Journal of Environmental Research And Development Vol. 5 No. 1, July-September 2010

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1 COMPARATIVE STUDY OF HYDRO-MORPHOLOG- ICAL PARAMETERS EXTRACTED FROM DIGITAL ELEVATION MODEL (DEM) GENERATED FROM STEREO PAIR OF CARTOSAT- I SATELLITE DATA, SHUTTLE RADAR TOPOGRAPHIC MISSION (SRTM) AND GTOPO Vishal Arora 1 and Parmita Bose* 2 1. Gujarat State Disaster Management Authority (GSDMA), Gandhinagar, (INDIA) 2. Center of Remote Sensing and GIS, SOS Earth Science, Jiwaji University, Gwalior, (INDIA) Received February 13, 2010 Accepted August 09, 2010 ABSTRACT Hydro-morphologic parameters such as the flow direction, flow accumulation and basin boundary are the most important for hydrological study of an area. Digital Elevation Model (DEM) is an important tool for delineation of hydro-morphologic parameters. Recent days there are various sources from where the Digital Elevation Model (DEM) data can be acquired. In the present study the hydro-morphologic parameter which has been derived from the DEM of Cartosat-1 stereo data has been compared with the parameter derived from the DEM of Shuttle Radar Topographic Mission (SRTM) and GTOPO data. The study shows that Cartosat -I data gives a better result for the extraction of Hydrological parameters as compared to SRTM and GTOPO. Key Words : Digital Elevation Model (DEM), Cartosat -I stereo pair, RPC, Orthorectification, Sink Fill, Flow Direction, Flow Accumulation INTRODUCTION Understanding of the hydro-morphological characteristics helps to create a better picture of an area which can be applied for better * Author for correspondence planning and management purpose. Hydromorphologic parameters are the most important for hydrological study of an area. These parameters include slope, aspect, hill shading, flow direction, flow accumulation, flow length, and watershed boundaries etc. In 60

present day, Satellite Remote Sensing with the combination of Geographical Information technology and relevant ground data can bused to monitor, assess of hydromorphologic parameters.

2 present day, Satellite Remote Sensing with the combination of Geographical Information technology and relevant ground data can bused to monitor, assess of hydromorphologic parameters. The high resolution satellite images and advance photogrammetric techniques have brought a major change in this respect. 1 With the availability of satellite data with stereo capability, it has become possible to generate accurate Digital Elevation Model (DEM) with the high level of accuracy and extract its terrain parameters. Now a day there are various sources from where the Digital Elevation Model (DEM) data can be acquired. 2 Many approaches have been done in this context by many researchers But in order to ensure hydromorphologic product s accuracy, comparative study of DEMs is necessary. So, in the present paper, the comparative study of the hydro-morphological parameters has been carried out using SRTM DEM, GTOPO DEM and the DEM derived from stereo pair of Carotosat- I satellite data. Mainly the two hydro-morphological parameters i.e. Flow direction and the Flow Accumulation has been taken into consideration. Study area The study area is a part of river Kelua and Birupa located in the Jajpur district of Orissa state with geographical area of about 2,888 km 2. Jajpur is honoured for its natural resources, mines and industries and is located between the 'N and 'N latitudes and 'E and 'E longitudes as shown in Fig. 1. In the Northern boundary of the district, there are river Baitarini and districts Keonjhar and Bhadrak, in the south there is Cuttack district, in the east there is Dhenkanal and in the west lies Kendrapara district. Laterite and brown kind of earth soil are found in this area, which is broadly deep sandy loamy to clayey loam with low organic matter; it is saline and slightly acidic. The average annual rainfall in this area is mm. For the extraction and comparison of hydro- morphologic parameters a micro watershed has been considered (Fig.1). Fig.1: Location map of the study area 61

3 MATERIAL AND METHODS Data Used Cartosat-1 stereo data (2.5m spatial resolution), acquired on 2nd June 2006, SRTM (90meter spatial resolution) acquired on 7th April 2004, GTOPO (1 km spatial resolution) acquired on 23rd February 2006, Survey of India Topographical sheet No. 73L/2, GPS Field Data: The total of 21 Ground Control Points (GCPs) around Kelua and Birupa Rivers (Table 1.) Table 1 : Ground Control Points (GCP) and relative difference GPS TOPOSHEET S.No. Longitude Latitude Elev. Longitude Latitude Elev Differ ence

The DEM extraction and the Hydrologic parameter extraction has been carried out in different steps. Fig. 2 is showing the detailed methodology of the study.

The undefined low- lying Toposheet Cartosat SRTM Gtopo Dem Generation Accuracy assessment Extraction of Hydro morphological parameters cells were then compared to their surrounding cells.

4 The DEM extraction and the Hydrologic parameter extraction has been carried out in different steps. Fig. 2 is showing the detailed methodology of the study. Generation of depression less SRTM and GTOPO DEM SRTM and GTOPO data has been imported and reprojected. The undefined low- lying Toposheet Cartosat SRTM Gtopo Dem Generation Accuracy assessment Extraction of Hydro morphological parameters cells were then compared to their surrounding cells. Those low lying cells are known as sinks. Sinks or the local depressions are removed with the SINK Comparison Fig. 2 : Flow chart of the methodology FILL command, as the sinks in the data may mislead to distorted results. So the Sinks firstly removed from the data and depression less DEM has been generated (Fig. 3a and 3b). 3a. SRTM data 3b. GTOPO data Fig. 3 : Showing the DEM of SRTM and GOPO data 63

Ortho rectification and DEM extraction from Cartosat-1 stereo pair In the study, the Digital Elevation Model was generated using Band A (Aft image) and Band F (Fore image) of Cartosat-1 stereo data.

5 Ortho rectification and DEM extraction from Cartosat-1 stereo pair In the study, the Digital Elevation Model was generated using Band A (Aft image) and Band F (Fore image) of Cartosat-1 stereo data. Leica Photogrammetry Suite classical point measurement tool was used to generate DEM using Cartosat-1Rational Polynomial Coefficient (RPC) file. A field survey was carried out by GARMIN GPS and Ground Control Points (GCPs) have been collected and used for the reference to get the tie points for othorectification (Table 1). Survey of India topographical sheet, 73-L/2 was also used as reference. The elevations in the Topographical sheet were in Mean Sea Llevel (MSL). So these were converted into WGS 84 datum as the relative difference between both the datum was 60m, so the elevations taken from SOI Topographical sheet were increased in the same proportion. Firstly the.blk file has been created using co-ordinate system in Horizontal (Projection type UTM, Spheroid/Datum WGS 84) and Vertical (Spheroid/Datum WGS 84, Elevation Units meters, Elevation Type height) and after adding GCPs, the Triangulation has been done and the DEM was generated. For the better accuracy, the iteration process has been adopted and the final DEM prepared (Fig. 4). Fig. 4 : Digital Elevation Model (DEM) derived from Cartosat I stereo pair Extraction of hydro-morphological parameters A watershed boundary digitized from Survey of India topographical sheet in 1 : 50,000 scale was laid on the DEMs and the boundary of the watershed was subseted from the SRTM and GTOPO DEM, and the DEM prepared from Cartosat-1 satellite image. Firstly the Flow direction maps have been calculated using the depression less DEM for Catrosat-1, SRTM and GTOPO DEM using the flow direction 64 function separately for each (Fig. 5a to 5c). Then the Flow Accumulation Maps have been extracted using flow accumulation function by giving the Flow direction map as input (Fig. 6a to 6c). Cells with a high flow accumulation are areas of concentrated flow and used to identify stream channels. The operation has been used to find the drainage pattern of a terrain. Those hydro-morphological parameters extracted from the different DEMs were

6 a b c Fig. 5 : Flow direction maps derived from the DEM of Cartosat- 1(Fig. 5a), SRTM (Fig. 5 b) and GTOPO (Fig. 5c) a b c Fig. 6 : Flow accumulation maps derived from the DEM of Cartosat-1(Fig.6a), SRTM (Fig. 6b) and GTOPO(Fig. 6c) 65

7 compared for the sake of maximum accuracy RESULTS AND DISCUSSION DEM validation and comparison of hydromorphological parameters The hydro-morpho parameters derived from all the three DEMs have been compared one by one. The Flow direction map derived from Cartosat-1 DEM showing the highest number of pixels. The drainage derived from topographical sheet in 1:50000 scale is perfectly matching on this image though it is not joined from several places and is showing a large dendritic drainage pattern. The SRTM map is also not joined and having a number of pixels indicating certain flow direction. When the drainage derived from topographical sheet in 1:50000 scales is laid over it is not fitting perfectly comparatively. In the Flow direction map of GTOPO, as the resolution is very low, it is unable to show the desired results. The main flow of the drainage is towards SE direction. In the Flow accumulation map, in spite of showing some disjoints, drainage is matching accurately on map derived from the DEM of Cartosat-1, as well as on SRTM map but again on GTOPO, it is not showing any interpretable result. CONCLUSION In the accuracy point of view, the Cartosat- I data is good for the extraction of hydrological parameters as compared to GTOPO30 and SRTM data. The error percentage is also very low and is most useful in assessing the amounts and quality of water moving and accumulating on the surface. It can also help in real time monitoring, early warning and quick damage assessment of the disasters thereby applying the best and the most suitable technique for better planning purposes. The Hydro- Morphological parameters derived from Cartosat-1 DEM are supposed to give the best results and accuracy if compared with Hydro-Morphological parameters derived from SRTM and GTOPO30 DEMS. REFERENCES 1. Krishnaswamy M. and Kalyanraman S., Indian Remote Sensing Satellite Cartosat- 1: Technical features and data products, GIS Develop., (2004). 2. Reinartz P., Müller R. L. M. and Schroeder M., Accuracy analysis for DSM and orthoimages derived from SPOT HRS stereo data using direct georeferencing, ISPRS J. Photogram. Remote Sen., 60, , (2006). 3. Hashim M. and Kadir W.H.W., Comparison of JERS-1 and Radarsat Synthetic Aperture Radar Data for Mapping Mangrove and Its Biomass, AARS, ACRS, (1999). 4. Andrea S., Johnson D.E., Harris N.R. and Casady G.M., Stream change analysis using Remote Sensing and Geographic Information Systems(GIS), J. Range Manage, 54, ( A 22 - A50), (2001). 5. Hiranao A., Roy W. and Lang H. Mapping from ASTER stereo image data: DEM validation and accuracy assessment, ISPRS J. Photogram. Remote Sen., 57, , (2002). 6. Hye-jin K., Dae-sung K., Hyo-sung L. and Yong-il K., A study on the generation 66

8 of the KOMPSAT-1 RPC Model, ISPRS Commission III Symposium, Sept. 9-13, Graz, Austria, (2002). 7. Kamp U., Bolch T. and Olsenholler J., DEM Generation from ASTER Satellite Data for Geomorphometric analysis of Cerro Sillajhuay, Chile/Bolivia, ASPRS, Anchorage, Alaska, (2003). 8. Grodecki J., Dial G. and Lutes J., Mathematical Model for 3D feature extraction from multiple satellite images described by RPCs. ASPRS Annual Conference Proc., Denver, Colorado, USA, (2004). 9. Das B. P., Environmental Problem of Drainage Congestion in Mahanadi Delta, India: Case Study of a Remedial Direct Cut, Proc. World Water Environ. Resou., Alaska, USA. doi /40792(173), 502, (2005). 10. Fraser C. S., Dial G. and Grodecki J. Sensor orientation via RPCs., ISPRS J. Photogram. Remote Sen., 60(3), , (2005). 11. Kornus W., Alamus R., Ruiz A. and Talaya J., DEM generation from SPOT-5 3-fold along track stereoscopic imagery using autocalibration, ISPRS J. Photogram. Remote Sens., 60, , (2005). 12. Kumar A., Cartosat-1 (IRS P-5) Stereo data processing : A case study of Dehradun area, GIS Development Map India Forum, New Delhi, India, (2006). 13. Lehner M. and Müller R. R. P., Stereo Evaluation of CARTOSAT-1 Data on Test Site 5 First DLR Results, Proc. ISPRS- TC IV Symposium, Sept , Goa, India, (2006). 14. Beurs K.M.D. and Henebry G.M., Beurs, A statistical framework for the analysis of long image time series, Int. J. Remote Sens., 26(8), , (2005). 15. Department of Water Resources, G. O. I., River system Orissa, ( 2004). 16. Lillesand T. M. and Kiefer R. W., Remote Sensing and Image Interpretation, New York, John Willy and Sons, (2000). 17. Portmann F. T., Hydrological runoff modeling by the use of remote sensing data with reference to the and 1995 Floods in the River Rhine Catchment, Hydrological Processes, 11, , (1997). Save Earth. We have no where else to go! 67

Evaluation of DEM, and orthoimage generated from Cartosat-1 with its potential for feature extraction and visualization

American Journal of Remote Sensing 2013; 1(1) : 1-6 Published online February 20, 2013 (http://www.sciencepublishinggroup.com/j/ajrs) doi: 10.11648/j. ajrs.20130101.11 Evaluation of DEM, and orthoimage