Skip to main content

Linking Copernicus Sentinel data and services into forest management processes



Fig.: Trees with unique ID in the field (left) and the corresponding point clouds (right) generated with TLS (Terrestrial Laser Scanner)

Fig.: Trees with unique ID in the field (left) and the corresponding point clouds (right) generated with TLS (Terrestrial Laser Scanner)

Fig. 2 Individual tree point clouds and accurate measurement of location, DBH and tree stem curvature

Fig. 2 Individual tree point clouds and accurate measurement of location, DBH and tree stem curvature

2. Creating the Marteloscope geospatial data

2. Creating the Marteloscope geospatial data

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 1

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 1

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 2

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 2

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 3

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 3

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 4

3. Analyzing the relations between Marteloscope data and Copernicus data Analyzing Vegetation indexes from Sentinel 2 data NDVI relations - 4

The main objective of the action is to build a strong demo case conducting to a downstream service in which Copernicus satellite observations (especially Sentinel 2 and 1) are used in combination with in-situ observations to for supporting forest management activities by

  • Building a network of monitoring sites with a size of 1 ha in the forest
  • Validating existing vegetation indices calculated from Copernicus data
  • Creating the scientific support to identify new vegetation indices or procedures to harness the big data extracted from monitoring sites
  • Showcase and raise awareness among the potential end-users on the advantages of using satellite data in connection with the classical marteloscope methodology.

A PSP (permanent sampling plots) network will be established in order to provide a framework for understanding forest dynamics and the possibility of linking Copernicus satellite data in monitoring and taking decision in the forest management process. One plot is designed using the definition of marteloscope. The Marteloscope is a 1-hectare rectangular plot (100x100 m) in which the species and dbh (diameter at breast height) of every tree greater than 10 cm are measured and recorded. The location of each of the trees is mapped and an identifying number provided with which each tree is labelled. Each tree is also assigned to one of four quality classes: the definition of these classes relating to the interaction between quality and the selection process. In this action 10 marteloscopes will be placed and we are going to monitor their signatures and forest influences in the Copernicus satellite data (from our knowledge such integration is an absolute novelty).

Building the Marteloscope plots is done in the following steps

  1. Extracting the Forest Stand Core data: tree unique identity, location, diameter, height, crown height,  >10 cm DBH using a Terrestrial Laser Scanner

Fig.: Trees with unique ID in the field (left) and the corresponding point clouds (right) generated with TLS (Terrestrial Laser Scanner)

Fig. 2 Individual tree point clouds and accurate measurement of location, DBH and tree stem curvature

  1. Creating the Marteloscope geospatial data
  2. Analyzing the relations between Marteloscope data and Copernicus data

Analyzing Vegetation indexes from Sentinel 2 data

NDVI relations

External implementation would be a first option (identified companies with previous experience will be contracted) but direct implementation is not excluded having ROSA as an ultimate recipient of the results to be further exploited in R&D (free and open distribution) and demonstration activities. Extending the activity outside RO could also be considered.

The in-situ observations will be used in combination with the results obtained from the processing of satellite data in order to develop a demonstration case. The initial requirements for the execution of the in-situ observations are already defined in the description of the activity based on current knowledge coming from past R&D projects. Both the statement of work, acquisition procedure, the evaluation of the proposals received and contracting will be made by ROSA.

Outputs and Results

Main results could include

  • Standardized protocols proposal to ensure consistent measuring and recording of marteloscope data.
  • Setup marteloscope demo sites;
  • In-situ observations database
  • Workshop with forest management end-user
  • Promotion and demonstration material