European Journal of Remote Sensing最新文献

{"title":"GNSS-R monitoring of soil moisture dynamics in areas of severe drought: example of Dahra in the Sahelian climatic zone (Senegal)","authors":"M. Ha, J. Darrozes, M. Llubes, M. Grippa, G. Ramillien, F. Frappart, F. Baup, Håkan Torbern Tagesson, E. Mougin, I. Guiro, L. Kergoat, H. Nguyen, L. Seoane, G. Dufrechou, P. Vu","doi":"10.1080/22797254.2022.2156931","DOIUrl":"https://doi.org/10.1080/22797254.2022.2156931","url":null,"abstract":"","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47920610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial-spectral hierarchical vision permutator for hyperspectral image classification","authors":"Lifan Ji, Yihao Shao, Jianjun Liu, Liang Xiao","doi":"10.1080/22797254.2022.2153747","DOIUrl":"https://doi.org/10.1080/22797254.2022.2153747","url":null,"abstract":"","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46701731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the application of big data visualization technology in urban road congestion","authors":"Haitao Guo, Lunhui Xu","doi":"10.1080/22797254.2022.2147448","DOIUrl":"https://doi.org/10.1080/22797254.2022.2147448","url":null,"abstract":"","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45772529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Satellite-derived land surface temperature spatial sharpening: A comprehensive review on current status and perspectives","authors":"M. K. Firozjaei, M. Kiavarz, S. K. Alavipanah","doi":"10.1080/22797254.2022.2144764","DOIUrl":"https://doi.org/10.1080/22797254.2022.2144764","url":null,"abstract":"ABSTRACT The purpose of this study is to comprehensively review of Satellite-derived Land Surface Temperature Spatial Sharpening (SLSTSS) studies and provide appropriate solutions to error reduction in SLSTSS presses. Firstly, the initial search was done for the related keywords to SLSTSS, and 391 papers were found over the period 1985 to 2020. Secondly, to eliminate non-relevant papers, several criteria were applied and 207 out of 391 papers were selected for this review. Finally, the assembled database was used to extract important information. Perspectives for future studies can be (1) integrating the results obtained from different models and strategies based on decision level-fusion, (2) solving challenges of remained low-spatial pixel blocking and smoothing effects on sharpened LST image, (3) considering landscape, textural and climatic variables and anthropogenic heat flux in SLSTSS presses, (4) using LST obtained from unmanned aerial vehicles at the satellite overpass time to the SLSTSS results, (5) determining the optimal number of classes in conceptual approaches as well as the size of moving window and the segmentation scale of object-based window in local approaches to train and implement SLSTSS models, (6) and providing a physical approach based on energy balance equations in order for error reduction in SLSTSS presses.","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"55 1","pages":"644 - 664"},"PeriodicalIF":4.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43685850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral-based regression model for destriping of abnormal pixel values in PRISMA hyperspectral image","authors":"P. Sajadi, M. Gholamnia, S. Bonafoni, F. Pilla","doi":"10.1080/22797254.2022.2141659","DOIUrl":"https://doi.org/10.1080/22797254.2022.2141659","url":null,"abstract":"ABSTRACT Hyperspectral imageries are often degraded by systematic sensor-based errors known as “striping noises”. This study implements a spectral-based regression algorithm from highly correlated consecutive bands, i.e. left band, right band or both, to model and reconstruct the abnormal pixel values, stripe noises, in various bands of PRISMA (PRecursore IperSpettrale della Missione Applicativa) imagery. The modeling performance was evaluated based on the statistical difference between the reconstructed images’ pixel values (reflectance) and their corresponding original pixel values. Results referred to the model’s high accuracy in R 2, RMSE, rRMSE and skewness in most bands ). Furthermore, the results indicated that the combination of both bands had higher accuracy and pixels’ homogeneity preservation compared to single-band modeling. Our findings suggested that the algorithm significantly depends on the spectral similarities between neighboring bands so that the higher spectral similarities lead to the higher model performance and vice versa. Subsequently, the minimum model performance was observed in band 143 due to lower spectral similarity, lower spectral correlation and higher wavelength differences with its adjacent right band. Finally, the study suggests that alongside other methods, our algorithm may be used as a reliable, straightforward and accurate alternative for destriping different Earth observation satellite imageries. Limitations of the proposed approach are also discussed.","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"55 1","pages":"622 - 643"},"PeriodicalIF":4.0,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45085053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple-input multiple-output radar, ground-based MIMO SAR for ground deformation monitoring","authors":"F. Mugnai, D. Tarchi","doi":"10.1080/22797254.2022.2141660","DOIUrl":"https://doi.org/10.1080/22797254.2022.2141660","url":null,"abstract":"ABSTRACT This study focuses on investigating the capabilities of a Multiple-input multiple-output RADAR. A Radar interferometer, based on an electronically scanned array in MIMO configuration (MIMO‐SAR), has been assessed for operational use in monitoring phenomena of geological interest, such as landslides unstable slopes. The system applies the very well‐known and proven Ground-Based Interferometric technique. It guarantees a very short refreshing time compared to traditional systems based on the mechanical movement of the radar transceiver on a rail or the mechanical steering of a real antenna. The system can monitor several phenomena having deformation rates too high to be correctly retrieved by traditional systems currently in use. Implementing a prototype termed MELISSA allowed the testing technique’s performances in two real case studies: a landslide and an unstable volcanic flank. The experimental results were compared with LISA, a well-known Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) interferometer. MELISSA allows for obtaining an excellent accuracy, better than 0.01 mm. The range and angular resolution are on the same order of magnitude as those obtained through LISA. However, the refreshing rate obtained from MELISSA, 0.01 s, guarantees a strong coherence even in challenging environmental scenarios as a flank of an active volcano.","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"55 1","pages":"604 - 621"},"PeriodicalIF":4.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44327991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shoreline erosion due to anthropogenic pressure in Calabria (Italy)","authors":"G. Foti, G. Barbaro, G. C. Barillà, P. Mancuso, P. Puntorieri","doi":"10.1080/22797254.2022.2140076","DOIUrl":"https://doi.org/10.1080/22797254.2022.2140076","url":null,"abstract":"","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46235092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Satellite thermographies as an essential tool for the identification of cold air pools: an example from SE Spain","authors":"David Espín Sánchez, J. Olcina Cantos, Carmelo Conesa García","doi":"10.1080/22797254.2022.2133744","DOIUrl":"https://doi.org/10.1080/22797254.2022.2133744","url":null,"abstract":"ABSTRACT The processes involved in the formation of nocturnal temperature inversions (NTIs) are of great relevance throughout the year, notably influencing the surface distribution of minimum temperatures during nights of atmospheric stability. The low density of surface meteorological stations in the study area motivated the use of thermographies for the mapping and identification of cold air pools CAPs. Thermal distribution during stable nights leads to the formation of CAPs in valley areas and depressed areas, and in areas with warmer air (WAM) in orographically complex areas. The thermographies carried out with satellite products from AQUA and SUOMI-NPP (MODIS and VIIRS LST) represent the only tool capable of fully radiographing the territory under study, thus overcoming the limitations in the interpolation of minimum surface temperatures. The main objective of the research was, therefore, to value thermography as an important tool in the identification of CAPs. The products used were subjected to statistical validation with the surface temperatures recorded in meteorological observatories (R2 0.87/0.88 and Bias −1.2/-1.3) with a new objective of making thermal distribution maps in nocturnal stability processes …","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"55 1","pages":"586 - 603"},"PeriodicalIF":4.0,"publicationDate":"2022-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47072564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrieval of land surface temperature from FY3D MERSI-II based on re-fitting Split Window Algorithm","authors":"Zhang Dejun, Yang Shiqi, S. Liang, Liu Xiaoran, Tang Shihao, Zhu Hao, Ye Qinyu, Zhang Xinyu","doi":"10.1080/22797254.2022.2133016","DOIUrl":"https://doi.org/10.1080/22797254.2022.2133016","url":null,"abstract":"ABSTRACT Medium Resolution Spectral Imager II (MERSI-II) is one of the core sensors mounted on the FengYun-3D (FY3D) satellite. Two adjacent 250 m long-wave thermal infrared (TIR) channels provide a considerable opportunity for retrieving Land Surface Temperature (LST) with high spatiotemporal resolution. In this paper, Thermodynamic Initial Guess Retrieval (TIGR) dataset and MODTRAN 4.0 model were used to re-fit the parameters of the Split-Window (SW) algorithm suitable for MERSI-II TIR channels, and then the daily 250 m resolution MERSI-II LST product was retrieved. The Radiance-based (R-based) method results showed that the bias value between simulated by MODTRAN4.0 and the input is 0.16 K, and the MAE value is 0.38 K. Inter-comparison method results showed that the MERSI-II LST and MODIS LST products were consistent in spatial distribution, but there were certain differences between MODIS LST and MERSI-II LST at different land cover types. T-based method results showed that R values between the site-observed LST and MERSI-II LST retrieved by SW algorithm exceeded 0.92, the bias value was between 3.6 K and 4.4 K, and the MAE value was between 2.6 K and 4.5 K. The above results indicating that the SW algorithm proposed in this study has good accuracy and applicability.","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"55 1","pages":"1 - 18"},"PeriodicalIF":4.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41515962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning for earth resource and environmental remote sensing","authors":"Carlos Enrique Montenegro Marín, Xuyun Zhang, N. Gunasekaran","doi":"10.1080/22797254.2022.2128432","DOIUrl":"https://doi.org/10.1080/22797254.2022.2128432","url":null,"abstract":"Remote sensing and image analysis are now key mechanisms for environmental surveillance as well as other environmental assets. Specifically, remote sensing involves evaluating objects without communicating with them. As a result of the growing number of people and numerous human processes, long-term monitoring techniques are becoming increasingly important. Over the past few decades, deep learning has gained prominence in the analysis of remotely sensed data, and today it is widely used in real-time image processing. As a consequence, the systems became more effective and could be applied to a variety of remote sensing applications, including the monitoring of earth resources, environmental assessment, and earth science. As well as the capability to cope with high-resolution satellite imaging information, the deep learning methodology offers the features of global resource monitoring and environmental assessment. Additionally, a quality metric illustrating deep learning’s accomplishments is provided, as well as future constraints and aspirations related to monitoring the planet’s resources and environmental assessment via deep learning. The effectiveness of deep learning approaches for remote sensing applications would significantly improve when the aforementioned gaps in research are acknowledged. This special issue intends to investigate foundational and practical studies in deep learning for remotely sensed data. Following the peer-review process, five articles were qualified for publication in this special issue in accordance with the evaluation standards. The following essential characteristics highlight the recognised works’ notable technological advancement: The first article, entitled “Study on Characteristics of Tight Oil Reservoir in Ansai Area of Ordos Basin – Take the Chang 6 Section of Ordos Basin as an example” (Liu et al., 2021) have investigated the reservoir properties of the Chang 6 oil establishment in the Ordos Basin’s Ansai area using a number of theoretical statistics. The findings indicate that the lithologic features of the Chang 6 reservoir group in the Ansai area in the northeast seem to be mostly feldspathic sandstone, preceded by lithic feldspathic sandstone. Both the reservoir categories and Chang 6 member reservoirs in the Ansai area depict the lowest porosity and ultra-low permeability. The next article, entitled “Deep Transfer Learning based Fusion Model for Environmental Remote Sensing Image Classification Model” (Hilal et al., 2022) have proposed the DTLF-ERSIC approach in this research, is a novel DTL-based fusion model for environmental remote sensing image classification that concentrates on the building of a fusion prototype to merge numerous feature vectors and therefore achieve greater classification efficiency. The DTLFERSIC approach combines three methods for feature extraction using entropy. A detailed experimental examination of the DTLF-ERSIC approach was performed on a testing dataset, and the outcome","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"55 1","pages":"1 - 2"},"PeriodicalIF":4.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44453575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}