Forestry TEP provides a range of features to support you to take full advantage of the expanding databases of Earth Observation and auxiliary datasets and the benefits of powerful online processing approaches in your forest monitoring activities.
Through Forestry TEP, you can
- Sentinel 1, 2 and 3 (globally)
- Landsat 5, 7 and 8 (for Europe)
- Ancillary datasets (e.g. forest field plots)
- Access to the databases of CREODIAS
- Access to additional datasets can be arranged, please contact us to see how we could arrange it.
- Cloud masking (FMask4.0) and basic image processing (Vegetation Indices etc., see below)
- Open source software Orfeo Tool Box, SNAP and QGIS
- Specialized forest monitoring applications (Probability, Autochange etc., see below)
- Docker based development interface allows easy implementation of your own processing scripts and services in your preferred programming language.
- Easy sharing of scripts within the Forestry TEP community
- Easy sharing of data, services and products within the forestry community, and marketing commercial forest and land monitoring services.
- To support the efficient use of the platform. The training events and consulting can be fully tailored to your needs. Contact us for more information.
The Forestry TEP service portfolio covers thematic processing services and supporting processing services, as well as interactive applications. The User Manual gives detailed guidance on how to use each service and tool.
In the tables below, services and tools that are listed as being available in either the Basic or Standard packages are readily available to all platform users. The services listed as “by agreement” are also deployed on the platform, and they can be made available for use through a separate agreement. Interested users are encouraged to contact us for enquiries.
Thematic Processing Services
|Standard package||VegetationIndices||Computation of radiometric indices (NDVI, TNDVI, RVI, SAVI, TSAVI, MSAVI, MSAVI2, GEMI, IPVI) Note: supports batch processing||Sentinel-2 L1C (1 or more)||GeoTiff|
|Standard package||ForestChangeS2||Forest change mapping based on the ratio of red reflectance between two images||2 x Sentinel-2 L1C||GeoTiff|
|Standard package||LandCoverGeotiff||Land cover mapping with image classification trained by the Random Forest model, based on the algorithm implementation in the Orfeo ToolBox||GeoTiff Reference data (Shapefile)||GeoTiff|
|by agreement||AutoChange||Change detection between two multispectral images from (preferably) the same satellite system; based on VTT-developed AutoChange methodology, which utilizes K-means clustering and subdivision of clusters of the first image||
GeoTiff image. File name heuristics used to detect image type to be able to use default parameters:
Sentinel 2: S2A_MSIL1C_*, S2B_MSIL1C_*, S2A_L1C_* S2B_L1C_*, S2A_MSIL2A_*, S2B_MSIL2A_*, S2A_L2A_* or S2B_L2A_*.
Landsat 8: LC08_*, LO08_*, LC8_* or LO8_*
Or Envimon output
|by agreement||ProbaCluster||Unsupervised K-means clustering Part of the Probability classification and estimation chain||GeoTiff or ERS image, or the Envimon output (zip)||ProbaCluster output (zip)|
|by agreement||ProbaModel||Associates ground reference data with the clusters from ProbaCluster, by producing variable (forest or other) spatial averages Part of the Probability classification and estimation chain||ProbaCluster output (zip), Reference data (plot data, shapefile or an estimates image)||ProbaModel output (zip)|
|by agreement||ProbaEstimates||Produces a variable estimates output for (forest or other) spatial variables using clusters from ProbaCluster and cluster content data from ProbaModel Part of the Probability classification and estimation chain||GeoTiff or ERS image, or the Envimon output (zip), ProbaModel output (zip)||ProbaEstimates output (zip)|
|by agreement||MaskProbaEstimates||Masks the output from ProbaEstimates with cloud mask generated in the Envimon service and with an optional forest mask Part of the Probability classification and estimation chain||ProbaEstimates output (zip), Envimon output (zip), Forest mask (GeoTiff), optional||ProbaEstimates output (zip)|
|by agreement||ForestPropertyDataXml2Shape||Converts ForestPropertyData from the Finnish Forest Information Standard to ESRI shapefiles||ForestPropertyData xml||Shapefile|
|by agreement||Estimate2Vector||Appends existing forest stand data with forest variable estimates provided as a raster image; the vector formatted stand data can be GeoJSON, ESRI shapefile or ForestPropertyData from the Finnish Forest Information Standard||Estimate image in GDAL supported format Stand data (ForestPropertyData xml, GeoJSON or Shapefile)||Updated stand data (XML, GeoJSON or Shapefile)|
Supporting Processing Services
||Performs atmospheric-, terrain and cirrus correction of Top-Of- Atmosphere Sentinel-2 L1C input data||Sentinel-2 L1C||GeoTiff|
|Basic package||Fmask40||Generates cloud masks for the input images using Fmask 4.0 algorithm; supports Sentinel 2 Level 1C and Landsat 8 images||Sentinel-2 L1C, Landsat 8||GeoTiff|
|Basic package||Envimon||Extracts Sentinel-2 data to a multi-band image, and performs cloud masking with a VTT in-house method; outputs the contained images and the generated cloud masks||Sentinel-2 L1C, Sentinel-2 L2A, Landsat 8||Envimon output (zip)|
|Basic package||ALSMetrics||Derives metrics from airborne laser scanning data into a raster file that is suitable for joint use with Sentinel-2 data||ALS data in LAS format||GeoTiff|
||Runs gdalinfo on given image(s)||One or more images in GDAL supported format||Text file|
||Runs gdal_translate on a given image||An image in GDAL supported format||An image in GDAL supported format|
||Runs gdalwarp on given image(s)||One or more images in GDAL supported format||An image in GDAL supported format|
||Runs gdal_calc.py for one or two input images||One or two images in GDAL supported format||An image in GDAL supported format|
|Standard package||S1stack||Mosaic Sentinel-1 images along the orbit, generating a separate image band per each acquisition day in the output product||Sentinel-1 GRD/SDV collection in the same geometry||image stack (GeoTiff)|
|Standard package||S1stackTempvar||Mosaic Sentinel-1 images along the orbit, generating VV and VH bands per each acquisition day in the output product; additionally produces outputs with the interpolated stack and the temporal variability information||Sentinel-1 GRDH/SDV images in the same geometry||image stack (GeoTiff) image stack interpolated (GeoTiff) temporal variability (GeoTiff)|
|Standard package||CombS2granules||Combines multiple Sentinel-2 tiles, belonging to the same full acquisition image, into a single output||N x Sentinel-2 L1C||GeoTiff|
|Standard package||CombS2granulesZ||Combines multiple Sentinel-2 tiles, belonging to the same full acquisition image, into a single output; additionally performs projection to support tiles belonging to different UTM zones||N x Sentinel-2 L1C||GeoTiff|
|by agreement, API use only||Sentinel image selection||Metadata query service for sentinel image selection that creates a database of the available images matching the search criteria and their metadata||Parameters describing the required image characteristics||Sqlite3 database|
|by agreement||Analysis-ready S2||Combines a time series of Sentinel-2 L2A data to a uniform mosaic. Includes selection of usable data, atmospheric correction and relative radiometric normalization.||N x Sentinel-2 L2A||Analysis-ready Sentinel-2 GeoTiff|
|by agreement||S3toTiff||Converts Sentinel-3 OLCI data to GeoTiff format.||Sentinel-3 OLCI||GeoTiff in EPSG:3857|
|Basic package||Monteverdi||Satellite image viewer and analysis tool from the open source Orfeo ToolBox v5.8.0||several input types||[can export output]|
|Basic package||QGIS 3||QGIS v3.6, a free and open source Geographic Information System||several input types, e.g. GeoTiff, Shapefile||[can export output]|
|Basic package||QGIS 2||QGIS v2.18, a free and open source Geographic Information System||several input types, e.g. GeoTiff, Shapefile||[can export output]|
|Basic package||SNAP||Sentinel Applications Platform (SNAP) v6.0, an application for processing and analysis of Sentinel and other data – by Brockmann Consult, Array Systems Computing and C-S||any Sentinel data||[can export output]|
|by agreement||ProbaUI||GUI for the Probability classification and estimation chain that consists of ProbaCluster, ProbaModel and ProbaEstimates||image data reference data||[can export output]|