Satellite remote sensing- based forest stock estimation technology (WoodStock)

Agreement with Central Financing and Contracting Agency (CFCA)  Nr.1.1.1.1/18/A/165

Scientific manager: Dr.sc.comp. Ints Mednieks (ints.mednieks@edi.lv).

Project objective: to develop a novel technology for the cost-effective estimation of forest stock volume based on high-resolution satellite remote sensing data.

The project is focused on the development of the prototype technology for estimation of forest stock volume from high-resolution satellite data, including methods for identification of tree species, estimation of tree height, estimation of forest density and estimation of forest stock volume from information about tree species, tree height and forest density.

The project is implemented by the Institute of Electronics and Computer Science in cooperation with company SIA “Baltic Satellite Service”.

Duration: 36 mēneši, from March 1, 2019 to February 28, 2022.
Planned cost: 498 026 EUR

25.07.2019. A progress report for the 1. phase (01.03.2019.g – 30.06.2019.g) has been submitted for the ERAF project “Satellite remote sensing- based forest stock estimation technology (WoodStock)” Agreement with Central Financing and Contracting Agency (CFCA) Nr.1.1.1.1/18/A/165.

 

Project “Satellite remote sensing- based forest stock estimation technology (WoodStock)”.  Discussion in the forest.

29.10.2019. A progress report for the 2. phase (01.07.2019.g – 30.09.2019.g) has been submitted for the ERAF project “Satellite remote sensing- based forest stock estimation technology (WoodStock)” Agreement with Central Financing and Contracting Agency (CFCA) Nr.1.1.1.1/18/A/165.

02.12.2019. Topical issues of the project implementation were discussed during the meeting of the scientific group of the project. General data processing scheme is developed. High resolution satellite data and field data procured. It was decided to continue research aimed at qualitative segmentation of forest areas.

24.03.2020. Project “Satellite remote sensing- based forest stock estimation technology (WoodStock)”. Field data collection using UAV performed for the project in Daudzeses parish.

15.06.2020. Paper J.Sinica-Sinavskis, R. Dinuls, J. Zarins, I.Mednieks “Automatic tree species classification from Sentinel-2 images using deficient inventory data” submitted to conference BEC-2020.

Related Scientists

    Dr.sc.comp. Juris Siņica-Siņavskis

    Researcher

    +371 67558192
    [protected]
    Dr. sc. comp. Ints Mednieks

    Senior Researcher

    Mg. math. Tamāra Laimiņa

    Assistant

    +371 67558202; +371 67558207
    [protected]
    Mg. Math. Romāns Dinuls

    Assistant

    +371 67558166
    [protected]