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How Much Would You Pay for a Satellite Image?: Lessons Learned From French Spatial-Data Infrastructure

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Abstract

Satellite imagery is increasingly employed for land-use analysis and planning. In this article, we examine the economic value of high-resolution (HR) satellite images as perceived by direct users. Drawing on a French spatial-data infrastructure (SDI), the direct users of which are mostly from public bodies, we used a contingent-valuation method to evaluate their willingness to pay (WTP) for satellite imagery. A clear understanding of the value of these images is critical for justifying the large investments made in this sector and supporting policies that aim to develop and sustain these resources. We analyze the differences in the stated values according to the various types of users.

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... It is responding to the needs of the scientific community, through a pooling system developed specifically to better sharing the benefits of the open innovation processes. For instance, an absence of such a system (an investment of e11 million), would have cost e110 million to GEOSUD users to acquire images separately from independent spatial data providers at preferential rates [33]. ...
... The HR satellite imagery provided through the GEOSUD SDI comes as additional concrete example. Since its launch, GEOSUD is facilitating the access to a wide variety of geospatial data and services [33]. This shift is a major result from the United States open and free data policy adopted in 2008. ...
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... So far, little effort has been dedicated to formalizing, aggregating and sharing expert knowledge in remote sensing applications [32]. This paper provides a methodology that can contribute to support the transition from a data-centric to a knowledge-centric approach [92]. This transition is strongly encouraged by the Group of Earth Observation (GEO) in support to decision makers. ...
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Traditional space relations among civilian space actors are undergoing in the post-cold war era a rapid evolution with a growing number of new institutional entities. The cold war era and its resulting political environment, which limited space cooperation to ‘intra-bloc’ cooperation has disappeared, allowing the development of new axes and mechanisms of cooperation. The internationalization and regionalization of space activities witnessed in recent years is foreseen to gain momentum, leading therefore to a new geography of civilian space activities.
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One of the key responsibilities of any government is to communicate and disseminate safety information and warnings to the general public in case of an emergency. Traditionally, warnings are issued by the government through a broadcast approach using communication channels such as TV and radio. However this monopolistic approach is now challenged by new technologies and media capable of providing individualised warnings to personal mobile devices. Location-based emergency services and mobile alerts are becoming increasingly prevalent in the provision of emergency warnings. These new modes of emergency services have been adopted by several countries worldwide including Australia. One example is the Australian National Emergency Alert (EA) which is a telephone-based service enhanced with location-based capabilities. This paper introduces the concept of applying global satellite navigation systems such as the Japanese satellite system in the domain of emergency warning and alerting. The Japanese satellite warning system can be tailored to transmit real-time location-based emergency warnings to people's mobile devices while not being constrained by the limitations of ground-based communication technologies. A key advantage of satellite based communication is its high resilience to communication network overload and failure of ground systems and network infrastructure during a disaster. This enables people to obtain necessary information anywhere (outdoor) and anytime during times of disaster. A satellite-based warning system could also be integrated with existing warning services and be used as a complementary technology. This paper examines opportunities and challenges for using satellite navigation systems to deliver warnings and safety messages during emergencies and disasters.
Book
The book examines applications in two disparate fields linked by the importance of valuing information: public health and space. Researchers in the health field have developed some of the most innovative methodologies for valuing information, used to help determine, for example, the value of diagnostics in informing patient treatment decisions. In the field of space, recent applications of value-of-information methods are critical for informing decisions on investment in satellites that collect data about air quality, fresh water supplies, climate and other natural and environmental resources affecting global health and quality of life.
Article
In this special issue, the authors provide in-depth historical and contemporary studies to examine how land is known and the ways in which land management and expertise are produced, disseminated, experienced and contested. The papers analyze the production of models, frameworks, calculations, tools, and ideas that shape land use and access to resources. These empirical and conceptual insights are particularly critical today as declarations of crisis precipitate the search for ‘new,’ ‘empty,’ or ‘unproductive’ land. The themes of expertise, (in)visibility/ignorance, displacements, and crisis frame our treatment of the relationship between knowledge and the politics of land management.
Article
While the U.S. government does not charge for downloading Landsat images, the images have value to users. This paper demonstrates a method that can value Landsat and other imagery to users. A survey of downloaders of Landsat images found: (a) established US users have a mean value of $912 USD per scene; (b) new US users and users returning when imagery became free have a mean value of $367 USD per scene. Total US user benefits for the 2.38 million scenes downloaded is $1.8 billion USD. While these benefits indicate a high willingness-to-pay among many Landsat downloaders, it would be economically inefficient for the US government to charge for Landsat imagery. Charging a price of $100 USD a scene would result in an efficiency loss of $37.5 million a year. This economic information should be useful to policymakers who must decide about the future of this and similar remote sensing programs.
Article
This article argues that local knowledge building and global (nonlocal) knowledge-accessing practices in economic development are intrinsically interwoven. They generate fundamental feedback loops, which are channeled through and lead to ongoing knowledge circulation. To better understand the nature of the specific mechanisms and conditions underlying these processes, three key areas of research are identified for current and future research. These are related to (i) creative agents and the nature of local creative processes, (ii) community formation and local creativity from ideas to market penetration and (iii) temporary gatherings as translocal knowledge platforms.
Article
This article reviews the developing links between economic geography and innovation theory and practical management in terms of research and literature. This article identifies five main themes, where this has been most evident, namely: coordination issues; proximity and geographical environment (including clusters, spillovers, agglomerations and networks); flows and connections: transactions and trade; enterprise and entrepreneurship; and innovation and knowledge. This article positions the papers in this Special Issue within this framework and identifies areas for future research between the two fields.
Article
Organizational routines are considered basic components of organizational behavior and repositories of organizational capabilities (Nelson & Winter, 1982). They do, therefore, hold one of the keys to understanding organizational change. The article focuses on how the concept of organizational routines can be applied in empirical research to understand organizational change. We identify problems encountered in such research and present proposals for how to deal with them, in order to advance our knowledge of routines and our understanding of organizational change. Developing these themes, we also introduce the articles in the special section ‘Towards an Operationalization of the Routines Concept’.
Article
The debate about behavioral economics--the incorporation of insights from psychology into economics--is often framed as a question about the foundational assumptions of economic models. This paper presents a more pragmatic perspective on behavioral economics that focuses on its value for improving empirical predictions and policy decisions. I discuss three ways in which behavioral economics can contribute to public policy: by offering new policy tools, improving predictions about the effects of existing policies, and generating new welfare implications. I illustrate these contributions using applications to retirement savings, labor supply, and neighborhood choice. Behavioral models provide new tools to change behaviors such as savings rates and new counterfactuals to estimate the effects of policies such as income taxation. Behavioral models also provide new prescriptions for optimal policy that can be characterized in a non-paternalistic manner using methods analogous to those in neoclassical models. Model uncertainty does not justify using the neoclassical model; instead, it can provide a new rationale for using behavioral nudges. I conclude that incorporating behavioral features to the extent they help answer core economic questions may be more productive than viewing behavioral economics as a separate subfield that challenges the assumptions of neoclassical models.
Article
Error: Its Sources, Propagation, and Analysis. Rootfinding for Nonlinear Equations. Interpolation Theory. Approximation of Functions. Numerical Integration. Numerical Methods for Ordinary Differential Equations. Linear Algebra. Numerical Solution of Systems of Linear Equations. The Matrix Eigenvalue Problem. Appendix. Answers to Selected Problems. Index.
Article
The relative operating characteristic (ROC) is a widely-used method to measure diagnostic signals including predictions of land changes, species distributions, and ecological niches. The ROC measures the degree to which presence for a Boolean variable is associated with high ranks of an index. The ROC curve plots the rate of true positives versus the rate of false positives obtained from the comparison between the Boolean variable and multiple diagnoses derived from thresholds applied to the index. The area under the ROC curve (AUC) is a summary metric, which is commonly reported and frequently criticized. Our manuscript recommends four improvements in the use and interpretation of the ROC curve and its AUC by: (1) highlighting important threshold points on the ROC curve, (2) interpreting the shape of the ROC curve, (3) defining lower and upper bounds for the AUC, and (4) mapping the density of the presence within each bin of the ROC curve. These recommendations encourage scientists to interpret the rich information that the ROC curve can reveal, in a manner that goes far beyond the potentially misleading AUC. We illustrate the benefit of our recommendations by assessing the prediction of land change in a suburban landscape.
Article
Coffee is one of the most important crops in Brazil. Monitoring the crop is necessary to understand future production and a sound understanding of coffee's biophysical properties improves such monitoring. Biophysical properties such as dry biomass can be estimated using remote sensing, including the new generation of high-resolution images (GeoEye-1, for instance). In this study we aim to investigate the relationship between vegetation indices (VI) of high-resolution images (GeoEye-1) and coffee biophysical properties, including dry biomass and carbon. The study also aims at establishing an empirical relationship between remote sensing data (vegetation indices), simple field measurements and dry biomass, allowing calculation of coffee biomass and carbon without resorting to destructive methods. Individual GeoEye-1 satellite's bands (NIR, RED and GREEN) showed significant correlation with biomass, but the best correlation occurred with vegetation index. There is a strong correlation between NDVI, RVI, GNDVI and dry biomass, allowing the estimation of coffee crops' carbon stock. RVI had correlation with plant area index (PAI). The empirical correlation was established and the forecast equation of coffee biomass was created.
Article
This paper reviews the potential applications of satellite remote sensing to regional science research in urban settings. Regional science is the study of social problems that have a spatial dimension. The availability of satellite remote sensing data has increased significantly in the last two decades, and these data constitute a useful data source for mapping the composition of urban settings and analyzing changes over time. The increasing spatial resolution of commercial satellite imagery has influenced the emergence of new research and applications of regional science in urban settlements because it is now possible to identify individual objects of the urban fabric. The most common applications found in the literature are the detection of urban deprivation hot spots, quality of life index assessment, urban growth analysis, house value estimation, urban population estimation and urban social vulnerability assessment. The satellite remote sensing imagery used in these applications has medium, high or very high spatial resolution, such as images from Landsat MSS, Landsat TM and ETM+, SPOT, ASTER, IRS, Ikonos and QuickBird. Consistent relationships between socio-economic variables derived from censuses and field surveys and proxy variables of vegetation coverage measured from satellite remote sensing data have been found in several cities in the US. Different approaches and techniques have been applied successfully around the world, but local research is always needed to account for the unique elements of each place. Spectral mixture analysis, object-oriented classifications and image texture measures are some of the techniques of image processing that have been implemented with good results. Many regional scientists remain skeptical that satellite remote sensing will produce useful information for their work. More local research is needed to demonstrate the real potential and utility of satellite remote sensing for regional science in urban environments.
Article
This paper introduces a generative model of organizational routines and their change over time. The model demonstrates that variation and selective retention of patterns of action are necessary and sufficient to explain the features of organizational routines that are most relevant in relation to dynamic capabilities, such as formation, inertia, endogenous change, and learning. The model directly links micro‐level actions to the macro‐level dynamics of routines. The results suggest that focusing on action provides a useful and parsimonious foundation for a theory of organizational routines and capabilities.
Article
A time series of Landsat MSS and TM images was used to extract land use/cover change data of the Atlanta, Georgia metropolitan area in the United States over the past 25 years as a component of Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air-quality). ATLANTA is funded by NASA EOS Interdisciplinary Science (IDS) program, which has the objective of modelling the impact of land use/cover change on temperature and air quality in Atlanta. This paper describes a suite of techniques that have been used to develop an operational approach, which will ensure high accuracy and compatibility in image classification from the satellite images of different resolutions and varying quality. These techniques include radiometric normalization to establish a common radiometric response among multi-date/multi-sensor data, an unsupervised image classification approach using image clustering and cluster labelling, a GIS-based image spatial reclassification procedure to deal with classification errors caused by spectral confusion, and post-classification comparison with GIS overlay to map the spatial dynamics of land use/cover change. The loss of forest and urban sprawl have been revealed by the analysis as the major problems of Atlanta's accelerated urban development.
Article
Traditional space relations among civilian space actors are undergoing in the post-cold war era a rapid evolution with a growing number of new institutional entities. The cold war era and its resulting political environment, which limited space cooperation to ‘intra-bloc’ cooperation, has disappeared, allowing the development of new axes and mechanisms of cooperation. The internationalization and regionalization of space activities witnessed in recent years is foreseen to gain momentum, leading therefore to a new geography of civilian space activities.
Article
In this essay, I review recent research on the effects of economic development on democracy. On the theoretical side, for the first time there has been a systematic attempt to bring the types of formal models developed by economists and political scientists outside of comparative politics to bear on the origins of democracy. I present a simple analytical framework that captures some of the results in this literature. On the empirical side, the issue of identifying causal relationships in the data is finally receiving attention. However, the application of techniques adopted from best-practice econometrics shows no evidence that economic development has a causal effect on democracy. Neither does it support the idea that economic development influences the probability of coups but not democratizations. More likely, and in line with the model I develop, income per capita and democracy are correlated because the same features of a society simultaneously determine how prosperous and how democratic it is. There is still a lot to learn on this topic.