UN Handbook on Remote Sensing for Agricultural Statistics

Welcome to the age of big Earth observation data! Petabytes of images are now openly accessible in cloud services. Having free access to massive data sets, we need new methods to measure change on our planet using image data. An essential contribution of big EO data has been to provide access to image time series that capture signals from the same locations continually. Time series are a powerful tool for monitoring change, providing insights and information that single snapshots cannot achieve. Better measurement of natural resources depletion caused by deforestation, forest degradation, and desertification is possible. Experts improve the production of agricultural statistics. Analysts can use large data collections to detect subtle changes in ecosystem health and distinguish between various land classes more effectively.

This book is a practical guide on how to use remote sensing for agricultural statistics. It provides readers with the means of producing high-quality maps of agricutural areas and prediction of crop yields. Given the natural world’s complexity and huge variations in human-nature interactions, only local experts who know their countries and ecosystems can extract full information from big EO data.

One group of readers that we are keen to engage with is the national authorities on forest, agriculture, and statistics in developing countries. We aim to foster a collaborative environment where they can use EO data to enhance their national land use and cover estimates, supporting sustainable development policies.

Intellectual property rights

This book is licensed as Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) by Creative Commons. The sits package is licensed under the GNU General Public License, version 3.0.

Disclaimer

You are viewing a draft version of the UN Handbook. The final version is planned for November 2025.