[SSNI] [Tian JIA] [20382558] Supervisor: Prof. Vladimir Brusic, Dr. Ping Fu and Automated Approaches to Glacial Landform Mapping Dr. Cheng-Zhi Qin Introduction There are abundant glacial landforms in high mountain and cold regions formed by This research aims to develop a new automated approach to accurately detect and past glaciers. They are important for reconstructing the past glacier activity and map the comprehensive glacial landforms in the Tibetan Plateau, the largest climatic change. The traditional approach to mapping glacial landforms involves glaciation area outside the polar regions. The research has the following objectives. manual delineation of landform units from DEM and remotely sensed images. This • Develop an automated approach for mapping individual glacial landforms by is very time-consuming and laborious. Hence, semi-automated and automated using spatial structure information of landforms in the Tibetan Plateau. glacial landforms mapping approaches are developed for improving manual • Combine the individual glacial landforms mapping into integrate approach for mapping efficiency. However, most of the methods take insufficient account of mapping complex glacial landforms system. spatial structure information and were only applied to simple landforms in small • Apply this combined approach to map complex glacial landforms near by areas areas. of Himalayas. Glacial Landform Classification Glacial landform classification is based on alpine glacial landforms, whose classification table, schematic diagram and photographs are shown in Table 1 and Figure 1. Table 1. The classification of alpine glacial landforms that corresponding shapes are shown in Figure 1. (a) (c)

Glacial Cirque (a) (b) Erosional U-shaped valley (b) (e) Source: National Park Service Glacial valley Landforms Hanging valley (c)

Source: Google Earth Glacial lineation (d) (e) (d) Alpine Lateral moraine (e) Medial moraine (e) Glacial Glacial Moraine Landforms Terminal moraine (e) Depositional Source: Google Earth Source: NSIDC Landforms Recessional moraine(e) Drumlin (f) (f) (g) (h) (i) (j) Glacial boulder field (g) Outwash plain (h) Glaciofluvial Kettle (i) Kettle Landforms Source: www3.nd.edu Source: AntarcticGlaciers.org Kame (j) Source: AntarcticGlaciers.org Source: AntarcticGlaciers.org Source: (Menzies and Ross, 2020) Figure 1. The schematic diagram and photographs of glacial landforms. Glacial Landform Mapping Approaches Manual mapping Automated mapping In manual mapping of glacial landforms processes, experts define the features of Automated and semi-automated mapping techniques typically use either a pixel- target glacial landforms initially. Then, they identify the features of the landforms based or an object-based approach (Robb et al., 2015). The techniques of recent on remotely sensed sources. They use definitions from digital image processing research on the automated or semi-automated mapping approaches are shown system or a GIS (Smith et al., 2001; Greenwood and Clark, 2008). An example in Table 2. explains the process of delineating the glacial valley on Digital Elevation Model Table 2. The summary of recent semi-automated or automated mapping methods research. (DEM) (Figure 2a and 2b). They visualize the cross-section profiles of the valley to determine whether it is a glacial valley (Figure 2c) (Fu et al., 2012). Glacial landform type Author Techniques Multi-resolution segmentation Eisank et al. (2014) (a) (b) (c) algorithms (MRS) Drumlins Curvature based relief separation Yu et al. (2014) technique (CBRS) Saha et al. (2011) Object-based image analysis (OBIA) Glacial lineation Smith et al. (2016) Clustering algorithms Moraines, Flutes, Drumlins, Eskers and Robb et al. (2015) Object-based image analysis (OBIA) Sandur Figure 2. The process of determining glacial valleys by experts (Jia, 2019). Ongoing work: Data Preparation and Pre-processing for Mapping Glacial Cirques

Data preparation (a) (b) (c) Satellite imagery: The outline of a Landsat 8 images Manual The features of a glacial cirque ACME mapping glacial cirque (Figure 4a, b and c) DEM: SRTM 30m Perimeter = 4298m Figure 3. The process of cirques polygon and features preparation. ACME is an ArcGIS tool named Automated Cirque Metric (d) (e) (f) Extraction developed by Spagnolo et al. in 2017. Data pre-processing Threshold Area midpoint 2D = 1399719m2 • The metrics of 11 cirque features are shown in Figure 4d, e, f, g, h and i. Surface = 1401822m2 • The metrics are extracted by summarizing the spatial pattern of the cirque. • The hypothesis is that we can use the metrics to perform automated mapping approaches.

The future work will involve several stages. Z-min = 4398m Slope mean = 17° Aspect mean = 103° 1. Demonstrate the utility of the method on studying cirques by using the polygon delineation (g) (h) (i) and features extraction approach in controlling Figure 3.

2. This method will be extended to other landforms such as u-shaped valleys and moraines. Plan closure 3. We will deploy ontology design pattern (ODP) to make glacial landform definitions and deploy = 235° them with the data structure. It will be a semantic program for the automation of mapping.

References NSIDC. (2020). Glacier Landforms: Moraines. Accessed: https://nsidc.org/cryosphere/glaciers/gallery/moraines.html. Z-max = 4671m Eisank, C., Smith, M., and Hillier, J. (2014). Geomorphology, 214, 452-464. Robb, C., Willis, I., Arnold, N., and Guðmundsson, S. (2015). Remote Sensing of Environment, 163, 80-90. Fu, P., Heyman, J., Hättestrand, C., Stroeven, A. P., and Harbor, J. M. (2012). Journal of Maps, 8(1), 48-55. Saha, K., Wells, N. A., and Munro-Stasiuk, M. (2011). Computers & geosciences, 37(9), 1324-1336. Greenwood, S. L., and Clark, C. D. (2008). Subglacial bedforms of the Irish ice sheet. Journal of Maps, 4(1), 332-357. Smith, M. J., Clark, C. D., and Wise, S. M. (2001). Slovak Geological Magazine, 7(3), 263-274. Jia, T. (2019). Dissertation of Bachelor of Science degree in University of Nottingham Ningbo China. Spagnolo, M., Pellitero, R., Barr, I. D., Ely, J. C., Pellicer, X. M., and Rea, B. R. (2017). Geomorphology, 278, 280-286. Figure 4. The cirque polygon visualized on Google Earth and its 11 features visualized on DEM. Menzies, J., and Ross, M. (2020). Glacial Processes and Landforms—Transport and Deposition☆. Yu, P., Eyles, N., and Sookhan, S. (2015). Geomorphology, 246, 589-601.