Articles
<![CDATA[Novel Image Mosaicking of UAV’s Imagery using Collinearity Condition ]]>
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fourry Handoko]]>;
<![CDATA[Silvester Sari Sai]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 3: June 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijece.v7i3.pp1188-1196
<![CDATA[This paper presents a preliminary result of ongoing research on unmanned aerial vehicle (UAV) for cooperative mapping to support a large-scale urban city mapping, in Malang, Indonesia. A small UAV can carry an embedded camera which can continuously take pictures of landscapes. A convenient way of monitoring landscape changes might be through accessing a sequence of images. However, since the camera’s field of view is always smaller than human eye’s field of view, the need to combine aerial pictures into a single mosaic is eminent. Through mosaics, a more complete view of the scene can be accessed and analyzed. A semi-automated generation of mosaics is investigated using a photogrammetric approach, namely a perspective projection which is based on collinearity condition. This paper reviews the general projection model based on collinearity condition and uses that to determine a common projective plane from images. The overlapped points for each RGB channel are interpolated onto that of orthographic plane to generate mosaics. An initial attempt shows a promising result.]]>
<![CDATA[Aplikasi Metode Object Based Image Analysis (OBIA) untuk Identifikasi Atap Bangunan ]]>
<![CDATA[Alifah Noraini]]>;
<![CDATA[I Nyoman Sudiasa]]>;
<![CDATA[Martinus Edwin Tjahjadi]]>
<![CDATA[ Poltanesa Vol 22 No 1 (2021): Juni 2021 ]]>
Publisher : <![CDATA[P2M Politeknik Pertanian Negeri Samarinda ]]>
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DOI: 10.51967/tanesa.v22i1.462
<![CDATA[Salah satu permasalahan dalam proses pembuatan peta skala besar adalah belum terdapat metode ekstraksi objek secara otomatis, sehingga dijitasi secara manual masih dilakukan. Metode ekstraksi objek secara otomatis diharapkan dapat mempercepat pemetaan skala besar. Di Indonesia, pemetaan skala besar digunakan untuk penyusunan Rencana Detil Tata Ruang (RDTR) Kota/ Kabupaten. Objek detil yang terdapat dalam dokumen RDTR tersebut adalah bangunan. Tujuan dilakukan penelitian ini adalah identifikasi atap bangunan menggunakan metode klasifikasi berbasis objek. Data yang digunakan berupa citra foto udara. Dilakukan proses segmentasi menggunakan algoritma multiresolusi dengan parameter segmentasi skala, bentuk, dan kekompakan Setelah proses segmentasi, dilakukan proses klasifikasi menggunakan metode nearest neighbor. Hasil penelitian menunjukkan bahwa masih terdapat kesalahan dalam proses klasifikasi objek. Atap bangunan tidak teridentfikasi secara keseluruhan dalam kelas objek bangunan.]]>
<![CDATA[Fast and stable direct relative orientation of UAV-based stereo pair ]]>
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fransisca Dwi Agustina]]>
<![CDATA[ International Journal of Advances in Intelligent Informatics Vol 5, No 1 (2019): March 2019 ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
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DOI: 10.26555/ijain.v5i1.327
<![CDATA[Coplanarity-based relative orientation (RO) is one of the most crucial processes to obtain reliable 3D model and point clouds in Computer Vision and Photogrammetry community. Whilst a classical and rigorous procedure requires very close approximate values of five independent parameters, a direct method needs additional constraints to solve the parameters. This paper proposes a new approach that facilitates a very fast but stable and accurate solution from five point correspondences between two overlapping aerial images taken form unmanned aerial vehicle (UAV) flight. Furthermore, if 3D coordinates of perspective centers are available form geotagged images, rotational elements of the RO parameters can be quickly solved using three correspondences only. So it is very reliable for a provision of closed-form solutions for the rigorous methods. Our formulation regards Thompson’s parameterizations of Euler angles in composing a coplanarity condition. Nonlinear terms are subsequently added into a stereo parallax within a constant term under a linear least squares criteria. This strategy is considered new as compared with the known literatures since the proposed approach can find optimal solution. Results from real datasets confirm that our method produces a fast, stable and reliable linear solution by using at least five correspondences or even only three conjugate points of geotagged image pairs.]]>
<![CDATA[Precise Wide Baseline Stereo Image Matching for Compact Digital Cameras ]]>
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fourry Handoko]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
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DOI: 10.11591/eecsi.v4.1015
<![CDATA[Numerous image matching methods for wide range of applications have been invented in the last decade. When high precision and reliability of the object space point coordinates is highly demanding, a stereo image matching method which can produce conjugate point of images and a standard deviation of the matched point is examined. In this approach, image gradients are used locally to seek a conjugate patch. The normalized cross correlation is first utilized to estimate an approximate location of the conjugate patch between two normalized images. Then the location of conjugate patch is further refined by using Gaussian-Newton least squares image matching. Both radiometric and geometric parameters of least squares models are used selectively in seeking the best possible accuracy. Iterative computation is conducted to incrementally refine the geometric location of the conjugate point. After a matched patch has been found, a variant-covariant matrix of the parameter is analyzed to inform the precision of the conjugate points both on images and object space. This method can compute high precision object space points and some examples demonstrate the insight of the approach.]]>
<![CDATA[Single Frame Resection of Compact Digital Cameras for UAV Imagery ]]>
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fourry Handoko]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
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DOI: 10.11591/eecsi.v4.1070
<![CDATA[Recently, UAVs (Unmanned Aerial Vehicles) gaina wider acceptance from many disciplines. One major applicationis for monitoring and mapping. Flying beyond eye sightautonomously and collecting data over large areas are theirobvious advantages. To support a large scale urban city mapping,we have developed a UAV system which can carry a compactdigital camera as well as a navigational grade of a GlobalPositioning System (GPS) board mounted on the vehicle.Unfortunately, such a navigational system fails to providesufficient accuracy required to process images become a largescale map. Ubiquitous digital compact cameras, despite their lowcost benefits, are widely known to suffer instabilities in theirinternal lenses and electronics imaging system. Hence thesecameras are less suitable for mapping related purposes. However,this paper presents a photogrammetric technique to preciselydetermine intrinsic and extrinsic camera parameters ofphotographed images provided that sufficient numbers ofsurveyed control points are available. A rigorous Mathematicalmodel is derived to compute each image position with respect tothe imaging coordinate system as well as a location of theprincipal point of an image sensor and the focal length of thecamera. An iterative Gaussian-Newton least squares adjustmentmethod is utilized to compute those parameters. Finally, surveyeddata are processed and elaborated to justify the mathematicalmodels.]]>
<![CDATA[A Relative Rotation between Two Overlapping UAV's Images ]]>
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fransisca Agust]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
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DOI: 10.11591/eecsi.v5.1681
<![CDATA[In this paper, we study the influence of varying baseline components on the accuracy of a relative rotation between two overlapping aerial images taken form UAV flight. The case is relevant when mosaicking UAV's aerial images by registering each individual image. Geotagged images facilitated by a navigational grade GPS receiver on board inform the camera position when taking pictures. However, these low accuracies of geographical coordinates encoded in an EXIF format are unreliable to depict baseline vector components between subsequent overlapping images. This research investigates these influences on the stability of rotation elements when the vector components are entered into a standard coplanarity condition equation to determine the relative rotation of the stereo images. Assuming a nadir looking camera on board while the UAV platform is flying at a constant height, the resulted vector directions are utilized to constraint the coplanarity equation. A detailed analysis of each variation is given. Our experiments based on real datasets confirm that the relative rotation between two successive overlapping image is practically unaffected by the accuracy of positioning method. Furthermore, the coplanarity constraint is invariant with respect to a translation along the baseline of the aerial stereo images.]]>
<![CDATA[Focal Length Lens Effect at Non-Metric Camera for Three-Dimensional Models Result ]]>
<![CDATA[Nur Alfan Wisnu Hardiatmojo]]>;
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fransisca Dwi Agustina]]>
<![CDATA[ Journal of Applied Geospatial Information Vol 6 No 1 (2022): Journal of Applied Geospatial Information (JAGI) ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jagi.v6i1.3564
<![CDATA[Selections of non-metric cameras can be calculated properly starting from choosing the right camera sensor size and lens focal length to get better results. Differences in the choice of focal length in shooting can affect the resulting photo. The resulting photo may differ from how much of the object is captured and may suffer distortion due to different selections of the focal length. The purpose of this study is to show the magnitude of the effect of focal length variation in making a three-dimensional model based on the comparison of the results of the three-dimensional model visualization, the comparison of the results of geometric accuracy based on the independent checkpoint coordinate data, and the comparison of the distance results between retro targets. The results of this study indicate that a focal length of 70 mm has better results with the formation of the object completely resembling its original object compared to a focal length of 28 mm which is not good at forming a safety pillar on the bridge. The results of the RMSE value based on ICP coordinate data at a focal length of 70 mm are better with a value of 0.083 m compared to a focal length of 28 mm with a large value of 0.123 m. The results of the RMSE value based on the distance between retro targets at a focal length of 70 mm are better with a value of 0.003 m compared to a focal length of 28 mm with a large value of 0.004 m.]]>
<![CDATA[Analisis Deformasi Jembatan Akibat Banjir Bandang Berbasis Fotogrametri Jarak Dekat ]]>
<![CDATA[Larasaty Ayu Parsamardhani]]>;
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fransisca Dwi Agustina]]>
<![CDATA[ Jambura Geoscience Review Vol 4, No 1 (2022): Jambura Geoscience Review (JGEOSREV) ]]>
Publisher : <![CDATA[Universitas Negeri Gorontalo ]]>
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DOI: 10.34312/jgeosrev.v4i1.12013
<![CDATA[Monitoring the deformation of objects in the natural disaster area is one of the anticipative steps to reduce losses. In this case, this is an attempt to implement mitigation for the safety and viability of the community. Until this time, many constraint factors in the process of obtaining information regarding the strength of the structure and the changes of shape and dimension (per time unit) of the objects, one of which is the high operational cost and the duration of data processing while using a conventional measuring instrument. Through this article, a fast, cheap, easy, and accurate alternative method to detect deformation of the bridge material structure due to flash flood is only by using a Digital Single Lens Reflex (DSLR) camera. The bridge’s structures were photographed and processed with proprietary software to obtain the retro-reflective coordinate of the target that has been evenly attached to the bridge surface as a reference point. From a series of periodic photoshoots conducted from July 2020 to July 2021, deformation of the bridge structure was successfully detected with a magnitude between 0.026 mm – 5.867 mm with a measurement accuracy level was 0.081 mm. With this measurement accuracy level, this system is able to detect the deformation of structures smaller than 0.1 mm, and even invisible deformation can still be detected. This article will explain the technique and methodology of deformation measurement quickly and accurately only with a DSLR camera.]]>
<![CDATA[Kajian Perbandingan Akurasi DTM Pengolahan Data Foto Udara Menggunakan Metode Otomatis Dan Semi-Otomatis Filtering ]]>
<![CDATA[Raynier Geraldino Dadu Kerong]]>;
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[Fransisca Dwi Agustina]]>
<![CDATA[ Jambura Geoscience Review Vol 4, No 1 (2022): Jambura Geoscience Review (JGEOSREV) ]]>
Publisher : <![CDATA[Universitas Negeri Gorontalo ]]>
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DOI: 10.34312/jgeosrev.v4i1.12046
<![CDATA[Advances in UAV technology produce various superior products that can be utilized for the development and analysis of natural dynamics. One of them is DTM which is a visual representation of the shape of the ground surface that is displayed in 3 dimensions. DTM is obtained from the results of DSM filtering, where all features above the ground are digitally removed using a certain method. To produce a good DTM, a good quality DSM is needed, therefore a Horizontal and Vertical accuracy analysis was carried out based on ASPRS 2015. In this study, two software with different data processing methods were used, namely automatic filtering and semi-automatic filtering from DSM to DTM. To determine the quality of DTM, spot-height data is used as a comparison which is considered to be the actual form in the field. From the series of data processing processes, DTM results were obtained which were then tested for accuracy utilizing statistical validation tests using the calculation of RMSEZ values and non-statistical validation tests (Visual) using the transverse profile method. The test results show that the DTM produced by the PCI Geomatica software with the semi-automatic filtering method has more accurate and precise quality than the DTM from the SAGA GIS software with the automatic filtering method with an elevation value of 1,249 m and RMSEz 3,542 m to the spot-height. Then the visualization of the DTM transverse profile produced by the PCI Geomatica software semi-automatic filtering method to the spot height also does not appear to experience a significant difference where the elevation at Point 1 is 0.5 m and Point 2 is 0.5 m.]]>
<![CDATA[Identifikasi Kekeringan Lahan Kabupaten Lamongan Berdasarkan Citra Satelit ]]>
<![CDATA[Alifah Noraini]]>;
<![CDATA[Martinus Edwin Tjahjadi]]>;
<![CDATA[I Nyoman Sudiasa]]>
<![CDATA[ Poltanesa Vol 23 No 1 (2022): Juni 2022 ]]>
Publisher : <![CDATA[P2M Politeknik Pertanian Negeri Samarinda ]]>
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DOI: 10.51967/tanesa.v23i1.958
<![CDATA[Kekeringan lahan merupakan salah satu permasalahan masyarakat Indonesia yang terjadi pada musim kemarau. Kekeringan lahan mengakibatkan aktivitas pertanian terganggu karena pasokan air terhambat. Salah satu kabupaten yang mengalami kekeringan lahan adalah Kabupaten Lamongan. Penelitian ini bertujuan untuk mengidentifikasi wilayah yang mengalami kekeringan lahan di Kabupaten Lamongan agar dampak kekeringan dapat diminimalisir. Metode identifikasi kekeringan lahan yang digunakan berdasarkan pengolahan data penginderaan jauh, yaitu memanfaatkan data citra satelit Landsat 8 saluran 4 (merah), saluran 5 (Near InfraRed/ NIR), dan saluran 6 (Short Wavelength InfraRed/ SWIR). Sebelum proses pengolahan citra, dilakukan proses penggabungan antar scene (mosaicking). Citra Landsat 8 dipotong sesuai batas administrasi wilayah kabupaten dan diolah berdasarkan algoritma NDDI untuk mengidentifikasi kekeringan lahan. Algoritma yang digunakan terdiri dari parameter tingkat kebasahan air dan tingkat kehijauan vegetasi yang menutupi wilayah Kabupaten Lamongan. Tingkat kebasahan diperoleh dari pengolahan citra menggunakan algoritma NDWI, sedangkan tingkat kerapatan vegetasi diperoleh berdasarkan pengolahan citra menggunakan algoritma NDVI. Hasil pengolahan citra satelit Landsat 8 menunjukkan bahwa Kabupaten Lamongan didominasi oleh tingkat kebasahan kelas rendah sebesar 893,236 Km2 dan kerapatan vegetasi kelas sedang sebesar 691,012 Km2. Adapun hasil identifikasi kekeringan lahan di Kabupaten Lamongan didominasi oleh kelas klasifikasi kekeringan berat sebesar 62,14% atau 1.097,087 Km2 dari total luas area.]]>
