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Tag: hyperspectral

SUP FCP HIGH-RESOLUTION ENHANCED ANALYSIS TOOL FOR URBAN HYPERSPECTRAL AND INFRARED SATELLITE EVALUATION (HEATWISE)

Prime company: BROCKMANN CONSULT GMBH (DE)

Objective of the activity is to develop three key urban products that can be generated through the synergistic use of hyperspectral and thermal data of LSTM and CHIME together with S-2, S-3 and ESA’s Next Generations Sentinel Continuation missions. Specifically, the products are: Maps of the thermal properties of Urban Materials; Advanced Local Climate Zone …

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QUANTUM ADVANTAGE FOR EARTH OBSERVATION STUDY (QA4EO STUDY)

Prime company: DLR – GERMAN AEROSPACE CENTER (DE)

The main scope of the QA4EO project (Quantum Advantage for Earth Observation) is to identify three to five intractable Earth Observation Use-Cases (EO UCs) of practical importance based on their computational advantage as well as strategic value that can be usefully expressed and solved by a quantum computing approach on quantum computers (QC). The proposed …

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W4Repp: Wind for Renewable Energy Production Prediction

Prime company: Verisk Analytics GmbH (DE)

The objective of this project is to improve short-term wind forecast by regional-scale numerical weather prediction (NWP) models, through innovative assimilation of spaceborne observations, which at the moment are underutilised. Although an accurate wind forecast is important for large number of applications, the project will focus on short-range prediction of wind and solar energy production …

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Super-Resolution Enhanced Data for EO Applications and Services – Topic C: Hyperspectral Data Super-Resolution

Prime company: KP Labs Sp. z o.o. (PL)

This activity implements and validates SR algorithms for hyperspectral imagery (HSI). With respect to the input data presented for reconstruction, these considered algorithms will be either 1) fusing of HSI (PRISMA) with an auxiliary panchromatic image of higher spatial resolution; or 2) fusing of a HSI without any additional data, exploiting the spatial-spectral fusion of …

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EO AFRICA Food Security and Safety in Africa – AFRI4Cast

Prime company: AGROAPPS PC (GR)

Afri4Cast project will develop a modeling platform making full exploitation of satellite remote sensing of PRISMA and ECOSTRESS sensors for climate change impact analyses on agriculture and making it available to African stakeholders for shaping future agricultural policies in the African Continent.  Afri4Cast will provide national-, regional-, parcel-, pixel-specific in season production estimates, mycotoxin formation …

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EO AFRICA PRISMA 4 AFRICA

Prime company: E-GEOS (IT)

This project aims to exploit new opportunities offered by the EO technological advances, in order to favour the development of EO local experts in Africa, by providing geospatial information and natural resources mapping/monitoring. Policy makers and relevant regional stakeholders (”Early Adopters”) will take a direct advantage on the availability of EO products describing the status …

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EO AFRICA Earth Observation system to Manage Africa’s food systems by Joint-knowledge of crop production and Irrigation digitization – EO-MAJI

Prime company: UNIVERSITY OF LEICESTER (GB)

Primary objective of this project is to utilize the unique spatial, spectral and temporal characteristics of ECOSTRESS thermal sensor and PRISMA hyperspectral sensor to develop novel methods addressing the growing challenges affecting the nexus of water resource management and food security in Africa. Irrigated agriculture is right in the centre of those two domains and …

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MAchine Learning Tool for Calibration of Hyperspectral data (MATCH)

Prime company: COSINE RESEARCH B.V. (NL)

The project aims at the development of algorithms for cross-calibration of hyperscout with S-2 and the development of the phi-sat 1 brain for cloud detection.  The team is assessing Machine Learning methodology, techniques, and a suite of applications (ranging from Radiometric calibration of a single band L2A data, Calibration of data products, e.g. NDVI or …

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GENESIS

Prime company: KP Labs Sp. z o.o. (PL)

Farmers and field owners need information about the soil parameters to optimize the fertilization process. This may ultimately lead to selecting a better mix of fertilizers, and to reducing the overall amount of them. The current approach toward quantifying the soil parameters (e.g., macroelements) is very user-dependent, laborious, time-consuming, vastly manual – we have to …

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