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Rola klasyfikacji nadzorowanej wyzokorozdzielczych obrazów satelitarnych QuickBird w nowej koncepcji wyznaczania przemysłowych stref uszkodzeń drzewostanów na przykładzie Miasteczka Śląskiego

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EN
The role of supervised classification of the vhr quickbird satellite image in a new concept of forest industrial damage zones delineation based on the example of Miasteczko Śląskie.
Języki publikacji
PL
Abstrakty
EN
During the last decades the influence of industry left its trace on Polish forests worsening significantly their health condition, expressed e.g. by the defoliation degree. Direct negative influence of industrial contamination was in certain forests so high that they have been considered the zones of ecological disaster. The new Instruction of Forest Management issued in 2003 does not describe precisely the method of zone delineation . leaving a serious gap . due to which the zones determined 10 or 20 years ago are taken over by new forest management. The purpose of this paper is to point out the usefulness of application of the VHR QuickBird satellite images (04.09.2004; region of 89 km2), which is the socalled supervised classification in assisting the new method of the forest damage zones delineation. Forests of the .wierklaniec Forest Inspectorate (RDLP Katowice) surrounding the zinc and lead metallurgical plant in Miasteczko Śląskie was the region of interest. Distinct damages of stands, including even the so-called industrial turfs caused by heavy metals dust emission and toxic concentrations of gases are still visible in this region. The calibration of image was based on vector data from the Digital Forest Map and GCP (RMSXY <1.50 m) control measurements. The supervised classification (Maximum Likelihood) was performed by means of DGPS measurements in ROI. The results of classification of the QuickBird image were compared with the determined Test Areas and information in the database of the LAS/SILP system prepared during the last forest management review (2003). The obtained classification likelihood for the .FOREST. class was 92.6%, Chile for the .NON FOREST. class: 95.3%. The likelihood of the classification for individual tree species was from 82% for Scots pine (Pinus sylvestris L.) to 38% for Black alder (Alnus glutinosa L.). For industrial damage zones (II, III and IV) determined more than 10 years ago, the supervised classification allowed to establish the approximate parameter of the crown density as being: 90.37% (zone II), 90.43% (zone III) and 71.93% (zone IV . the so-called .death zone.). Detailed analyses of the selected evaluating features proved the possibility of utilizing the QuickBird image for the determination of such parameters as the crown density or the number of trees in a unit area. The value of the crown canopy oscillated from 94.9% to approximately 7.9% in the damage zone IV. The investigations have shown, beyond any doubt, that the VHR QuickBird satellite images can assist works on site and decision-making processes in delineation of new damage zones. High resolution in the region of interest and variety of radiometric information cause that the QuickBird images are valuable cartometric material, which due to the integration with other geoinformatic technologies (GPS, GIS) can be used for the verification and updating of LMN and SILP databases, including information on already existing forest damage zones.
Czasopismo
Rocznik
Strony
87--96
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
  • Laboratorium GIS i Teledetekcji Katedra Ekologii Lasu, Wydział Leśny Akademii Rolniczej w Krakowie
autor
  • Laboratorium GIS i Teledetekcji Katedra Ekologii Lasu, Wydział Leśny Akademii Rolniczej w Krakowie
Bibliografia
  • 1. de Vries W. (ed.) 2000: Intensive monitoring of forest ecosystems in Europe. FIMCI Technical Report 2000.Forest Intensive Monitoring Coordinating Institute. Brussels, Geneva.
  • 2. EC-UN/ECE 2000: Forest condition in Europe, Result of the 1999 Survey, 2000 Report. EC-UN/ECE, Brussels, Geneva.
  • 3. Forest ICP, 1994. Manual on Methodologies and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests, International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests, Programme Coordinating Centres, Hamburg and Prague.
  • 4. IUL 2003: Instrukcja Urz'ldzania Lasu. Zal'lcznik do Zarz'ldzenia nr 43 Dyrektora Generalnego Las6w Panstwowych z dnia 18 kwietnia 2003 r.
  • 5. Kayitakire F., Farcy C., Defourny P., Culvenor D.C., 2002: IKONOS-2 imagery potential for forest stands mapping. http://www.enge.ucl.ac.be/staff/curr/kayitaki/forestsat.pdf., ss. 11.
  • 6. Kuliesis A., Bajorunas A., Study on GPS technology application in Lithuanian forest survey. In: ConferenceProceedings: Remote Sensing and Forest Monitoring. IUFRO. Rog6w 1-3 1999. p. 154-166, 1999. Sasakawa H., Tsuyuki S. 2003: Development of forest type classification technique for the mixed forest with
  • 7. coniferous and broad-leaved species using the high resolution satellite data; http://definiens-imaging.com/ documents/reference2003.htm
  • 8. Seidling W., Fischer R., De Vries W., Lorenz M., W6jcik J. 2001: Organisation, Methods, and Results of the European Programme on Forest Condition under UN/ECE and EC. W: Zintegrowany Monitoring Srodowiska Przyrodniczego. Funkcjonowanie i monitoring geoekosystem6w z uwzględnieniem zanieczyszczeń powietrza. IOS, Biblioteka Monitoringu Srodowiska, Warszawa.
  • 9. Solberg R., Wttzyk P., 2000. Forest Environmental Monitoring and Management System FOREMMS - contribution to the development of sustainable use of natural resources. [In:] Application of Remote Sensing in Forestry, 12-14 09 2000 Zvolen, Slovakia.
  • 10. Ustawa z dnia 28 wrzesnia 1991 r. o lasach (tekst jednolity, Dz. U. 91.101.444).
  • 11. Wawrzoniak J., (red.), 2003: Forest condition in Poland in 2002. IOS, Biblioteka Monitoringu Srodowiska, Warszawa.
  • 12. Wttzyk P., 2004: Integracja technologii geoinformatycznych w systemie monitoringu i zarządzania ekosystemami lesnym Europy, na przykladzie projektu FOREMMS (5 PR UE). Teledetekcja Srodowiska. Nr 33. s.75-81.
  • 13. Wttzyk P., de Kok R., Zajaczkowski G., 2004: The role of statistical and structural texture analysis in VHR image analysis for forest applications. A case study on QuickBird data in the Niepolomice Forest. [In:] Strobl et al. Hrsg. Angewandte Geoinformatik 2004; ss. 770-775. Wichman. Heidelberg.
  • 14. Wttzyk P., Malek S., Koziol K., Guzik M., Zielinski B., 2000. Monitoring of forest litter contamination in the Ojcow National Park (South Poland) using GIS tools. Application of remote sensing in forestry. Zvolen, Slovakia.
  • 15. Zajączkowski G., Wttzyk P., 2004: Techniki teledetekcyjne w inwentaryzacji urządzeniowej lasu. RocznikiGeomatyki, Tom II, Z. 4, ss. 41-50.
  • 16. Zawila-Niedzwiedzki T., 1994. Ocena stanu lasu w ekosystemach zagrożonych z wykorzystaniem zdjęć satelitarnych i systemu informacji przestrzennej. Prace lnstytutu Geodezji i Kartografii, Tom XLI, Z. 90.
  • 17. Zawila-Niedzwiedzki T., Wisniewska E., Iracka M., 2001: Zdjęcia lotnicze i satelitarne w leśnictwie. Mat. XI Konf. PTIP Systemy Inf. Przestrz., Warszawa, ss. 317-327.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPW9-0005-0030
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