Semi-Automatic Mapping of Landscape Features within the framework of GAEC. A selected case study from the Czech Republic.

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1 1 Semi-Automatic Mapping of Landscape Features within the framework of GAEC. A selected case study from the Czech Republic. R. de Kok MarS Unit, IPSC, JRC Ispra Main Topics The 6 mayor Landscape Feature classes (in CZ) and their appearance are confronted with field data. 2 The limitations of automatic class construction with 6 classes The confusion matrix and statistics (Area,Length/Width, Density) The usefulness of an automatic dual classification Landscape Features can be considered as elements in ongoing Landscape Processes. A Scenario is possible because driving and pressure agents are known. This could facilitate Landscape Management.

2 3 The LF defined by CZ A. balk / grass strip of land that may include woody vegetation (i.e. trees and bushes) and stone walls; used against water and wind erosion. B. terraces (may include woody vegetation) C. grass strip in thalweg, that may include woody vegetation D. group of woody plants with at least 2 woody plants; area under 2000 m2; cannot be part of a forest E. tree row with at least 5 woody plants F. solitary trees with a projected crown of at least 8 m2; cannot be part of any of the previously defined LF 4 First some field observations of the Landscape Features Landscape Features are difficult to differentiate in an automatic system A dual system might be a solution (AGRI/NON-AGRI) Confusion matrices can be confusing themselves, 3 different approaches will be shown Scenario and driving agents

3 5 A ; balk / grass strip of land that may include woody vegetation (i.e. trees and bushes) and stone walls; used against water and wind erosion. 6

4 7 8

5 9 10

6 11 Thalweg 12

7 The LF defined by CZ 13 A balk / grass strip of land that may include woody vegetation (i.e. trees and bushes) and stone walls; used against water and wind erosion. B terraces (may include woody vegetation) C grass strip in Thalweg, that may include woody vegetation D group of woody plants with at least 2 woody plants; area under 2000 m2; cannot be part of a forest E tree row with at least 5 woody plants F solitary trees with a projected crown of at least 8 m2; cannot be part of any of the previously defined LF Vegetated With texture Vegetated Non- textured Image F D E DTM/ Hydrologic B A C Agricultural Lands Financial consequences might be needing a dual agri/non-agri classification. The LF are based upon ecological definitions which are part of a landscape scenario. Ecological/biological ontology might become necessary for management decisions in Landscape Change (Scenario) 14 First some field observations of the Landscape Features Landscape Features are difficult to differentiate in an automatic system A dual system might be a solution (AGRI/NON-AGRI) Confusion matrices can be confusing themselves, 3 different approaches will be shown

8 15 16 Not connected to a line feature

9 17 18

19 First some field observations of the Landscape Features Landscape Features are difficult to differentiate in an automatic system A dual system might be a solution (AGRI/NON-AGRI) Confusion

10 19 First some field observations of the Landscape Features Landscape Features are difficult to differentiate in an automatic system A dual system might be a solution (AGRI/NON-AGRI) Confusion matrices can be confusing themselves, 3 different approaches will be shown Scenario and driving agents Ha total LPIS area 4.34 Ha only in digitalization Ha digitized Landscape Features 7.99 Ha in overlap Ha only detected with automatic detection

11 21 The 2% Map of Landscape Features Digitized on screen 22 According to automatic analysis, this map shows that Ha out of Ha is fit for agricultural production. On less than 5% of the area, restrictions on agricultural production might be expected due to available Landscape Features. According to visual interpretation this is less than 2%

23 48000Ha 21643 Ha LPIS 90 Ha LF digitized 154 Ha LF Automatic If trees cast contrasting shadows on agricultural land they will appear in this map.

12 Ha Ha LPIS 90 Ha LF digitized 154 Ha LF Automatic If trees cast contrasting shadows on agricultural land they will appear in this map. How usefully is this dual information agri/non-agri and at what price level? 30 cent/km²? 24 First some field observations of the Landscape Features Landscape Features are difficult to differentiate in an automatic system A dual system might be a solution (AGRI/NON-AGRI) Confusion matrices can be confusing themselves, 3 different approaches will be shown Scenario and driving agents

13 25 37 Parcels 4 Parcels completely planted with trees. 3 parcels partly planted 26 Oversimplified Confusion Matrix Field Observations Automatic Agriculture Non-Agriculture Agriculture 33 Non- Agriculture 4

14 Automatic Analysis Field Observations & Visual interpretation Textured and contrasting vegetation Non-Textured Vegetation (Agriculture) 27 Textured and contrasting vegetation 1288 polygons ±25 Ha < 5% <25 Polygons <2.5 Ha Non-Textured Vegetation (Agriculture) <20 polygons 0.1 Ha?? 509 Ha Textured and contrasting vegetation Non-Textured Vegetation (Agriculture) Automatic Analysis Field Observations & Visual interpretation Textured and contrasting vegetation 1288 Polygons ±25 Ha <20 polygons 0.01 Ha?? Non-Textured Vegetation (Agriculture) <25 Polygons <0.25 Ha 509 Ha Always 95% or larger 28

15 29 Field Observations A B C D E F A B Automatic Analysis C D E F 30 First some field observations of the Landscape Features Landscape Features are difficult to differentiate in an automatic system A dual system might be a solution (AGRI/NON-AGRI) Confusion matrices can be confusing themselves, 3 different approaches will be shown Scenario and driving agents.

16 31 Does a Biophysical property influences the payment? Row of Trees E Group of trees D Single tree F Can be part of a deteriorating or senility process. The categories can be observations inside an ongoing process 32 Senility

17 33 Degradation ; Young plants with active cattle pressure or..? 34 Succession?

18 35 Pressure Agents and Landscape Mmanagement on LF 36

19 37 Trees you don t miss 38 Trees you might miss

20 Meter Succession of Betula 40

21 41 42

22 43 LF reconstruction? 44

23 45 46

24 47 48

25 49 50 Concluding remarks A basic dual classification AGRI / NON-AGRI is possible. NON-AGRI is difficult to diversify. Diversification can be done according to ecological scenario s and pressure on the system (succession, deterioration, senility) A GIS layer has a role in decision support. If the decision is Pay or not-pay, a dual classification would be useful. If biophysical properties of Landscape features are playing a role in the payment, more classification parameters (Features) must become available (DTM/DSM) The bio/physical parameters might be needed in case of management actions like Landscape Feature re-constructions, an expensive measure, which incidentally takes place in the region.

26 51 Acknowledgment to: Ing. G. Tobolka & Ing. J. Bukovsky Central admin. Dept. of registers, ministry of agriculture of the Czech Republic For their Data support and Fieldtrip preparations.

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