Ufuk Avrupa · Horizon Europe (HORIZON)
Integrating Remote Sensing and in-situ observations of Biodiversity, towards a fully interoperable observation and data framework
Çağrı özeti
Resmi metinden, ilk bölüm
Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: advancing robust, policy-relevant ecosystem assessment, nature protection and restoration planning activities, and biodiversity trend prediction based on fit for purpose data, thus supporting EU biodiversity and climate objectives; strengthened capacity of researchers, practitioners and decision-makers to improve biodiversity monitoring practices and address knowledge gaps via the integration of data and observations across sensors and platforms, ranging from omics-based data (genomic, transcriptomic, metabolomic), various in-situ to satellite-based Earth observation data; enhanced usability of in-situ datasets as training and validation resources for statistical, machine learning and advanced AI-based approaches, in support of applications such as habitat classification, ecosystem map… devamı
Biodiversity conservationBiological systems analysis, modelling and simulationEarth Observation / Services and applicationsEcologyValorisation and capacity buildingEarth ObservationEarth ObservationsEuropean Space AgencyFAIRIn-situRemote SensingSatellite Remote Sensing
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%71AYHAN ATEŞOĞLU
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%69BURAK SARI
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%66EMRE AKTÜRK
Ortak konular: Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture
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%61ABDURRAHİM AYDIN
Ortak konular: Remote Sensing and LiDAR Applications
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%58ANIL AKIN TANRIÖVER
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%57CEM ÜNSALAN
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%56FATİH SİVRİKAYA
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%55DÖNDÜ BULUR
Ortak konular: Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture
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%54DİLEK KÜÇÜK MATCI
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%54FEVZİ KARSLI
Ortak konular: Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture
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%54GORDANA KAPLAN
Ortak konular: Remote Sensing in Agriculture · Remote Sensing and LiDAR Applications · Remote-Sensing Image Classification
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%54GÜNAY ÇAKIR
Ortak konular: Remote Sensing and LiDAR Applications
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%53MUSTAFA ÜMİT GÜMÜŞAY
Ortak konular: Remote Sensing and LiDAR Applications
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%52YASİN DEMİREL
Ortak konular: Remote Sensing and LiDAR Applications · Satellite Image Processing and Photogrammetry
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%52YILMAZ TÜRK
Ortak konular: Remote Sensing and LiDAR Applications
Örtüşen yayınlar: Determination of forest road cut slope surface material types using machine learning methods in UAV data (2025) · Determination of Excavation Volume Using UAV-Based PPK Method in Open Mining Sites Tatlıdere Forests in Düzce (2025)
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%51AHMET TARIK TORUN
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%51HALİL İBRAHİM GÜNDÜZ
Ortak konular: Remote Sensing in Agriculture
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%51LEVENT GENÇ
Ortak konular: Remote Sensing in Agriculture
Örtüşen yayınlar: Suitable Storage Areas for Estimated Demolished Waste Using InSAR and GIS-Based AHP For Kahramanmaraş Earthquake, Türkiye (2025) · Evaluation of Earthquake Impacts on Land Use and Land Cover (LU/LC) Using Google Earth Engine (GEE), Sentinel-2 Imageries, and Machine Learning: Case Study of Antakya (2023)
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%51RESUL ÇÖMERT
Ortak konular: Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture
Örtüşen yayınlar: Wall-to-wall mapping of Fagus orientalis Lipsky distribution across Türkiye’s forests using satellite remote sensing (2026) · Using Machine Learning to Extract Building Inventory Information Based on LiDAR Data (2022)
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%51TAŞKIN KAVZOĞLU
Ortak konular: Remote-Sensing Image Classification · Remote Sensing in Agriculture · Remote Sensing and LiDAR Applications · Remote Sensing and Land Use
Örtüşen yayınlar: Extraction of Water Bodies from High-Resolution Aerial and Satellite Images Using Visual Foundation Models (2024) · Google Earth Engine for Monitoring Marine Mucilage: Izmit Bay in Spring 2021 (2022)
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%50ALİ İHSAN KADIOĞULLARI
Ortak konular: Remote Sensing and LiDAR Applications
Örtüşen yayınlar: Comparing forest sites classifications using two different satellite images and ground measurements in Eastern Turkey (2014) · Classifying Oriental Beech Fagus orientalis Lipsky Forest Sites Using Direct Indirect and Remote Sensing Methods A Case Study from Turkey (2008)
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%50ALİİHSAN ŞEKERTEKİN
Ortak konular: Remote Sensing in Agriculture · Remote Sensing and Land Use · Soil Moisture and Remote Sensing
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%50BEKİR TANER SAN
Ortak konular: Remote-Sensing Image Classification · Remote Sensing in Agriculture
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%50MERVE KALAYCI KADAK
Ortak konular: Remote Sensing in Agriculture
Örtüşen yayınlar: Spatiotemporal Assessment of LULC Changes Using Remote Sensing Approaches (2025) · Predicting climate-based changes of landscape structure for Turkiye via global climate change scenarios: a case study in Bartin river basin with time series analysis for 2050 (2024)
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%50SEDAT KELEŞ
Ortak konular: Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture
Örtüşen yayınlar: Monitoring thirty years of land cover change Secondary forest succession in the Artvin Forest planning unit of Northeastern Turkey (2007) · Comparative study on crown closure estimations using two different remote sensing data Landsat ETM and IKONOS (2012)
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%50SİNAN DEMİR
Ortak konular: Remote Sensing in Agriculture
Örtüşen yayınlar: Post-fire erosion dynamics in the Dim River Basin: A remote sensing and Google Earth Engine approach (2025) · A spatial analysis of human–soil interactions using remote sensing and soil data: impacts of the conflict in Ukraine on food security (2026)
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%49FİLİZ BEKTAŞ BALÇIK
Ortak konular: Remote Sensing in Agriculture · Remote-Sensing Image Classification · Remote Sensing and LiDAR Applications
Örtüşen yayınlar: The use of remote sensing and geographic information systems for the evaluation of river basins A case study for Turkey Marmara River Basin and Istanbul (2009) · EVALUATION OF SENTINEL-2 MSI DATA FOR LAND USE / LAND COVER CLASSIFICATION USING DIFFERENT VEGETATION INDICES (2018)
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%49NUR YAĞMUR AYDIN
Ortak konular: Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture
Örtüşen yayınlar: Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline (2020) · Integrated time-series analysis of remote sensing imagery and crowdsourced data to monitor water hyacinth (Eichhornia crassipes) in the Orontes (asi) River (2025)
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%49TOLGA BAKIRMAN
Ortak konular: Remote Sensing and LiDAR Applications · Remote-Sensing Image Classification
Örtüşen yayınlar: Temporal Dynamics of Lake Burdur's Water Surface Area: A Two-Decade Remote Sensing Analysis and Future Forecasts (2025) · The Role of Ensemble Deep Learning for Building Extraction from VHR Imagery (2025)
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