DEVELOPMENT OF DIGITAL ELEVATION MODEL FOR SEMERU VOLCANO

Transcription

1 DEVELOPMENT OF DIGITAL ELEVATION MODEL FOR SEMERU VOLCANO Cahyo Crysdian 1 1 Department of Teknik Informatika, Faculty of Sains dan Teknologi Universitas Islam Negeri Maulana Malik Ibrahim Jl. Gaayana 50 Malang Indonesia crysdian@yahoo.com 1 ABSTRACT Research to develop digital elevation model (DEM) of Semeru volcano is reported. The motivation is to visualize the volcano in 3D, thus its physical appearance can be presented in detail. The works consists of four phases i.e. elevation data collection, 3D visualization using legacy elevation data, development of blank data removal, and benchmarking among the developed methods. Elevation data collected by Shuttle Radar Topographic Mission (SRTM) is used in this research. An effort to use legacy data of SRTM to visualize the surface of the volcano from different view angle settings is failed due to the existence of blank data contained in SRTM dataset. Blank data are blank spots which the shuttle space fails to retrieve the elevation of some location on the earth. Thus the enhancement to SRTM dataset is required to solve this problem. Here two methods of blank data removal are presented i.e. neighborhood average and population average. The first is to remove blank data using its neighboring value, while the latter based on population average of statistic. Comparison among both methods shows that neighborhood average outperforms population average to support 3D visualization, in which it capable to produce smoother surface of the volcano compared to its counterpart. Keyword: Digital Elevation Model, 3D Visualization, Semeru Volcano 1. INTRODUCTION Semeru is widely recognized as the highest volcano on Java [1,2]. The volcano is situated inside Bromo-Tengger-Semeru National Park, a beautiful tourism place in the east side of Java Island that span across four local administrative regions namely Kabupaten Malang, Kabupaten Pasuruan, Kabupaten Probolinggo, and Kabupaten Lumaang [3]. Therefore the existence of Semeru volcano creates a significant impact to those regions and their people. In term of tourism, Semeru volcano has been attracting thousands rock-climber due to its beautiful scenery [1]. From top of Semeru that has 3676m elevation above the sea level, they could see other surrounding volcanoes, mountains, towns, and even shoreline. Some useful medical plants could also be found in the area of Semeru [4]. Indeed, the volcano becomes the habitat of many floras and faunas [5]. Beside its benefit, Semeru has been known creating small to medium eruptions that happened frequently since 1967 [2]. The explosions occasionally follow by lava flows and rock falls that caused human victims [5,6]. Due to the phenomenon above, it is very important to study Semeru. However, very few literatures could be found recording research outcomes on Semeru such as done by [4,7]. Therefore extending research on Semeru is necessary to disclose the phenomenon and activities of this volcano. Since Semeru is renown for beautiful sceneries and become a challenging place for climbing activities [1,2,3,5] and have caused some human victims due to its volcanic activities [5,7], it is necessary to have a model of the volcano. Efforts to build 3D visualization of Semeru become important to reach this obective. However, no outcome of such research has been recorded up to present time. Although efforts such as done by Google Earth [8] and Yahoo Maps [9] to some extent deliver fascinating results, system constraint of those applications has restricted the development of a good and detail model of the volcano. 2. CONSTRUCTION OF ELEVATION DATA A set of elevation data is required to develop 3D visualization of Semeru volcano. Currently, there are some data sources could be used to build this data namely ETOPO, GTOPO, and SRTM. Although those data sets are distributed and available widely, they have different characters. In term of resolution, ETOPO has two versions namely ETOPO2 and ETOPO5 which have VI-57

2 VI-58 The 6 th International Conference on Information & Communication Technology and Systems approximately 3.6 and 9 Km resolution respectively, while GTOPO and SRTM hold approximately 900 meters and 90 meters resolution respectively. Since smaller resolution is desired to get more detail presentation of an obect, SRTM data set is used in this research SRTM Data SRTM (Shuttle Radar Topographic Mission) is a set of global elevation data of earth collected using radar system of a space shuttle [10]. It covers about 80% of earth surface that lay between 60 degrees north latitude and 54 degrees south latitude. The data is publicly distributed with 1 arc-second resolution (approximately 30 meters) over US territories and 3 arc-second (approximately 90 meters) for non US territories. To get the elevation data of Semeru volcano from SRTM data bank, the geographical coordinate of Semeru which is located at 08 06'30" south latitude and ' east longitude [2] is used as a reference point. Based on the reference point, the elevation of Semeru is retrieved using GetSRTMData function [11]. This function is capable to obtain elevation data from a line between two independent coordinates,. Nevertheless, it fails to extract data from the area of a spatial obect. Thus to employ GetSRTMData function to obtain the elevation of Semeru volcano, a small algorithm is developed as shown in Figure 1. This algorithm enables GetSRTMData to retrieve a set of elevation data from the area of Semeru, and put the result into i matrix. LON = GetSRTMData([lon1 lat1],[lon2 lat1]); size_horizontal = size(lon,1); for i=1 to size_horizontal end LAT = GetSRTMData([LON(i,1) lat1],... [LON(i,1) lat2]); elevation(:,i)=lat(:,3); Figure 1. Algorithm to retrieve SRTM data D Visualization of SRTM Data Next stage after reading the elevation data to i matrix is creating a 3D visualization from that matrix. The transformation from i matrix to 3D visualization is done by converting row, column, and the content of each cell from the matrix to the visualization coordinate represented by a set of axis namely x, y, and z-axis respectively. With this approach the row of matrix represents the x-axis, the column represent the y-axis, while the content of each cell represent the value of z-axis. Results of visualizations are shown in Figure 2. Figure 2. Results of visualizing i matrix To have better view of 3D visualization, a set of view angle is developed. The view angle is composed by two parameters as formulated below: V = (h,v) (1) Which V is a view angle, h is a horizontal setting from y-axis, and v is a vertical setting from x-y plane as shown in Figure 3. Results of applying different view angles to the visualization of Semeru volcano are shown in Figure 4. These results fail to present the elevation of Semeru volcano. It is due to the existence of blank data contained in the SRTM data set as noted by some researchers [10]. This type of data holds the value of 32768, which is much greater than the value for normal elevation data. Therefore, the improvement of SRTM elevation data is required to counter the effect of blank data. This effort is presented in the next section.

3 Development of Digital Elevation Model for Semeru Volcano Cahyo Crysdian VI-59 z v o x h o y Figure 3. View angle c. View angle (25,25) Figure 4. 3D visualization of Semeru volcano from SRTM data set using different view angle 3. BLANK DATA REMOVAL As described previously, efforts to improve elevation data obtained from SRTM data set are required due to the existence of blank data. The goal is to remove blank data since this type of data cancels presentation of spatial obect. The employed approaches are as follow. a. View angle (0,75) 3.1. Neighborhood Average This method relies on the value of neighboring data. Let M becomes a matrix of elevation data with i and become the index of row and column of M respectively, and d is the elevation data contained in M, a blank data b at coordinate (i,) is replaced with the following value: di 1, di 1, di, 1 di, 1 b i, (2) 4 b. View angle (45,45) Equation 2 is applicable only if di 1, b or d i, 1 b. If either one or both value of d i 1, or d i, 1 is a blank data, then the value of d i 1, or d i, 1 is replaced with d i 1, or d i, 1 prior to employ Equation 1 to a matrix of elevation data. Results for running this method to the elevation data retrieved from SRTM data set as explained in Section 2 are presented in Figure 5.

4 VI-60 The 6 th International Conference on Information & Communication Technology and Systems 3.2. Population Average Since the presented Neighborhood Average requires a step to identify neighboring blank data prior to running the main enhancement step, this section present a method that run main enhancement process without any prior preprocessing step. This method relies on the average value of the elevation data population. Following the definition of Equation 2, the method is formulated as follow. A rm ( M ) cm( M ) i 0 d 0 n i, d i, b (3) a. View angle (0,75) With A is a population average value, n is the number of times d being added as a population member, and rm( ) and cm( ) is the function to determine the maximum value of row and column respectively from a matrix M. Results produced by Population Average method are given in Figure 6. b. View angle (45,45) a. View angle (0,75) c. View angle (25,25) Figure 5. 3D visualization of Semeru volcano employing Neigborhood Average b. View angle (45,45)

5 Development of Digital Elevation Model for Semeru Volcano Cahyo Crysdian VI-61 c. View angle (25,25) Figure 6. 3D visualization produced by Population Average 4. DISCUSSION AND COMPARISON AMONG BLANK DATA REMOVAL METHODS Evaluation on the presented methods to remove blank data was conducted by comparing and scrutinizing their output as shown in Figure 5 and 6. Figure 5a as the output of Neighborhood Average delivers a smooth and natural presentation of Semeru volcano. Meanwhile, Population Average produces abnormal contour as appeared in the left side of Figure 6a. The shortcoming of Population Average become more apparent as the view angle setting were changed to become (45,45) and (25,25) degree. The last settings of view angle clearly show drastic changes of elevation data as shown in Figure 6b and 6c. After scrutinizing the matrix of elevation data produced by Population Average, it is obviously known that the phenomenon is due to the discrepancy between the elevation values produced by Population Average to replace blank data against the elevation data of the surrounding pixel value. Thus Population Average method creates the problem of unrealistic elevation data. The phenomenon of drastic changes of elevation data as suffered by Population Average is not presented in the result of Neighborhood Average method as shown in Figure 5b and 5c. Smooth visualization of the surface of volcano is produced by Neighborhood Average method. Thus, it can be concluded that Neighborhood Average outperforms Population Average in terms of removing blank data problem exist in SRTM data set. 5. CONCLUSION SRTM data set which has 3 arc-seconds or approximately 90 meters resolution is used in this research to develop DEM of Semeru Volcano, the highest volcano in Java island. Due to the problem of blank data contained in SRTM data set, visualization in 3D of the develop DEM fails to present the surface of the volcano. Therefore, methods to counter the existence of blank data are developed in this research, namely Neighborhood Average and Population Average. The first is to replace blank data using the average value of the neighboring pixels, while the latter is to eliminate blank data using the average value of the whole pixels composing DEM. Comparison between those methods prove that the Neighborhood Average outperform Population Average, thus 3D visualization of DEM developed using Neighborhood Average produces smoother surface of Semeru volcano. REFERENCES: [1] SK Menhut No. 278/Kpts-VI/1997. (1997). Penyempurnaan Data Potensi ODTWA, Taman Nasional Bromo Tengger Semeru [Online]. Available at: [Accessed 17 August 2009]. [2]. (2004). Semeru [Online]. Available at: semeru.htm [Accessed 17 August 2009]. [3]. (2009). Gunung Semeru [Online]. Available at: everestamedia [Accessed 17 August 2009]. [4] Hidayat S and Risna RA. (2007). Ecological Research on Endangered Medical Plants in Bromo Tengger Semeru National Park. Journal Biodiversitas, Vol. 8, No. 3, pp , July [5]. (2009). Semeru [Online]. Available at: id.wikipedia.org [Accessed 17 August 2009] [6]. (2009). Hilang di Semeru, Mahasiswa UGM Belum Ditemukan [Online]. Available at: [Accessed 31 Juli 2009]. [7] Santoso B. (2000). Analisa Kimia Bahan Vulkanik Gunung Kelud, Gunung Semeru, dan Gunung Merapi. Journal Agrivita, Vol. 22, No. 1, February [8]. Google Earth [Online]. Available at: [Accessed 31 July 2009].

6 VI-62 The 6 th International Conference on Information & Communication Technology and Systems [9]. Yahoo Maps [Online]. Available at: maps.yahoo.com [Accessed 31 July 2009]. [10] Farr, TG, et al. (2007). The Shuttle Radar Topography Mission. Geophys, 45, RG2004, doi: /2005rg [11] Holz, S. (2004). GetSRTMData [Online]. Available at: [Accessed 3 December 2004].