Remote Sensing of Economic Development in Data-Poor Regions

Dear Colleagues,

The lack of reliable data in low-income countries holds back both development and disaster management. Large portions of the population are missed or ignored, and important aspects of people’s lives and environmental conditions are not measured. For example, the recently terminated Millennium Development Goals (MDGs) effort never achieved more than 70% of the 55 core indicators in 157 countries, if any for some of the poorest countries. The MDGs are now replaced with 17 interrelated Sustainable Development Goals (SDGs) with more than 169 targets. They cover a broad range of issues, such as poverty, hunger, climate change, gender, and equality. Without high-quality data to reduce uncertainty, designing, monitoring, and evaluating effective policies becomes almost impossible to achieve (IEAG, 2014). Traditional forms of data gathering such as surveys and census fail to provide the widespread coverage and rich levels of information necessary to inform and evaluate complex policy. Remote sensing has enormous potential to deliver timely, relevant, and cost-effective information about the impact of policies and the measurement of key targets.

Although many of the new digital forms of data provide exciting opportunities in terms of the variety of information which is available and the speed with which it can be collected, we recognize that large volumes of data from traditional data sources already exist. These data sources, include hundreds of thousands of on-the-ground surveys conducted by myriad public and private organizations and various satellite imagery datasets that date back to the beginning of the technology’s introduction in the 1970s. They are expected to continue to grow in volume and in the speed with which they are captured. However, a major problem with both new and existing data is that they are gathered in a heterogeneous and unstructured form. While we are now living in an age where a great deal of data is available, we are falling behind in developing useful information from it because we do not have the tools or resources to process it.

This Special Issue aims to publish high-quality research papers on original and novel studies demonstrating the applications of remote sensing to economic development, with emphasis on developing regions of the world. Addressing developmental challenges from an interdisciplinary perspective holds the potential to effectively tackle some of the most pressing challenges confronting humanity today. However, attempts at applying remote sensing tools to social science problems date as far back as the mid-1990s when the National Aeronautics and Space Administration approached the research community to exploit the potentials of satellite imagery. Despite the high hopes for People and Pixels: Linking Remote Sensing and Social Science (Liverman et al., 1998), results have not been outstanding (Longley 2002). Many of the limitations that limited satellite remote sensing application in the social sciences in the early stages have largely been ameliorated by recent improvements in the spatial and temporal resolution as well as significant strides in the developments in new platforms such as drones and methods such as machine learning. This Special Issue will publish original research papers which apply remote-sensing-based techniques or data to analyze economic development, especially as it relates to the Sustainable Development Goals. Furthermore, papers addressing methodological, theoretical, and ethical issues relating to remote sensing in development are encouraged. Review contributions are also welcomed.

Dr. Ola Hall
Dr. Ibrahim Wahab
Guest Editors

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• Spatio-temporal analysis of human activities
• Development mapping
• Data availability and quality in developing regions
• Data integration (e.g., household surveys and RS)
• Theoretical/ethical implications of remote sensing data collection
• Crop yield prediction
• Poverty and welfare indicators