Publicação
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal
| dc.contributor.advisor | Torres-Sospedra, Joaquín | |
| dc.contributor.advisor | Kuntz, Steffen | |
| dc.contributor.advisor | Meyer, Hanna | |
| dc.contributor.author | Petersen, Syver Jahren | |
| dc.date.accessioned | 2022-03-16T16:00:16Z | |
| dc.date.available | 2022-03-16T16:00:16Z | |
| dc.date.issued | 2022-03-02 | |
| dc.description | Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies | pt_PT |
| dc.description.abstract | Timely, reliable, and cost-efficient information about soil moisture is important for supporting agricultural practitioners in monitoring the impact of alternative agricultural practices. Regenerative agriculture is increasingly gaining traction; however, farmers lack easy access to information on key agricultural parameters such as soil moisture. Therefore, this study seeks to explore the feasibility of soil moisture estimation at high-resolution (around 10 m) using Sentinel-1 remote sensing radar data. A machine learning model was developed using a random forest regression algorithm with a combination of SAR-based, topography and Seninel-2 optical-based data as inputs. Through a k-fold cross-validation of the model, an average r-squared (R²) of 0.17, a root mean squared error (RMSE) of 3.51 (% VMC), and an mean absolute percentage error (MAPE) of 83.34, was achieved. | pt_PT |
| dc.identifier.tid | 202966194 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/134627 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | pt_PT |
| dc.title | High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Tecnologias Geoespaciais | pt_PT |
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