TREES 3 Forest monitoring from satellite remote sensing

TREES-III 2007-2013 Rationale: 1. to reduce uncertainties in global estimates of forest cover change and related biosphere-atmosphere processes with focus on the Tropics and boreal Eurasia 2. to provide information to European Commission services in support to the definition of policies in the framework of multilateral environmental agreements Objectives: 1. Improvement of existing regional forest cover products by using medium resolution imagery (250-300 m) 2. Updating and improving forest change estimates based on fine resolution satellite imagery (20-30m)

TREES 2 Regional Forest Cover Map 1km spatial resolution Example: Insular SE-Asia

Regional forest cover mapping in SE-Asia from SPOT coarse resolution satellite imagery (1km) SPOT VEGETATION Mosaic: generated from two years of imagery 1998-2000

MODIS 250m Medium resolution satellite images for regional forest mapping (Borneo)

Medium resolution satellite images for regional forest mapping (Sumatra)

TREES-III 2007-2013 Objectives: 1. Improvement of existing regional forest cover products by using medium resolution imagery (250-300 m) 2. Updating and improving forest change estimates based on fine resolution satellite imagery (20-30m) - Phase I tropical humid forests change: 1990-2000-2005 - Phase II tropical dry forests change: 1990-2000-2005 - Phase III + boreal forests change: + 1980-1990??

TREES 2 stratified Sampling for Change Assessment using Landsat TM and SPOT images

TREES Systematic Sample 1 x 1 number of sampling units in the tropics > 3800 distance between sample units = 1 degree

Interpretation & assessment of forest change : Sumatra

Forest Degradation TREES TROPICAL DOMAIN + MONDE AFRICA DOMAIN 1 Latin America Africa S& SE Asia Central + Caribian: 60 Humid: 451 South: 314 South America: 1168 Dry: 1473 1 Southeast: 421 Region: 1228 Region: 1924 Region: 735 Total: 3887

Sample S-Asia

Sample Continental SE-Asia

Sample Insular SE-Asia

Central box of 10 km x 10 km Size of TREES-3 Sample Unit

Change assessment for a test site in Papua New Guinea Automated segmentation and classification - analysis of change 1990 2000 Change

Legend: How much detail required? Tree cover (Forest) [ 5 m height, forest prop. in polygon (FP) > 70, Canopy Cover (CC) > 10 Needle-leaved Broadleaved Evergreen Deciduous Mangroves Other Inundated Mosaic 1: Tree cover / Other FP 40-70% (= fragmented) Evergreen Deciduous Mosaic 2: Other / Tree cover FP 10-40% Shrub cover (incl. re-growth <5m) Evergreen Deciduous Herbaceous cover (incl. lichen & moss) Cultivated & Managed Non Vegetated Clouds & No Data

Legend: How much detail required? Tree cover (Forest) [ 5 m height, forest prop. in polygon (FP) > 70, Canopy Cover (CC) > 10 Needle-leaved Broadleaved Evergreen Deciduous Mangroves Other Inundated Mosaic 1: Tree cover/ Other FP 40-70% (= fragmented) Evergreen Deciduous Mosaic 2: Other/Tree cover FP 10-40%? Shrub cover (incl. re-growth <5m) Evergreen Deciduous Other Clouds & No Data

Remarks Legend: Open-Closed forest Closed & Open forest = open, but continuous tree canopy. for evergreen & semi-evergreen forests = difficult to achieve consistent from Landsat imagery = exact application of thresholds (40% cc) impossible = interpretation of spectral differences misleading and subjective gradual transitions not visible impact such as slope illumination = possible where canopy is very open i.e. rather fragmented for (dry) deciduous forests almost impossible to specify crown cover density classes usually imagery available during the dry season trees are leafless & impact of soil, litter, burnt scars

Example: Mapping of dry forest cover Mekong Basin

Example: Mapping of dry forest cover

Remarks Legend: Open-Closed forest Closed & Open forest? drop this differentiation for interpretation from Landsat TM like data? assign attribute open by forest biome, deciduous forests in the dry forest biome are in general open?

Degradation = important process, Remarks Legend: Degraded Forest however 1. no standard definition available: primary - secondary forest? not-degraded - degraded forest? open - from natural or human impact? 2. Degradation can relate to different parameters 1. species richness 2. biodiversity usually not detectable 3. stand structure from Landsat imagery 4. logged over areas 5. canopy opening can be detected after heavy and recent impact presence of logging roads and infrastructure logged over and non-logged canopies similar after short time periods

Example of logging pattern on Kalimantan ASTER (15m) Landsat ETM+ 2000

Example of logging pattern on Kalimantan ASTER (15m) Landsat ETM+ 2000 ASTER 2004

Example of logging pattern on Kalimantan SPOT XS (10m)

Logging on New Britain (PNG) Landsat TM & SPOT

Remarks Legend: Degraded Forest Degradation? Avoiding term degraded? Dropping class degraded forest as a general forest class?

Disturbed forest canopies? Option -map areas of RS visible disturbance not all kind not all stages and not all areas of degradation will be documented! Concept of intact and non-intact forest - by analogy to the intact/non-intact forest definition given by WRI intact forest no signs of intervention or infrastructure non-intact forest all other forests

Example of intact and non-intact forest areas for a site on Borneo N-i Non-Forest N-F Intact No-Fo Non-intact Intact Non-intact No-Fo No-Fo Non-intact Intact N-F Intact Intact Intact No-Fo N-Fo Landsat ETM Bild ~ 2000, 30m GoogleEarth

Remarks: Legend Mosaic classes with segmentation approach and polygons output difficult to avoid: Mosaic 1: forest component dominant ( = fragmented forest) Mosaic 2: forest component not dominant or not present Mosaik 2 may be dropped if no need (i) to separate from pure agricultural land or (ii) to assign a forest cover percentage (25%). Forest Plantations = forest cover including e.g. Pinus, Eucalyptus, Tectona grandis, Hevea, etc - mapping only possible if large enough, homogeneous and of characteristic spatial shape - difficult to map completely in a global sampling approach Bamboo: forest or non-forest? many detectable pure bamboo areas correspond in terms of physiognomy rather to a shrub cover spots in disturbed canopies not detectable large and tall bamboo stands (China) better fit into forest Oil Palm plantations: Non-forest

Burnt Areas Burnt areas in the forest domain (excluding areas of regular annual burning cycles like in savannahs) where to assign forest? shrub & grass cover? vegetation?

Implementation & link to FAO FRA Regional Forest Mapping Component at 250 / 350m Processing at JRC with regional partners Change assessment in sample (10-30m) 1. automated segmentation 2. automated preliminary classification of objects and changes 3. interpreter intervention to verify and adjust automated labeling - in co-operation with sub-regional partners - 4. first result for regional sample Link to FAO FRA - details still to be defined - FAO FRA FAO national partners: verify, re-label if required & validation adding land use parameters and other info

Thank You!