linear feature extraction from formosat-2 image for

Jurnal Ilmiah Geomatika Vol. 16 No. 1, Agustus 2010

LINEAR FEATURE EXTRACTION FROM FORMOSAT-2 IMAGE FOR TOPOGRAPHIC MAP UPDATE Antonius B Wijanarto1, Yusuf Rahadian2 Geomatic Research Institute, National Coordinating Agency for Surveys and Mapping 2 Information Technology for Natural Resources Management, Bogor Agricultural University (IPB) 1

ABSTRACT Aerial or satellite remote sensing is rapidly being applied to map updating, and in other regions, most map series have been partly or fully digitized. It is important to update maps because nowadays, many countries face problems in relation to outdated topographic maps. In this paper FORMOSAT-2 images used as reference. This is based on the consideration that the image of FORMOSAT-2 has a high resolution, so that is expected to provide more accurate information than the previous RBI map. The aim of this work is to extract linear features such as road and river from FORMOSAT-2 image for topographic map updating. Keywords

:

Topographic Map, Map Update, FORMOSAT-2 Image.

ABSTRAK Penginderaan jauh maupun foto udara telah diaplikasikan dengan cepat untuk pemuktahiran peta, dan di daerah lain kebanyakan peta-peta serial sebagian atau secara menyeluruh digitasi. Penting untuk memuktahirkan peta karena akhr-akhir ini banyak negara menghadapi maslah terutama dengan pemuktahiran peta topografi. Makalah ini membahas citra FORMOSAT-2 yang mempunyai resolusi tinggi, yang diharapkan dapat menyediakan informasi yang lebih akurat dari pada peta topografi sebelumnya. Tujuan dari kegiatan penelitian ini adalah mengekstrak fitur linear seperti jalan dan sungai dari citra FORMOSAT-2 untuk pemuktahiran peta topografi. Kata kunci

:

Peta topografi, pemuktahiran peta, FORMOSAT-2

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INTRODUCTION Some understanding of map according to some experts, map is a picture of the earth's surface on a plane with a certain scale, through a projection system. Map is a picture of the earth's surface is lessened by certain scale according the need. Map is an overview of the elements of nature or man-made, which is above or below the earth's surface depicted on a flat surface with a certain scale. A map is a two-dimensional representation of a three-dimensional space. Map are used by human beings, since humans do exploration and research. Although still in a very simple form that is in the form of sketches on location somewhere. Map is a source of information. Hopefully with the maps should be understood or understand better than before getting the map, but even if the existence of maps makes people not understand and confused, so this map can be said that no map or unfavorable. Less good is defined as less communicative, less rigorous, less explanation and the like. One of these maps is the Rupa Bumi Indonesia (RBI/Topographic Map). RBI provides various kinds of information that is needed by every user. Therefore along with the progress of time, then the map updates are supposed to do, so that the information provided is not outdated. In this paper we will discuss the extent to which the image of FORMOSAT-2 could reliably perform map updates. Updates are done only include elements of linear features from the map RBI. Linear elements are shoreline, roads and rivers features. Topographic Map As part of a geoscience expert community, we're certainly familiar with topographic maps. This topographic map is important, because as a base map, it can be used as the basis for the development as other thematic maps. Topographic maps are maps that show the position and place wherever located with the standard rules. This map contains very complete information about the altitude and slope of a place (contour lines), the signs of nature (rivers, roads, forests, lakes, etc.) and also the boundaries of administrative areas. In Indonesia, this map was made by an official institution that is BAKOSURTANAL (JKPP 2005). In addition, the topographic map is defined as a map that illustrates the form of relief (high or low) the earth's surface. A topographic map used in the contour lines (countur line) is the line connecting places that have the same height (Romenah et.al.) Topographic maps are also defined as a map showing the horizontal and vertical positioning of elements from natural and man-made elements in a certain shape, with attention to a map projection system used and the scale of the map. Generally, topographic maps are made for planning purposes, as presented on topographic maps elements of the earth's surface in accordance with the conditions at the time of making maps (Faridyuniar 2008). Topographic maps are also called the base map, because the topographic maps used as basis for the manufacture of other maps, either for making topographic maps with maps of

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smaller scale than the original map (original map), or also for making thematic maps. Here are examples of topographic maps: a) Planimetric maps Maps which provide information about several types of elements of the earth's surface, at the height of this map information is not presented. b) Technical Map Which presents detailed map Earth's surface for engineering projects (roads, dams), and also for purposes of construction cost estimates. c) Land Registration Maps / cadastre Map presents data on land ownership following the line angle and length, owner, parcel size, as well as some other information. d) Bathimetrik Map Map presents the water depth and configuration of the underwater topography, which generally has a coordinate system referenced to the topographic map coordinate system. Topographic maps have advantages compared with other maps which can be used to determine the height of a place and to estimate the steepness or slope. Some provisions in the topographic map: a) The more tightly contour distance from one another indicates the region has continued to widen. Conversely the less the distances between the contours show the more sloping areas. b) Contour lines are marked serrated showed depression (pit / basin) at the peak, eg peak heavily. c) Topographic maps using large-scale, between 1: 50,000 to 1: 100 000. Linear Feature Linear feature is a geographic feature that can be represented by a line or set of lines. All those lines on your map are symbols and are important. For example: rivers, roads, railways and boundaries are examples of linear features. Identifying a linear feature in the input image requires several steps. First, a list of pixels within a range of data values is found. Second, pixels within this list are examined to determine if they are colinear. Lastly, the task examines the colinear list of pixels and finds pixels which are adjacent within specified parameters. The colinearity detection is done via the Hough Transform (Gonzalez & Wintz 1987). Once features have been identified, information about the features is written to an output file and profile plots are generated. FORMOSAT-2 The first remote sensing satellite developed by National Space Organization (NSPO) of Taiwan Earth imaging satellite, FORMOSAT-2, successfully launched on May 21, 2004 with a high resolution of 2 meter panchromatic data and 8 meter multispectral satellite image data. The main mission of FORMOSAT-2 is to conduct remote sensing imaging over

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Taiwan and on terrestrial and oceanic regions of the entire earth. FORMOSAT-2 is use for a great variety of applications such as in land use, agriculture and forestry, environmental monitoring, natural disaster evaluation, and in support of research interests, in particular with the ISUAL (Imager of Sprites and Upper Atmospheric Lightning) instrument.

Figure 1. Linear Feature Symbol (Williams 2010). The images captured by FORMOSAT-2 during daytime can be used for land distribution, natural resources research, forestry, environmental protection, disaster prevention, rescue work, and other applications. When the satellite travels to the eclipsed zone, it will observe natural phenomena such as lighting in the upper atmosphere which can be used for further scientific experiments. FORMOSAT-2 carries both "remote sensing" and "scientific observation" tasks in its mission. The spacecraft is operating nominally as of 2006.

Figure 2. EADS Astrium SAS/ NSPO (National Space Programme Office) of Taiwan.

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Earth observation systems offer more or less broad coverage and ever-finer detail, but their revisit frequency is still limited for surveillance purposes. FORMOSAT-2, the first and only high-resolution satellite with a daily revisit capability, overcomes this obstacle to provide a new response to your surveillance needs.

Figure 3. Map of FORMOSAT-2 orbits and coverage areas: the satellite completes exactly 14 orbital revolutions every day. Daily monitoring capability of FORMOSAT-2 is to acquire repeat imagery of an area of interest every day with the same sensor, from the same angle and under the same lighting conditions guarantees a timely flow of compatible data. FORMOSAT-2’s very specific orbit means it can acquire any scene in its coverage area every day - geosynchronous orbit under the same lighting conditions - sun-synchronous orbit - and from the same angle. The satellite can also be tasked to cover a specific area and period of interest. This solution is unrivalled today in the civil high-resolution satellite market. Unlike other very-high-resolution satellites, FORMOSAT-2 guarantees the same viewing parameters every time, so you know how many images you will obtain and you can be sure they will register perfectly. FORMOSAT-2’s local equator-crossing time is 9.30 a.m., where most optical satellites currently operating cross one hour later. This slightly earlier time, combined with daily revisits, increases the chances of acquiring useful imagery in equatorial regions where convective clouds form throughout the morning. FORMOSAT-2’s spatial resolution — 2 metres in panchromatic (black and white) and 8 metres in multispectral (colour) mode — is an additional asset for surveillance. Ideally suited to strategic and operational intelligence missions, it is able to identify and characterize military sites, naval bases, air bases and refugee camps; perform reconnaissance of ships, aircraft and other assets; and surveillance of strategic or industrial facilities. Like very-high-resolution satellites, FORMOSAT-2 has four bands: blue, green, red and near-infrared. Combined with the red and green bands, the blue band affords the ability to produce natural-colour composites without special processing. Used alone or with other channels, it also provides specific information for mapping shallow waters, distinguishing between bare earth and vegetation, mapping forests and identifying crops, and making

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atmospheric corrections. FORMOSAT-2's unique advantages offer:  Guaranteed data acquisition: with the Priority option, the satellite can be tasked daily until it acquires the image you want, increasing the chances of obtaining imagery in unfavourable weather conditions.  Fast delivery: data are posted on an FTP site within 24 to 48 hours of acquisition, thus ensuring maximum currency of information.  Close tracking capability: imagery can be acquired daily or at regular intervals to keep track of fast-changing situations, providing a reliable revisit capability for your projects over the long term.  An ideal complement to submetric data: the combination of very-high-resolution archive imagery and FORMOSAT-2 multidate imagery provides a cost-effective monitoring solution.  A new coverage solution: FORMOSAT-2’s revisit frequency means you can quickly acquire coverage of your area of interest. FORMOSAT-2 products are available in 3 preprocessing levels:  Level 1A: Radiometric corrections to remove distortions due to variations in sensitivity of elementary detectors in the imaging sensor.  Level 2A: Radiometric corrections identical to Level 1A. Geometric corrections to frame the image in a given map projection (default projection is UTM WGS 84).  Ortho: Radiometric corrections identical to Level 1A. Geometric corrections to frame the image in a map projection specified by the user and to remove relief distortions (map and/or control points and digital elevation model supplied by user). RBI Map Indonesia as an archipelagic country consisting of land and sea areas covering approximately 17,504 islands (Ministry of Home Affairs, 2003). In these islands there are 726 local languages (by Summer Institute of Linguistics). Diversity of languages is very influential in the naming procedure Topographic elements that can result in certain cases on the topographic map of the writing element. Therefore, the National Standardization Team Name Topographic which was established by the President of the Republic of Indonesia Regulation No. 112 dated December 29, 2006, has full authority to regulate procedures for the standardization of topographic names. This is in accordance with UN Resolution No. 4 Year 1967 from The First UN Conference on Standardization of Geographical Names in Geneva to recommend to the establishment of the National Geographical Names Authority (the national institute of geographical names authorities) in each member state. Institutional forms of authority are tailored to the local government structure which has the task to standardize names and functions of the principal topographic elements, as a step to support the standardization of topographic element names in the international community. Topographic elements are part of the earth's surface that is above and / or below the sea surface that can recognize its identity as a natural element and / or man-made elements. Topographic elements consist of three elements, namely the physical elements, artificial elements, and elements of administration. Where:

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a)

b) c)

The physical element is the element that is on the surface of land, sea and below sea level, whose identity can be recognized. Examples include: mountain, mountains, hills, plateaus, caves, valleys, lakes, rivers, estuaries, oceans, seas, straits, bays, islands, island, cape, peninsula, seamount (seamount), and trough. Man-made element is the element of infrastructure is a public facility, social, economic and cultural. Examples include: airports, dams, reservoirs, bridges, tunnels, lighthouse, residential areas, industrial estates, forests, temples, monuments. The element is the functional areas of administrative government agencies, with clear administrative boundaries. Examples include: village, district, city, district, and province.

Topographic names are proper names of topographic elements which consist of two elements, namely elements of the generic and specific elements. Generic element is a name that describes and / or describes the general form of topographic elements in the Indonesian language or regional language. Specific element is the proper name of the generic elements that have been mentioned previously.

METHODS Time and Location This research will be conducted from February 2010 – March 2010, including data processing and make a final report. Meanwhile, data collecting and filed survey will be taken in Surabaya – East java. The study area is Surabaya Area which located in region of East Java Province. Geographically, it is located between 112o 36' – 112o 54' east longitude and 07o12' – 07o 21' south latitude. Topographically, Surabaya, located at an altitude of 36 meters above sea level (lowland), except in the southern part there are two sloping hill with a height of 25-50 meters above sea level. Data Requirement Data requirement to achieve the goal of this research can be divided into raster and vector data. Listed summarize as the following Table 1:

Table 1. Raster Data. Instrument Acquisition Date Time Data level Radiometric resolution Spatial resolution Viewing angel Along-track Across-track Satellite Angles Incidence Azimuth

Formosat 2 Pankromatic

Multispectral

2008/08/04 02:11:53.7 1A 8-bit P 2 meters

2008/08/04 02:11:54.1 1A 24-bit M 8 meter

0.526930 2.927296

0.361736 2.917039

3.394798 293.105721

3.354969 289.971366

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Table 2. Vector Data Data Type Topographic Map (Rupa Bumi Indonesia)

Date Production 2003

Spatial Resolution 1 : 25.0000

Source of Data BAKOSURTANAL

Geo Rectification General of research methodology can be seen in Figure 4. First, the image process is geo Rectification. The process is Ortho-Rectification image. There are two steps to rectify the original image into image map, namely: - Geometric operation to compute the cell coordinates in the original image for each map image cell; and - Radiometric operation to compute the intensity value or digital number (DN) of the map image cell.

Figure 4. Flowchart of the research method. However, it appears a new notion these last years: the true ortho-photo or ortho-image. The term true orthoimage is generally used for an ortho-image where all surface elements (generally buildings, bridges, trees) are also rectified to the orthogonal projection taking thus into account the height of the surface (Amhar et al.,1998). Because the reality of true ortho-image is a question of scale, this notion should now be addressed with satellite HR satellite images.

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False-color display of raw provides modest differentiation of surface materials for this small area of desert terrain (width of area is 5 km).

panchromatic band for the sample area. This band has 15-m spatial resolution (compared to 30-m resolution for the multispectral bands).

Areas of different surface material are thus more clearly defined than in the RGB display of raw image bands, but the image is noisy, and the lack of topographic context hampers interpretation of geologic relationships and structure.

Multiresolution fusion not only enhances the spatial resolution of the ratio combination, it also adds back topographic illumination and shading effects and suppresses ratio image noise, aiding both differentiation of materials and interpretation of their geologic and structural relationships.

Figure 5. Combining true color (RGB) and panchromatic (PAN) to pansharpening (Source: MicroImages 2006). Pansharpening Image Pansharpening is a process of merging high resolution panchromatic and lower resolution multispectral imagery to create a single high resolution color image. The pansharp algorithm applies an automatic image fusion that increases the resolution of multispectral (color) image data by using a high-resolution panchromatic (B&W) image. Most Earth resource satellites provide multispectral images at a lower spatial resolution and panchromatic images at a higher spatial resolution. This allows you to easily fuse images acquired simultaneously by the same sensor. Alternatively, you can fuse images from different sensors. The algorithm is an effective post processing algorithm that can produce a more natural result in the green band which is closer to what is found in aerial photography PANSHARP works with 8-bit, 16–bit, or 32-bit real data types.

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Image Digitizing Digitization can generally be defined as the process of converting analog data into digital format. Certain objects such as roads, rivers, settlements and other previously in raster format at a high resolution satellite image can be converted into digital format by the process of digitization. Digitization process undertaken in this research is directly digitized in the computer (on screen digitizing). Image Comparison This process is intended to compare the linear features derived from the RBI with linear features extracted from the FORMOSAT-2 image. This is necessary to see the precision and accuracy of the FORMOSAT-2 image in the interpretation of an area. So the output will be a recommendation whether the FORMOSAT-2 image could serve as a reference for updating the RBI or not.

EXPERIMENTAL AND RESULT In this experiment, we used maps of Surabaya with a scale of 1: 25 000 originating from the RBI as a reference which is then compared with FORMOSAT-2 image. Based on data from the field and processed data obtained as follows. The data is used to perform geometric ortho assessment to generate the image. After the delineation for each element belonging to the category of linear RBI the next feature comparison between linear features generated from FORMOSAT-2 with a linear feature on the RBI. The area is the coastline, road and river. Coastline Figure 6 provides information that based on the results of visual interpretation of the coastal area in areas of research, showed that the area has undergone substantial changes in large, especially at the pond area. The addition of the pond area looks quite large. In coastal areas FORMOSAT-2 has been able to do delineation of the boundary between the coastline, dykes and pools of water with very clear. Road and River With high resolution FORMOSAT-2 has a good ability in differenciating between one object with another object. In terms of delineation of linear features (roads and rivers) FORMOSAT-2 can show very well, judging by the detail and accuracy. This can be seen from the ability of FORMOSAT-2 is able to show road detail not only the major streets even though the aisles. From a visual comparison between the FORMOSAT-2 with RBI diiketahui that FORMOSAT-2 can mutually agree membekiran more information when compared with existing RBI. From the image obtained visually, FORMOSAT-2 can show the detail of each object with a very good and high level of accuracy.

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Table 3. RPC report. ENVI ENVI Map Total 112.72 112.74 112.73 112.74 112.76 112.79 112.8 112.8 112.77 112.75 112.75 112.73 112.68 112.68 112.69 112.71 112.76 112.77 112.77 112.77 112.75 112.73 112.77 112.79 112.73 112.68 112.69 112.71 112.67 112.68 112.7

Ground GCP (x,y,z), RMS

Control Points Image Error:

Points Table (x,y), 3.078393

Table

-7.25 -7.27 -7.28 -7.29 -7.28 -7.28 -7.28 -7.25 -7.25 -7.24 -7.23 -7.23 -7.23 -7.26 -7.26 -7.27 -7.3 -7.31 -7.34 -7.33 -7.33 -7.35 -7.38 -7.37 -7.36 -7.36 -7.34 -7.31 -7.31 -7.28 -7.29

21 24 26 30 38 32 21 23 21 21 20 17 16 17 16 16 22 21 22 20 22 22 19 23 20 27 28 22 27 38 37

3908.25 5398.24 4587.5 5486.61 6534.67 8048 8690 7984.5 6498.5 5581.22 5046.75 4159.25 1700.71 1939.46 2580.85 3423.23 6781 7284.76 7626.5 7521.78 6563.15 5603.9 8240.5 9435.25 5703.91 3187.13 3578.75 4145.25 2189.75 2434.76 3553

Predict

(x,y),

Error

(x,y),

RMS

Error

1237.25 2551.84 2778 3751.61 2706.15 2463.75 2225.25 1003.5 828.25 719.42 10.25 486.25 747.78 2288.5 2318.73 2479.87 3789.5 4224.89 6063.5 5428.85 5507.67 6575.17 8246 7522 7094.8 7688.85 6784 4978.5 5059.5 3497.16 3647

3908.43 5397.81 4594.13 5486.16 6534.17 8044.78 8688.91 7987.08 6502.75 5581 5045.75 4159.23 1701.38 1939.7 2580.92 3423.1 6777.86 7283.83 7627.91 7520.92 6562.59 5603.31 8242.59 9436.18 5703.35 3187.06 3580.69 4143.79 2192.07 2434.91 3544.77

1237.11 2551.75 2786.88 3751.36 2706.03 2463.88 2224.93 1001.67 830.25 719.27 8.52 485.91 747.63 2287.93 2318.4 2480.04 3788.22 4224.82 6062.52 5428.73 5507.75 6574.75 8246.61 7521.75 7094.55 7688.64 6786.34 4978.42 5055.86 3496.92 3646.34

0.18 -0.43 6.63 -0.45 -0.5 -3.22 -1.09 2.58 4.25 -0.22 -1 -0.02 0.67 0.24 0.07 -0.13 -3.14 -0.93 1.41 -0.86 -0.56 -0.59 2.09 0.93 -0.56 -0.07 1.94 -1.46 2.32 0.15 -8.23

-0.14 -0.09 8.88 -0.25 -0.12 0.13 -0.32 -1.83 2 -0.15 -1.73 -0.34 -0.15 -0.57 -0.33 0.17 -1.28 -0.07 -0.98 -0.12 0.08 -0.42 0.61 -0.25 -0.25 -0.21 2.34 -0.08 -3.64 -0.24 -0.66

0.23 0.44 11.08 0.52 0.51 3.22 1.14 3.16 4.69 0.26 2 0.34 0.69 0.61 0.33 0.21 3.39 0.93 1.72 0.87 0.56 0.72 2.18 0.96 0.61 0.22 3.04 1.46 4.32 0.28 8.25

CONCLUSION Results of map updating project in Surabaya have demonstrated that Formosat-2 panchromatic and multispectral image data are suitable for updating maps at 1: 25.000 scales. To update 1:25.000 scale maps, image orthorectification using physical model with GPS measurements for RPC collection. Merging of Formosat-2 panchromatic 2 m and multispectral 8 m data and pansharpening process enhances significantly interpretabilities of features in images. The success of this project has indicated that the updating procedure applied in the National Coordinating Agency for Surveys and Mapping are appropriate and effectives. Formosat-2 data could be used for revising of 1:10.000 scale map, but orthorectification accuracy need to be improved and surely it will need more field work compare to updating of 1/25.000 scale map.

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Figure 6. Coastal area – compare RBI (blue) and visual digitizing from FORMOSAT-2 (red).

(a)

(b) Figure 7. Comparing between FORMOSAT-2 (Pink) and RBI (red) to show street at Coastal Area (a), and Downtown (b).

Figure 8.

Figure 9. Comparing between FORMOSAT-2 (Light Blue) and RBI (Blue) to show river. 97

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REFERENCES Amhar, F., Jansa, J. and Ries, C. 1998. The generation of true orthophotos using 3D building model in conjunction with a conventional DTM. International Archives of Photogrametry and Remote Sensing, 32(B4), 16-22. Garulli A., Antonio G., Andrea R., Antonio V. _______. Simultaneous Localization and Map Building Using Linear Features. Dipartimento di Ingegneria dell’Informazione, Universit`a di Siena Via Roma 56, 53100 Siena, Italy. MicroImages, Inc. 2006. Multiresolution Fusion - Pan-Sharpening of Landsat Band-Ratio Images. 11th Floor - Sharp Tower • 206 South 13th Street • Lincoln, Nebraska USA Mulyana, A. K. 2007. Analisa Tekstur Citra IFSAR untuk Ekstraksi Fitur Rupa Bumi. Badan Koordinasi Survei dan Pemetaan Nasional. Bogor – Indonesia. National Space Organization (NSPO). FORMOSAT 2: Program Description. www.nspo.org.tw/2008e/projects/project2/intro.htm (Retrieved April 5, 2010). Romenah. ______. Pengetahuan Peta. Tersedia pada website elcom.umy.ac.id/ elschool/muallimin_muhammadiyah/file.php/1/materi/Geografi/PENGETAHUAN%20P ETA.pdf. Satellite Imaging Corporation. Formosat-2 Satellite Sensor. http://www. satimagingcorp.com/satellite-sensors/formosat-2.html (Retrieved April 25, 2010). Tsoulos, L., Andriani S. 2000. Assessment of Data Acquisition Error for Linear Features. Faculty of Rural and Surveying Engineering - Cartography Laboratory, National Technical University of Athens. Greece. William, H. 2003. What is Orienteering? http://www.williams.edu/Biology/ Faculty_Staff/hwilliams/Orienteering/o~index.html.

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