The Databases window

ZephyTOOLS gives access to several public databases, making it possible to automatically download and prepare the topographical data needed as input to any CFD wind farm modeling project.

From this window it is possible to visualize the data from each available database, and to manage the tiles which were downloaded.

Next to each database the user can see how many tiles have been downloaded, and how much disk space they occupy. Eventually, it is possible to clear a database of its downloaded tiles in order to free some disk space.


This window is only meant to visualize the databases, and to manage disk space. To use the databases in CFD projects, just choose a georeference and a database when creating a new project (cf. Project definition).

Data Visualization


The Databases visualization window

This window revolves around an interactive map, in which the data will be displayed on top of one of the available open-source maps (OpenStreetMap, Bing, Stamen…).

To visualize the data, it is possible to download previews of the data tiles closest to the center of the displayed map, using the GET PREVIEW button. Remove it with the REMOVE PREVIEW button. Like in other ZephyTOOLS visualizations, the map can be dragged by holding the left click.

It is also possible to directly download the complete data from a tile, using the GET DATA button on the right, and to delete it with the REMOVE DATA button.

To process more than one tile at a time, use the right arrow in the bottom-left of the window. It is possible to go up to 7x7 tiles at a time.

The other left/right arrows allow to adjust the data opacity and range.



Database name Data Class Original resolution Availability Source
ASTER Global Digital Elevation Map, version 2 Orography 1 arc-second (~30m) World astgtm_v002

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was developed jointly by the U.S. National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI).



ASTER GDEM used stereoscopic pairs and digital image correlation methods. Based on two images at different angles, it used stereopairs and photogrammetry to measure elevation. However, the amount of cloud cover affected the accuracy of ASTER which wasn’t the case for SRTM DEM. Because of how passive and active sensors work, this had the most significant effect on quality of DEM.

But over time, ASTER DEM data has improved its products with artifact corrections of their own. In October 2011, ASTER GDEM version 2 was publicly released, which was a considerable improvement.

Despite its experimental grade, ASTER GDEM-2 is considered a more accurate representation than the SRTM elevation model in rugged mountainous terrain.


Database name Data Class Original resolution Availability Source
Space Shuttle Radar Topography Mission (SRTM) Orography 1 arc-second (~30m) World srtmgl1_v003

The Shuttle Radar Topography Mission (SRTM) was flown aboard the space shuttle Endeavour February 11-22, 2000. The National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA) participated in an international project to acquire radar data which were used to create the first near-global set of land elevations.



Using two radar antennas and a single pass, it [SRTM] collected sufficient data to generate a digital elevation model using a technique known as interferometric synthetic aperture radar (inSAR). C-Band penetrated canopy cover to the ground better but SRTM still struggled in sloping regions with foreshortening, layover and shadow.

In late 2014, the United States government released the highest resolution SRTM DEM to the public. This 1-arc second global digital elevation model has a spatial resolution of about 30 meters. Also, it covers most of the world with absolute vertical height accuracy of less than 16m.


Database name Data Class Original resolution Availability Source
European Digital Elevation Model (EU-DEM), version 1.0 Orography 25m Europe eu-dem

Copernicus is a European programme for monitoring the Earth, in which data is collected by Earth observation satellites and combined with observation data from sensor networks on the earth’s surface.

Copernicus Land Monitoring Service (CLMS) provides geographical information on land cover to a broad range of users in the field of environmental terrestrial applications. This includes land use, land cover characteristics and changes, vegetation state, water cycle and earth surface energy variables.



EU-DEM v1.0 is a digital surface model (DSM) of EEA39 countries representing the first surface as illuminated by the sensors. It is a hybrid product based on SRTM and ASTER GDEM data fused by a weighted averaging approach. The statistical validation of EU-DEM v1.0 documents a relatively unbiased (-0.56 meters) overall vertical accuracy of 2.9 meters RMSE, which is fully within the contractual specification of 7m RMSE (European Commission 2009).



Database name Data Class Original resolution Availability Source
Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC), 2015 Roughness 30m World from-glc

FROM-GLC is a 30m resolution global land cover model produced using Earth observing sensors from the Landsat programmme, Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). It was developed at the Earth System Science department of Tsinghua University [1], using four different classification algorithms: conventional maximum likelihood classifier (MLC), J4.8 decision tree classifier, Random Forest (RF) classifier and support vector machine (SVM) classifier.

A total of 38,664 test samples were used for validation, in which The SVM produced the highest overall classification accuracy (OCA) of 64.9%



Database name Data Class Original resolution Availability Source
CORINE Land Cover (CLC), 2012 Roughness 100m Europe corine-land-cover

Like EU-DEM, CORINE Land Cover (CLC) is part of the Copernicus programme. It is meant to standardize data collection on land in Europe to support environmental policy development, and it currently includes the same 39 Europeans countries as EU-DEM. Initiated in 1985, its latest update was in 2012.

It was obtained by human interpretation of satellite images having an original resolution between 20 and 25m. In a few countries semi-automatic solutions were applied, using national in-situ data, satellite image processing, GIS integration and generalisation. The result is a global vectorial dataset of land coverage classification in 44 classes, with its smallest linear elements being 100m long.