Forest density stratification with Ecognition& Worldview-224/06/2014

Jonas van Duijvenbode - GIZ

Goals

Forest inventory through object-based image analysis of very high resolution satellite imagery.

Use of Worldview-2 data 0.5m pan-sharpened resolution 8 multispectral bands

Forest density mapping Closed forest (>40% canopy cover) Open forest (>10% canopy cover) Non-forest

Minimal mapping unit of 0.5 ha

Satellite image

canopy

other

Closed forest

Open forest

Non-forest

Mixed forest

mangrove

pine

Forest density and major forest type workflow

Canopy - other

Everything that can visually be determined as trees is used as samples

Trees show a certain texture a certain color shadowed surroundings

Knowledge has been gathered on confusing land use classes in: Dogotuki (February 2014) Sigatoka (March 2014)

Open, closed and non-forest

Closed forest is an area with trees that are connected through canopy or shadowing and larger than 0.5 ha or canopy and surroundings with >40% canopy cover

Non-forest is all land use classes beside canopy and all canopy-containing areas that are not classified as open- or closed-forest (<10% canopy cover)

Open forest is canopy and surroundings with more than 10% canopy cover and area larger than 0.5 ha

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2 3

1. Radius of area of 0.5 ha = 39.89m (max)2. Radius of tree(stand) with area of 0.05 ha

(10% of 0.5 ha) = 12.62 m 3. Radius of buffer around tree(stand) of 0.5

ha=39.89-12.62=27.29There is an almost linear relationship between canopy area and maximum distance from canopyThe end result is a buffer around treestands depending on the size of the treestand. This connects trees with not-connected canopy and determines the delineation and area of open forest.

Delineation of forest without connected canopy

Sigatoka area

One satellite image Little cloud cover Lowland and highland areas Dry and wet areas Close-by enough to visit for ground validation and

orientationThe result of the findings in this area is a toolbox. This toolbox can be applied to any Worldview-2 image of Fiji for automatic classification.

Final classification: from satellite to forest density

Results Knowledge for the people of Forestry on forest

stratification A Ruleset to automatically classify a Worldview-2

image into forest density classes Insights into the expected accuracy of the

stratification Insights into the transferability to other areas in Fiji Recommendations for good classification and

accuracy assessment habits Recommendations for future work

Other activities

Workshop on forest density classification with ecognition 17-18 April.

Workshop on Ecognition and nearest neighbour classification 26-27 May.

Instructing Forestry MSD remote sensers on Ecognition