5. GIS, Cartography and Visualization of Glacier Terrain

Transcription

1 5. GIS, Cartography and Visualization of Glacier Terrain 5.1. Garhwal Himalayan Glaciers Introduction GIS is the computer system for capturing, storing, analyzing and visualization of spatial and non-spatial data. GIS has been established as separate discipline in the end of decades of 1980s. Several earth scientists often use GIS as simply mapping tools (Wright et al 1997), assuming the main goal is to merely generate remarkable and attractive maps, which gives expression of shorter subject matter of discipline. However, GIS is not only related with creating maps on a computer for a variety of descriptive and analytical purposes. It can also help planners and analysts visualize data to better understand patterns and concentrations of spatial phenomena and it can assist in natural resource management of country in logical and analytical manner. In addition GIS has the useful ability to portray layers of information, to help uncover spatial relationships among multiple sets of data. It can be made based on digitizing each data layer map of a distinct theme or a classified image (e.g. from a satellite, aerial photo) or a scanned map (e.g. from a field survey). The latter two represent information storage in raster format (on a cell by cell basis) with regular grid spacing whereas the former contains only the boundary of a specific entity in vector format (Figure 5-1). Number of attributes related with specific themes can be stored by vector format in its database. However the raster format is better for storing continuous fields, such as elevation values of a DTM (see section 2.4.5). The use of GIS in glaciology has progressed relatively slowly in India, and 125

2 limited to glacier change and mapping studies most probably due to (1) the emphasis given to field investigations in glaciology and the lack of focused on GIS technology and (2) GIS education and technical training for glaciology as the discipline. However outside India, application of GIS in glaciology has been established in automated glacier mapping (Bolch et al 2007, Paul et al 2001), GLOFs modeling (Huggel et al 2003), glacier hazard modeling (Huggel et al 2004), glacial geomorphology (O'Sullivan and Unwin, 2003), alpine valley morphometry and glacial valley networks (e.g. Duncan et al 1998), glacier database management (Mennis and Fountain, 1997), glacier flow direction (Kääb, 2005), application of internet GIS in glaciers database (Li et al 2003) and identification of potentially dangerous glacial lakes (PDGLs) (Bolch et al 2008b). The use of geographic information systems (GIS) has seen a steady increase since the first PCbased GIS software developed in the latter half of the 1980s. Prior to that, GIS was run on mainframe computers and was a relatively crude technology by today s standards. In current scenario GIS software s has provided wizard based tools which is easy and very simple to understand and perform GIS operation in few seconds or minutes. However no software has the comprehensive tools for GIS operations but availability of conversion facility provided by standard GIS software it can be possible to work with different GIS platforms. Thus several popular softwares such as ArcGIS 9.3 with the extensions Spatial Analyst (for raster data processing) and 3D Analyst (for 3D visualization), ERDAS Imagine 10, ENVI - 4.7, SAGA, and Geomatica 9.2 have been extensively used for present work e.g. glacier database creation and management, image processing, DEM generation, orthorectification and radiometric correction. SAGA is only free ware software in above discussed softwares and can be easily downloadable from The use of software for particular application (e.g. DTM generation) is described in their related sections. 126

3 Figure 5-1 Representation of real world objects in the vector and raster domain. 127

4 Deriving glacier parameters The Geological Survey of India (GSI) compiled a glacier inventory for the Indian Himalayas based on Survey of India topographic maps, vertical aerial photographs and satellite images wherever available (Kaul, 1999). However, this information is assembled in statistical records which are not accessible in GIS database (Kulkarni, 2007). Recently, GSI further improved and revised Indian Himalayan glacier inventory (Raina and Srivastava, 2008; Sangewar and Shukla, 2009). However, this glacier inventory has included glacier parameters (e.g. minimum and maximum elevation) using manual cartography. Extraction of glacier parameters for a larger number of glaciers by traditional methods (e.g. manual cartography using planimeter) is time intensive, biased by human interpretation and almost unreproducible. The use of GIS technology provides uncomplicated, less time intensive and reproducible results. In addition GIS offers following advantages: (1) spatial coverage storage (e.g. 2D glacier outlines) in a vector layer for tracing of temporal geometry changes, (2) storage of associated glacier parameters (e.g. area, perimeter and ID) in a attribute data base, (3) retrieval of 3D glacier parameters and topographic indices using corresponding DTM, (4) wizard based tools and programming allows fully automatic processing of all data and (5) 3D visualization using 2D glacier outlines and satellite data draped on DEM by GIS software s. Glacier parameters derived from GIS technology is valuable assets for glaciology and hydrological modeling (Braithwaite, 2009). In present study, slope and aspect maps were generated using spatial analyst extension of ArcGIS 9.3. slope and average aspect of each polygon (glacier) was calculated from ASTER DEM (2006) automatically by zonal statistical tool (ArcGIS). 128

5

6 Glacier GIS database structure and relevance The first important task in building the Garhwal Himalayas GIS was the selection of the primary coordinate system. Universal Transverse Mercator projection (UTM) WGS-84 with the ellipsoid is the most widely projection used in world. The available Indian topography maps have the Lambert conical projection system with Everest datum. Open source satellite data (e.g. Landsat ETM+) and DEMs are accessible in UTM with WGS84. Current GIS software s offers abundant potential for projection conversion facilities. For the uniformity in spatial database, UTM projection with WGS-84 system was used in the present study. The vector data were presented in point data (e.g. weather stations, settlements and elevation points) and line data (such as contour lines and Rivers) and polygon data (e.g., glaciers and lakes). The vector data and raster data (such as scanned topographic maps, satellite data and different DTM) were stored in ArcGIS geodatabase structure. Geodatabase structure is most suitable for stores both vector and raster data in single file which supports by Microsoft access. The vector data also contain attribute data. Selected map layers (vector and raster) are illustrated in Figure 5-2. In the present study, fourteen glacier parameters such as orientation, name, morphology type, basin name and minimum, maximum, mean, median, standard deviation and range of elevations, average slope and average aspect, area, IDs were attached with corresponding glacier polygon and were stored in database (Appendix). The unique IDs were assigned to each glacier polygon derived from Corona images and same IDs provided to corresponding glacier polygon derived from ASTER imagery for the comparison of every glacier area from 1968 to

7 5.2. Cartography and 3D Visualization Introduction Cartography is the study and practice of making maps or globes. Maps have traditionally been made using pen and paper, however the beginning and spread of computers has revolutionized cartography. Now these days earth surface features can be interactively visualized by digital cartography. Innovative GIS tools and geo-visualization allow for more interactive maps including the ability to explore different layers of the map, to zoom in or out, and to change the visual appearance of the map. The Garhwal Himalayas is high mountainous regions with moving glacial bodies. A high Himalayan mountain is a very dynamic space, in which over the years, many different geomorphic processes produced changes in surface. Digital cartographic techniques enhance the surrounding relief properties to understand glacier-topography interaction using GIS software s. This facilitate for the viewer to understand the moving glacial topography. The digital technologies available nowadays introduce various ways to visualize the changes. The previous research has concentrated on the possibilities and limitations of the visualization of the glacier changes in the high mountains (Kääb et al 2003, Paul et al 2003). DTM is an important data source for the nearly realistic production of maps and visualizations in the high mountains. Many GIS softwares now include photorealistic display capabilities. Highresolution imagery can be draped over DTMs to display complex glacial landscapes using virtual fly-through utilities which helps user to understand high mountain environment. Kääb (1998) and Kaufmann and Ladstädter (2003) successfully represented the movement of glaciers and rock glaciers. 131

8 Overview and detailed maps The two levels of study area map were generated for spatial details of the Garhwal Himalayas. A study area map of Garhwal Himalayas with the surrounding mountain systems was generated in introduction (Chapter 1; Figure 1-1) and detailed map of the investigation valleys with glacier coverage also shown in introduction (Chapter 1; Figure 1-14). All maps were created using ESRI ArcGIS 9.3. SRTM DTM with resolution of 30 arc seconds (approximately 1 km) was used as the base for the relief of the small-scale map (Chapter 1; Figure 1-1). In addition SRTM data of 90 m was used for large scale map of study area (Chapter 1; Figure 1-14). The class interval between the altitude levels was 1000 m selected for different color codes. The unique color code for representation of relief enhanced the view ability. Additional hill shading in symbology was used for appearance of the relief shade. The coordinate grid in degree and minute was used. The labels were designed for a particular object (e.g. city names or country names) and the uniform fonts, sizes and colors were used for presented map with north direction and scale. The location of figures presented in different chapters also shown in study area maps. Study area coverage of glaciers was presented by two sets of maps (a) location of study area in Indian Himalayas and (b) clean and debris-covered ice coverage in study region (Chapter 1; Figure 1-14). Bhagirathi and Saraswati/Alaknanda basin were differentiated by different symbols and were presented by transparent tool of symbology. The location of climate stations was also presented. 132

9

10 Thematic Maps In addition to the maps, different thematic maps such as geological, climate and drainage maps were also prepared using various sources. Geological map was generated using base map of western Himalayas (Thakur and Rawat 1992) showing important structure of area with their age. Rock units or geologic strata were shown by different color and symbols (Figure 1-2). In addition, map of climate stations representing climate stations of Garhwal Himalayas were also presented in climate map (Figure 1-3). The background of this map is presented by SRTM DEM with hill shade effect. Climate diagrams of Mukhim and Bhojbasa were prepared by MAAT software and both were integrated in Photoshop (Figure 1-4). The climate diagrams were shown the temperature and the precipitation conditions of Mukhim and Bhojbasa. Drainage map of study region was generated by vector poly lines of streams in Garhwal Himalayas which was overlaid on SRTM DEM with hill shade effect. Streams were digitized from map of Uttarakhand. Junction of streams (prayag) was also presented in drainage map (Figure 1-5). The location of bench mark glaciers in Indian Himalayas was presented in the map of India (Figure 1-12) D visualization The principle objective of 3D visualization in the present investigation is easy to use realistic representation of the change in glacier landscape. For this purpose multi-temporal satellite images and glacier outlines were draped on DTM using ArcScene. For the present study, ASTER imagery (2006) was draped on ASTER DTM (2006) (Figure 5-3). ASTER sensor has no channel in the blue spectral range, therefore to obtain a good contrast and color perception, green band was assigned for blue band and infrared band was assigned for red band. The resulting false-color image in this way is dominated by the green, but appears very familiar to 134

11 the eye. The vegetation is appearing with green, rocks and debris with gray, snow and ice with white and water with blue colours. Just these four surface materials are in the high mountains and are dominant in this work can be clearly separated from each other. Also, the lateral moraines near the glacier surfaces occur very clearly. The image was created with ArcScene 9.3. This band combination also provided good results for the dry Andean (Kamp et al 2004). The retreat of Garhwal glaciers from 1968 to 2006 based on Corona and ASTER data were illustrated in Figure 6-5. The vector polylines extracted from different satellite data were overlaid on ASTER image (2006) and draped on ASTER DTM. The glacier extents of different years were presented by diverse colors. 135