Article
Remote Sensing
Igor Klein, Soner Uereyen, Christina Eisfelder, Vladimir Pankov, Natascha Oppelt, Claudia Kuenzer
Summary: Negative impacts of locust species on agriculture have always been a major threat to food security and livelihoods, especially for local communities. Locust management and control have reduced the frequency and intensity of plagues and outbreaks. However, political insecurity, armed conflicts, changing climate, and land use management can contribute to new outbreaks. Geospatial and remote sensing data are important for locust research and management, but their practical usage is still limited.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Environmental Sciences
Yongjing Mao, Daniel L. Harris, Zunyi Xie, Stuart Phinn
Summary: Coastal geomorphic classification is crucial for identifying the depositional environment along coastlines. Previous methods relied heavily on manual efforts and expert opinions, which limited their application at a global scale. In this study, satellite images and digital elevation models were used to classify coastal geomorphology on a global scale. The incorporation of shape descriptors extracted from shoreline vector data improved the accuracy of the classification. The output dataset can be used for various coastal management purposes.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Geochemistry & Geophysics
Ronny Haensch, Claudio Persello, Gemine Vivone, Javiera Castillo Navarro, Alexandre Boulch, Sebastien Lefevre, Bertrand Le Saux
Summary: The Image Analysis and Data Fusion Technical Committee of IEEE GRSS has been organizing the annual Data Fusion Contest since 2006, aiming to promote the development of methods for extracting geospatial information and establish benchmarks for scientific challenges in remote sensing image analysis.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2022)
Article
Environmental Sciences
Jiadi Yin, Ping Fu, Nicholas A. S. Hamm, Zhichao Li, Nanshan You, Yingli He, Ali Cheshmehzangi, Jinwei Dong
Summary: This study summarized the methods of integrating remote sensing and geospatial big data (GBD) and evaluated them through a case study of urban land use mapping in Hangzhou, China. The results showed that decision-level integration (DI) generally outperforms feature-level integration (FI) in classification, and a combination of the two methods can improve urban land use mapping.
Article
Computer Science, Artificial Intelligence
Jose F. Aldana-Martin, Jose Garcia-Nieto, Maria del Mar Roldan-Garcia, Jose F. Aldana-Montes
Summary: Remote sensing technology provides a technological framework for advanced applications in various fields, with Earth Observation becoming increasingly important. Knowledge-driven approaches remain a challenge in remote sensing, with semantic technologies showing high success in knowledge representation in the Earth Observation domain.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Theory & Methods
Maroua Masmoudi, Sana Ben Abdallah Ben Lamine, Hajer Baazaoui Zghal, Bernard Archimede, Mohamed Hedi Karray
Summary: This study introduces a knowledge hypergraph-based approach for data integration and querying, applied to Earth Observation data. Results show that the proposed method enhances query processing in terms of accuracy, completeness, and semantic richness of response.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Information Systems
Anjali Goswami, Deepak Sharma, Harani Mathuku, Syam Machinathu Parambil Gangadharan, Chandra Shekhar Yadav, Saroj Kumar Sahu, Manoj Kumar Pradhan, Jagendra Singh, Hazra Imran
Summary: Remote sensing technology has been widely used in natural resource fields, providing precise information. It is necessary to develop automatic change detection techniques to improve classification accuracy and reduce time. This study focuses on improving machine learning classification accuracy by comparing training samples and image differences.
Article
Environmental Sciences
Shridhar D. Jawak, Bo N. Andersen, Veijo A. Pohjola, Oystein Godoy, Christiane Hubner, Inger Jennings, Dariusz Ignatiuk, Kim Holmen, Agnar Sivertsen, Richard Hann, Hans Tommervik, Andreas Kaab, Malgorzata Blaszczyk, Roberto Salzano, Bartlomiej Luks, Kjell Arild Hogda, Rune Storvold, Lennart Nilsen, Rosamaria Salvatori, Kottekkatu Padinchati Krishnan, Sourav Chatterjee, Dag A. Lorentzen, Rasmus Erlandsson, Tom Rune Lauknes, Eirik Malnes, Stein Rune Karlsen, Hiroyuki Enomoto, Ann Mari Fjaeraa, Jie Zhang, Sabine Marty, Knut Ove Nygard, Heikki Lihavainen
Summary: SIOS is an international partnership focusing on the environment and climate in and around Svalbard, aiming to develop an efficient observing system and support various scientific activities for the Arctic science community. The COVID-19 pandemic has affected research activities in Svalbard, leading SIOS to initiate operational activities to mitigate the new challenges posed by the global crisis.
Article
Environmental Studies
Polina Lemenkova
Summary: This study documents the changes in Land Use/Land Cover (LULC) in the saline lakes region of north Tunisia, Sahara Desert. Remote sensing data and GIS software were used to evaluate the LULC changes in the salt pans of Tunisia. The study shows that the changes in salt lakes are influenced by seasonal variations and the extent of water/land/salt/sand/vegetation areas.
Article
Remote Sensing
Zhenfeng Shao, Wenfu Wu, Deren Li
Summary: Urban remote sensing is crucial for urban observation, requiring data with high resolution. Existing satellites cannot fulfill all requirements, thus coordination of data is necessary. This study introduced an urban spatio-temporal-spectral observation model to address the gap in existing frameworks, and proposed four specific applications.
GEO-SPATIAL INFORMATION SCIENCE
(2021)
Article
Environmental Sciences
Luca Oggioni, David Sanchez del Rio Kandel, Giorgio Pariani
Summary: This article investigates the application of a multiband spatial compressive sensing acquisition system based on pushbroom scanning in cryosphere monitoring. Through the analysis and comparison of reconstruction algorithms for static images and moving frames, design guidelines are provided.
Article
Geochemistry & Geophysics
Xiaoyang Zhao, Keyun Zhao, Siyao Li, Xianghai Wang
Summary: In this study, a geospatial-awareness network (GeSANet) based on the geospatial position matching mechanism (PMM) and the geospatial content reasoning mechanism (CRM) is proposed for RSI change detection (RSI-CD). The method effectively addresses the challenges of registration dependence and pseudo-change information response caused by high spatial resolution and low spectral resolution, respectively. Experimental results demonstrate the robustness and validity of the proposed method for multitemporal RSI-CD.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Alessandro Sebastianelli, Maria Pia Del Rosso, Silvia Liberata Ullo, Paolo Gamba
Summary: Quantum machine learning (QML), an emerging technology, is explored in the field of earth observation and remote sensing. A hybrid quantum neural network (QNN) structure is proposed for land cover classification, with a strategy for selecting the most efficient combination of qubits. The proposed method achieves better performance with less model complexity compared to standard techniques, and improves model resilience to dataset imbalance. The research code is publicly available.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Environmental Sciences
Pieter Kempeneers, Tomas Kliment, Luca Marletta, Pierre Soille
Summary: This paper focuses on optimizing computing resources for processing geospatial image data in a cloud computing infrastructure. The study tests parallelization using two strategies: image tiling and multi-threading, aiming to minimize processing time. The combination of tiling and multi-threading techniques achieves the maximum speedup. However, there is a trade-off between the two techniques, as tiling improves speedup but introduces overhead and increases the portion of the program that can only run serially. The optimal strategy depends on the application scale, algorithm implementation, and available computing resources.
Article
Computer Science, Software Engineering
Samantha Wittke, Anne Fouilloux, Petteri Lehti, Juuso Varho, Arttu Kivimaki, Maiju Karhu, Mika Karjalainen, Matti Vaaja, Eetu Puttonen
Summary: This article introduces a toolkit called EODIE that extracts object-level time-series information from multiple multispectral satellite remote sensing platforms and produces analysis-ready products for subsequent data analysis.
Article
Remote Sensing
Sergii Skakun, Eric F. Vermote, Andres Eduardo Santamaria Artigas, William H. Rountree, Jean-Claude Roger
Summary: A reliable cloud mask is essential for generating high-quality geoinformation products from optical satellite imagery. This paper introduces a new reference cloud dataset, GSFC-Cloud, based on ground-based images of the sky and proposes an automated system for ground-based data collection. By adding a parallax feature to estimate subpixel shifts between red and green bands in Sentinel-2 imagery, overdetection of clouds can be reduced and the performance of LaSRC for cloud detection can be improved.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Geochemistry & Geophysics
Jose Luis Villaescusa-Nadal, Eric Vermote, Belen Franch, Andres E. Santamaria-Artigas, Jean-Claude Roger, Sergii Skakun
Summary: The goal of this study is to develop accurate and consistent surface reflectance and albedo products for analyzing global albedo trends. Distinguishing between cloud and snow is challenging due to the limitations of the sensor used. To address this issue, the researchers propose an algorithm based on spectral analysis to identify clear land and snow pixels using satellite and reanalysis data.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Sergii Skakun, Jan Wevers, Carsten Brockmann, Georgia Doxani, Matej Aleksandrov, Matej Batic, David Frantz, Ferran Gascon, Luis Gomez-Chova, Olivier Hagolle, Dan Lopez-Puigdollers, Jerome Louis, Matic Lubej, Gonzalo Mateo-Garcia, Julien Osman, Devis Peressutti, Bringfried Pflug, Jernej Puc, Rudolf Richter, Jean-Claude Roger, Pat Scaramuzza, Eric Vermote, Nejc Vesel, Anze Zupanc, Lojze Zust
Summary: This paper summarizes the results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted by the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). Ten cloud detection algorithms developed by different organizations were evaluated and showed good agreement in detecting thick clouds but had higher uncertainties in detecting thin/semi-transparent clouds.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Xiaojuan Huang, Yangyang Fu, Jingjing Wang, Jie Dong, Yi Zheng, Baihong Pan, Sergii Skakun, Wenping Yuan
Summary: This study utilized synthetic aperture radar and satellite image data, combined with a time-weighted dynamic time warping method, to successfully generate a winter cereal map of Europe with a spatial resolution of 30 meters. Validation against agricultural census data showed high accuracy of the method. Additionally, the method can identify the distribution of winter cereals two months before harvest, providing timely monitoring and identification of crop growth at a continental level.
Article
Geography, Physical
Belen Franch, Juanma Cintas, Inbal Becker-Reshef, Maria Jose Sanchez-Torres, Javier Roger, Sergii Skakun, Jose Antonio Sobrino, Kristof Van Tricht, Jeroen Degerickx, Sven Gilliams, Benjamin Koetz, Zoltan Szantoi, Alyssa Whitcraft
Summary: Crop calendars are important for monitoring crop development, and existing global products only provide information at national or subnational level. This study presents gridded maps for wheat and maize crop calendars, capturing their spatial variability. The maps are generated using global products and evaluated using a Random Forest algorithm.
GISCIENCE & REMOTE SENSING
(2022)
Article
Geography, Physical
Yiming Zhang, Sergii Skakun, Michael Oluwatosin Adegbenro, Qing Ying
Summary: Worldwide economic development and population growth have led to significant changes in urban land use. This study utilizes a deep learning model trained on a benchmark dataset to map and quantify urban land use changes in the Washington DC-Baltimore area. The results show that a substantial portion of urban land experienced changes, particularly in the construction of commercial and residential buildings.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2022)
Article
Geography, Physical
Victor Hugo Rohden Prudente, Sergii Skakun, Lucas Volochen Oldoni, Haron A. M. Xaud, Maristela R. Xaud, Marcos Adami, Ieda Del ' Arco Sanches
Summary: Remote sensing plays a crucial role in the mapping of Land Use and Land Cover (LULC) worldwide, particularly in areas with frequent cloud cover. Combining optical and SAR data improves the accuracy of classification. This study investigates the incorporation of SAR data into the classification process using optical data in the mapping of LULC in the Roraima State, Brazil. The results show that a combination of multi-temporal surface reflectance, vegetation index, backscatter coefficient, and polarization data yields the most accurate LULC mapping.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Jaemin Eun, Sergii Skakun
Summary: The ongoing military conflict in Eastern Ukraine has led to significant changes in land use and economic activities, particularly in agriculture and industry. By analyzing the changes in nighttime light activity, the study evaluates and reflects the socio-economic impacts of human conflicts. The results show a nearly 50% decrease in nighttime light activity in the Donetsk and Luhansk regions from 2012 to 2016. Furthermore, the study finds that the sensitivity to nighttime light losses varies between areas inside and outside cities, and there are noticeable differences in losses attributed to industrial land-use types.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Christian Abys, Sergii Skakun, Inbal Becker-Reshef
Summary: The Russian wheat industry has experienced significant growth in the past two decades, becoming one of the top global wheat exporters. However, the volatility in wheat production continues to have an impact on the global commodities market and has lasting implications for land use and land cover change.
ENVIRONMENTAL RESEARCH COMMUNICATIONS
(2022)
Article
Environmental Sciences
Georgia Doxani, Eric F. Vermote, Jean-Claude Roger, Sergii Skakun, Ferran Gascon, Alan Collison, Liesbeth De Keukelaere, Camille Desjardins, David Frantz, Olivier Hagolle, Minsu Kim, Jerome Louis, Fabio Pacifici, Bringfried Pflug, Herve Poilve, Didier Ramon, Rudolf Richter, Feng Yin
Summary: The correction of atmospheric effects is crucial for remote sensing applications. A benchmark exercise called ACIX was conducted to assess the performance of different atmospheric correction methods. The results showed that the processors were successful in retrieving aerosol optical depth and water vapor retrievals, but there was still a need for better assessment of uncertainties in surface reflectance retrievals.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Erik C. Duncan, Sergii Skakun, Ankit Kariryaa, Alexander Prishchepov
Summary: Unexploded munitions have devastating effects on various aspects, and it is important to detect and map them accurately. This study applies a deep learning approach to identify and map artillery craters in agricultural fields in Eastern Ukraine. The model shows high accuracy in detecting craters, and the reliability improves with larger crater sizes. The estimated crater map reveals a significant number of craters in the region, providing valuable information for demining and assessing the impact of warfare on agriculture and the environment.
SCIENCE OF REMOTE SENSING
(2023)
Article
Environmental Sciences
Leonid Shumilo, Sergii Skakun, Meredith L. Gore, Andrii Shelestov, Nataliia Kussul, George Hurtt, Dmytro Karabchuk, Volodymyr Yarotskiy
Summary: The ongoing Russian-Ukrainian War has significant impacts on the protected areas of the Emerald Network. However, despite the conflict, the implementation of Bern Convention policies and forest management practices in the Luhansk region have helped maintain reforestation rates in Ukrainian-controlled territories.
COMMUNICATIONS EARTH & ENVIRONMENT
(2023)
Proceedings Paper
Geosciences, Multidisciplinary
E. Vermote, J. McCorkel, W. H. Rountree, A. Santamaria-Artigas, S. Skakun, B. Franch, J. C. Roger
Summary: This study validates the surface reflectance from Sentinel-2 produced by LaSRC using an automated camera system (CAMSIS). The results show good agreement between the surface reflectance and NDVI computed from CAMSIS calibrated data and the observations from Sentinel-2, indicating a good performance of LaSRC atmospheric correction.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Proceedings Paper
Geography, Physical
Mehdi Hosseini, Inbal Becker-Reshef, Ritvik Sahajpal, Pedro Lafluf, Guillermo Leale, Estefania Puricelli, Sergii Skakun, Heather McNairn
Summary: This study evaluated the potential of using Sentinel-1 dual-polarimetric data to forecast soybean yields at a field scale in central Argentina. By extracting polarimetric features and training an Artificial Neural Network (ANN) model, along with an innovative iterative retrieval method, the accuracy of soybean yield prediction was improved.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III
(2022)
Article
Meteorology & Atmospheric Sciences
Jean-Claude Roger, Eric Vermote, Sergii Skakun, Emilie Murphy, Oleg Dubovik, Natacha Kalecinski, Bruno Korgo, Brent Holben
Summary: This study proposes and implements a framework for developing an aerosol model using their microphysical properties, which are derived from the global AERONET. The research finds that these properties can be used to validate surface reflectance records over land and have an impact on the uncertainty of surface reflectance.
ATMOSPHERIC MEASUREMENT TECHNIQUES
(2022)
