T.2.1 – remote sensing and multispectral analysis (by fly)

SLOPE WP 2 – Task 2.1

Kick-off Meeting 8-9/jan/2014

Andrea Masini, PhD

Remote sensing and multispectral analysis

Remote Sensing DepartmentFlyby S.r.l.

Task 2.1: general description


• design of an automatic chain that provides a first level forest inventory exploiting satellite imagery

• calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment

• first level forest inventory used also to drive more accurate UAV/in-situ measurements

• satellite-based data fusion with other data to achieve more accurate results

Task 2.1: participants


•Flyby S.r.l. (Leader)

• CNR

• Coastway

• TreeMetrics

Task 2.1: expected output


• Deliverable D2.01 (month 8 – August 2014) :

Report on remote sensing data collected, on the methodologies

and the algorithm to extract needed information and on the

generated output

Use of satellite data for forestry


Satellite imagery can be extremely useful in the forestry sector in particular for :

• forest health near real-time monitoring

• accurate and wide forest inventory


Use of satellite data for forestry Studies

Different type of analysis


LOW SPATIAL RESOLUTION

EO data used so far for forestry


EO data used in the past for

• Cover Change Detection • Mapping biophysical structure • Mapping ecosystem services (carbon, water) • Modelling trends under change scenarios • Generating management plans


The vegetation indexes


Forest classification

RapidEye satellite imagery



RapidEye satellite – Forestry Studies


RapidEye satellite - Forestry


RapidEye satellite – Forestry Studies

Other high resolution satellite data


We will investigate the following data:


Task 2.1 main objectives

• design of an automatic chain that provides a first level forest inventory exploiting satellite imagery

• calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment

• first level forest inventory used also to drive more accurate UAV/in-situ measurements

• satellite-based data fusion with other data to achieve more accurate results

T.2.1 – remote sensing and multispectral analysis (by fly)

Technology

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