Yonah, Isack2026-03-252026-03-252016https://www.suaire.sua.ac.tz/handle/20.500.14820/7453DissertationMonitoring smallholder production systems for crop condition and yield through remote sensing techniques is challenging due to the heterogeneity of farming systems. The study was conducted at Sokoine University of Agriculture (SUA) and Magadu farmers’ maize fields in Morogoro Tanzania. This study investigated the relation between vegetation indices (Vls) and field measurements of crop condition and yield as indicated by maize growth (biophysical) parameters under mixed farming practices. Unmanned Aerial Vehicle (UAV) and Landsat 8 (green, red, red-edge, and near infrared spectral bands) were used to calculate four spectral vegetation indices; the normalized difference vegetation index (NDVI), wide dynamic range vegetation index (WDRVI), red-edge chlorophyll index (CIred-edge)» and the green chlorophyll index (CIgreen)- The Clgreen, Clred" edge and NDVI showed ability to detect differences in maize crop biophysical parameters With CIgreen and NDVI performing better than the other indices. The CIgreen and NDVI were the best indices for detection of the effect of fertilizer application (fertilizer and non­ fertilizer) and pigeon pea intercropping (with pigeon pea and without pigeon pea intercrop) on maize at 60 days after sowing due to R2 > 0.50. The best performance of these indices was on grain yield, where all UAV-VIs detected yield variability by higher R2 values (> 0.60) for both sole and intercropped maize. The assessment for the usefulness of satellite remote sensing Vls showed that the satellite derived Vis were significantly affected more by cloud cover than UAV-Vls. Thus, the NDVI and WDRVI derived from UAV and Landsat 8 were significantly different (p < 0.05); unlike UAV-CIgreen which exhibited some consistence with Landsat 8-Clgreen and their differences were not statistically significant except under heavy cloud cover. These findings clearly demonstrate the need to use multiple vegetation indices to best monitor maize crop conditions and yield differences attributed to different farming practices and weather conditions.enSmallholder production systemsMaize fieldsMonitoring smallholderHeterogeneity farming systemsThesis