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The increasing human population in the world has become drastically influence on urban land. Most of the urban area consisting of green land and buildings. Therefore, do a classification of green land area and the building uses image data Time Series of EVI Landsat in the study area of Tangerang, Bogor and Depok. The goal is to determine a pixel of the image is a green land or buildings; extracting and classifying characteristic of green land or buildings on the image; and perform comparisons process smoothing with non smoothing. In the classification of the study area of the city used a remote sensing system that produces a Landsat 7 satellite images to monitor the area of green land and buildings. In classifying the area of green land and buildings used a Time Series EVI Landsat Data. The method used is the Transformation Daubechies Wavelet one dimensional and Naive Bayes. Classification is done by evaluating the non-smoothing, smoothing level 1, level 2 smoothing, smoothing level 3, and smoothing level 4. The results of the classification by evaluation smoothing level 4 has the fewest number of errors and the highest percentage of correctness accuracy 90%. It can be concluded as a result of classification is best compared with the four other classification results.
classification, Time Series EVI, Transformasi Wavelet Daubechies, Naive Bayes, smoothing.
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