This study aims to map and evaluate digital classification methods of mapping
of LULC using Very High Resolution (VHR) Quickbird satellite imagery in one of
the Langkawi UNESCO Global Geopark, that is Kilim Karst Geoforest Park (KKGP)
which is located at northeast of Langkawi, Kedah, Malaysia. Object-based and
pixel-based classification methods were explored and compared. Object-based
method involved multi-resolution segmentation part where scale parameter,
shape and compactness should be assigned as accurate as possible, so that the
image is segmented to homogenous area. Both segmentation and classification
processes were conducted in e-Cognition software. While, a supervised
classification, Maximum Likelihood Classification (MLC) involved selection of
training areas was used for pixel-based method using ERDAS Imagine software.
Then, classification accuracies were assessed by comparing both techniques
using error matric and Kappa coefficient.

Categories: Guna Tanah, Tanah
Tags: Artikel Jurnal, Data Penerbitan, Terbuka