Dario Simonetti

TL;DR: It is shown that there was a gross loss of tropical forests in the 1990s and 2000s and that carbon loss rates did not change between the two last decades, reconciling recent low estimates of carbon emissions from tropical deforestation.

TL;DR: The potential of Landsat MSS and TM data for large scale land cover change assessment in West Africa is demonstrated and the importance of consistent and systematic data processing methods with targeted image acquisition procedures for long-term monitoring is highlighted.

TL;DR: The authors showed that 17% of tropical moist forests have disappeared since 1990 with a remaining area of 1071 million hectares in 2019, from which 10% are degraded, and suggested that reinforcing actions are needed to prevent the initial degradation that leads to forest clearance in 45% of the cases.

TL;DR: In this article, the TREES-3 project has processed more than 12,000 Landsat TM and ETM+ data subsets systematically distributed over the tropics, and the results show that the haze correction algorithm has improved the visual appearance of the image and significantly corrected the digital numbers for the red band.

TL;DR: A fully automatic phenology-based synthesis (PBS) classification algorithm was developed to map land cover based on medium spatial resolution satellite data using the Google Earth Engine cloud computing platform and the combined overall accuracy was over 90%, which demonstrates the potential of the classifier and the power of cloud computing in geospatial sciences.