Remote sensing for mapping ecosystems: landscapes and biodiversity

Maxim Dubininsim@gis-lab.info

2 из 24

Remote sensing and Ecosystem services

Remote sensing data

provides basis for

assessment of:

3 из 24

Remote sensing and Ecosystem services

4 из 24

● Provides data for non-spatial assessment ...● but... Spatially explicit● Up-to-date and operational● Large areas● Independent

Why Remote Sensing

5 из 24

● Proxy● Uncertainty● Wrong scales● High technological capacity is required

Why NOT remote sensing...

6 из 24

● Regression Models● Radiative Transfer Models● Thematic mapping● Land Use/Land Cover● Provision of Input Data for Biophysical Models

Methods

7 из 24Costanza, R. et al. 1997. The value of the world's ecosystem services and natural capital. Nature 387:253-260

8 из 24

●

Valuable ecosystems — old-growth forests

Dmitry Aksenov et al. The Last of The Last: The Old-growth Forests of Boreal Europe. Moscow. Taiga Rescue Network. 1999.

9 из 24

●

Mapping with Remote Sensing data

10 из 24

Mapping with Remote Sensing data

Dmitry Aksenov et al. Atlas of Russia’s Intact Forest Landscapes. - Moscow, 2002

11 из 24

IFL to HCVF

● From Intact Forest Landscapes to High Conservation Value Forests, which are forested areas with:

1. Concentrations of biodiversity values

2. Rare, threatened or endangered ecosystems

3. Basic services of nature in critical situations (e.g. watershed protection, erosion control)

4. Fundamental to meeting basic needs of local communities and/or critical to local communities' traditional cultural identity

12 из 24

From IFL to HCVF

М.Л. Карпачевский и др. Природа Подмосковья: утраты последних двух десятилетий. Москва, Изд-во Центра охраны дикой природы, 2009.

13 из 24

From IFL to HCVF

Д.Е.Аксенов, М.Ю.Дубинин и др. Выделение лесов высокой природоохранной ценности в Приморском крае. Категории, важные для сохранения растительного покрова. Владивосток - Москва, 2006

14 из 24

Problem

● Only highest priority or endangered ecosystems are mapped

15 из 24

Landcover

Bartalev, S.A., A.S. Belward, D. V. Erchov, and A. S. Isaev, 2003, A new SPOT4-VEGETATION derived land cover map of Northern Eurasia, International Journal of Remote Sensing, Vol. 24, No. 9, 1977 - 1982

16 из 24

Landcover

Bicheron P., et al., “GlobCover 2005 – Products description and validation report”, Version 2.1, 2008 (a). Available on the ESA IONIA website (http://ionia1.esrin.esa.int/).

17 из 24

Forest map

Bartalev, S., Ershov, D., Isaev, A., Potapov, P., Turubanova, S. and Yaroshenko A.Yu. Russia's Forests. Dominating Forest Types and Their Canopy Density. Scale 1 : 14 000 000. Moscow, 2004

18 из 24

Vegetation

Отдел «Технологии спутникового мониторинга» ИКИ РАН. http://smiswww.iki.rssi.ru/default.aspx?page=317

19 из 24

● Direct: Observations and RS measures and derivatives are correlated with species richness and diversity

● Indirect: RS-derived habitat maps can be used to assess particular species status and extrapolate

Biodiversity

20 из 24

Biodiversity

ImageSat Int.27 Mar 2010

Visible traces and theprobable habitats of animals

Satellite technology to map harp seal (White Sea)

R&D Center Scanex. Earth Remote Sensing Data Continue to Help Saving Harp Seal Population. http://press.scanex.ru/index.php?option=com_k2&view=item&id=3832

21 из 24

●

Biodiversity

St-Louis, V., A. M. Pidgeon, M. K. Clayton, B. A. Locke, D. W. Bash, and V. C. Radeloff. 2009. Satellite image texture and a vegetation index predict avian biodiversity in the Chihuahuan Desert of New Mexico. Ecography, 32:468-480.

22 из 24

Biodiversity

Поспелов, И.Н., Дубинин, М.Ю. Выделение гнездовых местообитаний гаршнепа в большеземельской тундре по материалам космической съемки высокого разрешения. 2005, Вестник охотоведения, 2, 178-192

23 из 24

● Massive free RS data: Landsat 8/OLI, Terra,Aqua/MODIS● New classification methods: machine learning, object

recognition● New technologies: LIDAR

Opportunities

24 из 24

● Lack of baseline landcover data: no NLCD or CORINE equivalent

● Undeveloped network of constant field plots● Lack of open data for more detailed then subject level

National RS-related problems