guidelines for enhancement of high...

GUIDELINES FOR ENHANCEMENT OF HIGH-RESOLUTION

LAYERS PRODUCED UNDER GMES INITIAL OPERATIONS (GIO) LAND MONITORING 2011 – 2013

Supplement to the documents:

GMES Initial Operations (GIO) Land Monitoring 2011 – 2013 in the framework of regulation (EU) No 911/2010 Pan-EU Component

Terms of Reference and template for national project plan

Framework service contract(s) for the provision of GMES Initial Operations 2011-2013 Land Monitoring Services: High Resolution

land cover characteristics of 5 main land cover types (6 lots). Ref-erence: Open call for tenders EEA/SES/11/004

Guidelines for verification of high resolution layers produced un-

der GMES Initial Operations (GIO) land monitoring 2011 - 2013

GMES Initial Operations (GIO) Land Monitoring 2011-2013

Guidelines for enhancement of high-resolution layers

21 May 2012 2

The Delegation Agreement is funded by the European Union in the context of the GMES programme

and implemented by European Environment Agency.

DISCLAIMER

The views expressed herein can in no way be taken to reflect the official opinion of the European Union.

Reporting information

Report title: Guidelines for enhancement of high-resolution layers

produced under GMES Initial Operations (GIO) Land

monitoring 2011 – 2013

Report number: N/A

Report website: N/A

Report version: 1.0

Date of preparation: 21.05.2012

Beneficiary organisation: National Land Cover Teams, Service Providers

Prepared by: György Büttner

Project coordinator: Hans Dufourmont

Project coordinator organisation: European Environment Agency

Project coordinator telephone number: +45 2494 1115

Project coordinator email address: [email protected]

mailto:[email protected]



21 May 2012 3

1 Contents

2 Executive summary ......................................................................................................................... 4

3 Background and purpose of the document ..................................................................................... 5

4 Purpose of the enhancement .......................................................................................................... 5

5 Basic principles of enhancement .................................................................................................... 7

6 Strategies of enhancement ............................................................................................................. 9

6.1 ENHANCEMENT BASED ON GENERAL OVERVIEW ........................................................................... 9 6.2 ENHANCEMENT BASED ON LOOK-AND-FEEL VERIFICATION ............................................................ 9 6.3 DECISION BASED ON QUANTITATIVE VERIFICATION ....................................................................... 9

7 Data specification .......................................................................................................................... 10

8 Examples ....................................................................................................................................... 20

8.1 HRL IMPERVIOUSNESS ............................................................................................................ 20 8.2 HRL TREE COVER DENSITY ...................................................................................................... 20 8.3 HRL FOREST TYPE MAP ........................................................................................................... 20 8.4 HRL GRASSLAND MAP ............................................................................................................. 23 8.5 HRL WETLAND MAP ................................................................................................................ 23 8.6 HRL MAP OF PERMANENT WATER BODIES ................................................................................. 23

9 Annex 1: HRL Enhancement report template ............................................................................... 24

Acknowledgements ............................................................................................................................... 25



21 May 2012 4

Revision history

Revision nr. Date Modified by Comments

2 Executive summary

Five1 high-resolution layers (HRL) will be produced in the frame of GIO Land (2011-2013)

covering EEA39: imperviousness, forests (tree cover density and forest type), grasslands,

wetlands and permanent water bodies. Service Providers are in charge of production of the

HRLs. The so-called intermediate products (20 x 20 m resolution) will be verified by national

teams (if national teams are not interested, by Service Providers).

Additionally, enhancement of the products is to be done in order to improve the intermediate

HRLs based on the results of the verification. Enhancement shall be carried out on the in-

termediate products at full resolution (20m x 20m, in national projection), based on existing

reference data (e.g. ground survey, topographic maps, thematic maps, aerial photography or

others). Similarly to verification, enhancement is done by national teams (if national teams

are not interested, by Service Providers).

Countries (and Service Providers) are expected to use the available resources (expertise,

budget and the best in-situ data) in an optimal way to increase the accuracy of the interme-

diate product to the feasible maximum. The enhancement should consist of reduction of

commission and omission errors. Commission errors (to be deleted from the intermediate

database) can be handled in case of all HRLs. However, omission errors) can be dealt with

only in case of map layers and not with density layers. The results of the enhancement will

be coded with different attributes than those used by SPs in the intermediate dataset. Con-

trary to the verification procedure, where former Eionet experience exists, no such previous

experience is available for the enhancement.

The purpose of this document is to provide guidelines for the enhancement to be applied for

HRLs produced under GIO-land. This document should be considered as a „living document‟

and will be shaped as experience will accumulate.

1 In reality there are 6 layers, because of two layers in forestry



21 May 2012 5

3 Background and purpose of the document

The Land monitoring service of the Global Monitoring of Environment and Security

(GMES) led by DG ENTR2 of the European Commission, has entered its Initial Operations

(GIO) phase following the entry into application of Regulation (EU) n°911/2010 of 22 Sep-

tember 2010 of the European Parliament and the Council on the European Earth monitoring

programme (GMES) and its initial operations (2011 to 2013).

Pursuant to the GMES Work Programme 2011 these activities will start with the production

of the 5 High Resolution pan-European layers. To that aim, a call for tender has been or-

ganised, comprising 6 lots, following a distribution according to a combination of geographic

and thematic criteria. On 5th October 2011 the EEA addressed the National Focal Points and

National Reference Centres Land Cover in 39 European countries requesting for a letter of

intent for participation in GIO Land. The request was accompanied with a Terms of Refer-

ence and template for national project plan.

Some of the tasks in the Technical Specification, namely “Verification of high-resolution lay-

ers (HRL)” and “Enhancement of HRLs” were not fully described in technical terms and

“comprehensive guidelines” were promised to the countries as well as to Service Providers

(SP) in a later stage. Guidelines for verification are presented in a separate document3, re-

ferred to as GLV in this document. The purpose of the present document is to provide guide-

lines for enhancement of high-resolution layers. Contrary to the verification, where former

Eionet experience exists (Fast Track Service Land Monitoring), no such experience is avail-

able for the enhancement.

4 Purpose of the enhancement

The envisaged purpose of the enhancement is to improve the quality of the intermediate

HRL products (20m x 20m) produced by SPs. Following the enhancement, the intermediate

product will become the final product. In a majority of countries verification and enhancement

is foreseen to be done by the national teams. However, in some countries enhancement will

be done by the SP, if the country is not interested in participating in this process. Responses

of countries regarding intention of participation in verification and enhancement are included

in Table 1. (Note that response is pending for some countries.)

Enhancement means:

Removing an area from the intermediate HRL produced by the SP, because there is

evidence showing that the area does not belong to the HRL (i.e. commission error).

Supplementing the intermediate HRL produced by the SP with an area, because

there is evidence showing that the area does belong to the HRL (i.e. omission error).

2 Directorate General Enterprise and Industry

3 Guidelines for verification of High-Resolution Layers Produced under GMES Initial Operations (GIO) Land Monitoring 2011 –

2013, EEA, April 2012 (Version 2)



21 May 2012 6

Table 1 Interest of countries in verification and enhancement (status: 15 May 2012)

country Interested in verification Interested in enhancement

Albania + +

Austria + +

Belgium + +

Bosnia and Herzegovina + +

Bulgaria + + Croatia + +

Cyprus + +

Czech Republic + +

Denmark + +

Estonia - -

Finland + +

France + +

Germany + *

Greece + +

Hungary + +

Iceland + +

Ireland + -

Italy + +

Kosovo - -

Latvia + -

Liechtenstein + +

Lithuania + +

Luxemburg - -

FYR of Macedonia + -

Malta + +

Montenegro + +

The Netherlands + +

Norway + - Poland * *

Portugal + *

Romania + +

Serbia + +

Slovak Republic + +

Slovenia + -

Spain + +

Sweden - - Switzerland * *

Turkey + + United Kingdom + + Interested: at least 34 at least 26

* response is pending



21 May 2012 7

The following six intermediate products (20m x 20m, national projection) will be subject to

enhancement:

Imperviousness density (or built-up map)

Tree cover density (or tree cover map)

Forest type map

Grasslands map

Wetlands map

Map of permanent water bodies

5 Basic principles of enhancement

Determining density values (imperviousness and tree cover) needs a dedicated processing

methodology4, which is rarely available at country level. Consequently, errors of omission

found in the imperviousness and tree cover density datasets are not expected to be correct-

ed by the countries with regards to the density values itself, only by the SPs (in cases where

the country is not interested in implementing enhancement). Countries will only be able to

enhance the built-up map (produced from imperviousness by applying a threshold to the

density values) and the tree cover map (produced from tree cover densities by applying a

threshold), respectively (see Ch. 6.2 in GLV). However, outlines of missing patches (i.e.

omitted in intermediate HRL) for impervious areas and tree-covered areas should be provid-

ed where possible, but not the density values inside the outlined patches (Table 2). These

patches can then be used in the next inventory of the HRL density product (i.e. in the opera-

tional phase of GMES) by the SP who will produce the updated HRL density product.

Table 2 Possibilities to correct omission errors (adding new areas to the HRLs) by en-

hancement

HRL Density / Map Enhancement by

countries Enhancement by

SP

Imperviousness Density not possible possible

Built-up map (derived by using 30% threshold)

possible5 NA

Tree cover

Density not possible possible

Tree-cover map (derived by using 30% threshold)

possible6 NA

Forest type Map possible possible

Grassland Map possible possible

Wetland Map possible possible

Permanent water Map possible possible

4 Processing of calibrated HR satellite imagery

5 Outlines of omitted impervious areas should be provided but not densities

6 Outlines of omitted areas with tree cover should be provided but not densities



21 May 2012 8

Removing areas (commission errors) from HRL is possible from density layers, as well as

from map layers.

It is not easy to provide general guidance for the enhancement which is valid for all six HRLs

to be enhanced. However, the following basic principles are important to consider:

The volume of the enhancement, i.e. the work to be done depends on: (1) quality of

the SP‟s intermediate product; (2) quality of in-situ data; (3) available technical tools;

(4) available manpower and expertise and (5) budget. Usually it will be not realistic

aim to enhance the product to have 100% accuracy, but to use the available re-

sources in an optimal way to increase the accuracy of the intermediate product to the

feasible maximum.

An enhancement over the whole area of a country (even if less complete) is preferred to a very intense focus on a specific region (and then no resources to cover the rest of the country).

The enhancement should be based on the best available in-situ data. Potential in-situ

data for each HRL are listed in GLV Ch. 8. “Best” is meant regarding completeness,

timeliness, resolution, etc.

If an existing thematic map (database) is used as in situ source, control by recent or-

tho-photo is highly recommended to avoid the transfer of inconsistencies of the map

(database) into the HRL.

The enhancement should consist of a reduction of commission and omission errors,

as pointed out in Ch.4. The results of the enhancement should be coded with differ-

ent attributes than those used by SPs in the intermediate datasets, in order to clearly

separate the intermediate product and the enhanced one.

No preference is given to automated or manual enhancement methods. The selected

method should depend on the type of in-situ data and availability of technical tools.

Even if an automated process is used, some human control is indispensable to avoid

degradation of the HRL quality by errors of the in-situ data. In addition to the usual

problem of thematic maps, i.e. being frequently outdated, pre-dating of databases al-

so can occur, i.e. showing a status planned in the future.

If a good quality, recent built-up database is available there seems to be an easy way to en-

hance the imperviousness layer; not only the built-up map, but also the densities by placing the

20m x 20m grid on top of the built-up map, calculating the densities and having them substituted

into the intermediate layer.

This solution is not recommended, because:

There is a scaling difference between the densities derived by SPs, extracted from satel-

lite imagery, and densities based on in-situ data. I.e. the densities provided by the pre-

liminary data processing will not necessarily be compatible with densities produced by

the enhancement. This might introduce mistakes in the final 100m x 100m products by

SP.



21 May 2012 9

6 Strategies of enhancement

The basis of the enhancement process should be the result of the verification. As shown in

GLV the following types of verification processes are carried out:

General overview of data quality (mandatory, qualitative)

Look and feel (mandatory, qualitative)

Statistical verification (highly recommended, quantitative)

6.1 Enhancement based on general overview

If no significant systematic mistakes are identified during verification, the result of general overview can be used to guide the enhancement. Based on an ordered list of disagreements between the HRL and the best available in-situ data, disagreements with the largest area can be examined. If the disagreement is confirmed to be an error of the HRL product, it can be corrected.

Benefits: largest decrease in misclassified area (omission and commission errors) can be achieved.

Drawbacks: if the best available in-situ data are not up-to-date, there will be lots of false-alarms, i.e. disagreements that are not mistakes of the HRL, but mistakes of the in-situ data. For this reason use of up-to-date ortho-photos for control is highly recommended.

6.2 Enhancement based on look-and-feel verification

If look-and-feel verification shows that one or more strata of the HRL are not precise enough, but the product is otherwise good, the efforts of enhancement can concentrate on these problematic strata.

Benefits: enhancement proceeds stratum-wise, which is easy for the operator. E.g. in HRL Imperviousness settlements or continuity of highways are checked.

Drawbacks: non-systematic mistakes with large area might not be corrected.

6.3 Decision based on quantitative verification

If statistical analysis shows that the accuracy of the intermediate HRL is below 80% and de-pending on the amount of effort needed to achieve the requested 85% accuracy7, the 3 stakeholders involved (EEA, country and SP) shall meet (teleconference) to analyse the sit-uation and to discuss appropriate mitigation measures, working closely together in order to reach a good final result.

7 The required man days have to be estimated.



21 May 2012 10

7 Data specification

Table 3 List of products as results of the enhancement

HRL Product name Product

no.

Imperviousness

Enhanced HRL Imperviousness, 20m x 20m,

national projection, enhanced by SP 1a

Enhanced HRL Imperviousness, 20m x 20m,

national projection, enhanced by country 1b

Forests

Tree cover

density

Enhanced HRL Tree cover density, 20m x

20m, national projection, enhanced by SP 2.1a

Enhanced HRL Tree cover density, 20m x

20m, national projection, enhanced by country 2.1b

Forest type Enhanced HRL Forest Type, 20m x 20m, na-

tional projection, enhanced by country or SP 2.2

Grasslands Enhanced HRL Grassland, 20m x 20m, na-

tional projection, enhanced by country or SP 3

Wetland Enhanced HRL Wetland, 20m x 20m, national

projection, enhanced by country or SP 4

Permanent

water bodies

Enhanced HRL Permanent water bodies, 20m

x 20m, national projection, enhanced by coun-

try or SP

5



21 May 2012 11

Product 1a: Detailed specification of the Enhanced HRL Imperviousness (enhanced by SP)

Product

Enhanced Degree of Imperviousness 2012, 20m x 20m, national projection

Methodology

Based on the results of verification the Service Provider enhanced the intermediate De-gree of Imperviousness product.

Geometric resolution

Pixel size 20m x 20m

Coordinate Reference System

National projection systems for country data sets

Geometric accuracy (positioning scale)

According to ortho-rectified satellite imagery delivered by ESA (target accuracy: 20m RMSE)

Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-impervious areas in intermediate product 1-100: imperviousness values in intermediate product 101-200: imperviousness values obtained during enhancement (correcting omission errors) 201: all non-impervious areas obtained during enhancement (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow)

255: outside area

Metadata

According to INSPIRE metadata standards



21 May 2012 12

Product 1b: Detailed specification of the Enhanced HRL Imperviousness (enhanced by

country)

Product

Enhanced Degree of Imperviousness 2012, 20m x 20m, national projection

Methodology

Based on the results of verification, the country enhanced the intermediate Degree of Im-perviousness product. Adding new densities into the database (reducing omission errors) is not possible. Instead, the Built-up map derived from HRL Imperviousness (by using a 30% threshold) has been enhanced. Patches of erroneous Built-up areas (commission errors) have been marked in the intermediate Degree of Imperviousness database.


Pixel size 20m x 20m





Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-impervious areas in intermediate product 1-100: imperviousness values in intermediate product 101: all built-up areas obtained during the enhancement process (correcting omission errors) 102: all non-built-up (non-sealed) areas obtained during the enhancement process (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow)

255: outside area

Metadata




21 May 2012 13

Product 2.1a: Detailed specifications for the Enhanced HRL Tree cover density (enhanced

by SP)

Product

Enhanced tree cover density 2012, 20m x 20m, national projection

Methodology

Based on the results of verification the Service Provider enhanced the intermediate Tree

Cover density product.


Pixel resolution 20m x 20m




According to ortho-rectified satellite imagery delivered by ESA

Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-tree areas in intermediate product 1-100: tree cover densities in intermediate product 101-200: tree cover densities obtained during enhancement process (correcting omission errors) 201: all non-tree cover areas obtained during enhancement process (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside areas

Metadata




21 May 2012 14

Product 2.1b: Detailed specifications for the Enhanced HRL Tree cover density (enhanced

by country)

Product

Enhanced tree cover map 2012, 20m x 20m, national projection

Methodology

Based on the results of verification the country enhanced the intermediate Tree cover

density product. Adding new densities into the database is not possible (reducing omis-

sion errors). Instead, the Tree cover map derived from HRL Tree Cover density (by using

a 30% threshold) has been enhanced. Patches of erroneous Tree-cover areas (commis-

sion errors) have been marked in the intermediate Tree cover density database.







Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-tree areas in intermediate product 1-100: tree cover densities in intermediate product 101: all tree areas obtained during the enhancement process (correcting omission errors) 102: all non-tree areas obtained during the enhancement process (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside area

Metadata




21 May 2012 15

Product 2.2: Detailed specifications for Enhanced HRL Forest type

Product

Enhanced HR Forest type 2012, 20m x 20m, national projection

Methodology

Based on the results of verification the intermediate HRL Forest Type map has been en-

hanced by country or by Service Provider. In addition to the dominant leaf type layer (de-

ciduous, coniferous) the support grid (including “trees used for agricultural practices” and

“trees in urban context”) might have been also enhanced. Patches of erroneous areas

(omission and commission errors) have been integrated into the intermediate database.


Pixel resolution 20m x 20m, 0.5 ha MMU





Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values for dominant leaf type grid 0: all non-tree areas in intermediate product 1: broadleaf forest in intermediate product 2: coniferous forest in intermediate product 101: all broadleaf forest obtained during the enhancement process (correcting omission errors) 102: all coniferous forest obtained during the enhancement process (correcting omission errors) 105: all non-tree areas obtained during the enhancement process (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside area

Thematic pixel values for additional support grid on non-forest trees 0: all non-tree areas in intermediate product 3: trees predominantly used for agricultural practices in intermediate product 4: trees in urban context, in intermediate product 103: trees predominantly used for agricultural practices obtained during the enhancement process (correcting omission errors) 104: trees in urban context, obtained during the enhancement process (correcting omission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside area

Metadata




21 May 2012 16

This layer (product 2.2) includes two grids (GLV, Table 2b): (1) a dominant leaf type grid

(deciduous and coniferous) and (2) additional support grid with non-forest data (trees used

for agricultural purposes and trees in urban context). The HRL Forest type is produced by

GIS operation using these two layers. Therefore enhancement should tackle both grids (Ta-

ble 4).

Table 4 Enhancement of HRL Forest type (cases simplified)

HRL Forest type

intermediate product

In-situ data Action

Forest non-

forest

case 1:

non-forest trees (agriculture or

urban use)

Enhance the support

grid (reduce omission

error in support grid, i.e.

commission error in

forest type grid)

case 2:

non-trees

Enhance the dominant

leaf type grid (reduce

commission error)

Non-forest forest Enhance the dominant

leaf type grid (reduce

omission error)



21 May 2012 17

Product 3: Detailed specification for Enhanced HRL Grassland

Product

Enhanced HRL Map of permanent grassland 2006-2009-2012, 20m x 20m

Methodology

Based on the results of verification the intermediate HRL Grassland map has been en-hanced by country or by Service Provider. Patches of erroneous areas (omission and commission errors) have been integrated into the intermediate database.







Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-grassland areas in intermediate product 1: grassland areas in intermediate product 101: all grassland areas obtained during the enhancement process (correcting omission errors) 102: all non-grassland areas obtained during enhancement process (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside area

Metadata




21 May 2012 18

Product 4: Detailed specification for Enhanced HRL Wetland

Product

Enhanced HRL Wetland map 2012, 20m x 20m

Methodology

Based on the results of verification the intermediate HRL Wetland map has been en-hanced by country or by Service Provider. Patches of erroneous areas (omission and commission errors) have been integrated into the intermediate database.







Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-wetland areas in intermediate product 1: wetland areas in intermediate product 101: all wetland areas obtained during the enhancement process (correcting omission errors) 102: all non-wetland areas obtained during enhancement process (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside area

Metadata




21 May 2012 19

Product 5: Detailed specification for Enhanced HRL Permanent water bodies

Product

Enhanced HRL Permanent water bodies 2006-2009-2012, 20m x 20m

Methodology

Based on the results of verification the intermediate HRL Permanent water bodies map

has been enhanced by country or by Service Provider. Patches of erroneous areas (omis-

sion and commission errors) have been integrated into the intermediate database.







Verification

Not planned

Data type

Raster

Raster coding

Thematic pixel values 0: all non-permanent water areas in intermediate product 1: all permanent water areas in intermediate product 101: all permanent water areas obtained during the enhancement (correcting omission errors) 102: all non- permanent water areas obtained during enhancement (correcting commission errors) 254: unclassifiable (no satellite image available, or clouds, shadows, or snow) 255: outside area

Metadata




21 May 2012 20

8 Examples

Contrary to the verification, where former Eionet experience exists (Fast Track Service Land

Monitoring), no such experience is available for the enhancement. At the moment very few

real examples are available, therefore hypothetic examples are provided. The number of real

examples will grow during the training workshops and the implementation of the project.

8.1 HRL Imperviousness

Fringe zones of built-up areas, characterised with moderate imperviousness densities are sometimes omitted from HRL Imperviousness (see Example 1 from GLV).

In situ data used: topographic map and recent colour ortho-photo

Layer to be enhanced: Built-up map (because densities, compatible with the ones provided by the SP are not possible to derive; see Ch.5)

Enhancement based on: “look-and-feel” of rural settlements

Way of enhancement: visual delineation of the outline of the missing area, based on the ortho-photo as spatial reference. The HRL Built-up map was displayed to achieve precise delineation.

The HRL Imperviousness (density) data have to be checked also in order to see if the area was missing because of the 30% threshold applied in deriving the HRL Built-up map.

8.2 HRL Tree cover density

The country enhances the tree cover map derived from HRL Tree cover density by applying

a 30% threshold.

Example: Fields planted with energy crop8 is removed from tree cover density map

(commission error).

8.3 HRL Forest type map

Example 2 from GLV is used for the demonstation.

In situ data used: topographic map and recent colour ortho-photo. Topographic map is outdated (see missing forest patch at the yellow arrow).

Layer to be enhanced: HRL Forest type map

Enhancement based on: “look-and-feel” of wet forests

Enhancement (removal of commission errors): the area with commission error (blue arrow) is outlined on the ortho-photo, coded by 105 (Product 2.2) and added to the intermediate product.

Enhancement (removal of omission errors): The area with omission error (yellow ar-row) is outlined on the ortho-photo, coded by 101 (Product 2.2) and added to the in-termediate product.

No modification in the additional support grid was needed (neither trees with agricul-ture nor with urban use are present).

8 The classifier was confused by the spectral signature of the energy crop (similar to broadleaved forest)



21 May 2012 21

Example 1: Omission error in HRL Imperviousness (2006) Top: Topographic map with HR built-up area map (pro-duced with 30% threshold on Soil Sealing Enhancement 2006 data) overlaid (black/yellow outlines) Middle: IMAGE2006 Bottom: VHR natural colour orthophoto Location: Mihályi, Hungary Enhancement: SW part of the built-up area is outlined on the ortho-photo, coded by 101 (Product 1b) and added to the intermediate product. Densi-ties cannot be estimated by countries, only by SPs.



21 May 2012 22

Example 2: Commission and omission errors in HRL Forest (2008) Top: Topographic map with HR Forest area overlaid (red outlines) Bottom: VHR natural colour orthophoto Middle: IMAGE2006 (addition-al data) Location: Near Zalakaros, Hungary Enhancement:

The area with commission error (blue arrow) is out-lined on the ortho-photo, coded by 105 (Product 2.2) and added to the interme-diate product.

The area with omission error (yellow arrow) is out-lined on the ortho-photo, coded by 101 (Product 2.2) and added to the interme-diate product.

No modification in the ad-ditional support grid was needed (neither trees with agriculture nor with urban use are present).



21 May 2012 23

8.4 HRL Grassland map

Example: a hayfield indicated by a recent ortho-photo is included in the intermediate HRL

grassland map product (omission error). Enhancement based on delination of the missing

grassland area on the orthophoto. Code = 101 (product 3).

8.5 HRL Wetland map

Example: a wetland indicated by the national wetland map and confirmed by a recent

orthophoto is not included in the the intermediate HRL wetland map. Enhancement based on

delination of the missing wetland area on the orthophoto or taking over the outline from the

national wetland map, if it is precise enough. Code = 101 (product 4).

8.6 HRL Map of permanent water bodies

A liquid dumpsite shown by the national topographic map is erronously included in the inter-

mediate map of HRL water bodies. Enhancement based on excluding the water body from

the intermediate HRL water map based on information of the topographic map. Code = 102

(product 5).



21 May 2012 24

9 Annex 1: HRL Enhancement report template

The report shall be identical for all HRLs.

I. Administrative part

High Resolution Layer

Country (and region, if regions are analyzed separately)

Institution carrying out the work

Expert carrying out the work (name, position and e-mail)

Internal quality control by (name, position and e-mail)

Date and place of writing the report

II. Technical part

Which methods of the verifica-tion were used to guide the en-hancement? (write (X) in the appropriate box)

( ) General overview of data quality ( ) Look-and-feel analysis ( ) Statistical verification

In situ data used. Replace Data-1 with the proper type. How can you estimate the usa-bility / quality of in-situ data (ex-cellent, good, average, bad, very bad – keep one answer only)

Data-1 (excellent, good, average, bad, very bad)

Data-2 (excellent, good, average, bad, very bad)

….

Data-n (excellent, good, average, bad, very bad)

Methodology of enhancement (write (X) in the appropriate box)

( ) Fully automatic ( ) Semi-automatic with lots of manual editing ( ) Semi-automatic with few manual editing ( ) Fully manual

Removal of commission errors: Which kind of improvement has been achieved?

(Provide short text about the types and quantity of mis-takes removed)

Removal of omission errors: Which kind of improvement has been achieved?

Provide short text about the types and quantity of mis-takes removed)

Provide an overall evaluation of the improvements achieved: (excellent, good, average, mod-est, weak– keep one answer only)

excellent means that most of the errors were eliminated good means that at least 75% of errors were eliminated average means that around 50% of errors were eliminat-ed modest means that about 25% of errors were eliminated weak means that less than 25% of errors were eliminated



21 May 2012 25

Acknowledgements

Gergely Maucha and Barbara Kosztra (ETC-SIA partner FÖMI), Ana Sousa, Alan Steel and Tobias Langanke (EEA) have contributed to writing of the guidelines.

guidelines for enhancement of high...

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