With every new constellation of satellites sent into space over the decades, carrying ever more powerful arrays of optical and radar sensors, the treasure trove of Earth observation (EO) data has been growing – and with the likes of NASA and the European Space Agency often giving it away, this vast and growing pool of information is now available to smaller organizations with modest budgets.
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.