Task Team on Satellite Imagery and Geo-Spatial Data
Mission and Strategies
The demand for more diversified, sophisticated and rapid statistical services could be met by leveraging the emerging sources of Big Data, such as those relating to remote sensing imagery, transactional and social media data and mobile device data.
Statistical agencies around the world have a strong interest in investigating the viability of using satellite imagery data to improve official statistics on a wide range of topics spanning agriculture, the environment, business activity and transport. Satellite imagery has significant potential to provide more timely statistical outputs, to reduce the frequency of surveys, to reduce respondent burden and other costs and to provide data at a more disaggregated level for informed decision making.
Satellite imagery may also support the monitoring of the Post-2015 development goals by improving timeliness and relevance of indicators without compromising their impartiality and methodological soundness.
The Task Team on Satellite Imagery and Geo-Spatial Data aims to provide strategic vision, direction and development of a global work plan on utilising satellite imagery and geo-spatial data for official statistics and indicators for post-2015 development goals. We are building on precedents to innovatively solve the many challenges facing the use of satellite imagery and geo-spatial data sources.
Specifically, we will
- Identify reliable and accurate statistical methods for estimating quantities of interest;
- Suggest approaches for collecting representative training and validation data of sufficient quality;
- Research, develop and implement assessment methods for the proposed models including measures of accuracy and goodness of fit;
- Establish strategies to reuse and adapt algorithms across topics and to build implementations for large volumes of data.
Pilot Projects
Stock-taking satellite sensing datasets
The International Telecommunication Unit is the entity responsible for coordinating the assignment of both radio spectrum and satellite orbits. By surveying its membership of satellite operators, the pilot will identify the satellite sensing datasets that could potentially be used for official statistics, as well as the different characteristics of available datasets.
Crop Density mapping
The Food and Agriculture Organization of the United Nations (FAO), in collaboration with the US Geological Survey, will aim to improve the reliability of MODIS-based and Landsat-based products for agricultural area statistics. The pilot will improve the calibration and validation methods involving the collection of ground-based data to be used for verifying the accuracy of the estimated cropland products.
Agricultural Statistics
The Australian Bureau of Statistics will assess the feasibility of statistical methodology for classifying satellite surface reflectance data to crop type and for estimating crop production. This will help answer the questions of whether it is possible to statistically distinguish crop types and whether different models need to be developed for different regions or countries.
Land cover and land use statistics
The Colombian National Department of Statistics (DANE) will assess the feasibility of applying remote sensing processing methodologies for the estimation of land consumption rate, and applying GIS spatial analysis for the calculation of the relationship between land consumption and population growth in metropolitan areas. The pilot study will help answer the questions of whether it is possible to use this as a measure of land-use efficiency. This indicator would provide the frame for the implementation of several goals referred to in health, food security, energy and climate change.
Crude oil inventory
The pilot with Google will explore the estimation of crude oil inventory using analytics derived from satellite imagery as a means to promote economic transparency.
Spatial and Statistical Analysis of Historic Climate Data
A century or so of daily meteorological data for several thousand meteorological stations in Mexico will be analysed. The Mexican National Institute of Geography and Statistics will look for spatial and temporal patterns and long-term trends.
Urban-Rural Systems
Urban-Rural systems are portions of territory where the economic and social dynamics gravitate towards a city, thus constituting a geospatial guide for the implementation of public policies. A project of the National Institute of Geography and Statistics, Mexico, will identify paths (origin-destination) and patterns of functional dependency for localities, both urban and rural, that have a relationship to a larger population center. Georeferenced twitter feeds will be used along with other socio-demographic, economic and territorial indicators.
Members
Chair Dr. Siu-Ming Tam, Australian Bureau of Statistics
Australian Bureau of Statistics
Participants: Siu-Ming Tam, Sybille McKeown, Jacinta Holloway
Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Participants: Arnold Dekker, Flora Kerblat, Alex Held
National Administrative Department of Statistics
Departamento Administrativo Nacional de Estadística - DANE
Participants: Mauricio Perfetti del Corral, DirectorSandra Yaneth Rodriguez Figueroa, Geostatistics
Ramon Ricardo Valenzuela Gutierrez, Regulation, Planning, Standardization and Normalization
International Telecommunication Union
Participants: Yvon Henri and Ivan Vallejo Vall
United Nations Statistics Division
Participants: Ronald Jansen, Ivo Havinga, Gregory Scott, Alessandra Alfieri and Julian Chow
Australian Research Council Centre of Excellence For Mathematical and Statistical Frontiers
Participants: James McBroom, Gentry White and Kerrie Mengersen
Food and Agriculture Organization of the United Nations
Participants: Fabio Grita and Francesco N. Tubiello
IBM Research
Participants: Peder OlsenLinks
Reference
- Report of the Global Working Group on Big Data for Official Statistics
- Results of the UNSD/UNECE Survey on organizational context and individual projects of Big Data
- Big data and modernization of statistical systems
- Emerging issue: the data revolution
- UN Data Revolution
- OGC/W3C Spatial Data on the Web Working Group
