The advantage of image classification is to provide earth's surface information like landcover and time-series changes. Nowadays, pixel-based image classification technique is commonly performed with variety of algorithm such as minimum distance, parallelepiped, maximum likelihood, mahalanobis distance. On the other hand, landcover classification can also be acquired by using object-based image classification technique. In addition, object-based classification uses image segmentation from parameter such as scale, form, colour, smoothness and compactness. This research is aimed to compare the result of landcover classification and its change detection between parallelepiped pixel-based and object-based classification method. Location of this research is Bogor with 20 years range of observation from 1996 until 2016. This region is famous as urban areas which continuously change due to its rapid development, so that time-series landcover information of this region will be interesting.
|IOP Conference Series: Earth and Environmental Science
|Published - 20 Dec 2017
|5th Geoinformation Science Symposium 2017, GSS 2017 - Yogyakarta, Indonesia
Duration: 27 Sept 2017 → 28 Sept 2017
- land cover
- object-based classification
- pixel-based classification