Monitoring crop growth and performance during crop developmental stages is an important aspect of agricultural management. It enables the farmer to implement timely interventions that ensure that optimal yield is obtained at the end of the season.
Stress factors often prevent crops from developing at the rate they are capable of. Examples include:
- Poor water availability (e.g. in-season drought)
- Extreme temperatures (heat)
- Competition among plants for sunlight, nutrients, water or space
- Nutrient deficiency (e.g. artificial fertilizer or manure)
- Uncontrolled use of chemicals (toxicity)
- Fungal, bacterial or viral infection
- Attack from insects or other organisms, above or below the ground
- Some of the above arise from shortcomings in labor investment on the plot
(Source: AgriSense / Tanzania Agricultural Extension Service)
RS images, by virtue of their wide area coverage and repetitive acquisition provides valuable information that can assist smallholder farmers to monitor crop growth and performance in a timely fashion throughout the cropping season (Atzberger, 2013; Boschetti et al., 2009; Roy et al., 2014; Shang et al., 2015). In other words, analysis of RS data can improve the identification of the above-mentioned stress factors in time and allow the appropriate interventions to be implemented. Despite its potentials, there are a number of factors that limit the use of RS data for agricultural management (Zurita-Milla et al., 2015). This section of the portal demonstrates the potentials and limitations of RS in supporting smallholder farmers and agricultural managers to efficiently manage their fields for optimal results. It will also inform policy-makers of the types of interventions they should be planning: e.g. large-scale fertilizer deserve different action than large-scale water shortages.