such as the urban heat island effect and rain island effect, which eventually brings about urban waterlogging and other problems. In this study, the data of precipitation, temperatures and impervious surfaces with long series [...] Read more.
Rapid urbanization leads to changes in urban micro meteorology, such as the urban heat island effect and rain island effect, which eventually brings about urban waterlogging and other problems. In this study, the data of precipitation, temperatures and impervious surfaces with long series and high resolution are used to study the rain island effect in Jinan City, China. MK-Sen’s slope estimator, Pettitt test and Pearson correlation analysis are used to quantitatively analyze the impact of urban expansion on extreme climate indices. The results show that Jinan City has experienced rapid urbanization since the 1978 economic reform, and the impervious surface areas have increased from 311.68 km2 (3.04%) in 1978 to 2389.50 km2 (23.33%) in 2017. Urban expansion has a significant impact on temperature, with large variations in extreme temperature indices over the intensive construction area relative to the sparse construction area. The extreme temperature indices have a significant correlation with impervious surfaces. Jinan City shows a certain degree of rain island effect, which seems to be spatially correlated with the urban heat island effect. The frequency of short-duration precipitation events significantly increases and the intensity of precipitation events generally increases. The magnitude and frequency of extreme precipitation indices in the intensive construction area significantly increase when compared to that in the sparse construction area, and they have a significant correlation with impervious surfaces. There is a tendency that Jinan City’s rainfall center moves towards to the intensive construction area. Full article
(This article belongs to the Special Issue Advances to GIS for Sensing of Earth and Human Interaction)
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Article
Quantitative Assessment of Landslide Risk Based on Susceptibility Mapping Using Random Forest and GeoDetector
Remote Sens. 2021, 13(13), 2625; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13132625 - 04 Jul 2021
Viewed by 722
Abstract
This study aims to evaluate risk and discover the distribution law for landslides, so as to enrich landslide prevention theory and method. It first selected Fengjie County in the Three Gorges Reservoir Area as the study area. The work involved developing a landslide [...] Read more.
This study aims to evaluate risk and discover the distribution law for landslides, so as to enrich landslide prevention theory and method. It first selected Fengjie County in the Three Gorges Reservoir Area as the study area. The work involved developing a landslide risk map using hazard and vulnerability maps utilizing landslide dataset from 2001 to 2016. The landslide dataset was built from historical records, satellite images and extensive field surveys. Firstly, under four primary conditioning factors (i.e., topographic factors, geological factors, meteorological and hydrological factors and vegetation factors), 19 dominant factors were selected from 25 secondary conditioning factors based on the GeoDetector to form an evaluation factor library for the LSM. Subsequently, the random forest model (RF) was used to analyze landslide susceptibility. Then, the landslide hazard map was generated based on the landslide susceptibility mapping (LSM) for the study region. Thereafter, landslide vulnerability assessment was conducted using key elements (economic, material, community) and the weights were provided based on expert judgment. Finally, when risk equals vulnerability multiplied by hazard, the region was categorized as very low, low, medium, high and very high risk level. The results showed that most landslides distribute on both sides of the reservoir bank and the primary and secondary tributaries in the study area, which showed a spatial distribution pattern of more north than south. Elevation, lithology and groundwater type are the main factors affecting landslides. Fengjie County landslide risk level is mostly low (accounting for 73.71% of the study area), but a small part is high and very high risk level (accounting for 2.5%). The overall risk level shows the spatial distribution characteristics of high risk in the central and eastern urban areas and low risk in the southern and northern high-altitude areas. Secondly, it is necessary to strictly control the key risk areas, and carry out prevention and control zoning management according to local conditions. The study is conducted for a specific region but can be extended to other areas around the investigated area. The developed landslide risk map can be considered by relevant government officials for the smooth implementation of management at the regional scale. Full article
(This article belongs to the Special Issue Advances to GIS for Sensing of Earth and Human Interaction)
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