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2009 | 11 | 2[21] |

Tytuł artykułu

Analiza obiektowa w lesnictwie

Autorzy

Treść / Zawartość

Warianty tytułu

EN
Object analysis forestry

Języki publikacji

PL

Abstrakty

PL
Techniki zautomatyzowanego rozpoznawania obiektów są wskazywane jako jeden z najważniejszych elementów rozwoju technologicznego w geoinformacji. Szczególnie dotyczy to praktyki, gdzie wymagana jest wysoka efektywność stosowanych metod połączona z dobrymi rezultatami analiz. Artykuł przedstawia istotne możliwości i zalety, powstałej na przełomie XX i XXI w. analizy obiektowej, w zakresie prowadzenia analiz przestrzennych obszarów leśnych. Metoda ta stanowi jednocześnie rozbudowane narzędzie analityczne, kontrola którego wymaga wysokiego poziomu wiedzy z zakresu teledetekcji i przetwarzania obrazów oraz umiejętności interpreteacji wyników. Główną tezę artykułu stanowi pytanie: Czy i w jakim zakresie metoda ta może zostać wykorzystana w praktyce leśnej? Wnioski nie są jednoznaczne, gdyż metoda ta znajduje się na etapie intensywnego rozwoju, co oznacza istotne niedostatki metodyczne. Jednocześnie niektóre jej elementy mogą być bardzo użyteczne.
EN
Automated object recognition techniques are identified as one of the most important elements of the technological development in geoinformation. It is particularly true in practice, where high efficiency of the methods is required combined with good analysis results. This paper presents significant opportunities and benefits of the late-century analysis of the object regarding spatial analysis of forest areas. This method is also a complex analytical tool, the control of which requires a high level knowledge of remote sensing and image processing and the ability to interpret results. The main thesis of the article is the question:Whether and to what extent this method can be used in practical forest management? Conclusions are not clear, since this method is at the stage of intensive development, which means significant methodological shortcomings. At the same time some of its elements can be very useful.

Wydawca

-

Rocznik

Tom

11

Numer

Opis fizyczny

s.144-161,fot.,rys.,bibliogr.

Twórcy

autor
  • Szkola Glowna Gospodarstwa Wiejskiego, Warszawa

Bibliografia

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  • Hese S., Schmullius C., 2005, Object Oriented Deforestation Mapping in Siberia – Results from the SIBERIA-II Project, DGPF Jahrestagung, Rostock, Proceedings CD.
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  • Johansen K., Arroyo L.A, Phinn S., Witte C., 2008, Development of process trees for object-oriented change detection in riparian environments from high spatial resolution multi-spectral images. W: Hay G.J., Blaschke T., Marceau D. (Red.). GEOBIA2008 – Pixels, Objects, Intelligence. GEOgraphic Object Based Image Analysis for the 21st Century. University of Calgary, Calgary Alberta, Canada, August 05-08. ISPRS Vol. No. XXXVIII-4/C1. Archives.
  • Kayitakire F., Farcy C., Defourny P., 2002, Ikonos-2 imagery potential for forest stands mapping. ForestSAT Symposium, Heriot Watt University, Edinburgh, August 5-9.
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  • Lang S., Blaschke T., 2006, Bridging Remote Sensing and GIS – which are the main supportive pillars?, W: Lang S., Blaschke T., Schöpfer E., (Red.), 1st International Conference on Objectbased Image Analysis (OBIA 2006), Workshop proceedings, Salzburg.
  • Leppänen V.J., Tokola T., Maltamo M., Mehtätalo L., Pusa T., Mustonen J., 2008, automatic delineation of forest stands from lidar data.W: Hay G.J, Blaschke T., Marceau D. (Red.). GEOBIA 2008 – Pixels, Objects, Intelligence. GEOgraphic Object Based Image Analysis for the 21st Century. University of Calgary, Calgary Alberta, Canada, August 05-08. ISPRS Vol. No. XXXVIII-4/C1. Archives.
  • Maier B., Tiede D., Dorren L., 2008. Characterising Mountain Forest Structure using landscape metrics on LiDAR-based Canopy Surface Models, W: Blaschke T., Lang S., Hay G. (Eds.). Object-Based Image Analysis – Spatial concepts for knowledge-driven remote sensing applications, Berlin: Springer.
  • Mallinis G., Mitsopoulos I., Dimitrakopoulos A., Gitas I., Karteris M., 2008, Local-Scale Fuel-Type Mapping and Fire Behavior Prediction by Employing High-Resolution Satellite Imagery. W: IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, volume 1, no. 4, December 2008.
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  • Onishi N., 2004, Approach to hierarchical forest cover type classification with object-oriented method. W: Proceedings of the 25th Asian Conference on Remote Sensing. Chiang Mai, Thailand. 22 - 26 November 2004.
  • Platt R.V., Schoennagel T., 2008, Have forests really become denser? An object-oriented assessment of a key premise in wildfire policy. W: Hay G.J, Blaschke T., Marceau D. (Red.). GEOBIA2008 – Pixels, Objects, Intelligence. GEOgraphic Object Based ImageAnalysis for the 21st Century. University of Calgary, Calgary Alberta, Canada,August 05-08. ISPRS Vol. No. XXXVIII-4/C1. Archives.
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  • Tokola T., Vauhkonen J., Leppänen V., Pusa T., Mehtätalo L., Pitkänen J., 2008, applied 3d texture features in als based tree species segmentation. W: Hay G.J, Blaschke T., Marceau D. (Red.). GEOBIA2008 – Pixels, Objects, Intelligence. GEOgraphic Object Based Image Analysis for the 21st Century. University of Calgary, Calgary Alberta, Canada, August 05-08. ISPRS Vol. No. XXXVIII-4/C1. Archives.
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Typ dokumentu

Bibliografia

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