Handheld optical sensor was used to measure canopy reflectance at red region (656 nm) and near-infrared region (774 nm) to generate NDVI data for monitoring rice productivity under soil amendment with combinations of fertilizers at two levels of water regime in smallholder Irrigation Scheme, in Lower Moshi, North Tanzania. The study was carried out in an experimental design which consisted of two irrigation water levels (flooding and system of rice intensification) with multi-nutrients (NPK) and single nutrient (urea) application replicated three times in a randomized complete block design. Flood irrigation water was applied at 7 cm height throughout the growing season, while SRI treatment irrigation water was applied at 4 cm height under alternate wetting and drying conditions. The annual rates of fertilizers applied was 120 kg N/ha, 20 kg P/ha, and 25 kg K/ha. The variety SARO-5 was used in this experiment. Simple correlation coefficient (r) was used to measure the degree of association between field crop performance parameters (plant height, number of tillers, biomass, yield) and NDVI across growth stages and three positions of the sensor above the canopy in the tested fertilizer combinations and water regimes. Results show that at any given fertiliser combinations and water levels, there was no significant correlation between plant height and NDVI except for the plant height at a vegetative stage for 0.6 m above the crop canopy and booting stage at 0.3 m and 0.6 m above the canopy, respectively (P < 0.05). A good correlation was also observed between NDVI at booting and full booting stage regardless of the position of the sensor above the canopy and the number of tillers at full booting growth stage (P < 0.05). A significant relationship was observed between rice grain yield and NDVI at the vegetative, booting, and full booting stage. The simple linear regression models explained only slightly < 30% of the yield predictions by NDVI at the early stage of the crop growth, decreasing gradually to 5% at the full booting growth stage. Results demonstrate a positive linear relationship between rice grain yield and NDVI for the tested soil fertiliser amendments and irrigation water regimes. Thus, we conclude that handheld NDVI-based sensor can be used in smallholder rice yield predictions for optimising soil fertiliser use and irrigation water management. This allows future multi-functional land management within the soil–water-food nexus.

Several studies in Tanzania focus on land use/cover change (LULC) at coarse scale and without considering the adjoining (interface) landscapes i.e. landscape link community farming systems and forest/nature reserves. In the Eastern Arc Mountains in particular, LULC change that confront the interface between surrounding community landscape and nature reserves and the associated livelihood are not well understood. A study was conducted in the Usambara Mountains, Tanzania to explore the potential impacts of LULC on the interface between Magamba Nature Reserve (MNR) and the landscape of the surrounding community villages. Remote sensing and GIS techniques were used to quantify and analyse the trend in LULC changes over the past 31 years whereby satellite images of 1984, 1995 and 2015 were used. Household surveys, field observations and focus group discussions to 72 households in 3 villages surrounding the nature reserve were employed to capture data on human activities in the interface. The change detection was done by post classification approach using image interpreter| GIS analysis| matrix tool in QGIS software and processed in an intensity analysis program (Pontius matrix excel sheet). Descriptive statistical analysis (frequency counts and percentages) was used to explain human activities of communities adjacent to the MNR. Qualitative data were analysed using content and structural functional analytical techniques. Over the period natural forest covering the major part of reserve decreased by 14%. The declining trend for forests in the study area is largely attributed to the increasing agricultural activities, settlements and infrastructure. Results revealed further that natural forest area and wetlands had active intensity of gain over the period 1984-1995 while in the 1995-2015 period had active intensity of loss. The most common human activities related to the spatial and temporal dynamics of LULC change in the MNR interface were firewood collection for household use, collection of medicinal plants, illegal timber harvesting, animal grazing, cutting trees for building poles and charcoal burning. Firewood collection is the most important human activity associated with forest degradation in MNR interface. Collection of medicinal plants from the reserve is associated with forest destructive process in the sense that it involves uprooting plants, root cutting, and tree ring debarking. The study recommends that policy makers as well as nongovernmental organizations should identify and establish potential low cost alternative sources of energy for usage by rural domestic household. Further research to predict and map spatial and temporal LULC dynamics at landscape scale should consider future scenarios on the evolution of forest-rural landscape interfaces and their impact on the provisioning of ecosystem services (ESS).

Handheld Optical Sensor was used to measure canopy reflectance at red region (656 nm) and near-infrared region (774 nm) to generate NDVI data for monitoring rice productivity under soil amendment with combinations of fertilizers at two levels of water regime in smallholder Irrigation Scheme, in Lower Moshi, Tanzania. The study was carried out in an experimental design consisted of two irrigation water levels (flooding and system of rice intensification) with multi-nutrients (NPK) and single nutrient (urea) application replicated three times in a randomized complete block design. Flood irrigation water was applied at 7 cm height throughout the growing season, while SRI treatment irrigation water was applied at 4 cm height under alternate wetting and drying conditions. The annual rate of fertilizers applied was 120 kg N/ha, 20 kg P/ha, and 25 kg K/ha. The variety SARO-5 was used in this experiment. Simple correlation coefficient (r) was used to measure the degree of association between field crop performance parameters (plant height, number of tillers, biomass, yield) and NDVI across growth stages and three positions of the sensor above the canopy in the tested fertiliser combinations and water regimes. Results show that at any given fertiliser combinations and water levels, there was no significant correlation between plant height and NDVI except for the plant height at a vegetative stage for 0.6 m above the crop canopy and booting stage at 0.3 m and 0.6 m above the canopy respectively (p < 0.05). A good correlation was also observed between NDVI at booting and full booting stage regardless of the position of the sensor above the canopy and the number of tillers at full booting growth stage (p < 0.05). A significant relationship was observed between rice grain yield and NDVI at the vegetative, booting, and full booting stage. The simple linear regression models explained only slightly less than 30% of the yield predictions by NDVI at the early stage of the crop growth, decreasing gradually to 5% at the full booting growth stage. Results from this study have demonstrated a positive linear relationship between rice grain yield and NDVI for the tested soil fertiliser amendments and irrigation water regimes. The study conclude that handheld NDVI-based sensor can be used in smallholder rice yield predictions for optimising soil fertiliser use and irrigation water management.