The Digital Elevation Model Intercomparison eXperiment DEMIX, a community-based approach at global DEM benchmarking

This paper presents an initiative recently launched under the auspices of the Committee on Earth Observation Satellites (CEOS) aiming at providing harmonised terminology and methods, as well as practical guidelines and results allowing the intercomparison of continental or global Digital Elevation Models (DEM). As the work is still ongoing the main purpose of this article is not the dissemination of the outcome but rather to inform the wider community about the initiative, communicate the chosen approach to raise awareness, and attract possible further participants. Nevertheless, some preliminary results are included and an outlook on planned next steps is provided

Digital Elevation Models: Terminology and Definitions

Digital elevation models (DEMs) provide fundamental depictions of the three-dimensional shape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record the interface between the atmosphere and the lithosphere using a discrete two-dimensional grid, with complexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere. The treatment of DEM surfaces, affected by these intervening spheres, depends on their intended use, and the characteristics of the sensors that were used to create them. DEM is a general term, and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) record the treatment of the intermediate surfaces. Several global DEMs generated with optical (visible and near-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars and products of satellite altimetry, share the common characteristic of a georectified, gridded storage structure. Nevertheless, not all DEMs share the same vertical datum, not all use the same convention for the area on the ground represented by each pixel in the DEM, and some of them have variable data spacings depending on the latitude. This paper highlights the importance of knowing, understanding and reflecting on the sensor and DEM characteristics and consolidates terminology and definitions of key concepts to facilitate a common understanding among the growing community of DEM users, who do not necessarily share the same backgroun

Monitoring loss of tropical forest cover from Sentinel-1 time-series: A CuSum-based approach

International audienceThe forest decline in tropical areas is one of the largest global environmental threats as the growth of both global population and its needs have put an increasing pressure on these ecosystems. Efforts are ongoing to reduce tropical deforestation rates. Earth observations are increasingly used to monitor deforestation over the whole equatorial area. Change detection methods are mainly applied to satellite optical images which face limitations in humid tropical areas. For instance, due to frequent cloud cover in the tropics, there are often long delays in the detection of deforestation events. Recently, detection methods applied to Synthetic Aperture Radar (SAR) have been developed to address the limitations related to cloud cover. In this study, we present an application of a recently developed change detection method for monitoring forest cover loss from SAR time-series data in tropical zone. The method is based on the Cumulative Sum algorithm (CuSum) combined with a bootstrap analysis. The method was applied to time-series of Sentinel-1 ground range detected (GRD) dual polarization (VV, VH) images forming a dataset of 60 images to monitor forest cover loss in a legal forest concession of the Democratic Republic of Congo during the 2018-2020 period. A cross-threshold recombination was then conducted on the computed maps. Evaluated against reference forest cut maps, an overall accuracy up to 91% and a precision up to 75% in forest clear cut detection was obtained. Our results show that more than 60% of forest disturbances were detected before the PlanetScope-based estimated date of cut, which may suggest the capacity of our method to detect forest degradation

Volume Changes of Lake Bracciano During the Sentinels Acquisition Period

International audienceLakes and reservoirs are considered sentinels of climate and anthropogenic changes. Lakes and reservoirs surface water storage is an essential hydrological variable but poorly known as this information is scarce. Earth Observation data are a reliable source of information to overcome this scarcity. Among these, the combined use of satellite images, to derive water extent, and radar altimetry, which enables to estimate water levels, provides valuable information on water storage changes. Here, we used Synthetic Aperture Radar images from Sentinel-1 and radar altimetry data from Sentinel-3 to monitor the water volume changes of Lake Bracciano from 2016 to 2021. This lake was affected by a water crisis in 2017 and the water supply to the city of Rome (Italy) was interrupted September 2017 to preserve its ecosystem. Hence, we demonstrate how Sentinel-1 and Sentinel-3 data can be useful to monitor water extent and level, which can be profoundly changed by the climate crisis