Cloud-computing and machine learning in support of country-level land cover and ecosystem extent mapping in Liberia and Gabon.

ABSTRACT: Liberia and Gabon joined the Gaborone Declaration for Sustainability in Africa (GDSA), established in 2012, with the goal of incorporating the value of nature into national decision making by estimating the multiple services obtained from ecosystems using the natural capital accounting framework. In this study, we produced 30-m resolution 10 classes land cover maps for the 2015 epoch for Liberia and Gabon using the Google Earth Engine (GEE) cloud platform to support the ongoing natural capital accounting efforts in these nations. We propose an integrated method of pixel-based classification using Landsat 8 data, the Random Forest (RF) classifier and ancillary data to produce high quality land cover products to fit a broad range of applications, including natural capital accounting. Our app

SUBMITTER: de Sousa C 

PROVIDER: S-EPMC6953846 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature