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 …
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 …
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 …
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 …
HyRELIEF will exploit hyperspectral narrowbands (HNBs) captured by Hyperspectral Precursor and Application Mission (PRISMA) and employ a co-production approach with knowledge users to increase the reliability and usability of ECOSTRESS ET and ESI for drought monitoring in Kenya.
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 …
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 …
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 …
The aim of this project is to develop and validate novel EO-based hyperspectral data generated by an unprecedented miniaturized hyperspectral sensor (HyperScout-2) employed in the ESA EO directorate small sat mission PhiSat-1. The processed data output of this project will advance existing EO capabilities. The processing and the distribution of the data to the community …
Hyperspectral imaging can capture hundreds of images acquired for narrow and continuous spectral bands across the electromagnetic spectrum, hence can allow us to precisely analyze the materials that are present in a scene of interest. However, the large volume of hyperspectral images (HSIs) makes their manual analysis and transfer very costly and time-expensive, especially when …
