New Era of Cartosat Satellites for Large Scale Mapping

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New Era of Cartosat Satellites for Large Scale Mapping 1031-1040_GS-003.qxd 8/12/10 2:39 PM Page 1031 New Era of Cartosat Satellites for Large Scale Mapping P.V. Radhadevi, S.S.Solanki, V.Nagasubramanian, Archana Mahapatra, D. Sudheer Reddy, M.V. Jyothi, Krishna Sumanth, J. Saibaba, and Geeta Varadan Abstract (Baltsavias et al., 2001; Jacobsen, 2003; Grodecki and Dial, Important considerations for large scale mapping from 2003; Fraser et al., 2002; Radhadevi et al., 2008), automatic satellite images are information content and geometric DTM/DSM generation (Jacobsen, 2004; Toutin, 2004; Poli et al., fidelity. Cartosat series of satellites with stereo mapping 2004). Comparison of information contents of high-resolution capability have become the mainstay towards large scale space images for the purpose of mapping is explained by mapping for urban and rural applications. Algorithms for Topan et al. (2004). The Indian space program witnessed processing of high-resolution Indian remote sensing satellite several major accomplishments and scaled newer heights in data has been developed at ADRIN and is used for opera- mastering space technology during the last few years. The tional generation of data products. Variations in the sensor Cartosat series of satellites with stereo mapping capabilities model with respect to the viewing geometries of Cartosat-1 have become technically suitable for large scale mapping for and Cartosat-2 are explained in the paper. Finally, an urban and rural applications. A method for strip processing assessment of the mapping potential of the satellites is the Cartosat-1 data is explained in Srivastava et al. (2008). discussed. The geometric accuracy achieved from Cartosat-1 In our work, the geometric model is based on the and Cartosat-2 images over the same checkpoints are com- viewing geometry of the satellite, combining the principles pared. DEM, geometric accuracy, and capability for topo- of photogrammetric collinearity equations, originally devel- graphic feature capture are good enough for making 1:10 000 oped for SPOT-1 (Radhadevi et al., 1994), and further adapted and 1:7 000 scale maps from Cartosat-1 and Cartosat-2, and tested for different sensor geometries from IRS-1C/1D to respectively. Based on the error estimation and analysis, it is Cartosat-2. The sensor position, velocity, and attitude is concluded that if the strict photogrammetric processing model derived from the given supplementary data (ADIF: Ancillary and ground control points are employed, high-resolution Data Information File format), and its variations are modeled satellite imagery can be used for the generation and update of using a simple polynomial model. The aim of this paper is topographic maps of scale 1:10 000 and larger. to bring out the correction methodologies for processing a stable and an agile satellite along with a comparative study on the mapping potential of the Cartosat series of satellites. Introduction Technical details for Bundle Block Adjustment (BBA) of The launch of high-resolution satellites, such as Cartosat-1 Multi-view images of Cartosat-2, DEM and Ortho-image and Cartosat-2 are revolutionizing the field of digital map- Generation and Matching of Ortho-images are explained. ping in India, particularly in urban areas where satellite imagery has rarely been used in the past. With the increased awareness of applications of high-resolution satellite imagery Features of Cartosat-1 and Cartosat-2 to solve local land administrative problems, more and more Cartosat-1 (IRS-P5) is the first satellite of ISRO designed to state governments are preferring high-resolution satellite provide high-resolution, along-track stereo imagery for mapping applications. The platform contains two panchro- imagery over existing methods. For the full exploitation of ϩ Ϫ the potential of this data, the “classical” satellite image matic camera payloads with 26° and 5° tilted with processing methods must be extended in order to describe respect to nadir. The base to height ratio is about 0.62. the imaging geometry. In general, the processing of these Stereo acquisition geometry of Cartosat-1 is shown in kinds of images provides a challenge for algorithmic Figure 1. Data is quantized with 10 bits and integration redesign, and this opens the possibility to reconsider and time is 0.336 ms with nominal GSD of 2.5 m. Each CCD has improve many photogrammetric processing components, 12,000 pixels, separated in to 6,000 each of odd and even such as image enhancement, image orientation (georeferenc- pixels. These odd and even pixel rows are separated by 35 ␮m (equal to five pixels in image plane). The staggered ing), ortho-rectification, DTM/DSM generation, and object extraction. Many different geometric models of varying array configuration of the cameras is shown in Figure 2. complexity, rigor and accuracy have been developed for Large swath, high-resolution and stable imaging configura- rectification of satellite images. In recent years, a large tions are the key features of Cartosat-1, which make it amount of research has been devoted globally to efficiently suitable for large scale mapping. utilize these high spatial resolution imagery data. Examples can be found in sensor modeling and image orientation Photogrammetric Engineering & Remote Sensing Vol. 76, No. 9, September 2010, pp. 1031–1040. Advanced data Processing Research Institute, Department 0099-1112/10/7609–1031/$3.00/0 of Space, Manovikasnagar P.O., Secunderabad -500 009, © 2010 American Society for Photogrammetry India ([email protected]). and Remote Sensing PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING September 2010 1031 1031-1040_GS-003.qxd 8/12/10 2:39 PM Page 1032 Figure 3. Paint-brush mode of acquisition of Cartosat-2. Figure 1. Stereo acquisition for Cartosat- 1 (source: ISRO). images of Cartosat-2, high-resolution DEMs can be produced. There are two CCD arrays in the payload: main array and redundant array, both having a 12,000 pixels array, similar to Cartosat-1. Several new technology elements like a high performance star sensor, improved Inertial Reference Unit, dual-gimbaled antenna, high-bit telemetry and data handling systems, light weight, and compact spacecraft structure have been introduced into the design of Cartosat-2. The precise ephemeris and attitude data allows for reducing the number of ground control points. Furthermore, this information enables direct georeferencing of the imagery without geomet- ric reconstruction of the imaging process and ground control. The data from the satellite is used for detailed mapping and other cartographic applications at the cadastral level, urban and rural infrastructure development and management, as well as applications in Land Information System and Geo- graphic Information Systems. More details about Cartosat-1 and Cartosat-2 payload systems are available in Krishnaswami (2002). Figure 2. Staggered array configuration. Preprocessing As illustrated in Figure 2, the optical detectors on the odd and even arrays are not arranged in a simple matrix of rows and columns on ground. The payload design of Cartosat-1 India’s highest resolution imaging satellite, Cartosat-2, and Cartosat-2 is such that the odd and even detectors are was launched in 2007. The advancement in GSD for Cartosat-2 staggered by five scan lines (35 ␮m) in the focal plane. is achieved with “Step and Stare” (SNS) mode of acquisition. However, this separation in the focal plane does not trans- Cartosat-2 is an advanced remote sensing satellite capable of late into a constant stagger in the image data. The impact of providing user requested scene-specific targeted imagery. line separation in the focal plane during imaging with With the panchromatic camera (PAN) on board, the satellite different viewing configurations is analyzed. Stagger varies can provide imagery with a spatial resolution of better than along the track with different scan angles which results in a one meter and a swath of 9.6 km on each overpass. In variable sampling pattern on ground. Therefore, video “SPOT” mode of imaging, the length of the strip can be as alignment by sliding the images from the two arrays (by five long as 290 km. If a programmed area of interest is wider lines) is not feasible. The stagger parameters are computed than 9.6 km, more than one swath is required to capture the by the reconstruction of the viewing geometry with a imagery. However, as the Cartosat-2 sensor can swing in any calibrated camera geometry model. Reconstruction of the direction, it can capture up to four swaths (covering an area viewing geometry includes the exterior and interior orienta- of up to 38 km wide) in one overpass or on one day. This is tions of the sensor. The image data of both staggered lines how the paint-brush mode of acquisition of Cartosat-2 is can be combined using a one-dimensional re-sampling exercised to increase swath in single overpass. The paint- which accounts for all these effects. The model is designed brush acquisition mode of Cartosat-2 is shown in Figure 3. to provide an accurate method of transforming points from The satellite can be steered up to 45° along as well as across image space to object space and vice versa. As Cartosat-2 is track, which make it a highly maneuverable satellite mission. more agile and its scan angle is continuously changing Because of the agility of the satellite, multi-view imagery also during acquisition, stagger correction and video alignment is can be acquired over the same area for production of digital a major preprocessing consideration for Cartosat-2 compared elevation models (DEMs). Three views; nadir, fore, and aft are to Cartosat-1. Figure 4 shows stagger value computed over a captured to form stereo triplets. By processing multi-view strip of Cartosat-2. 1032 September 2010 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING 1031-1040_GS-003.qxd 8/12/10 2:39 PM Page 1033 Ϫ where ( f, xs, ys) are the image coordinates, (X, Y, Z) are the coordinates of the object point, (Xp, Yp, Zp) is the perspective center d is the scale factor, and M is the rotation matrix, i.e., Ϫ Ϫ f m00 m01 m02 X Xp ϭ Ϫ xs d.
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