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Development of an Operational Algorithm for Automated Deforestation Mapping via the Bayesian Integration of Long-Term Optical and Microwave Satellite Data

Hiroki Mizuochi, Masato Hayashi, Takeo Tadono
2019 Remote Sensing  
In this paper, we introduce an operational algorithm for automated deforestation mapping using long-term optical and L-band SAR data, including a simple time-series analysis of Landsat stacks and a multilayered  ...  Although the sensor integration of optical and microwave sensors is of compelling research interest, particularly in the conduct of deforestation monitoring, this topic has not been widely studied.  ...  We also thank the GEE for archiving Landsat series and Sentinel-2 data. Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/rs11172038 fatcat:v3okegudanh55f3egx3hab4fyq

Historical background and current developments for mapping burned area from satellite Earth observation

Emilio Chuvieco, Florent Mouillot, Guido R. van der Werf, Jesús San Miguel, Mihai Tanasse, Nikos Koutsias, Mariano García, Marta Yebra, Marc Padilla, Ioannis Gitas, Angelika Heil, Todd J. Hawbaker (+1 others)
2019 Remote Sensing of Environment  
With the launch of the first Earth observation satellites, remote sensing quickly became a more practical alternative to detect burned areas, as they provide timely regional and global coverage of fire  ...  recent approaches to map burned areas and evaluates the existing burned area products (both at global and regional scales).  ...  However, an automated algorithm for nationwide BA and severity mapping using Geoscience Australia's (GA's) Landsat and Sentinel-2 data cube infrastructure was recently developed and is close to operational  ... 
doi:10.1016/j.rse.2019.02.013 fatcat:eywm3ix63ngvdczdtdci46etwu

Deep Learning and Earth Observation to Support the Sustainable Development Goals [article]

Claudio Persello, Jan Dirk Wegner, Ronny Hänsch, Devis Tuia, Pedram Ghamisi, Mila Koeva, Gustau Camps-Valls
2021 arXiv   pre-print
This paper reviews current deep learning approaches for Earth observation data, along with their application towards monitoring and achieving the SDGs most impacted by the rapid development of deep learning  ...  Exciting times ahead are coming where algorithms and Earth data can help in our endeavor to address the climate crisis and support more sustainable development.  ...  Also, an active research field is the joining of these two worlds via active learning [270] algorithms: by allowing interactive back and forth between the annotators and the DL models, significant speedups  ... 
arXiv:2112.11367v1 fatcat:7eve5dr45vcublfqyzzrccuvxa

Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

Donato Amitrano, Gerardo Di Martino, Raffaella Guida, Pasquale Iervolino, Antonio Iodice, Maria Nicolina Papa, Daniele Riccio, Giuseppe Ruello
2021 Remote Sensing  
This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detection and its applications to biosphere and hydrosphere monitoring, with special  ...  The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market.  ...  Data Availability Statement: Not applicable. Acknowledgments: The authors sincerely thank Airbus Defense and Space UK and Catapult SA for providing NovaSAR data from the commissioning phase.  ... 
doi:10.3390/rs13040604 fatcat:zgqmk5chjbc7hio5l6serraeym

An overview of MATISSE-v2.0

Luc Labarre, Karine Caillault, Sandrine Fauqueux, Claire Malherbe, Antoine Roblin, Bernard Rosier, Pierre Simoneau, Karin Stein, John D. Gonglewski
2010 Optics in Atmospheric Propagation and Adaptive Systems XIII  
The symposium, like our other conferences and activities, would not be possible without the dedicated contribution of our participants and members.  ...  This Programme is based on commitments received up to the time of publication and is subject to change without notice.  ...  for providing the Radarsat-2, TerraSAR-X and weather data respectively.  ... 
doi:10.1117/12.868183 fatcat:5anlqspzzzcftfufaxvlr45zve

Table of Contents

2020 IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium  
INFORMATION CONTENT ALGORITHM FOR AUTOMATED ........................................ AN IMPROVED TARGET EXTRACTION SCHEME FOR FORWARD-LOOKING .............................  ...  AND OPTICAL REMOTE SENSING TU2-R17.1: INVESTIGATION OF THE FMASK CLOUD MASKING ALGORITHM USING ...................................... 3432 SIMULATED MULTISPECTRAL DATA Robert Sundberg, Spectral Sciences  ... 
doi:10.1109/igarss39084.2020.9323828 fatcat:6aittajt35gufeaugcmemu5cya

Integrating Biodiversity, Remote Sensing, and Auxiliary Information for the Study of Ecosystem Functioning and Conservation at Large Spatial Scales [chapter]

Franziska Schrodt, Betsabe de la Barreda Bautista, Christopher Williams, Doreen S. Boyd, Gabriela Schaepman-Strub, Maria J. Santos
2020 Remote Sensing of Plant Biodiversity  
However, RS data comes with limitation of their own, and despite of the many opportunities offered by RS data, certain aspects and scales of biodiversity are currently not measurable using RS technology  ...  Thus, the combination of RS, in-situ and other auxiliary data, provides the most powerful approach to assessing ecosystem functioning and conservation at large spatial scales.  ...  Acknowledgments FS was supported by an Anne McLaren fellowship by the University of Nottingham (UK). We thank Nathalie Pettorelli for useful discussions and suggestions.  ... 
doi:10.1007/978-3-030-33157-3_17 fatcat:f3qfvseedjdqhgs7xzpc3wf6u4

Multi sensor validation and error characteristics of Arctic satellite sea surface temperature observations

Jacob L. Høyer, Ioanna Karagali, Gorm Dybkjær, Rasmus Tonboe
2012 Remote Sensing of Environment  
The lake processor is a modification of the processor built during the ATSR Reprocessing for Climate (ARC) project, that was funded by the UK Natural We will present the background to this approach and  ...  Acknowledgement This study was supported by the project "Research for the Meteorological Observation Technology and Its Application" at National Institute of Meteorological Research, KMA.  ...  It requires high accuracy and stability of satellite data for long-term climate data record of global SST.  ... 
doi:10.1016/j.rse.2012.01.013 fatcat:e64zv2bspzh7pkiaqqx76humiu

NASA workshop on issues in the application of data mining to scientific data

Jeanne Behnke, Elaine Dobinson
2000 SIGKDD Explorations  
The objectives of the workshop were to bring together computer scientists and physical scientists to assess the state of the practice in data mining for scientific applications; share experiences in applying  ...  this technology; and to help determine the direction of future work in data mining.  ...  -Data mining is one of these--develop loss functions for unusual features and look for data mining methodologies that look for features based on the loss function. This is implicitly Bayesian.  ... 
doi:10.1145/360402.360427 fatcat:5b6upxenlvfmfmqsk6xhjtynvm

Knowledge Extracted from Copernicus Satellite Data

Dumitru Octavian, Schwarz Gottfried, Eltoft Torbjørn, Kræmer Thomas, Wagner Penelope, Hughes Nick, Arthus David, Fleming Andrew, Koubarakis Manolis, Datcu Mihai
2019 Zenodo  
During the development of deep learning algorithms, a key activity is to establish a large amount of referenced Earth Observation data.  ...  In this publication, we focus on the Polar case which requires the selection of validation areas, the generation of a training dataset, the development and testing of deep learning algorithms, and the  ...  Hope that through our practices to promote the capacity of development, integration and utilization of marine data resources.  ... 
doi:10.5281/zenodo.3941573 fatcat:zzifwgljifck5bpjnboetsftfu

Conservation Tech Directory [article]

Carly Batist, Gracie Ermi, Gracie Ermie
*An interactive version of this directory is available at*A list of organizations, communities, companies, open-source projects and other resources within the conservation technology  ...  She builds machine learning platforms to support wildlife research, largely focused on automating image processing and bioacoustics analysis for marine mammal research.  ...  ear tags for large mammals; satellite remote data download sensing tech for monitoring tropical deforestation & forest degradation; automated system for converting satellite imagery  ... 
doi:10.6084/m9.figshare.15442200.v12 fatcat:b4bfumzexjec5lh4bdk3q35bia

Conservation Tech Directory [article]

Carly Batist, Gracie Ermi, Gracie Ermie
*An interactive version of this directory is available at*A list of organizations, communities, companies, open-source projects and other resources within the conservation technology  ...  She builds machine learning platforms to support wildlife research, largely focused on automating image processing and bioacoustics analysis for marine mammal research.  ...  Netherlands provides server-side components to run participatory mapping projects; can create custom data structures; integrate pictures & videos with maps; access data via open REST API for data collection  ... 
doi:10.6084/m9.figshare.15442200.v13 fatcat:qgs2d2chsbdo5hflfzwu3p2rzq

Towards Synoptic Water Monitoring Systems: A Review of AI Methods for Automating Water Body Detection and Water Quality Monitoring Using Remote Sensing

Liping Yang, Joshua Driscol, Sarigai Sarigai, Qiusheng Wu, Christopher D. Lippitt, Melinda Morgan
2022 Sensors  
An interactive web application designed to allow readers to intuitively and dynamically review the relevant literature was also developed.  ...  Based on this review, the main challenges of leveraging AI and RS for intelligent water information extraction are discussed, and research priorities are identified.  ...  Kappa Coefficient KNN K-Nearest Neighbors Classifier LORSAL Logistic Regression via Variable Splitting and Augmented Lagrangian LSTM Long Short-Term Memory MA Mapping Accuracy MAE Mean Absolute Error MAPE  ... 
doi:10.3390/s22062416 pmid:35336587 pmcid:PMC8949619 fatcat:yik4lq6xq5afvbrsluso7zdroq

Measuring atmospheric composition change

P. Laj, J. Klausen, M. Bilde, C. Plaß-Duelmer, G. Pappalardo, C. Clerbaux, U. Baltensperger, J. Hjorth, D. Simpson, S. Reimann, P.-F. Coheur, A. Richter (+41 others)
2009 Atmospheric Environment  
The variability of the atmospheric system and the extreme complexity of the atmospheric cycles for short-lived gaseous and aerosol species have led to the development of complex models to interpret observations  ...  The validation of numerical models requires accurate information concerning the variability of atmospheric composition for targeted species via comparison with observations and measurements.  ...  We are thankful to Mariana Berthet and the ACCENT project office for their support in the preparation of the article.  ... 
doi:10.1016/j.atmosenv.2009.08.020 fatcat:45zeml2sk5dizbnaydexgmtrhy

Emissions Trading [chapter]

2017 Encyclopedia of GIS  
In terms of processing and delivery, digital platforms (satellite and aerial) will soon be able to deliver data nearly on-demand as processing routines for image data, regardless of source, approach near  ...  Finally, in the Bayesian framework, it is necessary to define prior distributions for each of the data and process parameters.  ...  Figure 2 demonstrates an example of aggregating counts of n-gram subsequences from check-in location sequence collection of all users. For instance, the subsequence l 1 !  ... 
doi:10.1007/978-3-319-17885-1_100350 fatcat:qtqeulswn5fanpkosuygq57viq
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