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 be 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.
Anushka Ghildiyal
"MONITORING AND PREDICTION OF PASTURE QUALITY AND PRODUCTIVITY USING PLANET SCOPE SATELLITE DATA
FOR SUSTAINABLE LIVESTOCK PRODUCTION SYSTEMS IN COLOMBIA"
MSc Geoinformation Technology and Cartography
This zipped folder contains 9 folders which has files in multiple formats (.tiff, .csv, .rds, .shp, .docx etc)
2488539G_MScProduct_20200831_ArcGISPro_files
2488539G_MScProduct_20200831_Colombia_shapefile
2488539G_MScProduct_20200831_Dataset
2488539G_MSc_20200831_Dissertation
2488539G_MScProduct_20200831_ExtractedPoint_shapefile
2488539G_MScProduct_20200831_Figures
2488539G_MScProduct_20200831_Indices_Bands
2488539G_MScProduct_20200831_Patia_GroundTruth
2488539G_MScProduct_20200831_PlanetScope_datasets
2488539G_MScProduct_20200831_R scripts
File naming convention: Dissertation: StudentNo_MSc_YYYYMMDD_Title Product: StudentNo_MScProduct_YYYYMMDD_Title
StudentNo - Student Number MSc- To indicate it is a MSc project document MSc Project- Product of the project YYYYMMDD- Date last modified in year-month-date format Title- Name of the document folder