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Tytuł artykułu

Forest succession mapping for post-agricultural areas using Sentinel-2, PlanetScope imageries and LiDAR data

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The research investigates the possibility of applying Sentinel-2, PlanetScope satellite imageries, and LiDAR data for automation of land cover mapping and 3D vegetation characteristics in post-agricultural areas, mainly in the aspect of detection and monitoring of the secondary forest succession. The study was performed for the tested area in the Biskupice district (South of Poland), as an example of an uncontrolled forest succession process occurring on post-agricultural lands. The areas of interest were parcels where agricultural use has been abandoned and forest succession has progressed. This paper indicates the possibility of automating the process of monitoring wooded and shrubby areas developing in post-agricultural areas with the help of modern geodata and geoinformation methods. It was verified whether the processing of Sentinel-2, PlanetScope imageries allows for reliable land cover classification as an identification forest succession area. The airborne laser scanning (ALS) data were used for deriving detailed information about the forest succession process. Using the ALS point clouds vegetation parameters i.e., height and canopy cover were determined and presented as raster maps, histograms, or profiles. In the presented study Sentinel-2, PlanetScope imageries, and ALS data processing showed a significant differentiation of the spatial structure of vegetation. These differences are visible in the surface size (2D) and the vertical vegetation structure (3D).
Rocznik
Strony
art. no. e30, 2022
Opis fizyczny
Bibliogr. 53 poz., rys., tab.
Twórcy
  • University of Agriculture in Krakow, Krakow, Poland
Bibliografia
  • 1. Alberti, G., Boscutti, F., Pirotti, F. et al. (2013). A LiDAR-based approach for a multi-purpose characterization of Alpine forests: an Italian case study. iForest, 6(3), 156–168. DOI: 10.3832/ifor0876-006.
  • 2. Andersen, H.E., Reutebuch, S.E., and McGaughey, R.J., (2006). A rigorous assessment of tree height measurements was obtained using airborne lidar and conventional field methods. Can. J. Remote Sens., 32, 355–366.
  • 3. Bergen, K.M., and Dronova, I. (2007). Observing succession on aspen-dominated landscapes using a remote sensing-ecosystem approach. Landsc. Ecol., 22, 1395–1410. DOI: 10.1007/s10980-007-9119-1.
  • 4. Bochenek, J. (2019) Analysis of ALS point clouds to determine the spatial structure of vegetation in the areas of secondary forest succession in the Wieliczka district. Master’s Thesis, the University of Agriculture in Krakow, Poland.
  • 5. Bowen, M.E., Mcalpine, C.A., House, A.P.N. et al. (2007). Regrowth forests on abandoned agricultural land: A review of their habitat values for recovering forest fauna. Biol. Conserv., 140, 3-4, 273–296. DOI: 10.1016/j.biocon.2007.08.012.
  • 6. ESA (2022). Sentinel-2. Retrieved May, 2022, from https://sentinel.esa.int.
  • 7. Forest Resources Assessment (2004). Working Paper 83. Global Forest Resources Assessment Update 2005, Terms and Definitions.
  • 8. Forest Resources Assessment (2007). Working Paper 135. Specification of National Reporting Tables for FRA 2010.
  • 9. Forest Resources Assessment (2012). Working Paper 180. Forest Resources Assessment Update 2015, Terms and Definitions.
  • 10. Falkowski, M.J., Evans, J.S., Martinuzzi, S. et al. (2009). Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA. Remote Sens. Environ., 113(5), 946–956. DOI: 10.1016/ j.rse.2009.01.003.
  • 11. Forkuor, G., Dimobe, K., Serme, I. et al. (2018). Landsat-8 vs. Sentinel-2: Examining the added value of Sentinel-2’s red-edge bands to land-use and land-cover mapping in Burkina Faso. GIScience Remote Sens., 55, 331–354. DOI: 10.1080/15481603.2017.1370169.
  • 12. FUSION (2022). Retrieved May, 2022, from https://www.fs.usda.gov/pnw/tools/update-fusionldv-lidar-processing-and-visualization-software-version-360.
  • 13. Gniadek, J., Pijanowski, J., and Smigielski, M. (2017). Impact of the forest succession on efficiency of the arable land production. J. Water Land Dev., 34(VII–IX), 131–138. DOI: 10.1515/jwld-2017-0046.
  • 14. Hoscilo, A., Mironczuk, A., and Lewandowska, A. (2016). Determination of the actual forest area in Poland based on the available spatial datasets. Sylwan, 160(8), 627–634.
  • 15. Hyyppä, J., Hyyppä, H., Litkey P. et al. (2004). Algorithms and methods of airborne laser-scanning for forest measurements. In Thies M., Koch B., Spiecker H. and Weinacker H. (Eds.), Laser-Scanners for Forest and Landscape Assessment: Proceedings of the ISPRS Working Group VIII/2. International Archives of Photogrammetry, Remote Sensing, and the Spatial Information Sciences, XXXVI–8/W2. Germany: Freiburg.
  • 16. European Commission (2019). IoT and digital technologies for monitoring of the new CAP. AIOTI WG06 – Smart Farming and Food Security.
  • 17. Jablonski, M. (2015). National and international definition of forest and its importance for the forest area in Poland. Sylwan, 159(6), 469–482.
  • 18. Jablonski, M., Korhonen, K.T., Budniak, P. et al. (2017). Comparing land use registry and sample-based inventory to estimate forest area in Podlaskie, Poland. iForest, 10, 315–321. DOI: 10.3832/ifor2078-009.
  • 19. Jablonski, M., Mionskowski, M., and Budniak, P. (2018). Forest area in Poland based on national forest inventory. Sylwan, 162 (5), 365–372.
  • 20. Journal of Laws (1991). Act of Forest, Poland, No. 101, item. 444.
  • 21. Journal of Laws (2021). Act of land and building register. Regulation of the Minister of Development, Labor and Technology, No. 1390.
  • 22. Kolecka, N., Kozak, J., Kaim, D. et al. (2015). Mapping secondary forest succession on abandoned agricultural land with LiDAR point clouds and terrestrial photography. Remote Sens., 7(7), 8300–8322. DOI: 10.3390/rs70708300.
  • 23. Kolecka, N., Kozak, J., Kaim, D. et al. (2016). Mapping secondary forest succession on abandoned agricultural land in the Polish Carpathians. In Revelling in Reference: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B8, XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic.
  • 24. Kolecka, N. (2018). Height of Successional Vegetation Indicates Moment of Agricultural Land Abandonment. Remote Sens., 10(10), 1568. DOI: 10.3390/rs10101568.
  • 25. Koska, B., Jirkab, V., Urbana, R. et al. (2017). Suitability, characteristics, and comparison of an airship UAV with lidar for middle size area mapping. Int. J. Remote Sensing, 38, 2973–2990. DOI: 10.1080/01431161.2017.1285086.
  • 26. Lasanta, T., Arnáez, J., Pascual, N. et al. (2017). Space-time process and drivers of land abandonment in Europe. Catena, 149, 810–823. DOI: 10.1016/j.catena.2016.02.024.
  • 27. Maier, B., Tiede, D., and Dorren, L. (2008). Characterising mountain forest structure using landscape metrics on LiDAR-based canopy surface models. Lect. Notes Geoinf. Cartogr., 625–643. DOI: 10.1007/978-3-540-77058-9_34.
  • 28. Maltamo, M., Mustonen, K., Hyyppa, J. et al. (2004). The accuracy of estimating individual tree variables with airborne laser scanning in a boreal nature reserve. Can. J. For. Res., 34(9), 1791–1801. DOI: 10.1139/x04-055.
  • 29. Marangoz, A.M., Sekertekin, A., and Akçin, H. (2017). Analysis of land use land cover classification results derived from Sentinel-2 image. In Proceedings of the 17th International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM2017, Vienna, Austria, 27-29 November 2017, 25–32.
  • 30. McGaughey, R.J., Carson, W., Reutebuch, S. et al. (2004). Direct measurement of individual tree characteristics from lidar data. Proceedings of the Annual ASPRS Conference. Denver. In Proceedings of/Ire Annual ASPRS Conference, Denver. May 23–28.2004. American Society of Photogrammetry and Remote Sensing, Bethesda, MD.
  • 31. McGaughey, R.J. (2012). Fusion/ldv: Software for lidar data analysis and visualization. Software manual. USDA Forest Service. Pacific Northwest Research Station.
  • 32. Moudrý, V., Gdulová, K., Fogl, M. et al. (2019). Comparison of leaf-off and leaf-on combined UAV imagery and airborne LiDAR for assessment of a post-mining site terrain and vegetation structure: Prospects for monitoring hazards and restoration success. Appl. Geogr., 104, 32–41. DOI: 10.1016/j.apgeog.2019.02.002.
  • 33. Naesset, E. (2002). Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sens. Environ., 80, 80–99. DOI: 10.1016/S0034-4257(01)00290-5.
  • 34. Naesset, E., and Økland, T. (2002). Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve. Remote Sens. Environ., 79, 105–115. DOI: 10.1016/S0034-4257(01)00243-7.
  • 35. National Program for Increasing Forest Cover (2003). Document adopted for implementation by a resolution of the Council of Ministers in June 1995, updated in 2003. Ministry of the Environment. Warsaw.
  • 36. Ostrowski, W., Gorski, K., Pilarska, M. et al. (2017). Comparison of the laser scanning solutions for the unmanned aerial vehicles. Arch. Photogramm. Cartogr. Remote Sens., 29, 101–123. DOI: 10.14681/afkit.2017.008.
  • 37. Planet (2022). Retrieved May, 2022, from https://www.planet.com/products/planet-imagery/.
  • 38. Prishchepov, A.V., Volker, C.R., Dubinin, M. et al. (2012). The Effect of Landsat ETM/ETM ¸ Image Acquisition Dates on the Detection of Agricultural Land Abandonment in Eastern Europe. Remote Sens. Environ., 126, 195–209. DOI: 10.1016/j.rse.2012.08.017.
  • 39. Putz, F.E., and Redford, K. (2009). The Importance of Defining’ Forest’: Tropical Forest Degradation, Deforestation. Long-term Phase Shifts, and Further Transitions. Biotropica, 42(1), 10–20. DOI: 10.1111/j.1744-7429.2009.00567.x.
  • 40. Ruskule, A., Nikodemus, O., Kasparinska, Z. et al. (2012). Patterns of afforestation on abandoned agriculture land in Latvia. Agrofor. Syst., 85, 2, 215–231. DOI: 10.1007/s10457-012-9495-7.
  • 41. Sadkowski P. (2021) Identification areas of secondary forest succession in the areas of Milicz and Biskupice commune with the use of PlanetScope satellite imagery. Master’s Thesis, the University of Agriculture in Krakow, Poland.
  • 42. Sasaki, N., and Putz, F.E. (2009). Critical need for new definitions of “forest” and “forest degradation” in global climate change agreements. J. Soc. Conserv. Biol., 2(5), 226-232. DOI: 10.1111/j.1755-263X.2009.00067.x.
  • 43. Sekertekin, A., Marangoz, A.M., and Akcin, H. (2017). Pixel-based classification analysis of land use land cover using Sentinel-2 and Landsat-8 data. Int. Arch. Photogramm. Remote Sens., 42, 91–93. DOI: 10.5194/isprs-archives-XLII-4-W6-91-2017.
  • 44. Singh, K., Vogler, J., Shoemaker, D. et al. (2012). LiDAR-Landsat data fusion for large area assessment of urban land cover: Balancing spatial resolution, data volume, and mapping accuracy. ISPRS J. Photogramm. Remote Sens., 74, 110–121. DOI: 10.1016/j.isprsjprs.2012.09.009.
  • 45. Smigielski, M., Pijanowski J., and Gniadek, J. (2017). Forest succession and afforestation of agricultural land as a current challenge agricultural works. Acta Sci. Pol. Formatio Circumiectus, 16 (4), 51–63. DOI: 10.15576/ASP.FC/2017.16.4.51.
  • 46. Susyan, E.A, Wirth, S., Ananyeva, N.D. et al. (2011). Forest succession on abandoned arable soils in European Russia – Impacts on microbial biomass, fungal-bacterial ratio, and basal CO2 respiration activity. Eur. J. Soil Biol., 47, 3, 169–174. DOI: 10.1016/j.ejsobi.2011.04.002.
  • 47. Szostak, M., Wezyk, P., and Tompalski, P. (2014). Aerial orthophoto and airborne laser scanning as monitoring tools for land cover dynamics: A case study from the Milicz Forest District (Poland). Pure Appl. Geophys., 171, 857–866. DOI: 10.1007/s00024-013-0668-8.
  • 48. Szostak, M., Hawrylo, P., and Piela, D. (2019a). Using of Sentinel-2 images for automation of the forest succession detection. Eur. J. Remote Sens., 51, 142–149. DOI: 10.1080/22797254.2017.1412272.
  • 49. Szostak, M., Knapik, K., Likus-Cieslik, J. et al. (2019b). Fusing Sentinel-2 imagery and ALS Point Clouds for defining the LULC changes ongoing on reclaimed areas by afforestation. Sustainability, 11, 1251. DOI: 10.3390/su11051251.
  • 50. Szostak, M. (2020). Automated land cover change detection and forest succession monitoring using LiDAR Point Clouds and GIS analyses. Geosci., 10, 321. DOI: 10.3390/geosciences10080321.
  • 51. Szostak, M., Pietrzykowski, M., and Likus-Cieslik, J. (2020). Reclaimed area land cover mapping using Sentinel-2 Imagery and LiDAR Point Clouds. Remote Sens., 12, 261. DOI: 10.3390/rs12020261.
  • 52. Szwagrzyk. (2004). Forest succession on abandoned farmland; current estimates, forecasts and uncertainties. Sylwan, 4, 53–59.
  • 53. Wezyk, P., Szostak, M., and Tompalski, P. (2009). Comparison of the accuracy of the “PHOTO” check method with automatic analysis based on ALS data for direct control of subsidy payments. Arch. Photogramm. Remote Sens., 20, 445–456.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-85cce661-917f-4741-9a82-2a3aaa1ffe80
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