Course Data Download Links
Below are links to the data required for each session. More
information about the data will be provided in each session. The data is
additionally accessible via the O-drive
.
Precourse
S00
Download
The package includes:
- Two Landsat-7 Collection 2 Level-1 images covering parts of the
river Elbe, Germany
Session 1-2
S01-02
Download
The package includes:
- Two Level-1 (TOA) Landsat-8 scenes over the Polish Carpathians from
2014
- One Level-2 (BOA) Landsat-8 scene over the Polish Carpathians from
2014
- Reference image
- Vector-based forestry reference information
(“/vector/BDL_stand-species.gpkg”)
Session 3-4
S03-04
Download
The package includes:
- Preprocessed Landsat-7 and Landsat-8 surface reflectance time series
from 2014 to 2016 (“/imagery/time-series”)
- Calculated cloud distance and valid pixel time series needed for
best-pixel-compositing in session 4 (“/image/bap”)
- Calculated spectral-temporal-metrics for session 4 and session 5
(“/image/stm”)
- Vector-based of Landsat 30m pixel grid
(“/vector/landsat_30m_grid.gpkg/.kml”)
- Vector-based forestry reference information (S01, but EPSG:3035)
(“/vector/BDL_stand-species_EPSG3035.gpkg”)
Session 7
S07
Download
The package includes:
- Sentinel-2 image, BOA reflectance, cloud-masked, date of
acquisition: 26.07.2019
- Spectral library with pure spectra of PV, NPV and soil from the
Sentinel-2 image
- Validation points (.gpkg) for the date of image acquisition to
evaluate predictive performance
Session 8
S08
Download
The package includes:
- …sr_data/: Three Landsat 5 surface reflectance stacks (*_crp.tif) at
five-year intervals from 2000 to 2010.
- …vector/: A shapefile and a *.kmz file for GoogleEarth, which will
help you to accurately delineate the Landsat pixel locations and extents
for training data collection
- …validation/: A shapefile containing reference data for the accuracy
assessment.
- …gfc/: A subset of the Global Forest Change dataset by Hansen et
al. (2013). We reclassified the data to match the target classes of
today´s assignments.
Copyright © 2020 Humboldt-Universität zu Berlin. Department of Geography.