Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia
As the population increases, demand for food increases too, which has led to large-scale land conversion to improve livestock production in Colombia. Fulfilling these criteria of increasing demand in a sustainable way is a challenge and remote sensing data provides an accurate method to support this...
| Autores principales: | , |
|---|---|
| Formato: | Tesis |
| Lenguaje: | Inglés |
| Publicado: |
University of Glasgow
2020
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/114672 |
| _version_ | 1855532548374921216 |
|---|---|
| author | Ghildiyal, Anushka Cardoso, Juan Andrés |
| author_browse | Cardoso, Juan Andrés Ghildiyal, Anushka |
| author_facet | Ghildiyal, Anushka Cardoso, Juan Andrés |
| author_sort | Ghildiyal, Anushka |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | As the population increases, demand for food increases too, which has led to large-scale land conversion to improve livestock production in Colombia. Fulfilling these criteria of increasing demand in a sustainable way is a challenge and remote sensing data provides an accurate method to support this task. In this study, Planet Scope multispectral satellite datasets and coincident field measurements acquired over test fields in the study area (Patía) of September 2018 was used. Fresh and dry weight biomass was calculated and forage quality analyses, crude protein (CP), in vitro dry matter digestibility (IVDMD), Ash and standing biomass dry weight (DM) was carried out in the forage nutritional quality laboratory of International Centre for Tropical Agriculture (CIAT). Field data was related to the remote sensing data using the random forest regression algorithm. R was required for the statistical analysis, to figure out the model performance for IVDMD, CP, Ash and DM. This project also investigated the spatial distribution of livestock which is affected by quality and area of potential forage zones. The R2 values of the regression models were 0.74 for IVDMD, 0.69 for CP, 0.38 for Ash and 0.49 for DM using a predictor combination of vegetation indices, simple ratios and bands. |
| format | Tesis |
| id | CGSpace114672 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | University of Glasgow |
| publisherStr | University of Glasgow |
| record_format | dspace |
| spelling | CGSpace1146722025-11-05T12:12:50Z Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia Ghildiyal, Anushka Cardoso, Juan Andrés livestock sustainability pastures productivity ganado sostenibilidad pastizales productividad As the population increases, demand for food increases too, which has led to large-scale land conversion to improve livestock production in Colombia. Fulfilling these criteria of increasing demand in a sustainable way is a challenge and remote sensing data provides an accurate method to support this task. In this study, Planet Scope multispectral satellite datasets and coincident field measurements acquired over test fields in the study area (Patía) of September 2018 was used. Fresh and dry weight biomass was calculated and forage quality analyses, crude protein (CP), in vitro dry matter digestibility (IVDMD), Ash and standing biomass dry weight (DM) was carried out in the forage nutritional quality laboratory of International Centre for Tropical Agriculture (CIAT). Field data was related to the remote sensing data using the random forest regression algorithm. R was required for the statistical analysis, to figure out the model performance for IVDMD, CP, Ash and DM. This project also investigated the spatial distribution of livestock which is affected by quality and area of potential forage zones. The R2 values of the regression models were 0.74 for IVDMD, 0.69 for CP, 0.38 for Ash and 0.49 for DM using a predictor combination of vegetation indices, simple ratios and bands. 2020-08 2021-08-17T08:17:04Z 2021-08-17T08:17:04Z Thesis https://hdl.handle.net/10568/114672 en Open Access application/pdf University of Glasgow Ghildiyal, A.; Cardoso, J.A. (2020) Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia. Glasgow (Scotland): University of Glasgow. 51 p. |
| spellingShingle | livestock sustainability pastures productivity ganado sostenibilidad pastizales productividad Ghildiyal, Anushka Cardoso, Juan Andrés Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia |
| title | Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia |
| title_full | Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia |
| title_fullStr | Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia |
| title_full_unstemmed | Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia |
| title_short | Monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in Colombia |
| title_sort | monitoring and prediction of pasture quality and productivity using planet scope satellite data for sustainable livestock production systems in colombia |
| topic | livestock sustainability pastures productivity ganado sostenibilidad pastizales productividad |
| url | https://hdl.handle.net/10568/114672 |
| work_keys_str_mv | AT ghildiyalanushka monitoringandpredictionofpasturequalityandproductivityusingplanetscopesatellitedataforsustainablelivestockproductionsystemsincolombia AT cardosojuanandres monitoringandpredictionofpasturequalityandproductivityusingplanetscopesatellitedataforsustainablelivestockproductionsystemsincolombia |