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Remote Sensing, Geophysics and GIS

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 4858

Special Issue Editors

Dr. Muhammad Tauhidur Rahman

E-Mail Website
Guest Editor
Geospatial Information Sciences Program, School of Economic, Political and Policy Sciences, The University of Texas at Dallas, Richardson, TX 75080, USA
Interests: geospatial information sciences; environmental impacts of natural hazards; land use and land cover changes
Special Issues, Collections and Topics in MDPI journals
Dr. Muhammad Bilal

E-Mail Website1 Website2
Guest Editor
Architecture and City Design (ACD) Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia
Interests: atmospheric remote sensing; air quality; aerosols; air quality and human health; aerosol classification; aerosol retrievals; remote sensing of land and atmospheric parameters; atmospheric correction of remote sensing data
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of remote sensing and Geographic Information Systems (GIS) has revolutionized geophysics, providing geophysicists with unprecedented insights into Earth's subsurface dynamics. Remote sensing captures detailed spatial data from a distance, while GIS enables its integration, analysis, and visualization, facilitating the investigation of geological phenomena, subsurface mapping, and resource management.

Remote sensing satellites equipped with sophisticated sensors, including multispectral, hyperspectral, and synthetic aperture radar (SAR), collect vast amounts of data with remarkable spatial and temporal resolution. These data offer valuable insights into surface features, terrain characteristics, and environmental changes, supporting comprehensive geological studies. GIS serves as the digital backbone for organizing, analyzing, and interpreting geospatial data collected through remote sensing. By integrating remote sensing imagery with other geophysical datasets, such as gravity and magnetic and seismic data, GIS facilitates the development of comprehensive geological models and the identification of subsurface structures. GIS-based spatial analysis tools enable the precise delineation of geological boundaries, the characterization of rock formations, the vulnerability and damage assessment of natural disasters, and the mapping of potential mineral deposits.

This Special Issue aims to explore the multifaceted applications and advancements at the intersection of remote sensing, GIS, and geophysics. Through original research articles, case studies, and reviews, we showcase innovative methodologies, tools, and approaches for leveraging remote sensing and GIS technology in geological exploration, subsurface mapping, and environmental monitoring.

Dr. Muhammad Tauhidur Rahman
Dr. Muhammad Bilal
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. Sensors 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 2600 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

  • remote sensing
  • GIS
  • geophysics

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Published Papers (4 papers)

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Research

22 pages, 12069 KiB  
Article
Water Use Efficiency Spatiotemporal Change and Its Driving Analysis on the Mongolian Plateau
by Gesi Tang, Yulong Bao, Changqing Sun, Mei Yong, Byambakhuu Gantumur, Rentsenduger Boldbayar and Yuhai Bao
Sensors 2025, 25(7), 2214; https://doi.org/10.3390/s25072214 - 1 Apr 2025
Viewed by 358
Abstract
Water use efficiency (WUE) connects two key processes in terrestrial ecosystems: the carbon and water cycles. Thus, it is important to evaluate temporal and spatial changes in WUE over a prolonged period. The spatiotemporal variation characteristics of the WUE in the Mongolian Plateau [...] Read more.
Water use efficiency (WUE) connects two key processes in terrestrial ecosystems: the carbon and water cycles. Thus, it is important to evaluate temporal and spatial changes in WUE over a prolonged period. The spatiotemporal variation characteristics of the WUE in the Mongolian Plateau from 1982 to 2018 were analyzed based on the net primary productivity (NPP), evapotranspiration (ET), temperature, precipitation, and soil moisture. In this study, we used remote sensing data and various statistical methods to evaluate the spatiotemporal patterns of water use efficiency and their potential influencing factors on the Mongolian Plateau from 1982 to 2018. In total, 27.02% of the region witnessed a significant decline in the annual WUE over the 37 years. Two abnormal surges in the WUESeason (April–October) were detected, from 1997 to 1998 and from 2007 to 2009. The trend in the annual WUE in some broadleaf forest areas in the middle and northeast of the Mongolian Plateau reversed from the original decreasing trend to an increasing trend. WUE has shown strong resilience in previous analytical studies, whereas the WUE in the artificial vegetation area in the middle of the Mongolian Plateau showed weak resilience. WUE had a significant positive correlation with precipitation, soil moisture, and the drought severity index (DSI) but a weak correlation with temperature. WUE had strong resistance to abnormal water disturbances; however, its resistance to the effects of temperature and DSI anomalies was weak. The degree of interpretation of vegetation changes for WUE was higher than that for meteorological factors, and WUE showed weak resistance to normalized difference vegetation index (NDVI) disturbances. Delaying the start of the vegetation growing season had an increasing effect on WUE, and the interaction between phenological and meteorological vegetation factors had a non-linear enhancing effect on WUE. Human activities have contributed significantly to the increase in WUE in the eastern, central, and southern regions of the Mongolian Plateau. These results provide a reference for the study of the carbon–water cycle in the Mongolian Plateau. Full article
(This article belongs to the Special Issue Remote Sensing, Geophysics and GIS)
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29 pages, 36430 KiB  
Article
Pattern-Based Sinkhole Detection in Arid Zones Using Open Satellite Imagery: A Case Study Within Kazakhstan in 2023
by Simone Aigner, Sarah Hauser and Andreas Schmitt
Sensors 2025, 25(3), 798; https://doi.org/10.3390/s25030798 - 28 Jan 2025
Viewed by 1179
Abstract
Sinkholes are significant geohazards in karst regions that pose risks to landscapes and infrastructure by disrupting geological stability. Usually, sinkholes are mapped by field surveys, which is very cost-intensive with regard to vast coverages. One possible solution to derive sinkholes without entering the [...] Read more.
Sinkholes are significant geohazards in karst regions that pose risks to landscapes and infrastructure by disrupting geological stability. Usually, sinkholes are mapped by field surveys, which is very cost-intensive with regard to vast coverages. One possible solution to derive sinkholes without entering the area is the use of high-resolution digital terrain models, which are also expensive with respect to remote areas. Therefore, this study focusses on the mapping of sinkholes in arid regions from open-access remote sensing data. The case study involves data from the Sentinel missions over the Mangystau region in Kazakhstan provided by the European Space Agency free of cost. The core of the technique is a multi-scale curvature filter bank that highlights sinkholes (and takyrs) by their very special illumination pattern in Sentinel-2 images. Marginal confusions with vegetation shadows are excluded by consulting the newly developed Combined Vegetation Doline Index based on Sentinel-1 and Sentinel-2. The geospatial analysis reveals distinct spatial correlations among sinkholes, takyrs, vegetation, and possible surface discharge. The generic and, therefore, transferable approach reached an accuracy of 92%. However, extensive reference data or comparable methods are not currently available. Full article
(This article belongs to the Special Issue Remote Sensing, Geophysics and GIS)
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18 pages, 9894 KiB  
Article
Determination of Cenozoic Sedimentary Structures Using Integrated Geophysical Surveys: A Case Study in the Hebei Plain, China
by Yi Yang, Jie Zhang, Junjie Wu, Pei Li, Xingchun Wang, Qingquan Zhi, Guojiang Hao, Jianhua Li and Xiaohong Deng
Sensors 2025, 25(2), 486; https://doi.org/10.3390/s25020486 - 16 Jan 2025
Viewed by 532
Abstract
The strong multi-stage tectonic movement caused the northwest of the North China Plain to rise and the southeast to fall. The covering layer in the plain area was several kilometers thick. In addition to expensive drilling, it is difficult to obtain deep geological [...] Read more.
The strong multi-stage tectonic movement caused the northwest of the North China Plain to rise and the southeast to fall. The covering layer in the plain area was several kilometers thick. In addition to expensive drilling, it is difficult to obtain deep geological information through traditional geological exploration. In this study, gravity, magnetotelluric (MT) sounding and shallow seismic methods are used to explore the basement relief and stratigraphic structure of the alluvial proluvial area in front of Taihang Mount in the North China Plain so as to understand the geological structure and sedimentary evolution of the area. The gravity anomaly map reveals the basement uplift, depression shape and faults distribution on the horizontal plane in the whole area. The MT profile reflects the geoelectric characteristics of the three-layer distribution in the Cenozoic. The seismic profile deployed on the Daxing Uplift depicts the structural style of the uplift area. The well-to-seismic calibration establishes the relationship between the lithostratigraphic and the wave impedance interface so that we can accurately obtain the shape and depth of the bedrock surface and further subdivide Cenozoic strata. Finally, we have improved the accuracy of interface inversion by using a variable density model based on density logging parameter statistics to constrain the depth of geological interfaces determined through drilling and multi-geophysical methods. Through the combination of geology and comprehensive geophysics, we have obtained the undulating patterns of Paleogene and Quaternary bottom interfaces, the structural styles of the basement and the distribution of faults in the survey area, which provide strong support for the study of neotectonic movement and sedimentary environment evolution since the Cenozoic. The successful application of this pattern proves that geophysical surveys based on prior geological information are an important supplementary tool for geological research in thick coverage areas. Full article
(This article belongs to the Special Issue Remote Sensing, Geophysics and GIS)
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17 pages, 13099 KiB  
Article
Lumped Parameter Thermal Network Modeling and Thermal Optimization Design of an Aerial Camera
by Yue Fan, Wei Feng, Zhenxing Ren, Bingqi Liu and Dazhi Wang
Sensors 2024, 24(12), 3982; https://doi.org/10.3390/s24123982 - 19 Jun 2024
Cited by 2 | Viewed by 1597
Abstract
The quality of aerial remote sensing imaging is heavily impacted by the thermal distortions in optical cameras caused by temperature fluctuations. This paper introduces a lumped parameter thermal network (LPTN) model for the optical system of aerial cameras, aiming to serve as a [...] Read more.
The quality of aerial remote sensing imaging is heavily impacted by the thermal distortions in optical cameras caused by temperature fluctuations. This paper introduces a lumped parameter thermal network (LPTN) model for the optical system of aerial cameras, aiming to serve as a guideline for their thermal design. By optimizing the thermal resistances associated with convection and radiation while considering the camera’s unique internal architecture, this model endeavors to improve the accuracy of temperature predictions. Additionally, the proposed LPTN framework enables the establishment of a heat leakage network, which offers a detailed examination of heat leakage paths and rates. This analysis offers valuable insights into the thermal performance of the camera, thereby guiding the refinement of heating zones and the development of effective active control strategies. Operating at a total power consumption of 26 W, the thermal system adheres to the low-power limit. Experimental data from thermal tests indicate that the temperatures within the optical system are maintained consistently between 19 °C and 22 °C throughout the flight, with temperature gradients remaining below 3 °C, satisfying the temperature requirements. The proposed LPTN model exhibits swiftness and efficacy in determining thermal characteristics, significantly facilitating the thermal design process and ensuring optimal power allocation for aerial cameras. Full article
(This article belongs to the Special Issue Remote Sensing, Geophysics and GIS)
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