Enhancing Accuracy in Detection and Counting of Islands Using Object-Based Image Analysis: A Case Study of Kepulauan Seribu, DKI Jakarta
![](/public/site/images/admin/icons/icon-doi.png)
Laode Muhammad Golok Jaya(1*), Mutmainnah Muchtar(2), Sarimuddin Sarimuddin(3), Sitti Hairani Idrus(4)
(1) Department of Informatics, Faculty of Engineering, Universitas Halu Oleo, Kendari.
(2) Department of Computer Science, Faculty of Information Technology, Universitas Sembilanbelas Nopember, Kolaka
(3) Department of Computer Science, Faculty of Information Technology, Universitas Sembilanbelas Nopember, Kolaka
(4) Department of Public Administration, Faculty of Social and Political Science, Universitas Halu Oleo, Kendari, Indonesia
(*) Corresponding Author
Abstract
Based on previous observations, a series of steps using digital image processing methods is proposed for the automatic detection and counting of islands to avoid inaccuracies from satellite imagery by leveraging morphological properties of object. The need for accurate spatial data regarding the number of islands in Indonesia is crucial for various developmental purposes. Many small islands known to have beautiful landscapes remain unaccounted for due to the vast territorial waters of the country, posing challenges to manual evaluation of the numbers and distributions. Remote sensing methods offer a viable solution for efficiently counting and inventorying islands. Therefore, this study aimed to detect islands in Kepulauan Seribu, located north of DKI Jakarta, through the thresholding-based segmentation process and count the total number using morphological information. The methodology applied was Object-Based Image Analysis (OBIA), including image gray-scaling, thresholding, morphological operations, connected component labeling, and region-based object counting. The results obtained showed 111 islands, compared to direct observation of image from which 104 were found, with detection accuracy of 93.27%. The discovery not only contributes valuable insights into the specific region but also serves as a basis for potentially applying digital image processing methods on a larger scale to recalculate the number of Indonesian islands. Such recalculations could play a crucial role in informing and guiding future developmental initiatives.
Keywords
Full Text:
PDFReferences
Barbedo, J. G. A. (2014). Using digital image processing for counting whiteflies on soybean leaves. Journal of Asia-Pacific Entomology, 17(4), 685–694. https://doi.org/10.1016/j.aspen.2014.06.014
BPS, S. of K. S. R. (2017). Kepulauan Seribu in Figures 2017. In B.-S. of K. S. Regency (Ed.), BPS-Statistics of Kepulauan Seribu Regency (1st ed.). CV. Daistiq Kurnia Ma’Mur. https://kepulauanseribukab.bps.go.id
Bui, Q. T., Nguyen, Q. H., Pham, V. M., Pham, V. D., Tran, M. H., Tran, T. T. H., Nguyen, H. D., Nguyen, X. L., & Pham, H. M. (2019). A Novel Method for Multispectral Image Classification by Using Social Spider Optimization Algorithm Integrated to Fuzzy C-Mean Clustering. Canadian Journal of Remote Sensing, 45(1), 42–53. https://doi.org/10.1080/07038992.2019.1610369
Chao, X., Sun, G., Zhao, H., Li, M., & He, D. (2020). Identification of apple tree leaf diseases based on deep learning models. Symmetry, 12(7). https://doi.org/10.3390/sym12071065
Cipolletti, M. P., Delrieux, C. A., Perillo, G. M. E., & Cintia Piccolo, M. (2012). Superresolution border segmentation and measurement in remote sensing images. Computers and Geosciences, 40, 87–96. https://doi.org/10.1016/j.cageo.2011.07.015
Cleary, D. F. R., Suharsono, & Hoeksema, B. W. (2006). Coral diversity across a disturbance gradient in the Pulau Seribu reef complex off Jakarta, Indonesia. Biodiversity and Conservation, 15(11), 3653–3674. https://doi.org/10.1007/s10531-004-4692-y
Collin, A., Nadaoka, K., & Nakamura, T. (2014). Mapping VHR water depth, seabed and land cover using google earth data. ISPRS International Journal of Geo-Information, 3(4), 1157–1179. https://doi.org/10.3390/ijgi3041157
Davis, D. S. (2019). Object-based image analysis: a review of developments and future directions of automated feature detection in landscape archaeology. Archaeological Prospection, 26(2), 155–163. https://doi.org/10.1002/arp.1730
District, K. S. (2021). Kepulauan Seribu Region Profile. https://pulauseribu.jakarta.go.id/wilayah.
Farhan, A. R., & Lim, S. (2012). Vulnerability assessment of ecological conditions in Seribu Islands, Indonesia. Ocean and Coastal Management, 65, 1–14. https://doi.org/10.1016/j.ocecoaman.2012.04.015
Fauzi, A., & Buchary, E. A. (2002). A socioeconomic perspective of environmental degradation at Kepulauan Seribu Marine National Park, Indonesia. Coastal Management, 30(2), 167–181. https://doi.org/10.1080/089207502753504698
Fernandez-Gallego, J. A., Lootens, P., Borra-Serrano, I., Derycke, V., Haesaert, G., Roldán-Ruiz, I., Araus, J. L., & Kefauver, S. C. (2020). Automatic wheat ear counting using machine learning based on RGB UAV imagery. Plant Journal, 103(4), 1603–1613. https://doi.org/10.1111/tpj.14799
Fisher, R., Perkins, S., Walker, A., & Wolfart, E. (1997). Hypermedia image processing reference. Department of Artificial Intelligence, University of Edinburgh, 318. http://www.dsi.unive.it/~atorsell/Hipr.pdf%0Ahttp://cs.sookmyung.ac.kr/~ywchoi/course_cv/Hipr_top.pdf
Frost, A., Ressel, R., & Lehner, S. (2016). Automated Iceberg Detection Using High-Resolution X-Band SAR Images. Canadian Journal of Remote Sensing, 42(4), 354–366. https://doi.org/10.1080/07038992.2016.1177451
Givens, R. N., Walli, K. C., & Eismann, M. T. (2012). Fusion of LIDAR Data with Hyperspectral and High- Resolution Imagery for Automation of DIRSIG Scene Generation. 2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 1–7.
Gonzalez, R. C., & Woods, R. E. (2018). Digital image processing (4th editio). Pearson Education.
Goyal, M. (2011). Morphological Image Processing. IJST, 2(4), 161–165. https://doi.org/10.1002/9781118093467.ch13
Guo, X., & Yu, F. (2013). A method of automatic cell counting based on microscopic image. Proceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013, 1, 293–296. https://doi.org/10.1109/IHMSC.2013.76
Hakim, L., Hong, S. K., Kim, J. E., & ... (2007). Nature-based tourism in small islands adjacent to Jakarta City, Indonesia: a case study from Seribu Islands. Journal of Wetlands …, 1–5. https://www.koreascience.or.kr/article/JAKO200724578160180.page%0Ahttps://www.koreascience.or.kr/article/JAKO200724578160180.pdf
Jeyalaksshmi, S., & Prasanna, S. (2018). Measuring distinct regions of grayscale image using pixel values. International Journal of Engineering & Technology, 7(1.1), 121. https://doi.org/10.14419/ijet.v7i1.1.9210
Lainez, S. M. D., & Gonzales, D. B. (2019). Automated fingerlings counting using convolutional neural network. 2019 IEEE 4th International Conference on Computer and Communication Systems, ICCCS 2019, September 2019, 67–72. https://doi.org/10.1109/CCOMS.2019.8821746
Li, X. L., Ma, Z. H., Giagnocavo, C., Qin, F., Wang, H. G., & Álvarez-Bermejo, J. A. (2017). Development of automatic counting system for urediospores of wheat stripe rust based on image processing. International Journal of Agricultural and Biological Engineering, 10(5), 134–143. https://doi.org/10.25165/j.ijabe.20171005.3084
Liu, T., Wu, W., Chen, W., Sun, C., Zhu, X., & Guo, W. (2016). Automated image-processing for counting seedlings in a wheat field. Precision Agriculture, 17(4), 392–406. https://doi.org/10.1007/s11119-015-9425-6
Lumauag, R., & Nava, M. (2018). Fish tracking and counting using image processing. 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018, 1, 1–4. https://doi.org/10.1109/HNICEM.2018.8666369
Madduppa, H. H., SUBHAN, B., SUPARYANI, E., SIREGAR, A. M., ARAFAT, D., TARIGAN, S. A., ALIMUDDIN, A., KHAIRUDI, D., RAHMAWATI, F., & BRAHMANDITO, A. (2013). Dynamics of fish diversity across an environmental gradient in the Seribu Islands reefs off Jakarta. Biodiversitas Journal of Biological Diversity, 14(1), 17–24. https://doi.org/10.13057/biodiv/d140103
Muchtar, M., Suciati, N., & Fatichah, C. (2016). FRACTAL DIMENSION AND LACUNARITY COMBINATION FOR PLANT LEAF CLASSIFICATION. Jurnal Ilmu Komputer Dan Informasi, 9(2), 96. https://doi.org/10.21609/jiki.v9i2.385
Olaniyi, E. O., Oyedotun, O. K., & Adnan, K. (2017). Intelligent Grading System for Banana Fruit Using Neural Network Arbitration. Journal of Food Process Engineering, 40(1), 1–9. https://doi.org/10.1111/jfpe.12335
Padmavathi, K., & Thangadurai, K. (2016). Implementation of RGB and grayscale images in plant leaves disease detection - Comparative study. Indian Journal of Science and Technology, 9(6), 4–9. https://doi.org/10.17485/ijst/2016/v9i6/77739
Pasaribu, R. A., Cakasana, N., Maduppa, H., Subhan, B., Arafat, D., Sangadji, M. S., & Savana, M. S. (2020). Mangrove density level and area change analysis in small islands case study: Untung Jawa Island, Seribu Islands, DKI Jakarta. IOP Conference Series: Earth and Environmental Science, 429(1). https://doi.org/10.1088/1755-1315/429/1/012060
Pasrun, Y. P., Muchtar, M., Basyarah, A. N., & Noorhasanah. (2020). Indonesian License Plate Detection Using Morphological Operation. IOP Conference Series: Materials Science and Engineering, 797(1). https://doi.org/10.1088/1757-899X/797/1/012037
Prabowo, H. H., & Salahudin, M. (2016). Threats Drowning of Nkri ’ S Outermost Small Islands. Jurnal Geologi Kelautan, 14(2), 115–122.
Prakoso, Y. A., Komala, R., & Ginanjar, M. (2019). Characteristic of hawksbill turtle (Eretmochelys imbricata) nesting area in Kepulauan Seribu National Park, Jakarta. Prosiding Seminar Nasional Masyarakat Biodiversitas Indonesia, 5(1), 112–116. https://doi.org/10.13057/PSNMBI/M050121
Putra, D. (2010). Pengolahan Citra Digital. Penerbit ANDI.
Ramadhan, A., Lindawati, & Kurniasari, N. (2016). NILAI EKONOMI EKOSISTEM TERUMBU KARANG DI KABUPATEN WAKATOBI Economic Value of Coral Reef Ecosystem in the Wakatobi District.
Rivai, A. A., Siregar, V. P., Agus, S. B., & Yasuma, H. (2018). Analysis of habitat characteristics of small pelagic fish based on generalized additive models in Kepulauan Seribu Waters. IOP Conference Series: Earth and Environmental Science, 139(1). https://doi.org/10.1088/1755-1315/139/1/012014
Rudianto, Putra, H. M. P., Gemasabil, M. A., & Merryanti, D. P. (2019). Assessing the potential of coastal ecosystems to develop marine tourism in Pramuka Island, the Kepulauan Seribu National Park, Jakarta, Indonesia. IOP Conference Series: Earth and Environmental Science, 278(1). https://doi.org/10.1088/1755-1315/278/1/012068
Samet, H., & Tamminen, M. K. (1988). Efficient Component Labeling of Images of Arbitrary Dimension Represented by Linear Bintrees. IEEE Transactions on Pattern Analysis and Machine Intelligence, 10(4), 579–586. https://doi.org/10.1109/34.3918
Shafri, H. Z. M., Hamdan, N., & Saripan, M. I. (2011). Semi-automatic detection and counting of oil palm trees from high spatial resolution airborne imagery. International Journal of Remote Sensing, 32(8), 2095–2115. https://doi.org/10.1080/01431161003662928
Soemarmi, A., & Diamantina, A. (2019). Konsep Negara Kepulauan Dalam Upaya Perlindungan Wilayah Pengelolaan Perikanan Indonesia. Masalah-Masalah Hukum, 48(3), 241. https://doi.org/10.14710/mmh.48.3.2019.241-248
Soille, P., & Pesaresi, M. (2002). Advances in mathematical morphology applied to geoscience and remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 40(9), 2042–2055. https://doi.org/10.1109/TGRS.2002.804618
Wang, Y., Lv, H., Deng, R., & Zhuang, S. (2020). A Comprehensive Survey of Optical Remote Sensing Image Segmentation Methods. Canadian Journal of Remote Sensing, 46(5), 501–531. https://doi.org/10.1080/07038992.2020.1805729
Wei, J., Zhang, Y., Wu, H., & Cui, B. (2018). The Automatic Detection of Fire Scar in Alaska using Multi-Temporal PALSAR Polarimetric SAR Data. Canadian Journal of Remote Sensing, 44(5), 447–461. https://doi.org/10.1080/07038992.2018.1543022
Yuan, J., Wang, D. L., & Li, R. (2014). Remote sensing image segmentation by combining spectral and texture features. IEEE Transactions on Geoscience and Remote Sensing, 52(1), 16–24. https://doi.org/10.1109/TGRS.2012.2234755
Zubaida, V., Sartimbul, A., & Natsir, S. M. (2020). Study of benthic foraminifera and its connection with environmental condition in Bidadari Island, Kepulauan Seribu. IOP Conference Series: Earth and Environmental Science, 429(1). https://doi.org/10.1088/1755-1315/429/1/012007
![](/public/site/images/admin/icons/icon-doi.png)
Article Metrics
![](/public/site/images/admin/icons/icon-graph.png)
![](/public/site/images/admin/icons/icon-pdf.png)
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Laode Muhammad Golok Jaya
![Creative Commons License](http://i.creativecommons.org/l/by-nc/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)
ISSN 2354-9114 (online), ISSN 0024-9521 (print)