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Research Article

Evaluation of the influence of disturbances on forest vegetation using Landsat time series; a case study of the Low Tatras National Park

, , & ORCID Icon
Pages 40-66 | Received 03 Mar 2019, Accepted 07 Jan 2020, Published online: 02 Mar 2020

References

  • Albrechtova, J. , & Rock Barrett, N. (2003). Dalkovy pruzkum krusnohorskych lesu. Vesmir, 82(322) . Retrieved from https://vesmir.cz/cz/casopis/archiv-casopisu/2003/cislo-6/dalkovy-pruzkum-krusnohorskych-lesu.html
  • Bao, N. , Lechner, A.M. , Fletcher, A. , Mulligan, D. , Mellor, A. , & Bai, Z. (2012). Comparison of relative radiometric normalization methods using pseudo-invariant features for change detection studies in rural and urban landscapes. Journal of Applied Remote Sensing, 6. doi:10.1117/1.JRS.6.063578
  • Baumann, P.R. (2011, November 14–17). Landsat time series application: The Columbia Glacier, Canada – 1985 to 2010. In Pecora 18-forty years of earth observation … understanding a changing world . Herndon, Virginia. Retrieved from http://www.asprs.org/pecora18/proceedings/Baumann.pdf
  • Birth, G.S. , & McVey, G.R. (1968). Measuring the color of growing turf with a reflectance spectrophotometer. Agronomy Journal , 60, 640–643. doi:10.2134/agronj1968.00021962006000060016x
  • Bucha, T. (2014). Satelity v sluzbach lesa (pp. 202). Zvolen: Narodne lesnicke centrum. ISBN 978-80-89607-25-9.
  • Bucha, T. , & Koreň, M. (2017). Phenology of the beech forests in the Western Carpathians from MODIS for 2000–2015. iForest - Biogeosciences and Forestry , 10. doi:10.3832/IFOR2062-010
  • Butsic, V. , Munteanu, C. , Griffiths, P. , Knorn, J. , Radeloff, V.C. , Lieskovsky, J. , … Kuemmerle, T. (2017). The effect of protected areas on forest disturbance in the Carpathian Mountains 1985–2010. Conservation Biology , 31(3), 570–580. doi:10.1111/cobi.12835
  • Campbell, P.K.E. , Rock, B.N. , Martin, M.E. , Neefus, C.D. , Irons, J.R. , Middleton, E.M. , & Albrechtova, J. (2004). Detection of initial damage in Norway spruce canopies using hyperspectral airborne data. International Journal of Remote Sensing , 25(24), 5557–5584. doi:10.1080/01431160410001726058
  • Canty, M.J. , & Nielsen, A.A. (2008). Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation. Remote Sensing of Environment , 112, 1025–1036. doi:10.1016/j.rse.2007.07.013
  • Chen, X. , Vierling, L. , & Deering, D. (2005). A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment , 98(1), 63–79. doi:10.1016/j.rse.2005.05.021
  • Claverie, M. , Ju, J. , Masek, J.G. , Dungan, J.L. , Vermote, E.F. , Roger, J.C. , … Justice, C. (2018). The Harmonized Landsat and Sentinel-2 surface reflectance data set. Remote Sensing of Environment , 219, 145–161. doi:10.1016/j.rse.2018.09.002
  • Cohen, W.B. , Yang, Z. , Healey, S.P. , Kennedy, R.E. , & Gorelick, N. (2018). A LandTrendr multispectral ensemble for forest disturbance detection. Remote Sensing of Environment , 205(July 2017), 131–140. doi:10.1016/j.rse.2017.11.015
  • Cohen, W.B. , Yang, Z. , & Kennedy, R. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync - Tools for calibration and validation. Remote Sensing of Environment , 114(12), 2911–2924. doi:10.1016/j.rse.2010.07.010
  • Entcheva, P. , Rock, B.N. , Martin, M. , Albrechtova, J. , Solcova, B. , Tierney, M. , & Irons, J. (1999, June 21–2). Remote sensing assessment of forest stress in the Western Bohemian Mountains of Central Europe – applications of ground and airborne spectrometry (GER2600 and ASAS). In Fourth International Airborne Remote Sensing Conference and Exhibition/21 Canadian Symposium on Remote Sensing, Section H , Forestry; Ottawa, Canada, 128-143. doi:10.4315/0362-028x-62.2.128
  • Forkel, M. , Carvalhais, N. , Verbesselt, J. , Mahecha, M.D. , Neigh, C. , & Reichstein, M. (2013). Trend change detection in NDVI time series: Effects of inter-annual variability and methodology. Remote Sensing , 5(5), 2113–2144. doi:10.3390/rs5052113
  • Gloncak, P. (2009). Dynamika vegetacie prirodnych horskych smrecin (Dissertation thesis). Technicka univerzita vo Zvolene: depon in katedra fytologie.
  • Griffiths, P. , Kuemmerle, T. , Baumann, M. , Radeloff, V.C. , Abrudan, I.V. , Lieskovsky, J. , … Hostert, P. (2014). Forest disturbances, forest recovery, and changes in forest types across the Carpathian ecoregion from 1985 to 2010 based on landsat image composites. Remote Sensing of Environment , 151, 72–88. doi:10.1016/j.rse.2013.04.022
  • Griffiths, P. , Kuemmerle, T. , Kennedy, R.E. , Abrudan, I.V. , Knorn, J. , & Hostert, P. (2012). Using annual time-series of Landsat images to assess the effects of forest restitution in post-socialist Romania. Remote Sensing of Environment , 118, 199–214. doi:10.1016/j.rse.2011.11.006
  • Hais, M. , Jonasova, M. , Langhammer, J. , & Kucera, T. (2009a). Comparison of two types of forest disturbance using multitemporal Landsat TM/ETM+ imagery and field vegetation data. Remote Sensing of Environment , 113(4), 835–845. doi:10.1016/j.rse.2008.12.012
  • Hais, M. , & Kucera, T. (2009b). The influence of topography on the forest surface temperature retrieved from Landsat TM, ETM + and ASTER thermal channels. ISPRS Journal of Photogrammetry and Remote Sensing , 64(6), 585–591. doi:10.1016/j.isprsjprs.2009.04.003
  • Hais, M. , Wild, J. , Berec, L. , Bruna, J. , Kennedy, R. , Braaten, J. , & Broz, Z. (2016). Landsat imagery spectral trajectories-important variables for spatially predicting the risks of bark beetle disturbance. Remote Sensing , 8(8), 687. doi:10.3390/rs8080687
  • Hajek, F. , & Svoboda, M. (2007). Vyhodnoceni odumirani horskeho smrkoveho lesa na Trojmezne (NP Sumava) metodou automatizovane klasifikace leteckych snimku Assessment of bark beetle damage in the Trojmezna old-growth. Silva Gabreta , 13(1), 69–81.
  • Hansen, M.C. , Stehman, S.V. , & Potapov, P.V. (2010). Quantification of global gross forest cover loss. Proceedings of the National Academy of Sciences of the United States of America , 107(19), 8650–8655. doi:10.1073/pnas.0912668107
  • Havasova, M. , Bucha, T. , Ferencik, J. , & Jakus, R. (2015). Applicability of a vegetation indices-based method to map bark beetle outbreaks in the High Tatra Mountains. Annals of Forest Research , 58(2), 295–310. doi:10.15287/afr.2015.388
  • Hlasny, T. , Barka, I. , Sitkova, Z. , Bucha, T. , Konopka, M. , & Lukac, M. (2015). MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests. Annals of Forest Science , 72(1), 109–125. doi:10.1007/s13595-014-0404-2
  • Hlasny, T. , & Sitkova, Z. (2010). Spruce forest decline in the Beskydy . Zvolen: National Forest Centre – Forest Research Institute.
  • Jakobsen, H.H. , Carstensen, J. , Harrison, P.J. , & Zingone, A. (2015). Estimating time series phytoplankton carbon biomass: Inter-lab comparison of species identification and comparison of volume-to-carbon scaling ratios. Estuarine, Coastal and Shelf Science , 162, 143–150. doi:10.1016/j.ecss.2015.05.006
  • Jakus, R. , & Stolina, M. (1997). Starostlivost o ekosystemy. In Narodne parky, Sprava narodnych parkov SR, Tatranska Lomnica, 4/1997, 20-23. ISSN 1335-23OX
  • Jensen, J.R. (2007). Remote sensing of the environment: An earth resource perspective (2nd ed.). Upper Saddle River: Pearson Prentice Hall.
  • Jin, S. , & Sader, S.A. (2005). Comparison of time series tasseled cap wetness and the normalized difference moisture index in detecting forest disturbances. Remote Sensing of Environment , 94(3), 364–372. doi:10.1016/j.rse.2004.10.012
  • Kennedy, R.E. , Yang, Z. , & Cohen, W.B. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr - Temporal segmentation algorithms. Remote Sensing of Environment , 114, 2897–2910. doi:10.1016/j.rse.2010.07.008
  • Kern, A. , Marjanovic, H. , Dobor, L. , Anic, M. , Hlasny, T. , & Barcza, Z. (2017). Identification of years with extreme vegetation state in Central Europe based on remote sensing and meteorological data. South-East European Forestry , 8(1), 1–20. doi:10.15177/seefor.17-05
  • Kozak, J. (2010). Forest cover changes and their drivers in the polish carpathian mountains since 1800 BT - reforesting landscapes: linking pattern and process . In H. Nagendra & J. Southworth (Eds.), (pp. 253–273). Dordrecht: Springer Netherlands. doi:10.1007/978-1-4020-9656-3_11
  • Kozak, J. , Estreguil, C. , & Troll, M. (2007). Forest cover changes in the northern Carpathians in the 20th century: A slow transition. Journal of Land Use Science , 2(2), 127–146. doi:10.1080/17474230701218244
  • Kuemmerle, T. , Hostert, P. , Radeloff, V. , Perzanowski, K. , & Kruhlov, I. (2007). Post-socialist forest disturbance in the Carpathian border region of Poland, Slovakia, and Ukraine. Ecological Applications: a Publication of the Ecological Society of America , 17, 1279–1295. doi:10.1890/06-1661.1
  • Kunca, A. , Galko, J. , & Zubrik, M. (2014). Vyznamne kalamity v lesoch Slovenska za poslednych 50 rokov. In A. Kunca (Ed.), Aktualne problemy v ochrane lesa 2014, Zbornik referatov z 23. medzinarodnej konferencie konanej 23.-24.4.2014 v Kongresovom centre Kupelov Novy Smokovec, a.s (pp. 25–31). Zvolen: Narodne lesnicke centrum.
  • Kunca, A. , & Zubrik, M. (2012). Problemy ochrany lesa na Slovensku . Zvolen: Narodne lesnicke centrum - Lesnicky vyskumny ustav.
  • Kupkova, L. , Cervena, L. , Sucha, R. , Jakesova, L. , Zagajewski, B. , Brezina, S. , & Albrechtova, J. (2017). Classification of tundra vegetation in the Krkonose Mts. National park using APEX, AISA dual and sentinel-2A data. European Journal of Remote Sensing , 50(1), 29–46. doi:10.1080/22797254.2017.1274573
  • Kupkova, L. , & Potuckova, M. (2018). Forest cover and disturbance changes, and their driving forces: A case study in the Ore Mts., Czechia, heavily affected by anthropogenic acidic pollution in the second half of the 20th century. Environmental Research Letters , 13, 095008. doi:10.1088/1748-9326/aadd2c
  • Lastovicka, J. , Hladky, R. , Staych, P. , & Holman, L. (2017). Evaluation of forest disturbances in the Low Tatras National Park using time series of satellite images. In 17th International Multidisciplinary Scientific GeoConference SGEM 2017 (pp. 80-100), Albena, Bulgaria.
  • Mei, A. , Bassani, C. , Fontinovo, G. , Salvatori, R. , & Allegrini, A. (2016). The use of suitable pseudo-invariant targets for MIVIS data calibration by the empirical line method. ISPRS Journal of Photogrammetry and Remote Sensing , 114, 102–114. doi:10.1016/j.isprsjprs.2016.01.016
  • Musilova, R. (2012). Vyuziti dat DPZ pro hodnoceni aktualniho stavu a vyvoje smrkovych porostu v Krkonosich (Master thesis). Faculty of Science, Charles university. Retrieved from https://is.cuni.cz/webapps/zzp/detail/119490
  • Neigh, C. , Bolton, D. , Diabate, M. , Williams, J. , & Carvalhais, N. (2014). An automated approach to map the history of forest disturbance from insect mortality and harvest with Landsat time-series data. Remote Sensing , 6, 2782–2808. doi:10.3390/rs6042782
  • Polak, P. , & Saxa, A. (2005). Priaznivy stav biotopov a druhov europskeho vyznamu . Banska Bystrica: Statna ochrana prirody SR.
  • Potapov, P.V. , Turubanova, S.A. , Tyukavina, A. , Krylov, A.M. , McCarty, J.L. , Radeloff, V.C. , & Hansen, M.C. (2015). Eastern Europe’s forest cover dynamics from 1985 to 2012 quantified from the full Landsat archive. Remote Sensing of Environment , 159, 28–43. doi:10.1016/j.rse.2014.11.027
  • Rahman, M.M. , Hay, G.J. , Couloigner, I. , Hemachandran, B. , & Bailin, J. (2015). A comparison of four relative radiometric normalization (RRN) techniques for mosaicing H-res multi-temporal thermal infrared (TIR) flight-lines of a complex urban scene. ISPRS Journal of Photogrammetry and Remote Sensing , 106, 82–94. doi:10.1016/j.isprsjprs.2015.05.002
  • Rouse, J.W. , Hass, R.H. , Schell, J.A. , & Deering, D.W. (1973). Monitoring vegetation systems in the great plains with ERTS. In Third ERTS Symposium, NASA (Vol. 1, pp. 309–317). Retrieved from https://doi.org/citeulike-article-id:12009708
  • Roy, D.P. , Wulder, M.A. , Loveland, T.R. , Woodcock, C.E. , Allen, R.G. , Anderson, M.C. , … Zhu, Z. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment , 145, 154–172. doi:10.1016/j.rse.2014.02.001
  • Roy, D.P. , Zhang, H.K. , Ju, J. , Gomez-Dans, J.L. , Lewis, P.E. , Schaaf, C.B. , … Kovalskyy, V. (2016). A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance. Remote Sensing of Environment , 176, 255–271. doi:10.1016/j.rse.2016.01.023
  • Schroeder, T.A. , Cohen, W.B. , Song, C. , Canty, M.J. , & Yang, Z. (2006). Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon. Remote Sensing of Environment , 103(1), 16–26. doi:10.1016/j.rse.2006.03.008
  • Sitkova, Z. , & Pavlenda, P. (eds). (2017). Dlhodoby ekologicky vyskum a monitoring lesov: sucasne poznatky a vyzvy do buducnosti . Zvolen: Narodne lesnicke centrum – Lesnicky vyskumny ustav Zvolen.
  • S-NAPANT . (2007). Narodny park Nizke Tatry - prirodne hodnoty, historia, sucasny stav ochrany uzemia . Banska Bystrica: Sprava NP Nizke Tatry.
  • S-NAPANT Report . (2004). Predbezna sprava o dosledkoch veternej smrste z 19. 11.2004 na chranene uzemia a chranene druhy v uzemnej posobnosti Spravy Narodneho parku Nizke Tatry a moznosti eliminacie jej dosledkov . Banska Bystrica: Sprava NP Nizke Tatry.
  • S-NAPANT Report . (2008). Kratke zhodnotenie sucasneho stavu populacie podkorneho hmyzu na uzemi Narodneho parku Nize Tatry a jeho ochranneho pasma . Banska Bystrica: Sprava NP Nizke Tatry, p. 11.
  • Song, C. , Woodcock, C.E. , Seto, K.C. , Lenney, M.P. , & Macomber, S.A. (2001). Classification and change detection using Landsat TM data: When and how to correct atmospheric effects? Remote Sensing of Environment , 75(2), 230–244. doi:10.1016/S0034-4257(00)00169-3
  • Sovdat, B. , Kadunc, M. , Batic, M. , & Milcinski, G. (2019). Natural color representation of Sentinel-2 data. Remote Sensing of Environment , 225(September2017), 392–402. doi:10.1016/j.rse.2019.01.036
  • Syariz, M.A. , Lin, B.Y. , Denaro, L.G. , Jaelani, L.M. , Van Nguyen, M. , & Lin, C.H. (2019). Spectral-consistent relative radiometric normalization for multitemporal Landsat 8 imagery. ISPRS Journal of Photogrammetry and Remote Sensing , 147, 56–64. doi:10.1016/j.isprsjprs.2018.11.007
  • Vladovic, J. (2003). Oblastne vychodiska a principy hodnotenia drevinoveho zlozenia a ekologickej stability lesov Slovenska, Lesnicke studie 57/2003, vydavatelstvo Priroda s.r.o . Zvolen: Bratislava (pre Lesnicky vyskumny ustav. ISSBN 80- 07-01285-0.
  • Vladovic, J. (2011). Struktura a diverzita lesnych ekosystemov na Slovensku , 252.
  • Vogeler, J.C. , Braaten, J.D. , Slesak, R.A. , & Falkowski, M.J. (2018). Extracting the full value of the Landsat archive: Inter-sensor harmonization for the mapping of Minnesota forest canopy cover (1973–2015). Remote Sensing of Environment , 209, 363–374. doi:10.1016/j.rse.2018.02.046
  • Vogelmann, J.E. , Xian, G. , Homer, C. , & Tolk, B. (2012). Monitoring gradual ecosystem change using Landsat time series analyses: Case studies in selected forest and rangeland ecosystems. Remote Sensing of Environment , 122, 92–105. doi:10.1016/j.rse.2011.06.027
  • Vuolo, F. , Mattiuzzi, M. , & Atzberger, C. (2015). Comparison of the Landsat Surface Reflectance Climate Data Record (CDR) and manually atmospherically corrected data in a semi-arid European study area. International Journal of Applied Earth Observation and Geoinformation , 42, 1–10. doi:10.1016/j.jag.2015.05.003
  • Wang, J. , Sammis, T.W. , Gutschick, V.P. , Gebremichael, M. , Dennis, S.O. , & Harrison, R.E. (2010). Review of satellite remote sensing use in forest health studies. The Open Geography Journal , 3(1), 28–42. doi:10.2174/1874923201003010028
  • Wulder, M.A. , Masek, J.G. , Cohen, W.B. , Loveland, T.R. , & Woodcock, C.E. (2012). Opening the archive: How free data has enabled the science and monitoring promise of Landsat. Remote Sensing of Environment , 122, 2–10. doi:10.1016/j.rse.2012.01.010
  • Wulder, M.A. , White, J.C. , Loveland, T.R. , Woodcock, C.E. , Belward, A.S. , Cohen, W.B. , … Roy, D.P. (2016). The global Landsat archive: Status, consolidation, and direction. Remote Sensing of Environment , 185, 271–283. doi:10.1016/j.rse.2015.11.032
  • Xie, Z. , Phinn, S.R. , Game, E.T. , Pannell, D.J. , Hobbs, R.J. , Briggs, P.R. , & McDonald-Madden, E. (2019). Using Landsat observations (1988–2017) and google earth engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation. Remote Sensing of Environment , 232(July), 111317. doi:10.1016/j.rse.2019.111317
  • Yang, X. , & Lo, C.P. (2000). Relative radiometric normalization performance for change detection from multi-date satellite images. Photogrammetric Engineering and Remote Sensing , 66(8), 967–980. doi:10.1016/j.fertnstert.2005.08.009
  • Yang, Y. , Erskine, P.D. , Lechner, A.M. , Mulligan, D. , Zhang, S. , & Wang, Z. (2018). Detecting the dynamics of vegetation disturbance and recovery in surface mining area via Landsat imagery and LandTrendr algorithm. Journal of Cleaner Production , 178, 353–362. doi:10.1016/j.jclepro.2018.01.050
  • Zemek, F. , Cudlin, P. , Bohac, J. , Moravec, I. , & Herman, M. (2003). Semi-natural forested landscape under a bark beetle outbreak: A case study of the Bohemian Forest (Czech Republic). Landscape Research , 28(3), 279–292. doi:10.1080/01426390306522
  • Zhu, Z. , Wang, S. , & Woodcock, C.E. (2015). Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images. Remote Sensing of Environment , 159, 269–277. doi:10.1016/j.rse.2014.12.014
  • Zhu, Z. , & Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment , 118, 83–94. doi:10.1016/j.rse.2011.10.028
  • Zhu, Z. , & Woodcock, C.E. (2014). Continuous change detection and classification of land cover using all available Landsat data. Remote Sensing of Environment , 144, 152–171. doi:10.1016/j.rse.2014.01.011