A qualitative accuracy assessmentA qualitative accuracy assessment

Philippe Mayaux & the GLCers

Institute for Environment and Sustainability, EC Joint Research Centre, Italy

 

The general approachThe general approach

• Objective: to avoid macroscopic errors before the quantitative accuracy assessment

• Systematic descriptive protocol to document the verification per cell (± 220 km x 220 km)

• Use of ancillary data (maps, Landsat & SPOT images, aerial photographs…) and expert opinion

• Archive the evaluation in a database

The validation gridThe validation grid

• 40 N – 60 S: 2x2 degrees• 40 N – 60 N: 2x3 degrees• > 60 N: 2x4 degrees

The georeferencing systemThe georeferencing system

• Alphanumeric Cell_ID• Letter = latitude• Number = longitude of left

side

Qualitative evaluation fieldsQualitative evaluation fields

• Cell_ID• Name of the expert• GLC product• Type of reference material: high-res image, quick-look, thematic map,

aerial photograph, field photograph• Number and nature of LC classes• Spatial pattern: linear, diffuse, massive, insular• Nature of limits: sharp, fuzzy• Overall quality of the GLC product, very good, good, acceptable,

unacceptable• LC classes well-identified• LC classes poorly identified• Nature of problem: label, limit, missing class, other

Spatial patternsSpatial patterns

• 4 main systems– Diffuse– Massive– Linear– Insular

• + combinations• Dominant pattern within the

cell

Cell_ID

Name of the expert Francis White

GLC product

Reference material

Y/N

Type of reference material

H = High-res imageQ = Quick-lookT = Thematic mapA = Aerial photographF = Field photograph

Number of LC classes

n

LC classes

Spatial pattern

M = MassiveD = DiffuseL = LinearI = Insular

Nature of limitsS = SharpF = Fuzzy

Overall quality of the GLC

product

V = Very goodG = GoodM = ModerateU = Unacceptable

LC classes well-identified

LC classes poorly

identified

Nature of problem

A =Wrong labelL = LimitM = Missing classO = Other

Quantitative accuracy assessmentQuantitative accuracy assessment

• Objective: To provide a statistical assessment of the accuracy by class  

• Components to evaluate:– over/under estimation of LC classes– wrong location

• Constraints: Budget (data, interpretation), time, number of classes, spatial complexity

The futureThe future

• Continuation of this validation exercise• Involvement of other partners•