Approach to hierarchical forest cover type classification with object-oriented method
نویسندگان
چکیده
In order to comprehend detailed forest resources, the use of high spatial resolution data is expected. However, the efficeint forest cover type classification method of high spatial resolution data is not cleared yet. So, this study discussed the potential of the forest cover type classification such as classification of coniferous forest, broadleaved forest, and mixed forest, and tree speices classification, from high spatial resolution IKONOS data (1-m resolution) using image analysis software, eCognition which has adopted the object-oriented hierarchical classification method. The study site is the Kirishima area over Miyazaki Prefecture and Kagoshima Prefecture, Japan. This site contains natural coniferous forest, natural broadleaved forest and artificial plantation forest and so on. The consistency about IKONOS data classified for every forest cover type using eCognition and stand description data was assessed using the Kappa coefficient. Moreover, medium spatial resolution LANDSAT/TM date (30-m resolution) was analyzed by the same process, we compared with results of IKONOS.
منابع مشابه
Comparing the Capability of Sentinel 2 and Landsat 8 Satellite Imagery in Land Use and Land Cover Mapping Using Pixel-based and Object-based Classification Methods
Introduction: Having accurate and up-to-date information on the status of land use and land cover change is a key point to protecting natural resources, sustainable agriculture management and urban development. Preparing the land cover and land use maps with traditional methods is usually time and cost consuming. Nowadays satellite imagery provides the possibility to prepare these maps in less ...
متن کاملObject-Based Classification of UltraCamD Imagery for Identification of Tree Species in the Mixed Planted Forest
This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...
متن کاملSpectral-spatial classification of hyperspectral images by combining hierarchical and marker-based Minimum Spanning Forest algorithms
Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...
متن کاملشناسایی گونههای درختی در تودههای پهنبرگ آمیخته جنگلهای خزری با استفاده از تصاویر پهپاد (مطالعه موردی: جنگل دارابکلا)
Unmanned aerial vehicles (UAVs) images have high spatial resolution. They are a valuable source of information for mapping land cover and thematic information, particularly in the identification of tree species. The aim of this study was to investigate the capability of drone images and the base object method for detecting tree species in the Hyrcanian forests. For this purpose, part of an area...
متن کاملComparison of Performance in Image Classification Algorithms of Satellite in Detection of Sarakhs Sandy zones
Extended abstract 1- Introduction Wind erosion as an “environmental threat” has caused serious problems in the world. Identifying and evaluating areas affected by wind erosion can be an important tool for managers and planners in the sustainable development of different areas. nowadays there are various methods in the world for zoning lands affected by wind erosion. One of the most important...
متن کامل