Open Foris Collect Earth: a remote sensing sampling survey of Azerbaijan to support climate change reporting in the land use, land use change, and forestry.

Autor: Bassullu C; School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA. caglarbassullu@ufl.edu.; Foreign Relations, Training, and Research Department, General Directorate of Forestry, Ankara, Türkiye. caglarbassullu@ufl.edu., Sanchez-Paus Díaz A; Food and Agriculture Organization of the United Nations, 00153, Rome, Italy.
Jazyk: angličtina
Zdroj: Environmental monitoring and assessment [Environ Monit Assess] 2023 Sep 21; Vol. 195 (10), pp. 1236. Date of Electronic Publication: 2023 Sep 21.
DOI: 10.1007/s10661-023-11870-x
Abstrakt: Land use, land use change, and forestry (LULUCF) are critical in climate change mitigation. Producing or collecting activity data for LULUCF is essential in developing national greenhouse gas inventories, national communications, biennial update reports, and nationally determined contributions to meet international commitments under climate change. Collect Earth is a free, publicly accessible software for monitoring dynamics between all land use classes: forestlands, croplands, grasslands, wetlands, settlements, and other lands. Collect Earth supports countries in monitoring the trends in land use and land cover over time by applying a sample-based approach and generating reliable, high-quality, consistent, accurate, transparent, robust, comparable, and complete activity data through augmented visual interpretation for climate change reporting. This article reports forest extent estimates in Azerbaijan, analyzing 7782 0.5-ha sampling units through an augmented visual interpretation of very high spatial and temporal resolution images on the Google Earth platform. The results revealed that in 2016, tree cover existed in 31.9% of total land, equal to 2,751,167 ha and 1,301,188 ha or 15.1% of the total land, with a 5.4% sampling error covered by forests. The estimate is 15 to 25% higher than the previous estimates, equal to 169,418 to 260,888 ha of forest that was never reported in previous studies.
(© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
Databáze: MEDLINE
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