Glacier mapping with object based image analysis method, case study of Mount Everest region

Thanki, Dhval and Israni, Dippal and Makwana, Ashwin (2019) Glacier mapping with object based image analysis method, case study of Mount Everest region. Jurnal Kejuruteraan, 31 (2). pp. 215-220. ISSN 0128-0198


Official URL:


Substantial progress in Geoinformatics System in recent years leads to the research in monitoring and mapping of glaciers. Monitoring glacier in the mountain region with traditional manual method is very crucial and time-consuming. Glaciers are melting because of global warming. Melting of glaciers can causes calamities like rising in sea level, glacial lake outburst, avalanches etc. Glacier monitoring using multi-temporal data for objects on the surface of the glacier is hard to classify. This paper gives an insight into the importance of Geo-spatial data and object-based image analysis method for satellite image processing. The object-based image analysis benefits more compared to traditional pixel-based image analysis as it is more robust and noise removing more image features etc. Spectral data with multiple bands is the backbone of surveying and monitoring of glacier. In this paper case study of Mount Everest region (27 48° 32N, 86 54° 47E) is represented. The remotely sensed image needs to be taken in a cloud-free environment. Object-based image classification is done in recognition tool. Also, the step by step methodology of object-based classification, segmentation and post-classification possibilities are discussed. Finally, the paper presents several representations of indexes. The integration of indexes is useful for accurately classifying the different part of terrain, lake, vegetation and glacier.

Item Type:Article
Keywords:Glacier mapping; Object based image analysis; Classification; Geographic information system; Geo-spatial
Journal:Jurnal Kejuruteraan
ID Code:14814
Deposited By: ms aida -
Deposited On:06 Jul 2020 06:28
Last Modified:10 Jul 2020 02:06

Repository Staff Only: item control page