Wykorzystanie fotogrametrii cyfrowej, GPS i GIS w procesie kartowania szaty roślinnej Babiogórskiego Parku Narodowego

• Autorzy: Wężyk P. , Sztremer M.

Warianty tytułu

EN

Using digital photogrammetry, GPS and GIS in vegetation mapping of the Babia Gora National Park

• Języki publikacji: PL

Abstrakty

EN

The aim of this paper is to comparethe results of the vegetation mapping based on using GI technology (e.g. photogrammetric workout of CIR stereomodels and DGPS survey) with the traditional methods supported only by archival B&W aerial photos. Within the framework of the project .Temporal and spatial scales of dynamics of Norway spruce stands in West Carpathians. (granted by KBN 6 P04 F03021) flight mission was taken over The Babia Gora National Park on 30 Th September 2002, using CIR (Kodak Aerochrome III Infrared Film 1443) for aerial photos (scale 1: 10.000). Images were scanned at 1800 dpi resolution (pixel size 14 ?m; 14 by 14 cm ground resolution). There were 19 signalized GCP; their positions were gained with DGPS measurements (base station TPN, Zakopane) taken by cartographic receivers Trimble. Due to the delay of flight mission (expectation date: July/Aug. 2002) part of signalized GCP were damaged or impossible to identify. It was necessary to restore and add some new .natural. GCP. Results of aerotriangulation executed by OPGK Krakow were satisfactory for project requirements (?X = 0,49 m; ?Y = 0,47 and ?Z = 1,08 m). Mapping of vegetation of the Babia Gora National Park was realized through stereodigitalization of 17 models and covered 2,232.8 hectares. During the workout on the DEPHOS digital photogrammetric station, specified fragments of plant cover were separated and identified according to photointerpretation key (description of plant community, situation sketch, digital photos, DGPS position). The mapped objects were classified into 23 polygon classes (hierarchy code included forest and no-forest areas). In sum, there were 372 digitalized polygon objects (the mean area of a single polygon was 4.78 hectares). Topology correctness of this layer was obtained with ArcInfo ver. 8.2 ESRI software. Map compositions were created with ArcView 3.2a software. While creating BgNP Protection Plan in 1999, the map of vegetation was made based on .traditional. techniques of mapping and archival cartographic sources, including contact prints of B&W aerial photos from 1993. GPS receivers were not used at that time, but only altimeter and topographic map in the scale of 1: 10.000. The map created by this traditional method was compared with photogrammetric workout of CIR aerial photos from Sept. 2002. At the area of 2519.13 hectares the map of vegetation includes 1743 objects, while .CIR map. Had only 400 one of them. During detailed analyzing of 10 pairs of homologous objects generalizing of object borders at plant cover map was ascertained (perimeters were on average shorter by 10.04 %). Position errors at the plant cover map compared with the .CIR map. were at the level from 4 m to 19.4 m (11.48 m on average). This work shows a very good example of mutual support in a scientific project of geomatic techniques (digital photogrammetry, GIS and GPS) and the character of nature researches. The integration of GI tools enables verification of archived data and updating of geometric and attribute GIS databases.

Słowa kluczowe

PL

mapa roślinności; zdjęcia lotnicze CIR; stereodigitalizacja

EN

map of vegetation; air photos CIR; stereodigitalization

• Wydawca: Polskie Towarzystwo Informacji Przestrzennej
• Czasopismo: Roczniki Geomatyki
• Rocznik: 2005
• Tom: T. 3, z. 2
• Strony: 173--180
• Opis fizyczny: Bibliogr. 9 poz.

Twórcy

autor

Wężyk P.

• Laboratorium GIS i Teledetekcji Katedra Ekologii Lasu, Wydział Leśny Akademii Rolniczej w Krakowie

autor

Sztremer M.

• Laboratorium GIS i Teledetekcji Katedra Ekologii Lasu, Wydział Leśny Akademii Rolniczej w Krakowie

Bibliografia

• 1. Ciolkosz A., Masztalski J., Olt;dzki J. 1999: Interpretacja zdjt;C lotniczych. Wydawnictwo Naukowe PWN. Warszawa.
• 2. Haapanen, R., Ek, A., Bauer, M., Finley, A. 2004: Delineation of forestVnonforest land use classes using nearest neighbor methods. Remote Sensing of Environment 89:265-271.
• 3. Holopainen M. Laasasenaho J. 1999: Forests in Geopgraphic Information Systems. Conference on Remote Sensing and Forest Monitoring, Rog6w 1999, s. 97-102.
• 4. Jaworski A., Poznanski R. 2000: Nowoczesne metody gospodarowania w lasach górskich. Centrum Informacji Lasów Panstwowych. Warszawa.
• 5. Pellikka, P., King, D. J., Leblanc, S. G. 2000: Quantification and removal of bidirectional effects in aerial CIR imagery of deciduous forest using two reference land surface types. Remote Sensing Reviews, Special issue on "Multi-angle Measurements and Models", 19: 259-291.
• 6. Weiner J.(red.). 1995: Puszcza Niepolomicka. Reakcje ekosystemu na zanieczyszczania przemysłowe - analiza za pomoc GIS. GIS dla obszarów chronionych. Krak6w, s. 95-102.
• 7. Wt;Zyk P., Guzik M. 2004: The use of ,Photogrammetry-GIS" (P-GIS) for the analysis of changes in the Tatra Mountains' natural environment. In: A message from the Tatra. Geographical Information Systems and Remote Sensing in Mountain Environmental Research. Krak6w, Poland, Riverside, California, USA, pp. 31-46.
• 8. Wt;Zyk P., Mansberger R. 1997: Przyklad wykorzystania ortofotografii cyfrowej i systemu GIS w lesnictwie. Archiwum Fotogrametrii, Kartografii i Teledetekcji. Vol.6, s.133-155.
• 9. Wt;Zyk P., Mansberger R. 1998: Techniki fotogrametrii cyfrowej i GIS w ocenie degradacji drzewostan6w świerkowych w masywie Kudlonia w Gorcach. Archiwum Fotogrametrii, Kartografii i Teledetekcji. Vol. 8, s. 20-1:20-10.