Determining a Threshold to Delimit the Amazonian Forests from the Tree Canopy Cover 2000 GFC Data.

Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.

Modelling Dunes from Lençóis Maranhenses National Park (Brazil): Largest dune field in South America.

This paper presents a digital elevation model (DEM) of the dunes found in the Lençóis Maranhenses National Park, an environmental protection area located in the Maranhão state (Brazil). The DEM supports the modeling studies of sand-dune evolution using multi-temporal satellite images and ground truth data, obtained through the post-processed kinematic Global Navigation Satellite System (GNSS) positioning. The study area is located at the border of three major neotropical ecosystems: the Amazonia, Caatinga, and Brazilian savanna. It is located in the northeastern state of Maranhão and encompasses the largest dune fields in the country. Wide shrubby areas (restingas, in Portuguese), lakes, mangroves, and a multitude off reshwater lagoons compose the park's natural environments. The objective of the present study is to create an DEM that can evidence the complex dynamics of dune formation in the study area with use of GNSS. Geodetic techniques and precision mapping were employed to monitor the short-term coastal dynamics. The use of GNSS receivers is justified by the difficulty of mapping the dune's features using conventional methods such as theodolite, level, and total station systems, due to their high cost, time restriction sand low data precision. Surface surveys were carried out annually between December 2015 and January 2017 to create a DEM. The study results reveal that the area has a negative volumetric balance of erosion and a preferential direction of sediment transport by wind, which may justify the pattern of advancement and retraction observed in the dunes of the studied area.

Author Correction: Modelling Dunes from Lençóis Maranhenses National Park (Brazil): Largest dune field in South America.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.