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Identification of Multistrata Vegetation using High Resolution Satellite Imageries in Sumberjaya, Lampung, Indonesia

Widayati, Atiek (2001) Identification of Multistrata Vegetation using High Resolution Satellite Imageries in Sumberjaya, Lampung, Indonesia.

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Abstract:Coffee farming practices in Sumberjaya, Lampung, Indonesia, have environmental implica-tion to the soil and water conservation in the area, especially with regard to soil erosion. The types of coffee gardens which include the vegetation structure complexity and the canopy cover become the initial aspect of identification before further studies related to its configura-tion along with other land cover types on the landscape is further explored. High resolution satellite images have potential for such detailed level of identification taking into account dif-ferent remote sensing approaches to be applied in fulfilling the objectives. Two properties of remotely sensed data, spectral and spatial properties are the starting point in the application of the methods which eventually leads to the integration of both properties. Both approaches are realized through various techniques of image enhancements and image segmentation, fol-lowed by supervised classification procedures. Various transformations based on spectral pix-el values are explored, i.e. PCA, NDVI, IHS and resolution enhancement with image fusion. In addition, spatial approach, namely textural analysis and segmentation, are applied. This latter approach is useful in taking into account the high variability of spectral values in neigh-boring pixels, which is inherent to the high resolution satellite images. The results show that for a detailed classification of coffee gardens in the study area, with standard pixel-based classification a reasonably good accuracy is obtained. Integration of the pixel-based approach and the spatial-based approach of segmentation using majority rules gives an increased overall accuracy. However, the discrimination of several classes of coffee gardens with moderate canopy density and variable density of shade tress, is not fully satisfac-tory. Ways to improve their classification are indicated.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/87522
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