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The STARS Landscaping Study: identifying real and viable opportunities for agricultural development

The STARS Landscaping Study conducted literature reviews, workshops and individual expert consultations across several continents to identify a range of attractive and feasible opportunities for remote sensing to support agricultural development and alleviate poverty. We focused on situations that would involve people moving out of subsistence agriculture into some form of ‘family farming’ that would generate a significant and certain marketable surplus leading to a long-term improvement in household well-being.

Our analysis of past efforts to employ remote sensing in agriculture around the globe indicates that the rapid change and seemingly abundant range of possible new applications for remote-sensing technologies sometimes clouds judgement on which interventions will make a difference to agricultural development. There has been limited adoption of remote sensing in low-income countries for a range of reasons including failure to understand and plan for the constraints faced by individual farmers, the limitations of local and national institutions, and the overall market context. The result has been low impact and a residual reputation of remote sensing “over-promising and under-delivering”.

As a result, we identified four recurring questions that were used to guide our analysis of opportunities for new remote-sensing technologies.


1. Is there an analogue in an agriculturally developed country?

The farming systems of higher income countries have all evolved from smallholder subsistence systems. While the transitions associated with the Green Revolution in East and South Asia are most recent, many agricultural systems in Europe and North America underwent transitions several decades before (i.e. not centuries before). The role of information has common features across all these agricultural transitions. Farmers need basic guidance on the suitability of different farming technologies, as well as about risks from weather, pests and diseases, and market prices. There is nothing intrinsically different about the transitions that need to occur in low-income countries today.

Because of market and institutional constraints, the information services most likely to be useful for agricultural development in low-income countries today will be a subset of those found in more agriculturally developed systems. If sophisticated applications of remote sensing are not being used in high-income countries, then we should not expect them to be viable in less-developed settings. Furthermore, there will be applications of remote sensing in technologically advanced farming systems that are impractical or uneconomic in smallholder systems and it is critical to understand the factors that control the return-on-investment.

Technological optimists are quick to identify ‘leapfrog technologies’ (e.g. mobile telephony circumventing the need for transmission wires in many parts of Africa), but these tend to be exceptions to a more general rule of incremental advances and the reasons for their exceptionality need to be clearly understood. Some claimed technological advances are in fact institutional advances to circumvent other institutional barriers (e.g. electronic transfer of money using mobile phones in east Africa).


2. Does the information directly address agricultural development?

The food system within which agriculture is embedded in is a complex adaptive system. As a consequence, it is not easy to identify what factors are primary constraints to agricultural development and thus the priorities for gathering better information. It is tempting to select broad indicators for which technologies already exist, such as crop yields and yield gaps. However, information on crop yield from remote sensing is unlikely to directly assist a farmer who is already keenly aware of how his or her crop is faring. It is also unlikely to provide guidance on the most beneficial management actions because the gap between actual and potential yields in most poor developing areas is so large and obvious to farmers. Nevertheless, synoptic information on crop yields across a district is vitally important to a policy maker responsible for food security and famine relief. It also provides critical information for trade policies. Such applications are valuable, but only support agricultural development indirectly. Not all paths-to-impact lead directly to the smallholder.


3. Does the information help alleviate poverty?

A key step in alleviating poverty is to move people out of subsistence agriculture into some form of ‘family farming’ that generates a significant marketable surplus. Increasing yields of staple crops (e.g. maize, millet, cassava, rice) may not generate a significant marketable surplus because increases in supply may depress local market prices. In most cases, it is more profitable to generate the marketable surplus via higher-value products that can be grown on small areas without undermining the production of staples for household consumption. Rather than monitoring existing crops, the information needs in this scenario are for determining the potential for new crops, managing climate and market risks, and developing new supply chains.


4. Who pays and is free-riding an option?

It could be argued that remote sensing refutes the adage that ‘nothing comes for free’. The USA and Europe, in particular, have provided the world with almost free access to data that have cost billions of dollars to acquire. It makes a lot of sense for poor countries to utilise these data streams and take maximum advantage of established operational systems because these have a higher likelihood of being maintained in the long run. Of course, countries incur significant costs in establishing the technical capability to access and interpret the free streams of data, but focusing on established remote-sensing systems increases the likelihood of easy access to associated software and infrastructure, and consistent time series. While it may be feasible for donor agencies to fund establishment of new systems, longer term maintenance is another matter altogether. It is not uncommon to find GIS facilities and computing resources that lie idle because software updates have been unaffordable or system administrators have moved on. Low-income countries simply cannot afford to take the risks associated with new satellites and delivery systems, given all the other demands on their limited resources.

 ‘The STARS Landscaping Study provides an overview of how remote sensing can support agricultural development and poverty alleviation (Image courtesy of Plant, Creative Commons 4.0), Location: The Cubango River on the border of Namibia and Angola with diverse forms of agricultural development).


Further reading

The final report from the STARS Landscaping Study provides a review of the systems context for understanding how information systems can support agricultural development. It includes a review of recent advances in remote sensing and geospatial technologies along with an analysis of ten broad opportunities for remote sensing to support agricultural development and poverty alleviation.