But the full potential can only crystallize within the right framework; so far the main beneficiaries of the EO data bonanza have been large scale projects with the resources to analyze and make sense of this expanding resource — which in itself can be a major technological challenge. However, as suitable software and information platforms become more widely available, advanced uses of EO data are being brought within the reach of regional institutions, local governments and research organizations in developing and emerging countries, as well as smaller businesses and groups in the U.S. and Europe.
This is a particularly exciting development, as the availability of EO-based products across a much wider market will likely lead to many new, and some previously undreamed of, applications across fields such as conservation, development, economic strategy and agriculture. The Earth observation community is therefore grappling with the problem of how to turn vast resources of freely available data into economically viable information products. However, while technology is helping to remove barriers, social and economic factors are holding back development.
Because the market is fragmented and many of the potential beneficiary organizations are unaware of the possibilities inherent to EO data, it is difficult for technology providers to form a clear understanding of exactly what end user content is required. And without clear business cases for delivery, it is hard for firms to invest in, develop and deliver viable long-term services.
EO technology companies are currently working with a disparate and complex user base, comprising state and federal agencies, non-governmental organizations, businesses and the research community. The communities of users have become accustomed to using EO applications on a one-off basis to address specific questions, and each organization has typically resourced the work on a project-by-project basis for their own specific needs. While much of the work done is of good quality, it is often filed away in obscure locations in different media and formats and not really accessible. So while many EO analysts have been working hard over several years, the sum total of useful and available information and data products is disappointing.
A related challenge is ensuring long-term economic viability of information services. There is still a big gap in the understanding of users regarding the need to pay for information products when the raw data is free, versus the cost of developing and running data applications. At present, there is a common perception among end users that EO products should be free and open source, but while that may be desirable, it provides little incentive for firms to develop quality data products that address specific needs — let alone to guarantee their long-term provision.
Data processing, classification, calibration and quality controls all require time, effort and resources that are not readily provided by an open data model. One model that may work better is where a keystone client for a given information product commissions its development, and then tiers of free and paid content are provided for users requiring different levels of detail.
In order to create a way through the current economic impasse, attempts are being made to seed the appetite for EO, and develop an understanding of it, by supporting regional hubs. Regional development agencies in Latin America are among those experimenting with this approach. A new project supported by the UK Space Agency is setting up virtual regional Earth observation labs in partner countries, starting with stakeholders in the forest sectors of Mexico and Brazil.
The hub approach aims to tackle a situation in which EO information products are fragmented, of variable quality, discontinuous and limited in coverage. In the case of forestry projects in Latin America, there is generally a demand for a system which assesses the risks to different forest ecosystems from agricultural expansion, human-induced fires and timber extraction.
It is hoped that by providing access to EO via the hubs, and working with local partners to tailor development, products can be developed that offer complete coverage and defined quality levels. These could then be provided with a clear plan for continuity, making these much more usable and reliable for NGOs and local government organizations looking to promote conservation and monitor forest loss.
The regional lab model should prove to be a flexible and cost effective delivery mechanism, since it employs scalable cloud computing architecture that can be set up within an existing research organization, without the need for new physical infrastructure. The UK Space Agency project is also addressing economic issues preventing satellite-derived data from taking off, by stipulating that each regional lab must develop a business model to ensure it can continue to deliver and expand its services.
Despite these steps, the greatest effort will likely be required in the less glamorous area of dialogue with multiple stakeholders, business planning and collaboration. The sustainability of big data in the Earth observation arena will come down to dollars and cents, and good old-fashioned business sense. The U.S. has both of those, as well as the longest running and most established EO programs. It will therefore be interesting to see what economic and business models evolve to bring EO products to the dozens of markets that are, as yet, largely untapped.
Meanwhile, the hub approach should help seed EO in developing economies, where different models will likely emerge as a variety of local arrangements are devised for deploying EO to support regional development. Both in developed and developing economies, the potential of EO is still largely untapped by smaller organizations. By seeking ways to viably service these groups, the EO community can truly democratize the mass of information which is freely available, but currently unused.