Mapping Secondary Forest Succession on Abandoned Agricultural Land with LiDAR Point Clouds and Terrestrial Photography
Secondary forest succession on abandoned agricultural land has played a significant role in land cover changes in Europe over the past several decades. However, it is difficult to quantify over large areas. In this paper, we present a conceptual framework for mapping forest succession patterns using...
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| Vydáno v: | Remote sensing (Basel, Switzerland) Ročník 7; číslo 7; s. 8300 - 8322 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Basel
MDPI AG
2015
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| ISSN: | 2072-4292, 2072-4292 |
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| Abstract | Secondary forest succession on abandoned agricultural land has played a significant role in land cover changes in Europe over the past several decades. However, it is difficult to quantify over large areas. In this paper, we present a conceptual framework for mapping forest succession patterns using vegetation structure information derived from LiDAR data supported by national topographic vector data. This work was performed in the Szczawnica commune in the Polish Carpathians. Using object-based image analysis segments of no vegetation, and sparse/dense low/medium/high vegetation were distinguished and subsequently compared to the national topographic dataset to delineate agricultural land that is covered by vegetation, which indicates secondary succession on abandoned fields. The results showed that 18.7% of the arable land and 40.4% of grasslands, that is 31.0% of the agricultural land in the Szczawnica commune, may currently be experiencing secondary forest succession. The overall accuracy of the approach was assessed using georeferenced terrestrial photographs and was found to be 95.0%. The results of this study indicate that the proposed methodology can potentially be applied in large-scale mapping of secondary forest succession patterns on abandoned land in mountain areas. |
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| AbstractList | Secondary forest succession on abandoned agricultural land has played a significant role in land cover changes in Europe over the past several decades. However, it is difficult to quantify over large areas. In this paper, we present a conceptual framework for mapping forest succession patterns using vegetation structure information derived from LiDAR data supported by national topographic vector data. This work was performed in the Szczawnica commune in the Polish Carpathians. Using object-based image analysis segments of no vegetation, and sparse/dense low/medium/high vegetation were distinguished and subsequently compared to the national topographic dataset to delineate agricultural land that is covered by vegetation, which indicates secondary succession on abandoned fields. The results showed that 18.7% of the arable land and 40.4% of grasslands, that is 31.0% of the agricultural land in the Szczawnica commune, may currently be experiencing secondary forest succession. The overall accuracy of the approach was assessed using georeferenced terrestrial photographs and was found to be 95.0%. The results of this study indicate that the proposed methodology can potentially be applied in large-scale mapping of secondary forest succession patterns on abandoned land in mountain areas. |
| Author | Kolecka, Natalia Kozak, Jacek Dobosz, Monika Kaim, Dominik Ginzler, Christian Psomas, Achilleas |
| Author_xml | – sequence: 1 givenname: Natalia surname: Kolecka fullname: Kolecka, Natalia – sequence: 2 givenname: Jacek surname: Kozak fullname: Kozak, Jacek – sequence: 3 givenname: Dominik surname: Kaim fullname: Kaim, Dominik – sequence: 4 givenname: Monika surname: Dobosz fullname: Dobosz, Monika – sequence: 5 givenname: Christian surname: Ginzler fullname: Ginzler, Christian – sequence: 6 givenname: Achilleas surname: Psomas fullname: Psomas, Achilleas |
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| SubjectTerms | Abandoned Abandoned land Agricultural land Ecological succession Farmlands forest succession Forests Grasslands Land land cover LiDAR Mapping Mountain regions Mountains multiresolution segmentation Remote sensing terrestrial photography Vegetation |
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