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Remote Sensing Application for Environmental Monitoring
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Remote Sensing Application for Environmental Monitoring

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

Deadline for manuscript submissions: closed (25 February 2024) | Viewed by 8717

Special Issue Editors

Dr. Javier Fernández Calleja

E-Mail Website
Guest Editor
Department of Physics, University of Oviedo, Oviedo, Spain
Interests: remote sensing; albedo; surface temperature
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Susana del Carmen Fernández Menedez

E-Mail Website
Guest Editor
Department of Geology and Institute of Science and Aerospatial Technologies (ICTEA), University of Oviedo, Oviedo, Spain
Interests: earth and planetary sciences; quantitative geomorphology; soil modelling; spatial statistics; spectroscopy; remote sensing; GIS
Special Issues, Collections and Topics in MDPI journals
Dr. José González-Piqueras

E-Mail Website
Guest Editor
Department of Applied Physics, University of Castilla-La Mancha, Ciudad Real, Spain
Interests: remote sensing; water balance; radiometry; environmental impact assessment; environment; soil; environmental science; vegetation

Special Issue Information

Dear Colleagues,

Understanding the Earth’s systems is mandatory to predict its future and to provide decision-making organizations with the required information to take action when necessary. The World Meteorological Organization has defined Essential Climate Variables (ESV); these are physical, biological and chemical quantities that are critical for characterizing the Earth’s climate and for environmental monitoring. We focus here on the Land ESV and the corresponding phenomena they are linked to. The estimation of the Land ESV from remote sensors has been progressing dramatically in recent years. Nowadays , several algorithms are available to estimate surface temperature, air temperature, soil moisture, surface reflectance and albedo, wind speed, soil carbon and other variables from remote sensors at different time and spatial resolutions. This Special Issue aims to improve our knowledge on the estimation of the Land ESV and the phenomena they are linked to, using remote sensing data. Manuscripts must include data acquired by remote sensing platforms (UAV, airborne or spaceborne). Potential topics include:

  • New algorithms for the estimation of Land ESV from remote sensors.
  • Scaling from in situ to remote sensing data.
  • Ingestion of environmental quantities from remote sensors in theoretical models.
  • Land cover change detection and land cover time series.
  • Glaciers mass balance estimation from remote sensing data.
  • Evolution of polar ice sheets and ice shelves.
  • Thermal state of permafrost and permafrost active layer.
  • Surface energy balance for land .
  • Soil carbon distribution maps.

Dr. Javier Fernández Calleja
Prof. Dr. Susana del Carmen Fernández Menedez
Dr. José González-Piqueras
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
  • essential climate variables for land
  • environmental monitoring

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Published Papers (4 papers)

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Research

24 pages, 6420 KiB  
Article
Spatial and Temporal Variation of Urban Heat Islands in French Guiana
by Gustave Ilunga, Jessica Bechet, Laurent Linguet, Sara Zermani and Chabakata Mahamat
Sensors 2024, 24(6), 1931; https://doi.org/10.3390/s24061931 - 18 Mar 2024
Cited by 1 | Viewed by 1475
Abstract
A surface urban heat island (SUHI) is a phenomenon whereby temperatures in urban areas are significantly higher than that of surrounding rural and natural areas due to replacing natural and semi-natural areas with impervious surfaces. The phenomenon is evaluated through the SUHI intensity, [...] Read more.
A surface urban heat island (SUHI) is a phenomenon whereby temperatures in urban areas are significantly higher than that of surrounding rural and natural areas due to replacing natural and semi-natural areas with impervious surfaces. The phenomenon is evaluated through the SUHI intensity, which is the difference in temperatures between urban and non-urban areas. In this study, we assessed the spatial and temporal dynamics of SUHI in two urban areas of the French Guiana, namely Ile de Cayenne and Saint-Laurent du Maroni, for the year 2020 using MODIS-based gap-filled LST data. Our results show that the north and southwest of Ile de Cayenne, where there is a high concentration of build-up areas, were experiencing SUHI compared to the rest of the region. Furthermore, the northeast and west of Saint-Laurent du Maroni were also hotspots of the SUHI phenomenon. We further observed that the peak of high SUHI intensity could reach 5 °C for both Ile de Cayenne and Saint-Laurent du Maroni during the dry season when the temperature is high with limited rainfall. This study sets the stage for future SUHI studies in French Guiana and aims to contribute to the knowledge needed by decision-makers to achieve sustainable urbanization. Full article
(This article belongs to the Special Issue Remote Sensing Application for Environmental Monitoring)
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19 pages, 10657 KiB  
Article
Monitoring Off-Shore Fishing in the Northern Indian Ocean Based on Satellite Automatic Identification System and Remote Sensing Data
by Jie Li, Qianguo Xing, Xuerong Li, Maham Arif and Jinghu Li
Sensors 2024, 24(3), 781; https://doi.org/10.3390/s24030781 - 25 Jan 2024
Cited by 5 | Viewed by 2501
Abstract
Satellite-derived Sea Surface Temperature (SST) and sea-surface Chlorophyll a concentration (Chl-a), along with Automatic Identification System (AIS) data of fishing vessels, were used in the examination of the correlation between fishing operations and oceanographic factors within the northern Indian Ocean from March 2020 [...] Read more.
Satellite-derived Sea Surface Temperature (SST) and sea-surface Chlorophyll a concentration (Chl-a), along with Automatic Identification System (AIS) data of fishing vessels, were used in the examination of the correlation between fishing operations and oceanographic factors within the northern Indian Ocean from March 2020 to February 2023. Frequency analysis and the empirical cumulative distribution function (ECDF) were used to calculate the optimum ranges of two oceanographic factors for fishing operations. The results revealed a substantial influence of the northeast and southwest monsoons significantly impacting fishing operations in the northern Indian Ocean, with extensive and active operations during the period from October to March and a notable reduction from April to September. Spatially, fishing vessels were mainly concentrated between 20° N and 6° S, extending from west of 90° E to the eastern coast of Africa. Observable seasonal variations in the distribution of fishing vessels were observed in the central and southeastern Arabian Sea, along with its adjacent high sea of the Indian Ocean. Concerning the marine environment, it was observed that during the northeast monsoon, the suitable SST contributed to high CPUEs in fishing operation areas. Fishing vessels were widely distributed in the areas with both mid-range and low-range Chl-a concentrations, with a small part distributed in high-concentration areas. Moreover, the monthly numbers of fishing vessels showed seasonal fluctuations between March 2020 and February 2023, displaying a periodic pattern with an overall increasing trend. The total number of fishing vessels decreased due to the impact of the COVID-19 pandemic in 2020, but this was followed by a gradual recovery in the subsequent two years. For fishing operations in the northern Indian Ocean, the optimum ranges for SST and Chl-a concentration were 27.96 to 29.47 °C and 0.03 to 1.81 mg/m3, respectively. The preliminary findings of this study revealed the spatial–temporal distribution characteristics of fishing vessels in the northern Indian Ocean and the suitable ranges of SST and Chl-a concentration for fishing operations. These results can serve as theoretical references for the production and resource management of off-shore fishing operations in the northern Indian Ocean. Full article
(This article belongs to the Special Issue Remote Sensing Application for Environmental Monitoring)
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13 pages, 7250 KiB  
Article
OS-BREEZE: Oil Spills Boundary Red Emission Zone Estimation Using Unmanned Surface Vehicles
by Oren Elmakis, Semion Polinov, Tom Shaked, Gabi Gordon and Amir Degani
Sensors 2024, 24(2), 703; https://doi.org/10.3390/s24020703 - 22 Jan 2024
Viewed by 1881
Abstract
Maritime transport, responsible for delivering over eighty percent of the world’s goods, is the backbone of the global delivery industry. However, it also presents considerable environmental risks, particularly regarding aquatic contamination. Nearly ninety percent of marine oil spills near shores are attributed to [...] Read more.
Maritime transport, responsible for delivering over eighty percent of the world’s goods, is the backbone of the global delivery industry. However, it also presents considerable environmental risks, particularly regarding aquatic contamination. Nearly ninety percent of marine oil spills near shores are attributed to human activities, highlighting the urgent need for continuous and effective surveillance. To address this pressing issue, this paper introduces a novel technique named OS-BREEZE. This method employs an Unmanned Surface Vehicle (USV) for assessing the extent of oil pollution on the sea surface. The OS-BREEZE algorithm directs the USV along the spill edge, facilitating rapid and accurate assessment of the contaminated area. The key contribution of this paper is the development of this novel approach for monitoring and managing marine pollution, which significantly reduces the path length required for mapping and estimating the size of the contaminated area. Furthermore, this paper presents a scale model experiment executed at the Coastal and Marine Engineering Research Institute (CAMERI). This experiment demonstrated the method’s enhanced speed and efficiency compared to traditional monitoring techniques. The experiment was methodically conducted across four distinct scenarios: the initial and advanced stages of an oil spill at the outer anchoring, as well as scenarios at the inner docking on both the stern and port sides. Full article
(This article belongs to the Special Issue Remote Sensing Application for Environmental Monitoring)
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25 pages, 10377 KiB  
Article
Analysis of Long Time Series of Summer Surface Urban Heat Island under the Missing-Filled Satellite Data Scenario
by Jiamin Luo, Yuan Yao and Qiuyan Yin
Sensors 2023, 23(22), 9206; https://doi.org/10.3390/s23229206 - 16 Nov 2023
Cited by 3 | Viewed by 2005
Abstract
Surface urban heat islands (SUHIs) are mostly an urban ecological issue. There is a growing demand for the quantification of the SUHI effect, and for its optimization to mitigate the increasing possible hazards caused by SUHI. Satellite-derived land surface temperature (LST) is an [...] Read more.
Surface urban heat islands (SUHIs) are mostly an urban ecological issue. There is a growing demand for the quantification of the SUHI effect, and for its optimization to mitigate the increasing possible hazards caused by SUHI. Satellite-derived land surface temperature (LST) is an important indicator for quantifying SUHIs with frequent coverage. Current LST data with high spatiotemporal resolution is still lacking due to no single satellite sensor that can resolve the trade-off between spatial and temporal resolutions and this greatly limits its applications. To address this issue, we propose a multiscale geographically weighted regression (MGWR) coupling the comprehensive, flexible, spatiotemporal data fusion (CFSDAF) method to generate a high-spatiotemporal-resolution LST dataset. We then analyzed the SUHI intensity (SUHII) in Chengdu City, a typical cloudy and rainy city in China, from 2002 to 2022. Finally, we selected thirteen potential driving factors of SUHIs and analyzed the relation between these thirteen influential drivers and SUHIIs. Results show that: (1) an MGWR outperforms classic methods for downscaling LST, namely geographically weighted regression (GWR) and thermal image sharpening (TsHARP); (2) compared to classic spatiotemporal fusion methods, our method produces more accurate predicted LST images (R2, RMSE, AAD values were in the range of 0.8103 to 0.9476, 1.0601 to 1.4974, 0.8455 to 1.3380); (3) the average summer daytime SUHII increased form 2.08 °C (suburban area as 50% of the urban area) and 2.32 °C (suburban area as 100% of the urban area) in 2002 to 4.93 °C and 5.07 °C, respectively, in 2022 over Chengdu City; and (4) the anthropogenic activity drivers have a higher relative influence on SUHII than other drivers. Therefore, anthropogenic activity driving factors should be considered with CO2 emissions and land use changes for urban planning to mitigate the SUHI effect. Full article
(This article belongs to the Special Issue Remote Sensing Application for Environmental Monitoring)
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