The project "Topsoil properties Estimation from Hyperspectral Remote sensing for Agriculture" (TEHRA), funded by the Italian Space Agency (ASI), aims at developing methods and algorithms for the estimation of soil properties of agronomic and environmental interest from PRISMA satellite hyperspectral data, that could support: 1) the adoption of more sustainable and climate-smart farming practices, e.g. through the implementation of precision agriculture applications; 2) monitoring in support of agricultural and environmental policies, e.g. related to climate change and for the encouragement of the adoption of practices preserving soil health.In this paper, some results of the first year of the project are illustrated. They concern: 1) a scenario definition study; 2) studies on the confounding effect of soil moisture and crop residues; 3) exploitation of multi-temporal PRISMA data and 4) data fusion with proximal soil sensing.
Topsoil properties estimation for agriculture from prisma: the Tehra project / Casa, R.; Bruno, R.; Falcioni, V.; Marrone, L.; Pascucci, S.; Pignatti, S.; Priori, S.; Rossi, Francesco.; Tricomi, A.; Guarini, R.. - 2023-July:(2023), pp. 3209-3212. (Intervento presentato al convegno IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium tenutosi a Pasadena, CA, USA) [10.1109/igarss52108.2023.10283312].
Topsoil properties estimation for agriculture from prisma: the Tehra project
Pignatti, S.;Priori, S.;Rossi, Francesco.;
2023
Abstract
The project "Topsoil properties Estimation from Hyperspectral Remote sensing for Agriculture" (TEHRA), funded by the Italian Space Agency (ASI), aims at developing methods and algorithms for the estimation of soil properties of agronomic and environmental interest from PRISMA satellite hyperspectral data, that could support: 1) the adoption of more sustainable and climate-smart farming practices, e.g. through the implementation of precision agriculture applications; 2) monitoring in support of agricultural and environmental policies, e.g. related to climate change and for the encouragement of the adoption of practices preserving soil health.In this paper, some results of the first year of the project are illustrated. They concern: 1) a scenario definition study; 2) studies on the confounding effect of soil moisture and crop residues; 3) exploitation of multi-temporal PRISMA data and 4) data fusion with proximal soil sensing.File | Dimensione | Formato | |
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Casa_Topsoil properties_2023 .pdf
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