Sayı kadar nesne boyama

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Sayı kadar nesne boyama

In this study, it is aimed to detection the crop pattern in agricultural areas with high accuracy by using object-based classification technique from high spatial resolution IKONOS satellite images. Tomato, corn, pepper, wheat, rice and sugar beet are the main products grown in the region. The most appropriate value for the scale parameter, which is the most important parameter in the segmentation process, has been determined by ESP-2 Estimation of Scale Parameter software. Various combinations have been tried for shape and compactness parameters in order to find the optimal segmentation parameters. In order to increase classification accuracy, normalized difference vegetation index NDVI and GLCM texture measurement methods have been used, including homogeneity, contrast, dissimilarity, mean, variance, and entropy. Using the data set from consist 29 bands, the image classification process have been performed using the object-based nearest neighbor classification technique in the eCognition software. The obtained classification results have been tested on parcel basis using ground truth data. The overall accuracy of the classification has been calculated as The results show that the high spatial resolution IKONOS satellite image can be used to detection high accuracy with object-based classification of agricultural crop pattern. Agronomy Journal, 93 3 , , Remote Sensing, 2 4 , ,

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Sayı kadar nesne boyama

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We need 2 cookies to store this setting. Uploaded by nour yumi. Judul yang ditingkatkan AI. Odoo Docs Odoo Docs. International Journal of Remote Sensing, 28 5 , , Untuk Nanti. Images in this review. Bese 66 em Bese 66 em. International Journal of Remote Sensing, 32 10 , , Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation. Amazon Ads Reach customers wherever they spend their time.

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