Environmental Sciences Proceedings

1 pages, 129 KB

Open AccessEditorial

Statement of Peer Review

by Alexander Kokhanovsky

Environ. Sci. Proc. 2024, 29(1), 84; https://doi.org/10.3390/ECRS2023029084 - 19 Jun 2024

In submitting conference proceedings to Environmental Sciences Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of ECRS 2023)

4 pages, 215 KB

Open AccessEditorial

Preface: 6th International Electronic Conference on Atmospheric Sciences

by Anthony R. Lupo

Environ. Sci. Proc. 2023, 27(1), 40; https://doi.org/10.3390/ecas2023027040 - 19 Jun 2024

Abstract

The sixth International Electronic Conference on Atmospheric Sciences, the range of topics will remain more general, but we are open to subject areas with a thematic topic of importance, especially interdisciplinary or transdisciplinary science [...] Full article

(This article belongs to the Proceedings of The 6th International Electronic Conference on Atmospheric Sciences)

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1 pages, 138 KB

Open AccessEditorial

Statement of Peer Review

by Anthony R. Lupo

Environ. Sci. Proc. 2023, 27(1), 39; https://doi.org/10.3390/ecas2023027039 - 19 Jun 2024

Abstract

In submitting conference proceedings to Environmental Sciences Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of The 6th International Electronic Conference on Atmospheric Sciences)

6 pages, 1874 KB

Open AccessProceeding Paper

Synergy of CALIOP and Ground-Based Solar Radiometer Data to Study Statistical Characteristics of Aerosols in Regions with a Low Aerosol Load

by Anatoli Chaikovsky, Andrey Bril, Philippe Goloub, Zhengqiang Li, Vladislav Peshcherenkov, Fiodar Asipenka, Luc Blarel, Gael Dubois, Mikhail Korol, Aliaksandr Lapionak, Aleksey Malinka, Natallia Miatselskaya, Thierry Podvin and Ying Zhang

Environ. Sci. Proc. 2024, 29(1), 70; https://doi.org/10.3390/ECRS2023-16860 - 6 Jun 2024

Abstract

The statistical characteristics of combined lidar and radiometric measurements obtained from satellite lidar CALIOP and ground-based sun-radiometer stations were used as input datasets to retrieve the altitude profiles of aerosol parameters (LRS-C technique). The signal-to-noise ratio of the input satellite lidar signals increased [...] Read more.

The statistical characteristics of combined lidar and radiometric measurements obtained from satellite lidar CALIOP and ground-based sun-radiometer stations were used as input datasets to retrieve the altitude profiles of aerosol parameters (LRS-C technique). The signal-to-noise ratio of the input satellite lidar signals increased when averaging over a large array of measured data. An algorithm and software package for processing the input dataset of the LRS-C sounding of atmospheric aerosol in regions with medium and low aerosol loads was developed. This paper presents the results of studying long-term changes in the concentration profiles of aerosol modes in regions of East Europe (AERONET site Minsk, 53.92° N, 27.60° E) and East Antarctic (AERONET site Vechernaya Hill, 67.66° S, 46.16° E). Full article

(This article belongs to the Proceedings of ECRS 2023)

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10 pages, 4007 KB

Open AccessProceeding Paper

Dynamic Analysis of Water Surface Extent and Climate Change Parameters in Zarivar Lake, Iran

by Ehsan Rostami, Rasool Vahid, Arastou Zarei and Meisam Amani

Environ. Sci. Proc. 2024, 29(1), 71; https://doi.org/10.3390/ECRS2023-17345 - 18 Apr 2024

Cited by 2

Abstract

Wetlands are valuable natural resources that provide many services to both the environment and humans. Over the past several decades, climatic change and human activities have had a considerable impact on the water level of wetlands. Zarivar Lake, located in the northwestern region [...] Read more.

Wetlands are valuable natural resources that provide many services to both the environment and humans. Over the past several decades, climatic change and human activities have had a considerable impact on the water level of wetlands. Zarivar Lake, located in the northwestern region of Iran, represents a significant ecological unit and aquatic ecosystem. In this study, from 2015 to 2022, the relationship between seasonal changes in Zarivar Lake’s waterbody (LWB) area and weather factors like precipitation, evapotranspiration, and the temperature of the lake’s surface water (LSWT) were examined. For this purpose, the Google Earth Engine (GEE) cloud platform, a powerful and fast tool for processing the time series of images, was used. The LWB was extracted by utilizing the average images of the dual-polarized SAR Sentinel-1 imagery for each season. Furthermore, meteorological parameters encompass the utilization of the Landsat-8 satellite’s thermal band to determine LSWT by using statistical mono-window (SMW), the CHIRPS rainfall model data for assessing precipitation levels, and the employment of MODIS evapotranspiration products in the form of 8-day data. The study revealed significant correlations between variations in Zarivar Lake’s waterbody area and meteorological factors. Correlation coefficients indicated a positive relationship between LWB area and precipitation during the winter (r = 0.67) and spring (r = 0.73), while weaker positive correlations were observed in the summer (r = 0.29) and fall (r = 0.30). Conversely, the LWB area showed a relative relationship with LSWT, with positive correlations in winter (r = 0.10) and spring (r = 0.26), and negative correlations in summer (r = −0.30) and fall (r = −0.07). Additionally, evapotranspiration parameters aligned with precipitation changes throughout the seasons, highlighting the significant influence of climate on Zarivar Lake. Full article

(This article belongs to the Proceedings of ECRS 2023)

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7 pages, 4101 KB

Open AccessProceeding Paper

Generating Super Spatial Resolution Products from Sentinel-2 Satellite Images

by Mohammad Reza Zargar and Mahdi Hasanlou

Environ. Sci. Proc. 2024, 29(1), 78; https://doi.org/10.3390/ECRS2023-16889 - 27 Mar 2024

Abstract

Access to high spatial resolution satellite images enables more accurate and detailed analysis of these images. Furthermore, it facilitates easier decision-making on a wide range of issues. Nevertheless, there are commercial satellites such as Worldview that have provided a spatial resolution of fewer [...] Read more.

Access to high spatial resolution satellite images enables more accurate and detailed analysis of these images. Furthermore, it facilitates easier decision-making on a wide range of issues. Nevertheless, there are commercial satellites such as Worldview that have provided a spatial resolution of fewer than 2.0 m, but using them for large areas or multi-temporal analysis of an area brings huge costs. Thus, to tackle these limitations and access free satellite images with a higher spatial resolution, there are challenges that are known as single-image super-resolution (SISR). The Sentinel-2 satellites were launched by the European Space Agency (ESA) to monitor the Earth, which has enabled access to free multi-spectral images, five-day time coverage, and global spatial coverage to be among the achievements of this launch. Also, it led to the creation of a new flow in the field of space businesses. These satellites have provided bands with various spatial resolutions, and the Red, Green, Blue, and NIR bands have the highest spatial resolution by 10 m. In this study, therefore, to recover high-frequency details, increase the spatial resolution, and cut down costs, Sentinel-2 images have been considered. Additionally, a model based on Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) has been introduced to increase the resolution of 10 m RGB bands to 2.5 m. In the proposed model, several spatial features were extracted to prevent pixelation in the super-resolved image and were utilized in the model computations. Also, since there is no way to obtain higher-resolution (HR) images in the conditions of the Sentinel-2 acquisition image, we preferred to simulate data instead, using a sensor with a higher spatial resolution that is similar in spectral bands to Sentinel-2 as a reference and HR image. Hence, Sentinel-Worldview image pairs were prepared, and the network was trained. Finally, the evaluation of the results obtained showed that while maintaining the visual appearance, it was able to maintain some spectral features of the image as well. The average Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Spectral Angle Mapper (SAM) metrics of the proposed model from the test dataset were 37.23 dB, 0.92, and 0.10 radians, respectively. Full article

(This article belongs to the Proceedings of ECRS 2023)

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7 pages, 1774 KB

Open AccessProceeding Paper

Hydrothermal Alteration Features Enhancement and Mapping Using High-Resolution Hyperspectral Data

by Soufiane Hajaj, Abderrazak El Harti, Amine Jellouli, Saloua Mnissar Himyari and Abderrazak Hamzaoui

Environ. Sci. Proc. 2024, 29(1), 77; https://doi.org/10.3390/ECRS2023-16888 - 27 Mar 2024

Abstract

Hydrothermal alteration mapping is considered as a widely adopted step in the mineral exploration of numerous ore deposits. In this work, the wavelength mapping and relative absorption band depth (RBD) method were applied to map hydrothermal alterations in a site from the abandoned [...] Read more.

Hydrothermal alteration mapping is considered as a widely adopted step in the mineral exploration of numerous ore deposits. In this work, the wavelength mapping and relative absorption band depth (RBD) method were applied to map hydrothermal alterations in a site from the abandoned mine of Idikel, western Anti-Atlas, Morocco. Fe²⁺/Fe³⁺, Al-OH, and Mg-Fe-OH/CO₃ hydrothermal alteration minerals were targeted based on HyMap airborne imaging spectroscopy data. Using the wavelength mapping approach, the 900 to 1205 nm, 2094 to 2217 nm, and 2264 to 2318 nm ranges were selected to map Fe²⁺/Fe³⁺, Al-OH, and Mg-Fe-OH/CO₃ absorption features, respectively. By carefully selecting these spectral ranges, the study aimed to achieve the accurate and reliable mapping of hydrothermal alteration features. The highest interpolated depth of Al-OH features was matched with a major cluster of pixels at 2200 nm. The highest interpolated depth of Mg-Fe-OH/CO₃ was depicted at 2300 nm. The highest interpolated depth of Fe²⁺/Fe³⁺ was depicted between 900 and 1000. The relative absorption band depth method was also applied to enhance the detectability of hydrothermal alteration minerals. This method involves assessing the depth of the absorption bands associated with the target minerals, allowing for a detailed characterization of the alteration features. The combination of both wavelength mapping and enhancement methods contributed to a comprehensive and robust hydrothermal alteration mapping process. The identification of Fe²⁺/Fe³⁺, Al-OH, and Mg-Fe-OH/CO₃ manifestations provided valuable insights into potential mineralization zones within the study area. Overall, this research contributes to the advancement of hydrothermal alteration mapping using hyperspectral data by selecting the required HyMap bands for mapping targeted alterations. The combination of wavelength mapping and enhancement methods proves to be a powerful approach for accurately identifying and characterizing hydrothermal alteration features using specific hyperspectral channels. The findings from this study can aid future mineral exploration endeavors in similar geological settings, providing valuable guidance for locating potential mineral resources in mountainous and challenging terrains. Full article

(This article belongs to the Proceedings of ECRS 2023)

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7 pages, 2913 KB

Open AccessProceeding Paper

Evaluation of CartoDEM with the Ice, Cloud, and Land Elevation Satellite-2 and Global Ecosystem Dynamics Investigation Spaceborne LiDAR Datasets for Parts of Plain Region in Moga District, Punjab

by Ashutosh Bhardwaj, Hari Shanker Srivastava and Raghavendra Pratap Singh

Environ. Sci. Proc. 2024, 29(1), 73; https://doi.org/10.3390/ECRS2023-16887 - 27 Mar 2024

Cited by 1

Abstract

The CartoDEM Version 3 Release 1 openly accessible datasets are currently the most reliable datasets for relatively plain regions in India specifically. The aim of the presented study is to evaluate CartoDEM with respect to two openly accessible spaceborne LiDAR datasets from two [...] Read more.

The CartoDEM Version 3 Release 1 openly accessible datasets are currently the most reliable datasets for relatively plain regions in India specifically. The aim of the presented study is to evaluate CartoDEM with respect to two openly accessible spaceborne LiDAR datasets from two LiDAR sensors: the Advanced Topographic Laser Altimeter System (ATLAS) on board the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI) over the International Space Station (ISS). The differences and deviations were computed for CartoDEM and LiDAR footprint elevations for the two datasets, namely, ICESat-2 and GEDI. The difference values were filtered for footprints with differences between 0 and 2.5 in the DEM and LiDAR elevation values. Besides this, an overall estimate was also calculated for the elevation values obtained over the surface, i.e., the ground, as well as objects such as the trees or buildings. The RMSEs were observed to be 1.16 m and 1.74 m for the ICESat-2 and GEDI datasets for the points/footprints on the terrain, whereas when considering similar parameters for the two datasets, the RMSEs were found to be 1.78 m and 5.48 m for the ICESat-2 and GEDI footprints on the surface (terrain/object), respectively. This study reveals that CartoDEM is highly accurate in the plain regions when validated with respect to the ICESat-2 datasets, which work via the photon counting technique. Further, it was observed that ICESat-2’s performance is better than that of the GEDI mission for terrain height. Thus, it was observed that the spaceborne LiDAR datasets from ICESat-2 can be utilized for the validation of DEMs and can be useful for applications where an input to a DEM is required for engineering or modeling applications. Full article

(This article belongs to the Proceedings of ECRS 2023)

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1 pages, 140 KB

Open AccessEditorial

Statement of Peer Review

by Konstantinos Moustris and Nastos Panagiotis

Environ. Sci. Proc. 2023, 26(1), 213; https://doi.org/10.3390/environsciproc2023026213 - 25 Mar 2024

Abstract

In submitting conference proceedings to Environment Sciences Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of 16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023)

4 pages, 4180 KB

Open AccessProceeding Paper

Towards Modeling of the Landscape Evolution of Los Naranjos Archaeological Site, Honduras

by Nohemy Lizeth Rivera Gutiérrez

Environ. Sci. Proc. 2023, 28(1), 32; https://doi.org/10.3390/environsciproc2023028032 - 15 Mar 2024

Abstract

Los Naranjos is an archaeological site inhabited since approximately 800 BC. The objective is to analyze the landscape of this site to understand the territorial, social, and cultural dynamics, along with its natural environment, since pre-Hispanic times. The methodology involves a documentary review [...] Read more.

Los Naranjos is an archaeological site inhabited since approximately 800 BC. The objective is to analyze the landscape of this site to understand the territorial, social, and cultural dynamics, along with its natural environment, since pre-Hispanic times. The methodology involves a documentary review of investigations, and a search for mappings and reconstructions of previous studies, historical sources, and fieldwork. Preliminary results include a review of existing sources for model generation. Full article

(This article belongs to the Proceedings of IV Conference on Geomatics Engineering)

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5 pages, 237 KB

Open AccessProceeding Paper

Evaluation of Water Vapor-Weighted Mean Temperature Models in GNSS Station ACOR

by Raquel Perdiguer-López, José Luis Berné Valero and Natalia Garrido-Villen

Environ. Sci. Proc. 2023, 28(1), 31; https://doi.org/10.3390/environsciproc2023028031 - 7 Mar 2024

Cited by 1

Abstract

The delay of GNSS signals in the neutral atmosphere allow the determination of atmospheric water vapor. The conversion factor of the delay in the water vapor uses the water vapor-weighted mean temperature, T_m, which is a crucial parameter to improve the [...] Read more.

The delay of GNSS signals in the neutral atmosphere allow the determination of atmospheric water vapor. The conversion factor of the delay in the water vapor uses the water vapor-weighted mean temperature, T_m, which is a crucial parameter to improve the quality of conversion. This study analyzed two different types of models: linear models such as Bevis, Mendes and Ortiz de Galisteo, and empirical models such as GPT2w, GPT3 and GWMT_D. The performance of the models was analyzed using the models as the source of T_m to obtain the precipitable water vapor (PWV), which was compared to a reference set of PWV obtained from a matched radiosonde site. The results show a better performance of the linear models, with the Bevis model achieving the best performance. Full article

(This article belongs to the Proceedings of IV Conference on Geomatics Engineering)

2 pages, 179 KB

Open AccessEditorial

Statement of Peer Review

by María Belén Benito Oterino, José Fernández Torres, Rosa María García Blanco, Jorge Miguel Gaspar Escribano, Miguel Ángel Manso Callejo and Antonio Vázquez Hoehne

Environ. Sci. Proc. 2023, 28(1), 30; https://doi.org/10.3390/environsciproc2023028030 - 6 Mar 2024

Abstract

In submitting conference proceedings to Environment Sciences Proceedings, the volume editors of these proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of IV Conference on Geomatics Engineering)

5 pages, 1371 KB

Open AccessProceeding Paper

Detection of Methane Point Sources with High-Resolution Satellites

by Itziar Irakulis-Loitxate, Javier Roger, Javier Gorroño, Adriana Valverde and Luis Guanter

Environ. Sci. Proc. 2023, 28(1), 29; https://doi.org/10.3390/environsciproc2023028029 - 26 Feb 2024

Cited by 1

Abstract

Methane is the second most important anthropogenic greenhouse gas, whose emissions need to be mitigated to curb global warming. There is a large uncertainty about its point source, but thanks to a new generation of high-spatial-resolution satellites, this situation is changing drastically, revealing [...] Read more.

Methane is the second most important anthropogenic greenhouse gas, whose emissions need to be mitigated to curb global warming. There is a large uncertainty about its point source, but thanks to a new generation of high-spatial-resolution satellites, this situation is changing drastically, revealing thousands of emission point sources worldwide. In this paper, several hotspot areas are mapped, looking for methane emission point sources with different types of high-resolution satellites. Our results demonstrate the potential of satellite remote sensing to reveal methane emission point sources in different scenarios. Full article

(This article belongs to the Proceedings of IV Conference on Geomatics Engineering)

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5 pages, 578 KB

Open AccessProceeding Paper

Preliminary Results of Satellite-Derived Nearshore Bathymetry

by Ausiàs Roch-Talens, Josep Eliseu Pardo-Pascual and Jaime Almonacid-Caballer

Environ. Sci. Proc. 2023, 28(1), 28; https://doi.org/10.3390/environsciproc2023028028 - 15 Feb 2024

Abstract

This article presents the preliminary results of a study on satellite-derived bathymetry. The purpose of this research is to explore the use of remote sensing and optical imagery for mapping the depth of coastal waters. This study uses empirical models to estimate the [...] Read more.

This article presents the preliminary results of a study on satellite-derived bathymetry. The purpose of this research is to explore the use of remote sensing and optical imagery for mapping the depth of coastal waters. This study uses empirical models to estimate the water depth based on the optical properties of the water column. To carry this out, it employs atmospheric correction algorithms to remove the influence of atmospheric scattering and absorption on the optical signals. The authors then apply the empirical models to the corrected imagery to obtain the bathymetric maps. The study shows promising results (RMSE ranging between 0.49 and 0.96m using the Lyzenga methodology), with the estimated depths generally consistent with the available ground-truth data. However, the accuracy of the estimated depths varies depending on the water conditions, such as the presence of waves and bottom type. The authors conclude that satellite-derived bathymetry has great potential for coastal applications, such as environmental monitoring and coastal management. Full article

(This article belongs to the Proceedings of IV Conference on Geomatics Engineering)

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7 pages, 4419 KB

Open AccessProceeding Paper

Impact of Global Warming on Water Height Using XGBOOST and MLP Algorithms

by Nilufar Makky, Khalil Valizadeh Kamran and Sadra Karimzadeh

Environ. Sci. Proc. 2024, 29(1), 83; https://doi.org/10.3390/ECRS2023-16864 - 8 Feb 2024

Abstract

Over the past few years, the effects of global warming have become more pronounced, particularly with the melting of the polar ice caps. This has led to an increase in sea levels, which poses a threat of flooding to coastal cities and islands. [...] Read more.

Over the past few years, the effects of global warming have become more pronounced, particularly with the melting of the polar ice caps. This has led to an increase in sea levels, which poses a threat of flooding to coastal cities and islands. Furthermore, monitoring and analyzing changes in water levels has proven effective for predicting natural disasters caused by the rising sea levels. One vital factor in understanding the impact of global warming is the sea surface height (SSH). Measuring the SSH can provide valuable information about changes in ocean levels. This study used data from the Jason 2 altimetry radar satellite, which provided 36 cycle periods per year, to investigate the water heights around the Hawaiian Islands in 2019. To accurately evaluate the water height variations, a specific area near the Pacific Ocean close to the Hawaiian Islands was selected. By analyzing the collected satellite data, a chart of water heights was generated, which showed an overall increase in the height over one year. This analysis provided evidence of changing ocean levels in the region, highlighting the urgency of addressing the potential threats faced by coastal communities. This study also explored several factors that contribute to water height variations, such as the sea surface temperature, precipitation, and sea surface pressure in the Google Earth Engine cloud-based platform. Algorithms, including MLP and XGBOOST, were used to model the water height within the specified range. The results showed that the XGBOOST algorithm was superior in accurately predicting the water height, with an impressive R-squared value of 0.95. In comparison, the MLP algorithm achieved an R-squared value of 0.92. This study shows that advanced machine learning techniques are effective in understanding and modeling the complex changes in the water height due to climate change. This information can help policymakers and local authorities make informed decisions and create strategies to protect coastal cities and islands from the growing threats of rising sea levels. Taking proactive measures is crucial in reducing the risks posed by more frequent and severe natural disasters caused by global warming. Full article

(This article belongs to the Proceedings of ECRS 2023)

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7 pages, 1318 KB

Open AccessProceeding Paper

Super-Resolution of Sentinel-2 RGB Images with VENµS Reference Images Using SRResNet CNNs

by Amir Sharifi and Reza Shah-Hosseini

Environ. Sci. Proc. 2024, 29(1), 80; https://doi.org/10.3390/ECRS2023-16863 - 8 Feb 2024

Abstract

Super-resolution (SR) is a well-established technique used to enhance the resolution of low-resolution images. In this paper, we introduce a novel approach for the super-resolution of Sentinel-2 10 m RGB images using higher-resolution Venus 5 m RGB images. The proposed method takes advantage [...] Read more.

Super-resolution (SR) is a well-established technique used to enhance the resolution of low-resolution images. In this paper, we introduce a novel approach for the super-resolution of Sentinel-2 10 m RGB images using higher-resolution Venus 5 m RGB images. The proposed method takes advantage of a modified SRResNet network, integrates perceptual loss based on the VGG network, and incorporates a learning rate decay strategy for improved performance. By leveraging higher-resolution VENµS 5 m RGB images as reference images, this approach aims to generate high-quality super-resolved images of Sentinel-2 10 m RGB images. The modified SRResNet network was designed to capture and learn underlying patterns and details present in Venus images, enabling it to effectively enhance the resolution of Sentinel-2 images. In addition, the inclusion of perceptual loss based on the VGG network helps preserve important visual features and maintain the overall image quality. The learning rate decay strategy ensures the network converges to an optimal solution by gradually reducing the learning rate during the training process. Our research contributes to the field of super-resolution by offering a novel approach specifically tailored for enhancing the resolution of Sentinel-2 10 m RGB images using Venus 5 m RGB images. The proposed methodology has the potential to benefit various applications, such as remote sensing, land cover analysis, and environmental monitoring, where high-resolution imagery is crucial for accurate and detailed analysis. In summary, our approach presents a promising solution for the super-resolution of Sentinel-2 10 m RGB images, providing an effective means to obtain higher-resolution imagery by leveraging the complementary information from Venus 5 m RGB images. We used the SEN2VENµS dataset for this research. The SEN2VENµS dataset comprises cloud-free surface reflectance patches obtained from Sentinel-2 imagery. Notably, these patches are accompanied by corresponding reference surface reflectance patches captured at a remarkable 5 m resolution by the VENµS Micro-Satellite on the same acquisition day. To assess the effectiveness of the proposed approach, we evaluated it using widely used metrics such as the mean squared error (MSE), the peak signal-to-noise ratio (PSNR), and the structural similarity index (SSIM). These metrics provided quantitative measurements of the quality and fidelity of the super-resolved images. Experimental results demonstrate the effectiveness of our proposed approach in achieving improved super-resolution performance compared to existing methods. As an example, our method achieved a PSNR of 35.70 and a SSIM of 0.94 on the training dataset, outperforming the bicubic interpolation method, which yielded a PSNR of 29.53 and a SSIM of 0.92. On the validation dataset, our approach achieved a PSNR of 40.3809 and a SSIM of 0.98, while the bicubic interpolation method achieved a PSNR of 34.26 and a SSIM of 0.94. Finally, on the test dataset, our approach achieved a PSNR of 29.8231 and a SSIM of 0.90, whereas the bicubic interpolation method yielded a PSNR of 26.99 and a SSIM of 0.85. The evaluation based on MSE, PSNR, and SSIM metrics showcases the enhanced visual quality, increased image resolution, and improved similarity to the reference Venus images. Full article

(This article belongs to the Proceedings of ECRS 2023)

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6 pages, 1750 KB

Open AccessProceeding Paper

Remote Sensing Biological Pump Potential: Plankton Spatio-Temporal Modelling in the Philippine Seas with Emphasis on the Effects of Typhoons

by Khim Cathleen Saddi and Leni Yap-Dejeto

Environ. Sci. Proc. 2024, 29(1), 79; https://doi.org/10.3390/ECRS2023-16862 - 8 Feb 2024

Abstract

This study focuses on the quantification and forecasting of the biological pump potential in the Philippine seas, specifically inside the Exclusive Economic Zone (EEZ). Variabilities and disturbances that might potentially influence ocean productivity such as increased sea surface temperature (SST), and the high [...] Read more.

This study focuses on the quantification and forecasting of the biological pump potential in the Philippine seas, specifically inside the Exclusive Economic Zone (EEZ). Variabilities and disturbances that might potentially influence ocean productivity such as increased sea surface temperature (SST), and the high frequency of typhoons in the Philippines were investigated. CHL and SST spatio-temporal maps were used to provide visualization for the trends and phenomena before, during, and after typhoon occurrence for the years 2019–2021. Integrating the NASA Ocean Color data of CHL and SST with typhoon tracks, the biological pump potential annual estimate was generated. Full article

(This article belongs to the Proceedings of ECRS 2023)

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11 pages, 6485 KB

Open AccessProceeding Paper

Retrieval of Soil Moisture Using Time Series of Radar and Optical Remote Sensing Data at 10 m Resolution

by Mojtaba Atar, Reza Shah-Hosseini and Omid Ghaffari

Environ. Sci. Proc. 2024, 29(1), 75; https://doi.org/10.3390/ECRS2023-16861 - 7 Feb 2024

Cited by 2

Abstract

Soil moisture (SM) is an important variable related to the health of terrestrial ecosystems, agriculture, the continental water cycle, etc. It also provides an opportunity for drought monitoring, flood forecasting, weather forecasting, and the calibration of hydrological models. This study aims to estimate [...] Read more.

Soil moisture (SM) is an important variable related to the health of terrestrial ecosystems, agriculture, the continental water cycle, etc. It also provides an opportunity for drought monitoring, flood forecasting, weather forecasting, and the calibration of hydrological models. This study aims to estimate the surface soil moisture at a high spatial resolution (10 m) by combining radar and optical remote sensing data and improving the spatial resolution and accuracy. Synthetic aperture radar (SAR) operates with the competence to acquire data in any weather condition. The SAR images were acquired by C-band SAR sensors in the VV polarization boarded on Sentinel-1 satellites and the optical images were obtained from a Sentinel-2 multispectral instrument. The main algorithm involves the retrieval of soil moisture using radar data through a change detection (CD) method that is somehow combined with the WCM (parameters include vegetation descriptors and model coefficients) to estimate the SM and reduce the effect of vegetation cover. The method is applied to 13 months of time-series satellite data, from 7 November 2019 to 20 October 2020, over Salamanca (western Spain) and is validated using field data acquired at a study site with the use of a TDR sensor. The results showed good accuracy between the retrieved and ground measurement soil moisture data (Root Mean Square Error (RMSE) of 0.053

m^{3}

/

m^{3}

) and the obtained accuracy is promising compared to recent similar works. Full article

(This article belongs to the Proceedings of ECRS 2023)

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5 pages, 1853 KB

Open AccessProceeding Paper

Improved Hapke Model to Characterize Soil Moisture Content Variation

by Anxin Ding, Han Ma, Ping Zhao, Shenglian Ren, Kaijian Xu and Hailan Jiang

Environ. Sci. Proc. 2024, 29(1), 76; https://doi.org/10.3390/ECRS2023-16859 - 6 Feb 2024

Abstract

The Hapke model has been widely used in the field of soil remote sensing. However, the latest development of the Hapke model (i.e., Hapke-HSR model) adopted a simple hypothesis to consider the influence of the soil moisture content (SMC), which brought great difficulties [...] Read more.

The Hapke model has been widely used in the field of soil remote sensing. However, the latest development of the Hapke model (i.e., Hapke-HSR model) adopted a simple hypothesis to consider the influence of the soil moisture content (SMC), which brought great difficulties to SMC parameter inversion. This paper presents a method to improve the Hapke model using the improved multilayer radiative transfer model of soil reflectance (MARMIT-2), which can effectively improve the ability of the Hapke-HSR model to characterize the variation in the SMC. Finally, we used the soil database to comprehensively verify the ability of the improved Hapke model. The results show that the improved Hapke can effectively characterize the spectral characteristics of soil and show a higher fitting accuracy (RMSE = 0.009) compared with the Hapke-HSR model (RMSE = 0.031), especially at a high SMC (≥30%). Therefore, the improved Hapke model can better understand soil physical properties and improve the inversion accuracy of soil–vegetation physical parameters, which can be used to enhance agricultural water use efficiency. Full article

(This article belongs to the Proceedings of ECRS 2023)

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Journal Description

Environmental Sciences Proceedings

Vol. 29

ECRS 2023

Vol. 28

CIGEO 2023

Vol. 27

ECAS 2023

Vol. 26

COMECAP 2023

Vol. 25

ECWS-7 2023

Vol. 24

ECERPH-4 2022

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Journal Description

Environmental Sciences Proceedings

Vol. 29

ECRS 2023

Vol. 28

CIGEO 2023​

Vol. 27

ECAS 2023

Vol. 26

COMECAP 2023

Vol. 25

ECWS-7 2023

Vol. 24

ECERPH-4 2022

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

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