Research projects of Landuse changes in Latvia

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1 Research projects of Landuse changes in Latvia Ilmars Krampis University of Latvia, faculty of Geography and Earth Science Juris Zariņš Latvian State Forest Research Institute "Silava" Joint NASA LCLUC Science Team Meeting and GOFC-GOLD/NERIN, NEESPI Workshop Monitoring land cover and land use in boreal and temperate Europe Tartu,Estonia

2 Landuse research projects in Latvia since Corine Landcover project; 2. Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery; 3. Forestry GIS (State Forest Service); 4. GFM (Global Forest Monitoring) project.

3 Corine Land Cover project 1st implementation The Latvian CLC database for the year 1995 (CLC95) was the main delivery of the project. The consortium of the Latvian Environmental Data Centre and Department of Geodesy of Riga Technical University under European Commission 2nd implementation National CORINE Land Cover 2000 in Latvia project I&CLC2000 European Environment Agency (EEA) and Joint Research Centre (JRC) The main deliveries of the project were: 1. National CLC2000 and the Revised National CLC95 databases; 2. National land cover changes database; 3. National metadata (country level and working unit level).

4 Corine Land Cover project 3rd Implementation CORINE Land Cover 2006 activities in Latvia Latvian Environment, Geology and Meteorology Agency (LEGMA) - EIONET National Focal Point. The overall aim of the CLC2006 inventory was: To produce information about the land cover changes during the period ; To make national contribution for implementation of the infrastructure for spatial information in Europe (requirements of the Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE)).

5 Corine Land Cover project Methodology (2006) Standard CORINE Land Cover (3 level) classification 29 different CLC classes (from totally 44 classes of the CLC nomenclature) were detected for area of Latvia. The CLC changes was interpreted using visual comparison of IMAGE 2000 and IMAGE 2006 satellite data sets to identify real changes and afterwards the CLC2006 database was produced. The land cover changes database contains areas: Real changes between year 2000 and year 2006 and that are detectable on satellite images; larger than 5 ha and wider than 100 m. The land cover database for year 2000 and year 2006 contains areas that are larger than 25 ha and wider than 100 m.

6 Corine Land Cover project 11 Landsat 7 TM satellite scenes of the IMAGE2000 for full territory coverage were used. Time period July 1999 May satellite scenes of SPOT 4 and IRS-P6-LISS III were used to compile IMAGE2006 Spring data set. IRS scenes of the Spring data set were from 2005 and all SPOT scenes were from satellite scenes of SPOT 4 and IRS-P6-LISS III were used to compile IMAGE2006 Autumn data set. All were from 2006 But 3 of them were from spring period (April / May). Therefore the real autumn / spring comparison was able only for the Western and the Eastern part of Latvia.

7 Corine Land Cover project Ancillary data: Topographic map for whole area of Latvia in the scale 1:50000 (raster) Aerial photos for whole area of Latvia with 1m resolution corresponding to the scale 1:10000 ( ) Aerial photos for whole area of Latvia with 1m resolution corresponding to the scale 1:10000 ( ) Digital georeferenced plans of cities and towns with corresponding scale in the range from 1:10000 to 1:30000

8 Results Corine Land Cover project

9 Results Corine Land Cover project Agriculture and forest areas are dominant land cover classes in Latvia (they occupy ~80% of the total area). Most common CLC classes Area of land cover classes (%) in CLC Broad-leaved forest 312 Coniferous forest 313 Mixed forest 324 Transitional woodland -scrub 311 9% % % % % 211 Non-irrigated arable land 231 Pastures 242 Complex cultivation patterns 242 8% 243 Land principally occupied by agriculture with significant areas of natural vegetation 243 7% 412 2% 512 2% 112 1% Others 2% %

10 Corine Land Cover project Results The overall land cover changes (real and technical changes) that were identified in the project constitute ha that is approximately 2% of the total area of Latvia 98% Area affected by land cover changes in the time period Changes No changes 2%

11 Corine Land Cover project Results The most of all changes have area in the range between 5 and 10 ha mosaic landscape Number of land cover changes polygons depending on polygon area (ha) <

12 Corine Land Cover project Results The analysis of the most frequent land cover changes come up with clear link of absolute increasing of transitional woodlands -scrubs (324) and decreasing of forest areas (311, 312 and 313) The most frequent land cover changes in the time period Other changes The total are of land cover changes is ha Area of changes (ha)

13 Corine Land Cover project Example of land cover changes : Mixed forest to Transitional woodland-scrub Location of LC changes (5536 cases: mostly in the Western and Central part): Example of Spring CLC2006: Example of CLC2000: Example of Autumn CLC2006:

14 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Latvian State Forest Research Institute "Silava" Project goal to investigate if and how satellite imagery could be used for forest coverage and forest volume change detection Research tasks To determine pilot territory; Describe used satellite images; To determine coverage of satellite images; Point out classification tasks; To determine methodology of classification; To prepare support data; Results.

15 Forest statistical inventory project with data interpolation of pilot territory, using satelitte imagery Pilot territory Ogre un Rīga district

16 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Used satellite images SPOT5; Landsat; DMCII; IRS-P6 LISS-III; IRS-P6 AWiFS. Resolution from 2,5 to 60 m; Coverage from 60x60 (SPOT5) to 370x370 (DMCII) km; 3 to 7 bands; Up to 1,2 GB.

17 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Classification tasks Forest coverage - Unsupervised; Changes of forest coverage (Change detection); Dominating tree species (Supervised); Tree volume (Supervised); Health of forest (Vegetation index). Methodology of clasification Unsupervised (iso data); Forest changes (change detection); Supervised (max like, knn); Vegetation index NDVI (Normalized Difference Vegetation Index), RVI (Ratio Vegetation Index).

18 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Forest teritorry: Results (forest coverage) Classifcation problems with cuttings and young forest (transitional woodlands - scrubs) ~86% accuraccy; Results could be used as forest mask

19 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Results (Changes of forest coverage) (1) Different images similar result

20 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Results (Changes of forest coverage)(2) It is possible to point out even small changes. Cleaned forest roads (fire breaks); New build roads.

21 Forest statistical inventory project with data interpolation of pilot teritorry, using satelitte imagery Results (tree species) Forest Digital Map Classification from Sattelite imagery

22 Forest statistical inventory project with data interpolation of pilot territory, using satellite imagery Results (Tree volume) Results are not possible to compare with forest sections average volume Could be compare different satellite image results, excluding 2,5 m SPOT5. Forest Digital Map Classification from Satellite imagery

23 Using satellite imagery for Forestry GIS Research project goal: To explore the potential use of satellite image analysis in Latvia and other Baltic counties. To determine possibilities for future development directions and explore impact of modern remote sensing and GIS technologies. Study area was most developed industries in GIS and remote sensing usage area Forestry

24 Using satellite imagery for Forestry GIS High spatial resolution not less than 1m in panchromatic mode High radiometric resolution not less than 11 bits per pixel in panchromatic mode; Using 4 band channels, including 1 infrared; Wide-band reception up to 28,7 km; Possibility to process data with standard software; Possibility to maintain cartographic materials at scale from 1:2000 to 1:10 000; Possibility to regulary obtain images for one teritorry 1-5 days time; Access to large amount of archive data milions km2; Relatively low price from 7 USD per 1 km2; Easy ordering.

25 Using satellite imagery for Forestry GIS Results Based on literature review GIS technologies usage is more developed as Remote sensing in Landuse projects in Latvia, but both has big potential to develop Main limitations for GIS and remote sensing development: lack of highly qualified specialist and workforce in GIS and remote sensing study field; limited demand and need for highly accurate and detailed GIS and remote sensing products from businesses; lack of examples from large global projects and well reviewed studies; there is a large knowledge gap between industries and scientists; In Latvia small industry in general (around 2,5 bil Euro, by LIAA research); impact from global economical downturn.

26 Using satellite imagery for Forestry GIS Satellite imagery at SFS are used for updating of Forest Digital map, which is part of State Forest register. Forest Digital map consist of textual and graphical part. Information comes from inventory results. Forest Digital map captures all information of Forest coverage changes. Data are stored in central data base, with public internet access.

27 Using satellite imagery for Forestry GIS Within Forestry GIS project remote sensing technologies are used for forest change detection. Methodology change detection with PCI Geomatic software. SFS change detection analyse, using LANDSAT imagery from different time periods

28 GFM (Global Forest Monitoring) project SFS of Latvia incoorporation with State land service of Sweden has participated at GFM project The project goal is to analyze and monitor forest recovery processes and the control of seed trees that are left into cuttings. Project was performed on 2007 in two test sites that are located in Ogres and Cesu districts. For the research LANDSAT and SPOT imagery data with 10 m resolution was used. Methodology compare of satelitte images from different time series and change detections. Research conclusions: It is possible to accurate detect forest cutting areas and seed trees that are left after Forest cutting. Forest recovery is detectable after about 8 years, since the last cutout, because in first years new trees are overgrown by typical post-cutting vegetation.