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EXPLORING THE USE OF CLASSIFICATION UNCERTAINTY TO IMPROVE CLASSIFICATION ACCURACY

D. Moraes, P. Benevides, F. D. Moreira, H. Costa, M. Caetano
2021 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Supervised classification of remotely sensed images has been widely used to map land cover and land use.  ...  We conducted experiments in a region of Portugal (Trás-os-Montes), using multi-temporal Sentinel-2 images.  ...  Value-added data processed by CNES for the Theia data centre www.theia-land.fr using Copernicus products. The processing uses algorithms developed by Theia's Scientific Expertise Centres.  ... 
doi:10.5194/isprs-archives-xliii-b3-2021-81-2021 fatcat:pt2o2d7kojazrpewk7xrwrvv6u

The Potential of Sentinel-2 Satellite Images for Land-Cover/Land-Use and Forest Biomass Estimation: A Review [chapter]

Crismeire Isbaex, Ana Margarida Coelho
2021 Forest Biomass - From Trees to Energy  
Mapping land-cover/land-use (LCLU) and estimating forest biomass using satellite images is a challenge given the diversity of sensors available and the heterogeneity of forests.  ...  The Sentinel data have great potential for studies on LCLU classification and forest biomass estimates.  ...  and by FCT, Portugal, Fundação para a Ciência e Tecnologia, through IDMEC, under LAETA, project UIDB/05183/2020.  ... 
doi:10.5772/intechopen.93363 fatcat:v4bzh7jg4vdv7lli5bn2sbezoq

Mapping Land Cover and Tree Canopy Cover in Zagros Forests of Iran: Application of Sentinel-2, Google Earth, and Field Data

Saeedeh Eskandari, Mohammad Reza Jaafari, Patricia Oliva, Omid Ghorbanzadeh, Thomas Blaschke
2020 Remote Sensing  
First, we assessed the accuracy of Google Earth data using 300 random field plots in 10 different land cover types.  ...  In this study, we generated accurate land cover (LC), and tree canopy cover percentage (TCC%) maps for the forests of Shirvan County, a part of Zagros forests in Western Iran using Sentinel-2, Google Earth  ...  Acknowledgments: This research has been supported by the Research Institute of Forests and Rangelands (RIFR).  ... 
doi:10.3390/rs12121912 fatcat:bt42w6yko5c3tas35jmq3drz3u

Drivers of Forest Loss in a Megadiverse Hotspot on the Pacific Coast of Colombia

Jesús A. Anaya, Víctor H. Gutiérrez-Vélez, Ana M. Pacheco-Pascagaza, Sebastián Palomino-Ángel, Natasha Han, Heiko Balzter
2020 Remote Sensing  
By using Google Earth Engine to select pixels with minimal cloud content and applying a random forest classifier to Landsat and Sentinel data, we produced a wall-to-wall land cover map, enabling a diagnosis  ...  of the status and drivers of forest loss in the region.  ...  We built optical and radar mosaics for the study area (the size of Portugal) and then performed land cover classification and validation through the implementation of a random forest algorithm [28] using  ... 
doi:10.3390/rs12081235 fatcat:5iw2xwgj3rhjjjpf4ysivdkvzy

Designing a Validation Protocol for Remote Sensing Based Operational Forest Masks Applications. Comparison of Products Across Europe

Angel Fernandez-Carrillo, Antonio Franco-Nieto, Erika Pinto-Bañuls, Miguel Basarte-Mena, Beatriz Revilla-Romero
2020 Remote Sensing  
The spatial and temporal dynamics of the forest cover can be captured using remote sensing data.  ...  The forest masks presented here are binary forest/non-forest classification maps obtained using Sentinel-2 data for 16 study areas across Europe with different forest types.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12193159 fatcat:gyrtjfk6f5bujm45skklmwflii

Automated Production of a Land Cover/Use Map of Europe Based on Sentinel-2 Imagery

Radek Malinowski, Stanisław Lewiński, Marcin Rybicki, Ewa Gromny, Małgorzata Jenerowicz, Michał Krupiński, Artur Nowakowski, Cezary Wojtkowski, Marcin Krupiński, Elke Krätzschmar, Peter Schauer
2020 Remote Sensing  
The method uses a random forest classifier and existing land cover/use databases as the source of training samples.  ...  To address this issue, we developed a methodology for the automated classification of multi-temporal Sentinel-2 imagery.  ...  Acknowledgments: We wish to thank CREODIAS' staff for the help with using CREODIAS platform and implementing our tools.  ... 
doi:10.3390/rs12213523 fatcat:mpzccu67cbcnzakqqsls2d2y6y

Shrub Biomass Estimates in Former Burnt Areas Using Sentinel 2 Images Processing and Classification

José Aranha, Teresa Enes, Ana Calvão, Hélder Viana
2020 Forests  
Sentinel 2 VIS-NIR images are suitable to classify rural areas (overall accuracy = 79.6% and Cohen's K = 0.754) and to create normalized difference vegetation index (NDVI) images to be used in association  ...  The combined use of geographical information systems (GIS) and remote sensing (RS) supported by dedicated land survey and field work for data collection has been identified as a suitable method to manage  ...  Thus, it was necessary to carry out further analysis using Sentinel 2 images and an assisted classification process to classify the land cover in classes.  ... 
doi:10.3390/f11050555 fatcat:gppa3webbbe3zntzwzgm7x2kne

Green Infrastructure Mapping in Urban Areas Using Sentinel-1 Imagery

Mateo Gašparović, Dino Dobrinić
2021 Croatian Journal of Forest Engineering  
High temporal resolution of synthetic aperture radar (SAR) imagery (e.g., Sentinel-1 (S1) imagery) creates new possibilities for monitoring green vegetation in urban areas and generating land-cover classification  ...  Future research should address the use of multitemporal SAR data along with the pre-processing steps and ML algorithms described in this research.  ...  Acknowledgements Support by the Croatian Science Foundation for the GEMINI project entitled: »Geospatial Monitoring of Green Infrastructure by Means of Terrestrial, Airborne and Satellite Imagery« (Grant  ... 
doi:10.5552/crojfe.2021.859 fatcat:zjlzgfnzzrcebgb4skaedut53u

Assessment of k-Nearest Neighbor and Random Forest Classifiers for Mapping Forest Fire Areas in Central Portugal Using Landsat-8, Sentinel-2, and Terra Imagery

Admilson da Penha Pacheco, Juarez Antonio da Silva Junior, Antonio Miguel Ruiz-Armenteros, Renato Filipe Faria Henriques
2021 Remote Sensing  
This study analyzes the performance of the k-Nearest Neighbor (kNN) and Random Forest (RF) classifiers for the classification of an area that is affected by fires in central Portugal.  ...  For that, image data from Landsat-8, Sentinel-2, and Terra satellites and the peculiarities of each of these platforms with the support of Jeffries–Matusita (JM) separability statistics were analyzed.  ...  Acknowledgments: Research was supported by PAIUJA-2019/2020 and CEACTEMA from University of Jaén (Spain), and RNM-282 research group from the Junta de Andalucía (Spain).  ... 
doi:10.3390/rs13071345 fatcat:bucn4mdwpzew5e4xylkpi6ka6i

Automatic Extraction and Filtering of OpenStreetMap Data to Generate Training Datasets for Land Use Land Cover Classification

Cidália C. Fonte, Joaquim Patriarca, Ismael Jesus, Diogo Duarte
2020 Remote Sensing  
This paper tests an automated methodology for generating training data from OpenStreetMap (OSM) to classify Sentinel-2 imagery into Land Use/Land Cover (LULC) classes.  ...  The Random Forest classifier was then trained to classify a time-series of Sentinel-2 imagery into 8 LULC classes with samples extracted from: (1) The LULC maps produced by OSM2LULC_4T (TD0); (2) the TD1  ...  Acknowledgments: The authors are grateful to the OSM contributors that added data to OSM that may be used for projects such as the one presented in this paper.  ... 
doi:10.3390/rs12203428 fatcat:7w56735lqvbx3fmrmexynegj5u

Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data

Vasco Mantas, Luís Fonseca, Elsa Baltazar, Jorge Canhoto, Isabel Abrantes
2022 Remote Sensing  
The Random Forest model relied on a pre-wilting and an in-season image, calibrated with data from a 24-month long field campaign enhanced with Worldview-3 data and the analysis of biological samples (hyperspectral  ...  Independent validation results attested to the good performance of the model with an overall accuracy of 95%, particularly when decline affects more than 30% of the 100 m2 pixel of Sentinel-2.  ...  Acknowledgments: We acknowledge the continuous support of all stakeholders engaged in the projects that supported the development of the study.  ... 
doi:10.3390/rs14092028 fatcat:rn6saj2irndhde52xrgv46lzcy

Mapping of Eucalyptus in Natura 2000 Areas Using Sentinel 2 Imagery and Artificial Neural Networks

Andreas Forstmaier, Ankit Shekhar, Jia Chen
2020 Remote Sensing  
This study uses medium resolution, multi-spectral imagery of the Sentinel 2 satellites to map Eucalyptus across Portugal and parts of Spain with a focus on Natura 2000 areas inside Portugal, that are protected  ...  A qualitative assessment of Natura 2000 areas in Portugal has been performed and 15 areas have been found to be affected by Eucalyptus of which 9 are strongly affected.  ...  Also we thank the association Movimento Gaio, especially Bernardo and Teresa Markowsky who helped with their knowledge as well as with providing infrastructure and transport services during the field campaign  ... 
doi:10.3390/rs12142176 fatcat:p5iobu2tcrafzjv3nzvflzvgvm

'The Best of Two Worlds'—Combining Classifier Fusion and Ecological Models to Map and Explain Landscape Invasion by an Alien Shrub

Nuno Mouta, Renato Silva, Silvana Pais, Joaquim M. Alonso, João F. Gonçalves, João Honrado, Joana R. Vicente
2021 Remote Sensing  
By combining data from georeferenced invaded areas with multispectral imagery with 10-meter resolution from Sentinel-2 satellites, a map of areas invaded by the woody invasive Acacia longifolia in a municipality  ...  Through a Random Forest (RF) model, these maps were then used to explore the factors driving the landscape-level abundance of A. longifolia.  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/rs13163287 fatcat:7i3md7ztffae5jb2ddhhiqskpm

Review on Multitemporal Classification Methods of Satellite Images for Crop and Arable Land Recognition

Joanna Pluto-Kossakowska
2021 Agriculture  
This paper presents a review of the conducted research in the field of multitemporal classification methods used for the automatic identification of crops and arable land using optical satellite images  ...  For very fragmented regions, better results were achieved using Sentinel-2, SPOT-5 rather than Landsat images, but the level of accuracy can still be improved.  ...  Acknowledgments: The RAWGraphs application was used to create the graphs and charts. Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/agriculture11100999 fatcat:rlqklvjd3ncbpgbduybbxja2ny

Ecosystem Services in a Protected Mountain Range of Portugal: Satellite-Based Products for State and Trend Analysis

Claudia Carvalho-Santos, António Monteiro, Salvador Arenas-Castro, Felix Greifeneder, Bruno Marcos, Ana Portela, João Honrado
2018 Remote Sensing  
In situ and statistical data were also used to compute final indicators of ecosystem services.  ...  These services were evaluated using a set of different satellite products, namely grassland cover, soil moisture, and ecosystem functional attributes.  ...  lg=2) for the pictures in Figure 6 . Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs10101573 fatcat:swwfv6ncabd6db27xvis2mmz7i
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