MediaMonitoring the Sustainable Development Goals with the huge Remote Sensing archives (co-organized) | PICO
|Convener: Gary Watmough | Co-Convener: Steffen Fritz|
/ Tue, 25 Apr, 10:30–12:00
The Sustainable Development Goals (SDGs) are a globally agreed set of aspirations containing 17 goals and 169 targets covering many aspects of sustainable development. They include ending global poverty and hunger, improving human health and well-being and protection and restoration of marine and terrestrial ecosystems.
One of the main challenges to sustainable development and the success of the SDGs is the monitoring of goals. The monitoring of the SDG needs to be done by the whole world. Some of the SDG indicators can be generated by REmote Sensing data but this requires to be able to extract the right information from the Remote Sensing big data archives and recent Earth observations constellations. In the past the National Census and Household Surveys are the most commonly used method for monitoring changes in the global goals. They are expensive and time consuming and therefore usually conducted once every ten years. This gap between enumeration means that often it is possible to identify that a change has occurred but not how or why this change occurred. Another problem with census data is that they are delivered in aggregate form while Remote Sensing data can provide a very detailed spatial distribution of a variable and in daily of weekly frequencies. Another advantage of RS is that the most impoverished countries census and household surveys are collected infrequently and when collected can be of a poor quality while RS data is more evenly distributed. Integration of remotely sensed data and household survey data for monitoring and evaluation will require multi-disciplinary approaches. We welcome submissions from studies that combine satellite data with household survey data to measure spatially distributed variables that can serve a bases for indicators of the SDG targets. Research projects with examples of combining geospatial data with household survey data applied are welcome as well as technical projects focussing on integrating time series satellite data with changes in human development.