| publications-2341 |
Peer reviewed articles |
2022 |
Maria Sdraka; Ioannis Papoutsis; Bill Psomas; Konstantinos Vlachos; Konstantinos Ioannidis; Konstantinos Karantzalos; Ilias Gialampoukidis; Stefanos Vrochidis |
Deep Learning for Remote Sensing Image Downscaling: Fusion and Super-Resolution |
IEEE Geoscience and Remote Sensing Magazine |
10.1109/mgrs.2022.3171836 |
AI & Machine Learning |
Uncategorized |
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No abstract available |
101004152 |
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| publications-2342 |
Peer reviewed articles |
2022 |
Maria Ioannidou; Alkiviadis Koukos; Vasileios Sitokonstantinou; Ioannis Papoutsis; Charalampos Kontoes; |
Assessing the Added Value of Sentinel-1 PolSAR Data for Crop Classification |
Remote Sensing, volume 14, page 5,739 (eissn: 2072-4292) |
10.3390/rs14225739 |
Simulation & Modeling |
Precipitation & Ecological Systems |
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Crop classification is an important remote sensing task with many applications, e.g., food security monitoring, ecosystem service mapping, climate change impact assessment, etc. This work focuses on mapping 10 crop types at the field level in an agricultural region located in the Spanish province of Navarre. For this, multi-temporal Synthetic Aperture Radar Polarimetric (PolSAR) Sentinel-1 imagery and multi-spectral Sentinel-2 data were jointly used. We applied the Cloude–Pottier polarimetric decomposition on PolSAR data to compute 23 polarimetric indicators and extracted vegetation indices from Sentinel-2 time-series to generate a big feature space of 818 features. In order to assess the relevance of the different features for the crop mapping task, we run a number of scenarios using a Support Vector Machines (SVM) classifier. The model that was trained using only the polarimetric data demonstrates a very promising performance, achieving an overall accuracy over 82%. A genetic algorithm was also implemented as a feature selection method for deriving an optimal feature subset. To showcase the positive effect of using polarimetric data over areas suffering from cloud coverage, we contaminated the original Sentinel-2 time-series with simulated cloud masks. By incorporating the genetic algorithm, we derived a high informative feature subset of 120 optical and polarimetric features, as the corresponding classification model increased the overall accuracy by 5% compared to the model trained only with Sentinel-2 features. The feature importance analysis indicated that apart from the Sentinel-2 spectral bands and vegetation indices, several polarimetric parameters, such as Shannon entropy, second eigenvalue and normalised Shannon entropy are of high value in identifying crops. In summary, the findings of our study highlight the significant contribution of Sentinel-1 PolSAR data in crop classification in areas with frequent cloud coverage and the effectiveness of the genetic algorithm in discovering the most informative features. |
101004152 |
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| publications-2343 |
Peer reviewed articles |
2023 |
Hyun-Woo Jo, Eunbeen Park, Vasileios Sitokonstantinou, Joon Kim, Sujong Lee, Alkiviadis Koukos & Woo-Kyun Lee |
Recurrent U-Net based dynamic paddy rice mapping in South Korea with enhanced data compatibility to support agricultural decision making |
GIScience & Remote Sensing; VOL 60; NO. 1; 2206539 |
10.1080/15481603.2023.2206539 |
Simulation & Modeling |
Natural Water Bodies |
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No abstract available |
101004152 |
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| publications-2344 |
Peer reviewed articles |
2022 |
Stelios Andreadis; Ilias Gialampoukidis; Andrea Manconi; David Cordeiro; Vasco Conde; Manuela Sagona; Fabrice Brito; Nick Pantelidis; Thanassis Mavropoulos; Nuno Grosso; Stefanos Vrochidis; Ioannis Kompatsiaris |
Earthquakes: From Twitter Detection to EO Data Processing |
IEEE Geoscience and Remote Sensing Letters, 19 |
10.3929/ethz-b-000538275 |
Simulation & Modeling |
Natural Water Bodies |
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No abstract available |
101004152 |
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| publications-2345 |
Peer reviewed articles |
2024 |
Yemane Meresa, Abel Ruiz-Giralt, Alemseged Beldados, Carla Lancelotti, A. Catherine D’Andrea |
Pre‑Aksumite and Aksumite Agricultural Economy at Ona Adi, Tigrai (Ethiopia): First look at a 1000‑Year History |
African Archaeological Review |
10.1007/s10437-024-09574-9 |
Simulation & Modeling |
Natural Water Bodies |
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AbstractArchaeobotanical investigations at the site of Ona Adi in Tigrai were conducted during the 2013–2015 field seasons within the framework of the Eastern Tigrai Archaeological Project (ETAP). The site occupation spanned the Middle/Late Pre-Aksumite period (ca. 750/600 BCE) to the fall of the Aksumite Kingdom (ca. 700 CE), including the Pre-Aksumite to Aksumite transition (ca. 400 BCE–CE 1). The main objective of the study was to examine the agricultural economy in Eastern Tigrai during these periods and to evaluate the impact of social and cultural developments on the agricultural practices at Ona Adi. Recovered macrobotanical remains included wheat, barley, linseed, noog, lentil, and wild/weedy plants. In addition, evidence of finger millet was recovered along with tentative identifications of t’ef. The phytolith record shows evidence of grass processing, including morphotypes associated with Chloridoideae, Panicoideae, and Pooideae grasses. Results indicate that plants of both African and Southwest Asian origins were present in the region from the mid-eighth century BCE to the eighth century CE, but their relative importance varied throughout time in relation to socio-political changes at the regional level. Our data demonstrate a significant degree of continuity in the local agricultural economy, which remained largely unchanged even after the decline of Aksumite state. |
759800 |
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| publications-2346 |
Peer reviewed articles |
2023 |
A. Catherine D’Andrea, Lynn Welton, Andrea Manzo, Helina S. Woldekiros, Steven A. Brandt, Alemseged Beldados, Elizabeth A. Peterson, Laurie A. Nixon-Darcus, Michela Gaudiello, Shannon R. Wood, Habtamu Mekonnen, Stephen Batiuk, Yemane Meresa, Abel Ruiz-Giralt, Carla Lancelotti, Abebe Mengistu Taffere, Lucas M. Johnson |
The Pre-Aksumite Period: indigenous origins and development in the Horn of Africa |
Azania: Archaeological Research in Africa |
10.1080/0067270x.2023.2236484 |
Simulation & Modeling |
Natural Water Bodies |
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No abstract available |
759800 |
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| publications-2347 |
Peer reviewed articles |
2023 |
Alemseged Beldados; Abel Ruiz-Giralt; Carla Lancelotti; Yemane Meresa; A. Catherine D'Andrea |
Pre-Aksumite plant husbandry in the Horn of Africa |
Vegetation History and Archaeobotany |
10.1007/s00334-023-00949-7 |
IoT & Sensors |
Natural Water Bodies |
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No abstract available |
759800 |
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| publications-2348 |
Peer reviewed articles |
2021 |
Carla Lancelotti, Stefano Biagetti |
Mapping Food Production in Hyper-Arid and Arid Saharan Africa in the Holocene—A View from the Present |
Quaternary |
10.3390/quat4020013 |
Simulation & Modeling |
Natural Water Bodies |
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The reconstruction of land use practices in hyper-arid Saharan Africa is often hampered by the accuracy of the available tools and by unconscious biases that see these areas as marginal and inhospitable. Considered that this has been for a long time the living space of pastoral mobile communities, new research is showing that agriculture might have been more important in these areas than previously thought. In this paper, after a review of present-day land use strategies in Saharan Africa, we show how ethnographic and ethnoarchaeological data can offer us a different point of view and help in better defining land use and food production strategies in this area. Ultimately, these insights can be integrated into the ongoing efforts to reconstruct past land use globally. |
759800 |
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| publications-2349 |
Peer reviewed articles |
2023 |
Ruiz-Giralt Abel, Biagetti Stefano, Madella Marco,Lancelotti |
Small-scale farming in drylands: New models for resilient practices of millet and sorghum cultivation |
PLoS ONE |
10.5281/zenodo.6501883 |
Data Management & Analytics |
Uncategorized |
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No abstract available |
759800 |
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| publications-2350 |
Peer reviewed articles |
2023 |
Abel Ruiz-Giralt, Alemseged Beldados, Stefano Biagetti, Francesca D’Agostini, A. Catherine D’Andrea, Yemane Meresa, Carla Lancelotti |
Sorghum and Finger Millet Cultivation during the Aksumite Period: Insights from Ethnoarchaeological Modelling and Microbotanical Analysis |
Joural of Computer Applications in Archaeology |
10.5334/jcaa.132 |
Data Management & Analytics |
Uncategorized |
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No abstract available |
759800 |
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