Skip to main content
SpringerLink
Log in

Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

LiDAR (Light Detection and Ranging) is a remote sensing technology that uses light in the form of pulses to measure the range between a sensor and the Earth’s surface. Recent increase in availability of airborne LiDAR scanning (ALS) data providing national coverage with high point densities has opened a wide range of possibilities for monitoring landscape elements and their changes at broad geographical extent. We assessed the dynamics of the spatial extent of non-forest woody vegetation (NFW) in a study area of approx. 2500 km2 in southern Jutland, Denmark, based on two acquisitions of ALS data for 2006 and 2014 in combination with other spatial data. Our results show a net-increase (4.8%) in the total area of NFW. Furthermore, this net change comprises of both areas with a decrease and areas with an increase of NFW. An accuracy assessment based on visual interpretation of aerial photos indicates high accuracy (>95%) in the delineation of NFW without changes during the study period. For NFW that changed between 2006 and 2014, accuracies were lower (90 and 82% in removed and new features, respectively), which is probably due to lower point densities of the 2006 ALS data (0.5 pts./m2) compared to the 2014 data (4–5 pts./m2). We conclude that ALS data, if combined with other spatial data, in principle are highly suitable for detailed assessment of changes in landscape features, such as formations of NFW at broad geographical extent. However, in change assessment based on multi-temporal ALS data with different point densities errors occur, particularly when examining small or narrow NFW objects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Aksoy, S., Akcay, H. G., & Wassenaar, T. (2010). Automatic mapping of linear woody vegetation features in agricultural landscapes using very high resolution imagery. IEEE Transactions on Geoscience and Remote Sensing, 48(1), 511–522. doi:10.1109/TGRS.2009.2027702.

    Article  Google Scholar 

  • Amichev, B. Y., Bentham, M. J., Cerkowniak, D., Kort, J., Kulshreshtha, S., Laroque, C. P., et al. (2014). Mapping and quantification of planted tree and shrub shelterbelts in Saskatchewan, Canada. Agroforestry Systems, 89(1), 49–65. doi:10.1007/s10457-014-9741-2.

    Article  Google Scholar 

  • Badreldin, N., & Sanchez-Azofeifa, A. (2015). Estimating forest biomass dynamics by integrating multi-temporal Landsat satellite images with ground and airborne LiDAR data in the Coal Valley Mine, Alberta, Canada. Remote Sensing, 7(3), 2832–2849. doi:10.3390/rs70302832.

    Article  Google Scholar 

  • Baudry, J., Bunce, R. G. H., & Burel, F. (2000). Hedgerows: an international perspective on their origin, function and management. Journal of Environmental Management, 60(1), 7–22. doi:10.1006/jema.2000.0358.

    Article  Google Scholar 

  • Betbeder, J., Nabucet, J., Pottier, E., Baudry, J., Corgne, S., & Hubert-Moy, L. (2014). Detection and characterization of hedgerows using TerraSAR-X imagery. Remote Sensing, 6(5), 3752–3769. doi:10.3390/rs6053752.

    Article  Google Scholar 

  • Betbeder, J., Hubert-Moy, L., Burel, F., Corgne, S., & Baudry, J. (2015). Assessing ecological habitat structure from local to landscape scales using synthetic aperture radar. Ecological Indicators, 52, 545–557. doi:10.1016/j.ecolind.2014.11.009.

    Article  Google Scholar 

  • Black, K., Green, S., Mullooley, G., & Poveda, A. (2014). Carbon sequestration by hedgerows in the Irish landscape. Climate Change Research Programme (CCRP) 2007–2013 Report Series No. 32. Wexford, Ireland.

  • Boehm, H. D. V., Liesenberg, V., & Limin, S. H. (2013). Multi-temporal airborne LiDAR-survey and field measurements of tropical peat swamp forest to monitor changes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(3), 1524–1530. doi:10.1109/JSTARS.2013.2258895.

    Article  Google Scholar 

  • Burel, F., & Baudry, J. (1990). Structural dynamic of a hedgerow network landscape in Brittany France. Landscape Ecology, 4(4), 197–210. doi:10.1007/BF00129828.

    Article  Google Scholar 

  • Calvo Iglesias, M. S., Crecente-Maseda, R., Díaz Varela, R. A., Fra Paleo, U., & Ramil Rego, P. (2007). Changes in hedgerow structures during 1957–2000 in the Northern Mountains of Galicia (NW Iberian Peninsula). In A. Antoine & D. Marguerie (Eds.), Bocages & Sociétés (pp. 155–162). Book Section: Presses Universitaires de Rennes.

    Google Scholar 

  • COWI. (2007). National point cloud for 2006. Copenhagen.

  • Danish Agency for Data Supply and Efficiency. (2017). Elevation model creation code. Bitbucket. https://bitbucket.org/GSTudvikler/gstdhmqc/src/tip/qc/dem_gen.py?at=default&fileviewer=file-view-default

  • Díaz-Varela, R., de la Rosa, R., León, L., Zarco-Tejada, P., de la Rosa, R., León, L., & Zarco-Tejada, P. (2015). High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: application in breeding trials. Remote Sensing, 7(4), 4213–4232. doi:10.3390/rs70404213.

    Article  Google Scholar 

  • Edson, C., & Wing, M. G. (2011). Airborne light detection and ranging (LiDAR) for individual tree stem location, height, and biomass measurements. Remote Sensing, 3(11), 2494–2528.

    Article  Google Scholar 

  • European Commission. (2013a). Green infrastructure (GI)—enhancing Europe’s Natural Capital COM (2013) 249 final, 1–11.

  • European Commission. (2013b). Decision No 529/2013/EU of the European Parliament and of the Council of 21 May 2013 on accounting rules on greenhouse gas emissions and removals resulting from activities relating to land use, land-use change and forestry and on information concerning ac. Official Journal of the European Union, (165), 80–97.

  • Europeo, E. L. P., Consejo, E. L., Uni, D. E. L. A, Oficial, D, Europeo, P., Oficial, D., & Europeo, P. L 347/608 (2013).

  • Food and Agriculture Organization of the United Nations. (n.d.). Land Cover Categories. http://www.fao.org/gtos/tems/landcover.htm

  • Forman, R. T. T., Baudry, J., Management, E., & Sciences-Botany, B. (1984). Hedgerows and hedgerow networks in landscape ecology (Vol. 8). New Brunswick, New Jersey 08903, USA: Rutgers University.

  • Gómez, J. A., Zarco-Tejada, P. J., García-Morillo, J., Gama, J., & Soriano, M. A. (2011). Determining biophysical parameters for olive trees using CASI-airborne and Quickbird-satellite imagery. Agronomy Journal, 103(3), 644–654. doi:10.2134/agronj2010.0449.

    Article  Google Scholar 

  • Guerra-Hernandez, J., Gonzalez-Ferreiro, E., Sarmento, A., Silva, J., Nunes, A., Correia, A. C., et al. (2016). Short communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal. Forest Systems, 25(2), eSC09. doi:10.5424/fs/2016252-08895.

    Article  Google Scholar 

  • Hellesen, T., & Matikainen, L. (2013). An object-based approach for mapping shrub and tree cover on grassland habitats by use of LiDAR and CIR orthoimages. Remote Sensing, 5(2), 558–583. doi:10.3390/rs5020558.

    Article  Google Scholar 

  • Henry, M., Tittonell, P., Manlay, R. J., Bernoux, M., Albrecht, A., & Vanlauwe, B. (2009). Biodiversity, carbon stocks and sequestration potential in aboveground biomass in smallholder farming systems of western Kenya. Agriculture, Ecosystems & Environment, 129(1–3), 238–252. doi:10.1016/j.agee.2008.09.006.

    Article  CAS  Google Scholar 

  • Hernández-clemente, R., Navarro-Cerrillo, R. M., Ramírez, F. J. R., Hornero, A., & Zarco-Tejada, P. J. (2014). A novel methodology to estimate single-tree biophysical parameters from 3D digital imagery compared to aerial laser scanner data. Remote Sensing, 6(11), 11627–11648. doi:10.3390/rs61111627.

    Article  Google Scholar 

  • Hou, W., & Walz, U. (2013). Enhanced analysis of landscape structure: inclusion of transition zones and small-scale landscape elements. Ecological Indicators, 31, 15–24. Journal Article. doi:10.1016/j.ecolind.2012.11.014.

    Article  Google Scholar 

  • Hou, W., & Walz, U. (2014). Extraction of small biotopes and ecotones from multi-temporal RapidEye data and a high-resolution normalized digital surface model. International Journal of Remote Sensing, 35(20), 7245–7262. doi:10.1080/01431161.2014.967890.

    Article  Google Scholar 

  • Hyyppa, J., Kelle, O., Lehikoinen, M., & Inkinen, M. (2001). A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners. IEEE Transactions on Geoscience and Remote Sensing, 39(5), 969–975.

    Article  Google Scholar 

  • Kaartinen, H., Hyyppä, J., Yu, X., Vastaranta, M., Hyyppä, H., Kukko, A., et al. (2012). An international comparison of individual tree detection and extraction using airborne laser scanning. Remote Sensing, 4(4), 950–974. doi:10.3390/rs4040950.

    Article  Google Scholar 

  • Lechner, A. M., Stein, A., Jones, S. D., & Ferwerda, J. G. (2009). Remote sensing of small and linear features: quantifying the effects of patch size and length, grid position and detectability on land cover mapping. Remote Sensing of Environment, 113(10), 2194–2204. doi:10.1016/j.rse.2009.06.002.

    Article  Google Scholar 

  • Ma, H., Song, J., Wang, J., Yang, H. (2012). Comparison of the inversion ability in extrapolating forest canopy height by integration of lidar data and different optical remote sensing products. State Key Laboratory of Remote Sensing Science, Jointly Spo, 3363–3366.

  • McCollin, D., Jackson, J. I., Bunce, R. G. H., Barr, C. J., & Stuart, R. (2000). Hedgerows as habitat for woodland plants. Journal of Environmental Management, 60(1), 77–90. doi:10.1006/jema.2000.0363.

    Article  Google Scholar 

  • Ministry of Environment and Food. (2014). Field parcel map. Copenhagen: Ministry of Environment and Food.

    Google Scholar 

  • Moorthy, I., Miller, J. R., Berni, J. A. J., Zarco-Tejada, P., Hu, B., & Chen, J. (2011). Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology, 151(2), 204–214. doi:10.1016/j.agrformet.2010.10.005.

    Article  Google Scholar 

  • Penman, J., Gytarsky, M., Hiraishi, T., Krug, T., Kruger, D., Pipatti, R., et al. (2003). Good practice guidance for land use, land-use change and forestry. IPCC National Greenhouse Gas Inventorie Programme. http://www.cabdirect.org/abstracts/20083162304.html

  • Pirotti, F. (2010). Assessing a template matching approach for tree height and position extraction from LiDAR-derived canopy height models of Pinus pinaster stands. Forests, 1(4), 194–208. doi:10.3390/f1040194.

    Article  Google Scholar 

  • Riano, D., Chuvieco, E., Condes, S., Gonzalez-Matesanz, J., & Ustin, S. L. (2004). Generation of crown bulk density for Pinus sylvestris L. from LiDAR. Remote Sensing of Environment, 92(3), 345–352.

    Article  Google Scholar 

  • Rosell, J. R., & Sanz, R. (2012). A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and Electronics in Agriculture, 81(0), 124–141. doi:10.1016/j.compag.2011.09.007.

    Article  Google Scholar 

  • Schmucki, R., De Blois, S., Bouchard, A., & Domon, G. (2002). Spatial and temporal dynamics of hedgerows in three agricultural landscapes of southern Quebec, Canada. Environmental Management, 30(5), 651–664. doi:10.1007/s00267-002-2704-9.

    Article  Google Scholar 

  • Sheeren, D., Bastin, N., Ouin, A., Ladet, S., Balent, G., & Lacombe, J. P. (2009). Discriminating small wooded elements in rural landscape from aerial photography: a hybrid pixel/object-based analysis approach. International Journal of Remote Sensing, 30(19), 4979–4990 http://www.informaworld.com/10.1080/01431160903022928.

    Article  Google Scholar 

  • Simonson, W., Ruiz-Benito, P., Valladares, F., & Coomes, D. (2016). Modelling above-ground carbon dynamics using multi-temporal airborne LiDAR: insights from a Mediterranean woodland. Biogeosciences, 13(4), 961–973. doi:10.5194/bg-13-961-2016.

    Article  Google Scholar 

  • Styrelsen for Dataforsyning og Effektivisering. (2006). Summer orthophotos 2006. Copenhagen: Styrelsen for Dataforsyning og Effektivisering.

    Google Scholar 

  • Styrelsen for Dataforsyning og Effektivisering. (2014a). Summer orthophotos 2014. Copenhagen: Styrelsen for Dataforsyning og Effektivisering.

    Google Scholar 

  • Styrelsen for Dataforsyning og Effektivisering. (2014b). National topographic database. Copenhagen: Styrelsen for Dataforsyning og Effektivisering.

    Google Scholar 

  • Styrelsen for Dataforsyning og Effektivisering. (2015). National point cloud for 2014. Copenhagen: Styrelsen for Dataforsyning og Effektivisering.

    Google Scholar 

  • Tesfamichael, S. G., Ahmed, F. B., & van Aardt, J. A. N. (2010a). Investigating the impact of discrete-return LiDAR point density on estimations of mean and dominant plot-level tree height in Eucalyptus grandis plantations. International Journal of Remote Sensing, 31(11), 2925–2940. doi:10.1080/01431160903144086.

    Article  Google Scholar 

  • Tesfamichael, S. G., van Aardt, J. A. N., & Ahmed, F. (2010b). Estimating plot-level tree height and volume of Eucalyptus grandis plantations using small-footprint, discrete return LiDAR data. Progress in Physical Geography, 1–26. doi:10.1177/0309133310365596.

  • The Council of the European Communities. (1992). Council Regulation (EEC) No 2078/92 of 30 June 1992 on agricultural production methods compatible with the requirements of the protection of the environment and the maintenance of the countryside. Official Journal of the European Communities, 85–90.

  • van der Zanden, E. H., Verburg, P. H., & Mücher, C. A. (2013). Modelling the spatial distribution of linear landscape elements in Europe. Ecological Indicators, 27, 125–136. doi:10.1016/j.ecolind.2012.12.002.

    Article  Google Scholar 

  • Wallerman, J., Bohlin, J., & Fransson, J. E. S. (2012). Forest height estimation using semi-individual tree detection in multi-spectral 3D aerial DMC data. International Geoscience and Remote Sensing Symposium (IGARSS), 6372–6375. doi:10.1109/IGARSS.2012.6352717.

  • Welsch, J., Case, B. S., & Bigsby, H. (2014). Trees on farms: investigating and mapping woody re-vegetation potential in an intensely-farmed agricultural landscape. Agriculture, Ecosystems & Environment, 183, 93–102. doi:10.1016/j.agee.2013.10.031.

    Article  Google Scholar 

  • Wulder, M. A., White, J. C., Alvarez, F., Han, T., Rogan, J., & Hawkes, B. (2009). Characterizing boreal forest wildfire with multi-temporal Landsat and LIDAR data. Remote Sensing of Environment, 113(7), 1540–1555. doi:10.1016/j.rse.2009.03.004.

    Article  Google Scholar 

  • Zarco-Tejada, P. J., Diaz-Varela, R., Angileri, V., & Loudjani, P. (2014). Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. European Journal of Agronomy, 55(0), 89–99. doi:10.1016/j.eja.2014.01.004.

    Article  Google Scholar 

Download references

Acknowledgements

This research was carried out partly under the SINKS2 project (Documentation concerning the Kyoto Protocol article 3.4, SINKS in the second commitment period, 2013-2020), which receives funding from the Danish Ministry of Energy, Utilities and Climate.

Author information

Authors and Affiliations

  1. Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark

    Ioannis Angelidis & Gregor Levin

  2. Departamento de Botánica, GI-1809-BIOAPLIC, Universidade de Santiago de Compostela, Escola Politécnica Superior Campus Universitario s/n, E 27002, Lugo, Spain

    Ramón Alberto Díaz-Varela

  3. Space Research Centre, Polish Academy of Sciences, Bartycka 18A, 00-716, Warsaw, Poland

    Radek Malinowski

Authors
  1. Ioannis Angelidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gregor Levin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramón Alberto Díaz-Varela
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Radek Malinowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ioannis Angelidis.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Angelidis, I., Levin, G., Díaz-Varela, R.A. et al. Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR. Environ Monit Assess 189, 437 (2017). https://doi.org/10.1007/s10661-017-6119-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-017-6119-8

Keywords

Search

Navigation