Abstract

Abstract. An overall societal aim is to ensure a sustainable use and management of agricultural landscapes. This requires continuous delivery of reliable and up-to-date information to decision-makers. To be able to deliver this information, a monitoring program for agricultural landscapes was initiated in Norway 13 years ago. The program documents and reports on land use / land cover changes from data captured through interpretation of true colour aerial photos using stereo instruments. The monitoring programme is based on a sample of 1000 squares of 1 × 1 km and the entire sample of squares is photographed over a five-year period. Each square is then mapped repeatedly every fifth year to record changes. Aerial photo interpretation is based on a custom classification system which is built up hierarchically, with three levels. The first level comprises seven land type classes: Agricultural land, Bare ground, Semi-natural open vegetation, Unforested wetland vegetation, Forest, Urban areas and Water. These land classes are further divided into 24 land types at level two, and approximately 100 land types at level 3. In addition to land type units we map both line elements like stone fences and point elements like buildings and solitary threes. By use of indicators that describe status and change focusing on themes of particular policy interest, we can report on whether policy aims are being fulfilled or not. Four indicator themes have been in focus hitherto: landscape spatial structure, biological diversity, cultural heritage and accessibility. Our data is stored in databases and most of the data quality check/structure process and analyses are now being made in open source software like PostGIS and PostSQL. To assess the accuracy of the photo-interpretation, ground truthing is carried out on 10 % of the squares. The results of this operation document the benefits of having access to photos of the same area from two different years. The program is designed first and foremost to provide reliable statistics at a national level but the aim is also to report at regional levels – for example for counties or for agricultural landscape regions. The national coverage and application of standardized methods enable frequent updating. This method is cost effective and enables us to quantify changes in landscape qualities as well as adapting the programme to take account of e.g. new findings on relevant indicators.

Highlights

  • 1.1 Landscape monitoringTo ensure a sustainable use and management of agricultural landscape the decision-makers need reliable and up-to-date information

  • The squares are photographed each fifth year and the land use / land cover situation is digitized in stereo with a classification system that covers area, lines, points and accessibility (Strand, 2002)

  • Four indicator themes have been in focus hitherto: landscape spatial structure, biological diversity, cultural heritage and accessibility

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Summary

Landscape monitoring

To ensure a sustainable use and management of agricultural landscape the decision-makers need reliable and up-to-date information. A monitoring program where the main aim is to register this changes started in 1998. This program is based on a sample of 1000 squares of 1 x 1 km. The squares are photographed each fifth year and the land use / land cover situation is digitized in stereo with a classification system that covers area, lines, points and accessibility (Strand, 2002). Four indicator themes have been in focus hitherto: landscape spatial structure, biological diversity, cultural heritage and accessibility. Cultural heritage from existing register is displayed in the stereo model so that the interpreter will update the situation for each element that is registered. The classification system gives the interpreter the opportunity to use different types of codes describing the situation. Several controls are carried out on the captured data, e.g. illegal codes and missing features. 10 % of the squares are checked through a field control

Photos
Classification systems
Salt and brackish wetlands
Software systems
Field control
Seashore vegetation
ANALYSES
Findings
CONCLUSIONS
Full Text
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