Dr. Surya Gupta Department of Environmental Sciences Profiles & Affiliations OverviewResearch Publications Publications by Type Projects & Collaborations Academic Activities Academic Self-Administration Junior Development, Doctorate and Advanced Studies Academic Reputation & Networking Teaching Bachelor/Master Projects & Collaborations OverviewResearch Publications Publications by Type Projects & Collaborations Academic Activities Academic Self-Administration Junior Development, Doctorate and Advanced Studies Academic Reputation & Networking Teaching Bachelor/Master Profiles & Affiliations Projects & Collaborations 3 foundShow per page10 10 20 50 Accelerating collection and use of soil health information using AI technology to support the Soil Deal for Europe and EU Soil Observatory Research Project | 4 Project MembersThe objective of AI4SoilHealth is to co-design, create and maintain an open access European-wide digital infrastructure, compiled using state-of-the-art Artificial Intelligence (AI) methods combined with new and deep soil health understanding and measures. The AI-based data infrastructure functions as a Digital Twin to the real-World biophysical system, forming a Soil Digital Twin. This can be used for assessing and continuously monitoring Soil Health metrics by land use and/or management parcel, supporting the Commission's objective of transitioning towards healthy soils by 2030. The project is divided into seven (7) work-packages including: (WP2) Policy and stakeholder engagement - networking and synchronizing with EU and national programs, (WP3) Soil health methodology and standards - developing/testing methodology to be used by WPs 4-6, (WP4) Soil health in-situ monitoring tools and data - developing field and laboratory solutions for Observations & Measurements, (WP5) Harmonised EU-wide soil monitoring services - developing the final suite of tools, data and services, (WP6) Multi-actor engagement pilots - organizing field-works and collect users' feedback, (WP7) Soil literacy, capacity building and communication - organizing public campaigns and producing educational materials. Key deliverables include: 1) Coherent Soil Health Index methodology, 2) Rapid Soil Health Assessment Toolbox, 3) AI4SoilHealth Data Cube for Europe, 4) Soil-Health-Soil-Degradation-Monitor, and 5) AI4SoilHealth API and Mobile phone App. Produced tools will be exposed to target-users (including farmer associations in >10 countries), so their feedback is used to improve design/functionality. Produced high-resolution pan-European datasets will be distributed under an Open Data license, allowing easy access by development communities. AI4SoilHealth will provide an effective Soil Health Index certification system to support landowners and policy makers under the new Green Deal for Europe. Keywords: Biogeochemistry, biogeochemical cycles, environmental chemistry, Earth observations from space/remote sensing, Environment, resources and sustainability, Environmental monitoring systems, Terrestrial ecology, land cover change. Linking soil hydraulic properties with soil erosion estimations Research Project | 2 Project MembersLinking soil hydraulic properties with soil erosion estimations Saturated hydraulic conductivity Ks can be used to describe water movement under saturated conditions in the soils. It differentiates the amount of water infiltrating into the soil and the amount of water flowing over the surface as runoff. Soils with small values of hydraulic conductivity have low infiltration rates and during intense rains, water run-off will lead to consequent soil losses and surface transport of colloids, nutrients, and microbes, which can then cause problems of eutrophication and pollution of downstream areas (Dexter et al., 2004). Objectives: 1. To locate the hotspots with low saturated hydraulic conductivity and high soil erosion 2. To combine saturated hydraulic conductivity ( Gupta et al, 2021 ) and soil erosion ( Pasquale et al., 2017 ) spatial maps to modify risk classe s Mapping soil properties at high spatial resolution using remote sensing datasets and machine learning approaches Research Project | 2 Project MembersSpatial soil maps are essential for monitoring, management, and conservation. Maps of soil properties are available from regional to global scales, with global maps being urgently needed for global modelling and management endeavours (from soil degradation to climate change modelling and assessments). Objectives: 1. To link soil organic carbon, soil texture, nitrogen, and phosphorus to various remote sensing parameters (vegetation, topography, climate) and using machine learning algorithm. 2. To generate high resolution (20-30 m) spatial response and uncertainty maps of Switzerland 3. To compare the accuracy with different available maps 1 1 OverviewResearch Publications Publications by Type Projects & Collaborations Academic Activities Academic Self-Administration Junior Development, Doctorate and Advanced Studies Academic Reputation & Networking Teaching Bachelor/Master
Projects & Collaborations 3 foundShow per page10 10 20 50 Accelerating collection and use of soil health information using AI technology to support the Soil Deal for Europe and EU Soil Observatory Research Project | 4 Project MembersThe objective of AI4SoilHealth is to co-design, create and maintain an open access European-wide digital infrastructure, compiled using state-of-the-art Artificial Intelligence (AI) methods combined with new and deep soil health understanding and measures. The AI-based data infrastructure functions as a Digital Twin to the real-World biophysical system, forming a Soil Digital Twin. This can be used for assessing and continuously monitoring Soil Health metrics by land use and/or management parcel, supporting the Commission's objective of transitioning towards healthy soils by 2030. The project is divided into seven (7) work-packages including: (WP2) Policy and stakeholder engagement - networking and synchronizing with EU and national programs, (WP3) Soil health methodology and standards - developing/testing methodology to be used by WPs 4-6, (WP4) Soil health in-situ monitoring tools and data - developing field and laboratory solutions for Observations & Measurements, (WP5) Harmonised EU-wide soil monitoring services - developing the final suite of tools, data and services, (WP6) Multi-actor engagement pilots - organizing field-works and collect users' feedback, (WP7) Soil literacy, capacity building and communication - organizing public campaigns and producing educational materials. Key deliverables include: 1) Coherent Soil Health Index methodology, 2) Rapid Soil Health Assessment Toolbox, 3) AI4SoilHealth Data Cube for Europe, 4) Soil-Health-Soil-Degradation-Monitor, and 5) AI4SoilHealth API and Mobile phone App. Produced tools will be exposed to target-users (including farmer associations in >10 countries), so their feedback is used to improve design/functionality. Produced high-resolution pan-European datasets will be distributed under an Open Data license, allowing easy access by development communities. AI4SoilHealth will provide an effective Soil Health Index certification system to support landowners and policy makers under the new Green Deal for Europe. Keywords: Biogeochemistry, biogeochemical cycles, environmental chemistry, Earth observations from space/remote sensing, Environment, resources and sustainability, Environmental monitoring systems, Terrestrial ecology, land cover change. Linking soil hydraulic properties with soil erosion estimations Research Project | 2 Project MembersLinking soil hydraulic properties with soil erosion estimations Saturated hydraulic conductivity Ks can be used to describe water movement under saturated conditions in the soils. It differentiates the amount of water infiltrating into the soil and the amount of water flowing over the surface as runoff. Soils with small values of hydraulic conductivity have low infiltration rates and during intense rains, water run-off will lead to consequent soil losses and surface transport of colloids, nutrients, and microbes, which can then cause problems of eutrophication and pollution of downstream areas (Dexter et al., 2004). Objectives: 1. To locate the hotspots with low saturated hydraulic conductivity and high soil erosion 2. To combine saturated hydraulic conductivity ( Gupta et al, 2021 ) and soil erosion ( Pasquale et al., 2017 ) spatial maps to modify risk classe s Mapping soil properties at high spatial resolution using remote sensing datasets and machine learning approaches Research Project | 2 Project MembersSpatial soil maps are essential for monitoring, management, and conservation. Maps of soil properties are available from regional to global scales, with global maps being urgently needed for global modelling and management endeavours (from soil degradation to climate change modelling and assessments). Objectives: 1. To link soil organic carbon, soil texture, nitrogen, and phosphorus to various remote sensing parameters (vegetation, topography, climate) and using machine learning algorithm. 2. To generate high resolution (20-30 m) spatial response and uncertainty maps of Switzerland 3. To compare the accuracy with different available maps 1 1
Accelerating collection and use of soil health information using AI technology to support the Soil Deal for Europe and EU Soil Observatory Research Project | 4 Project MembersThe objective of AI4SoilHealth is to co-design, create and maintain an open access European-wide digital infrastructure, compiled using state-of-the-art Artificial Intelligence (AI) methods combined with new and deep soil health understanding and measures. The AI-based data infrastructure functions as a Digital Twin to the real-World biophysical system, forming a Soil Digital Twin. This can be used for assessing and continuously monitoring Soil Health metrics by land use and/or management parcel, supporting the Commission's objective of transitioning towards healthy soils by 2030. The project is divided into seven (7) work-packages including: (WP2) Policy and stakeholder engagement - networking and synchronizing with EU and national programs, (WP3) Soil health methodology and standards - developing/testing methodology to be used by WPs 4-6, (WP4) Soil health in-situ monitoring tools and data - developing field and laboratory solutions for Observations & Measurements, (WP5) Harmonised EU-wide soil monitoring services - developing the final suite of tools, data and services, (WP6) Multi-actor engagement pilots - organizing field-works and collect users' feedback, (WP7) Soil literacy, capacity building and communication - organizing public campaigns and producing educational materials. Key deliverables include: 1) Coherent Soil Health Index methodology, 2) Rapid Soil Health Assessment Toolbox, 3) AI4SoilHealth Data Cube for Europe, 4) Soil-Health-Soil-Degradation-Monitor, and 5) AI4SoilHealth API and Mobile phone App. Produced tools will be exposed to target-users (including farmer associations in >10 countries), so their feedback is used to improve design/functionality. Produced high-resolution pan-European datasets will be distributed under an Open Data license, allowing easy access by development communities. AI4SoilHealth will provide an effective Soil Health Index certification system to support landowners and policy makers under the new Green Deal for Europe. Keywords: Biogeochemistry, biogeochemical cycles, environmental chemistry, Earth observations from space/remote sensing, Environment, resources and sustainability, Environmental monitoring systems, Terrestrial ecology, land cover change.
Linking soil hydraulic properties with soil erosion estimations Research Project | 2 Project MembersLinking soil hydraulic properties with soil erosion estimations Saturated hydraulic conductivity Ks can be used to describe water movement under saturated conditions in the soils. It differentiates the amount of water infiltrating into the soil and the amount of water flowing over the surface as runoff. Soils with small values of hydraulic conductivity have low infiltration rates and during intense rains, water run-off will lead to consequent soil losses and surface transport of colloids, nutrients, and microbes, which can then cause problems of eutrophication and pollution of downstream areas (Dexter et al., 2004). Objectives: 1. To locate the hotspots with low saturated hydraulic conductivity and high soil erosion 2. To combine saturated hydraulic conductivity ( Gupta et al, 2021 ) and soil erosion ( Pasquale et al., 2017 ) spatial maps to modify risk classe s
Mapping soil properties at high spatial resolution using remote sensing datasets and machine learning approaches Research Project | 2 Project MembersSpatial soil maps are essential for monitoring, management, and conservation. Maps of soil properties are available from regional to global scales, with global maps being urgently needed for global modelling and management endeavours (from soil degradation to climate change modelling and assessments). Objectives: 1. To link soil organic carbon, soil texture, nitrogen, and phosphorus to various remote sensing parameters (vegetation, topography, climate) and using machine learning algorithm. 2. To generate high resolution (20-30 m) spatial response and uncertainty maps of Switzerland 3. To compare the accuracy with different available maps
