DARI MEJA TS. RUSLIZA HANIM BINTI MAARIF Ketua Editor Buletin Geospatial Sektor Awam Edisi 2024 Pengarah Pusat Geospatial Negara (PGN) KETUA EDITOR Assalamualaikum dan Salam Malaysia Madani Selamat datang ke Buletin Geospatial Sektor Awam (BGSA) Edisi 2024. Syukur ke hadrat Ilahi, pada tahun ini, Pusat Geospatial Negara (PGN) dengan jayanya dapat menerbitkan sebuah buletin yang padat dengan informasi dan perkembangan terkini berkaitan bidang geospatial. Edisi 2024 kali ini mengetengahkan artikel eksklusif mengenai pembangunan sistem untuk keselamatan awam menggunakan teknologi Geospatial Intelligence (GEOINT) oleh Polis Diraja Malaysia (PDRM). Artikel ini memberikan maklumat tentang bagaimana teknologi GEOINT digunakan sebagai usaha PDRM mempertingkatkan keselamatan awam secara berkesan, satu langkah ke arah Malaysia yang lebih selamat. Selain itu, BGSA Edisi 2024 turut memaparkan sumbangan artikel daripada para cendekiawan dan pakar daripada pelbagai institusi, seperti Institut Tanah dan Ukur Negara (INSTUN), Universiti Teknologi Malaysia (UTM), International Islamic University Malaysia (IIUM), termasuklah daripada PGN sendiri. Kepelbagaian pandangan dan ilmu yang dibawakan oleh penulis-penulis ini diharap dapat memberi manfaat yang besar kepada para pembaca dalam memahami dan mengaplikasikan teknologi geospatial dalam pelbagai bidang. Tidak ketinggalan, kolum tetap yang melaporkan aktiviti dan promosi program Infrastruktur Data Geospatial Negara (MyGDI), yang merupakan fungsi utama PGN, diteruskan juga dalam edisi kali ini. Kolum ini bukan sahaja berfungsi sebagai wadah untuk memperkenalkan perkembangan terkini MyGDI, tetapi juga sebagai platform untuk memperkukuhkan kerjasama antara agensi-agensi kerajaan dalam usaha memajukan pembangunan dan perkongsian data geospatial di Malaysia. Akhir kata, saya ingin merakamkan setinggi-tinggi penghargaan kepada semua terutamanya kepada penulis, penyelaras dan ahli sidang pengarang yang telah memberikan komitmen penuh dalam menjayakan penerbitan BGSA Edisi 2024 ini. Semoga buletin ini menjadi sumber inspirasi dan pengetahuan yang bermanfaat kepada semua pembaca. Selamat membaca! 1
TEKNIKAL 2 Pembangunan Sistem Geospatial Intelligence-Led Policing (GEOINT-LP) Melalui Perisian Sumber Terbuka (Open Source) Bagi Keberhasilan Keselamatan Awam Buletin Geospatial Sektor Awam SUPT. DR. HASRANIZAM BIN HASHIM hasranizam@rmp.gov.my Pusat Pengajian Sains Pengurusan Krisis dan Bencana Maktab PDRM Kuala Lumpur Polis Diraja Malaysia Abstrak Polis Diraja Malaysia (PDRM) adalah agensi utama yang bertanggungjawab bagi memastikan keselamatan awam negara. Sejajar dengan Dasar Revolusi Perindustrian Keempat (4IR) Negara dan Malaysia MADANI, PDRM telah mengorak langkah menggunakan maklumat geospatial ke arah pendekatan Intellingence-Led Policing dalam menghadapi cabaran kepolisan moden masa kini. Pembangunan modul sistem seperti pemetaan jenayah, analisis data raya jenayah dan perisikan berupaya memajukan lagi model kepolisan semasa, sekaligus menghasilkan sistem Geospatial Intellingence-Led Policing (GEOINT-LP) yang berkesan dalam menganalisis kejadian jenayah berasaskan lokasi serta merancang program pencegahan jenayah secara strategik dan dinamik. Dengan kewujudan perisian geospatial sumber terbuka pada masa kini, pembangunan sistem lebih mudah dipelajari, kos efektif dan memberi impak tinggi terhadap keberhasilan keselamatan awam. PDRM adalah sebuah agensi penguatkuasaan utama yang berperanan dalam menjaga keselamatan dan ketenteraman awam. Dalam menjalankan operasi harian, taktikal dan strategik, PDRM memerlukan satu sistem berasaskan teknologi geospatial keselamatan seperti Remote Sensing (RS), Global Positioning System (GPS), Geographic Information System (GIS) dan Satelite Image Data Analysis. Teknologi geospatial ini telah digunakan oleh agensi kepolisan antarabangsa sejak 30 tahun yang lalu. Sejak awal tahun 2003, PDRM menggunakan GIS dan GPS melalui Sistem C4i. Mulai tahun 2010, perkembangan teknologi geospatial mula diterapkan di beberapa jabatan dalaman PDRM. Keupayaan teknologi geospatial dalam PDRM bukan sahaja terhad kepada pemetaan dan analisis jenayah tetapi juga meluas kepada analisis Forensic GIS, Crime Geographic Profilling, Crime Location Prediction, Satellite Image Intelligence Processing, Crime Combat Location, IoT Crime based Location Analysis, Victim Crime Behaviour Repeat Location Analysis, Disaster Prevention Analytics dan Strategic Management based Location Sustainability. Ini menjadi asas kepada model Geospatial Intellingence-Led Policing yang turut diamalkan di peringkat antarabangsa. Geospatial Intellingence-Led Policing merujuk kepada penggunaan dan pengumpulan data raya untuk tujuan analitik, menghasilkan visualisasi lokasi dan trend jenayah bagi membantu membuat keputusan serta merancang pembanterasan aktiviti jenayah. Ketersediaan data raya dalam PDRM telah mendorong kepada pewujudan sistem Geospatial Intellingence-Led Policing (GEOINT-LP) sebagai inovasi dalam meningkatkan kualiti perkhidmatan kepada rakyat. Oleh itu, satu hab geospatial berpusat yang mengandungi pelbagai data keselamatan berasaskan lokasi diperlukan untuk memastikan PDRM terus maju dalam penggunaan teknologi ini. Platform GIS bersepadu juga diperlukan untuk menghubungkan data spatial daripada Pengenalan “ “ merujuk kepada penggunaan dan pengumpulan data raya untuk tujuan analitik, menghasilkan visualisasi lokasi dan trend jenayah, bagi membantu membuat keputusan serta merancang pembanterasan aktiviti jenayah.
3 Inovasi Sistem GEOINT-LP pelbagai sumber dalaman dan luaran PDRM dalam satu pusat data geospatial yang membekalkan data terkini, tepat dan cepat yang boleh dicapai melalui platform hab geospatial PDRM ini. Seperti amalan kepolisan antarabangsa yang menggunakan teknologi geospatial intelligence (GEOINT), PDRM juga tidak terkecuali dalam mengguna pakai teknologi ini bagi memastikan negara sentiasa aman dan selamat. Sistem GEOINT-LP adalah platform berasaskan perkhidmatan web y a n g menghubungkan data raya daripada pangkalan data utama bagi tujuan analitik serta menghasilkan visualisasi dalam bentuk pemetaan untuk pencegahan jenayah dan keselamatan awam. Projek ini telah disenaraikan dalam Pelan Strategik PDRM 2021-2025 serta dalam permohonan di bawah peruntukan Rancangan Malaysia K e - 1 2 . Memandangkan keperluan yang mendesak, projek ini dijalankan melalui MENU Clients Django Web App PostgreSQL/PostGIS (Vector Datasets) File System (Raster Datasets) GeoWebCache GeoServer pyCSW Rajah 1 Arkitektur Geonode pembangunan kendiri (in-house development) oleh PDRM kerana ia dianggap sebagai keperluan strategik dan penting. Asas platform utama sistem ini menggunakan perisian sumber terbuka geospatial iaitu Geonode yang mengikut piawaian Open Geospatial Consortium (OGC). Dengan menggunakan perkakasan pelayan (server) sedia ada, pembangunan kendiri sistem GEOINT-LP dimulakan pada tahun 2022. Penggunaan perisian Geonode dipilih kerana keupayaannya menyokong penyimpanan data dalam pelayan on-premises milik jabatan, keselamatan perlindungan tinggi seperti penggunaan oAuth dan LDAP serta komponen yang menyokong piawaian OGC seperti Django, pyCSW, CSW Metadata Catalogue, OpenLayers, geoExt Web Mapping Libraries, PostgreSQL/ PostGIS Spatial Databases, GeoServer OGC Services, 2D/3D map visualisation dan Geospatial Python Libraries seperti ditunjukkan dalam Rajah 1. Perisian GIS yang digunakan bagi pendigitalan data ialah Quantum GIS (QGIS). QGIS menyediakan sambungan terus kepada Geonode, memudahkan pengurusan dan perolehan data dengan sistematik serta secara masa nyata (real-time). Perkongsian data masa nyata juga boleh dijalankan menggunakan perkhidmatan web seperti Web Map Service (WMS), Web Feature Service (WFS), Web Coverage Service (WCS), Catalog Service for Web (CSW), Web Map Context (WMC) dan Tile Map Service (TMS). Dengan keupayaan teknologi ini, sistem GEOINT-LP berfungsi sebagai hab utama perkongsian data bukan sahaja bagi data spatial tetapi juga data bukan spatial. Teknik integrasi kedua-dua jenis data ini boleh dilaksanakan dengan mudah melalui Forward Link, Backward Link dan Bi-directional Link.
TEKNIKAL 4 Buletin Geospatial Sektor Awam Keberhasilan Sistem GEOINT-LP Pada masa kini, sistem GEOINT-LP mempunyai lima (5) modul utama dengan lima puluh (50) lapisan data spatial dan dua puluh tiga (23) lapisan data bukan spatial. Antara modul utama yang disediakan termasuk modul sub sistem Pemetaan Laporan Polis dan sub sistem Hotspot Laporan Polis. Sistem GEOINT-LP ini berkeupayaan menghasilkan data analitik secara masa nyata dengan visualisasi peta sama ada dalam bentuk 2D atau 3D, bagi memudahkan pemerhatian terhadap corak, trend data serta kedudukan lokasi dengan lebih mudah seperti yang digambarkan dalam Rajah 4, Rajah 5 dan Rajah 6. Rajah 2 Paparan web sistem GEOINT-LP Rajah 3 Paparan data sistem GEOINT-LP Rajah 4 Analisis hotspot dengan visualisasi 2D Rajah 5 Analisis hotspot dengan visualisasi 3D “ “ Sistem GEOINT-LP ini berkeupayaan menghasilkan data analitik secara masa nyata dengan visualisasi peta sama ada dalam bentuk 2D atau 3D
5 Sistem GEOINT-LP yang dibangunkan menggunakan perisian sumber terbuka bukan sahaja dapat dibangunkan dalam tempoh singkat, iaitu satu (1) bulan termasuk dengan analitik data tetapi juga berupaya menyumbang kepada penyusunan strategi pengurangan jenayah yang amat berkesan. Pendigitalan data serta visualisasi dinamik mempermudah dan mempertingkatkan keberkesanan pelaksanaan program-program pembanterasan jenayah secara berkala. Dengan keupayaan perkhidmatan web (web services), sistem ini boleh diakses di pelbagai peringkat pentadbiran PDRM, sekali gus memudahkan capaian maklumat dan membolehkan keberhasilan keselamatan awam dicapai serta diukur dengan lebih tepat. Melalui platform sumber terbuka, pembangunan sistem geospatial ini bukan sahaja berfungsi sebagai alat untuk mengukur pencapaian strategi program yang sedang dilaksanakan tetapi juga membolehkan penyediaan model ramalan bagi menguji impak dan kesan terhadap keselamatan awam di masa hadapan. Kesimpulan Penulis merakamkan perhargaan kepada Pusat Geospatial Negara (PGN), Kementerian Sumber Asli dan Kelestarian Alam, Putrajaya, yang telah memberikan ulasan dan nasihat teknikal bagi pembangunan sistem GEOINT-LP ini. Penghargaan RUJUKAN; Consortium, O. G. (2016). Catalogue Service. http://www.opengeospatial.org/standards/cat/. (accessed on 2-September-2024). Copernicus. 2019. Available online: https://www.copernicus.eu/ (accessed on 2 September 2024). Corti, P., Lewis, B., and Kralidis, A. T. (2018b). Hypermap registry: an open source, standards-based. geospatial registry and search platform. Open Geospatial Data, Software and Standards, 3(1):8. GeoNode. (n.d.). https://geonode.org/ (accessed on 2 September 2024). Kralidis, A. T. (2009). Geospatial web services: The evolution of geospatial data infrastructure. In The Geospatial Web, pages 223–228. Springer. PostGIS, (2016). PostGIS 2.0 Manual, http://postgis.net/docs/manual-2.0/ (accessed on 2 September 2024). VV.AA. SDI Cookbook; Technical Report; Global Spatial Data Infrastructure Association: Gilbertville, IA, USA, 2012. Rajah 6 Analisis hotspot dengan visualisasi 3D terperinci Sistem GEOINT-LP yang dibangunkan menggunakan perisian sumber terbuka bukan sahaja dapat dibangunkan dalam tempoh singkat, iaitu satu (1) bulan termasuk dengan analitik data tetapi juga berupaya menyumbang kepada penyusunan strategi pengurangan jenayah yang amat berkesan. “ “
TEKNIKAL 6 Geographic Information System (GIS) Implementation in Public Sector Buletin Geospatial Sektor Awam SULAIMI BIN AHMAD National Institute of Land and Survey (INSTUN) Abstract Geographic Information System (GIS) technology has revolutionised decision-making in government agencies, yet its adoption in Malaysia's public sector remains limited. The slow implementation rate is a significant factor behind the lack of interest. This study aims to identify critical success factors for GIS implementation in Malaysia's public sector. Research findings highlight six (6) essential success factors: GIS Champion, organisation structure, adequate sta , top management support, su cient training, and resources. This study serves as a guideline for future GIS implementations, potentially enhancing GIS project management best practices within the Malaysian government. Implementing GIS technology e ectively can optimise government spending and improve service delivery. “ “ This study serves as a guideline for future GIS implementations, potentially enhancing GIS project management best practices within the Malaysian government. Keywords : Geographic Information System, Implementation, Public Sector. The Malaysian government has adopted GIS as part of its e-Government initiative to enhance public sector services. GIS, an IT application that analyses spatial data, addresses issues of scattered, outdated, and manually kept data. By integrating GIS, the government aims to improve service delivery e ciency and e ectiveness. GIS supports various fields and decision-making processes, prompting the Malaysian government to encourage its adoption across public sector services. Despite its recognised benefits, GIS implementation in many ICT systems proposed under the Malaysian Public Sector ICT Strategic Plan is still nascent. Pusat Geospatial Negara (PGN) oversees the development of Malaysia's Geospatial Data Infrastructure (MyGDI), aiming to improve geospatial data access. PGN supports public sector agencies by developing policies, standards, and guidelines for GIS implementation. Introduction The 10th Malaysian Plan tasked MAMPU (Malaysian Administrative Modernisation and Management Planning Unit) with assessing GIS implementation e ectiveness over ten (10) years. The findings revealed that most government agencies are still at the preliminary stage of GIS usage. Key issues include: Lack of GIS Expertise: The public sector lacks a specific scheme of service for GIS professionals, despite local institutions producing graduates in this field. Institutional Issues: GIS development is hindered by the absence of a coordinating body, leading to uncoordinated and inconsistent GIS implementations. Additionally, there is a dearth of empirical studies on GIS implementation success factors in Malaysia. Problem Statement
7 The study seeks to answer the following research questions: What factors contribute to the success of GIS implementation? What are the most critical success factors for GIS projects in the Malaysian public sector? Identify factors contributing to GIS implementation success based on the research model. Rank the most critical success factors for GIS projects in the Malaysian public sector. GIS technology, recognised for its ability to synthesise and analyse spatial data, has become essential in various professions and fields (Ceccato & Snickars, 2000; Drummond & French, 2008; Gocmen, 2009). GIS is defined as a computer system for storing, displaying, and analysing spatial data (Burrough & McDonnell, 1998; Wang Fahui, 2006). Objectives Literature Review Successful GIS implementation requires a combination of components, typically following IT implementation processes: planning, user requirements analysis, system design, system development, and system maintenance. However, challenges such as funding and top management scepticism about GIS benefits can impede implementation. GIS o ers several capabilities that benefit public sector organisations: Increased E ciency: GIS can enhance project management e ciency, saving public funds and reducing expenses. Improved Communication: GIS visualises information through maps and reports, integrating with other platforms and media, including mobile devices. E ective Data Management: GIS handles spatial and attribute data, facilitating data sharing, accuracy, and control through database management systems. GIS Capabilities Overview of GIS Implementation Implementation involves technical and organisational issues (Azad, 1993; Croswell, 1991). Successful GIS implementation depends on appropriate sta , organisational structures, and a shared understanding of the technology's potential (Huxhold & Levinsohn, 1995; Chan & Williamson, 1996; Campbell & Masser, 1992). Financial, technical, technological, educational, organisational, and human behavioural factors can restrict GIS implementation (Branko. I. Cavric, 2002). Strong organisational support is crucial (Abdullah et al., 2002; Innes & Simpson, 1993; Ramasubramanian, 1999).
TEKNIKAL 8 Buletin Geospatial Sektor Awam Introduced in the early 1980s, GIS is used in various Malaysian fields, including surveying, engineering, urban planning, education, and agriculture. Significant applications include: Geology: GIS displays geological assessments, such as digital elevation models in the Klang Valley (Manap et al., 2009). Crime: GIS supports crime prevention by analysing relationships between variables and land parcels (Suryavanshi, 2001). Medicine: GIS maps health facilities and disease distributions, such as dengue fever (Shaharudin et al., 2002). Town Planning: GIS assists in managing and monitoring town planning processes (Mohd Ali Abu Bakar, 2004). Education: GIS is studied for its e ectiveness in enhancing students' interest in geography (Lateh et al., 2010). Success factors for GIS implementation, as identified by various researchers, include: User Requirement Analysis: Evaluating user needs to fulfil stakeholder requirements. Top Management Commitment: Support and commitment from top-level management. Su cient Resources: Adequate time, money, equipment, and personnel. Adequate Personnel: Skilled sta for GIS operations and management. GIS Implementation in Malaysia GIS Success Factors Su cient Training: Training to enhance user knowledge of GIS implementation. GIS Champion: A leader who drives GIS development and di usion. Research Methodology Research Model Organisation Structure: E ective communication and coordination within the organisation. This research employed a quantitative method for systematic and objective analysis. This research used research model by Onsrud and Pinto (1993) to identify GIS implementation success factors, as follows: Questionnaires were distributed to various government agencies, with 30 sets completed by respondents from federal and state departments. Data Collection GIS Implementation Success Evaluation of use requirement Top management support Allocation of resources Adequate personnel Su cient training GIS champion Organisational communication Independent Variable Dependent Variable
Respondents had varying levels of experience with GIS projects, mostly involving system application development and infrastructure. Most projects were relatively small in budget. The study identified di erences between the research model and actual findings as follows, emphasizing the importance of GIS champions, adequate sta ng, and su cient training. To strengthen the analysis, factor analysis was employed, specifically using the Kaiser Criterion to identify significant factors. Introduced by Kaiser (1961), this technique determines factors based on eigenvalues, with eigenvalues greater than one indicating a significant factor. The results of the factor analysis, summarised in Table 4, reveal the factors identified based on their eigenvalues. 9 Demographic profiles and respondents' experiences were analysed to understand their backgrounds and involvement in GIS projects. Most respondents were project team leaders or responsible o cers, with a majority holding bachelor's degrees. Few had professional project management certifications. Table 1 Demographic Profile Analysis Demographic Profile Demographic Profile Category Frequency % Gender Male Female Total 14 16 30 46.7 53.3 100.0 Group Age 7 13 7 3 30 23.3 43.3 23.4 10.0 100.0 20-29 30-39 40-49 50-59 Total Current Position 1 2 13 5 9 30 3.3 6.7 43.3 16.7 30.0 100.0 Top Management Project Manager Project Team Team Member End User Total Level of Education 5 2 9 13 1 30 16.7 6.7 30.0 43.3 3.3 100.0 SPM STPM Diploma Bachelor Master Total Factors Mean Rank User Requirements Top Management Su cient Resources Adequate Sta Su cient Training GIS Champion Organisation Structure 3.0333 3.3333 2.5667 4.000 3.800 4.700 3.6667 6 5 7 2 3 1 4 Component Factors 1 2 3 4 5 6 GIS Champion Organisation Communication Adequate Personnel Top Management Support Su cient Training Su cient Resource Component Initial Eigenvalues Rotation Sums of Squared Loadings Total (% of Variance) 1 2 3 4 5 6 12.714 6.060 2.023 1.695 1.202 1.109 21.985 21.175 20.870 8.590 6.962 5.949 Table 2 Respondents Experience Respondents Experience Category Frequency % Certification on Project Management CAPM PGMP None Total 1 1 28 30 3.3 3.3 93.3 100.0 Type of Project 13 14 3 30 43.3 46.7 10.0 100.0 GIS Infrastructure System Application GIS Hardware & Software Total Size of Project 22 1 3 4 30 73.3 3.3 10.0 13.3 100.0 <100 000 101K-200K 201K-500K >1M Total Project Approach 8 15 2 5 30 26.7 50.0 6.7 16.7 100.0 In Sourcing Out Sourcing Co Sourcing Unknown Total Respondents' Experience Table 3 Research model adapted from Onsrud and Pinto Table 4 Summarise of Critical Factors Organisational Structure Factors Critical Success Factors
As mentioned, the purpose of this research is to identify the critical success factors that contribute to the successful implementation of GIS in the public sector. The results highlight di ering perceptions during GIS implementation and the research model, indicating that various departments manage GIS implementation di erently. The analysis underscores that for successful GIS implementation, the Malaysian government must consider all highlighted factors. These include having a GIS champion, e ective organisational communication, adequate personnel, strong top management support, su cient training, and adequate resources. 10 Buletin Geospatial Sektor Awam The analysis underscores that for successful GIS implementation, the Malaysian government must consider all highlighted factors. These include having a GIS champion, effective organisational communication, adequate personnel, strong top management support, sufficient training, and adequate resources. “ “ Budget constraints hinder GIS implementation, particularly at the local authority level, where geospatial data tasks are often assigned to non-specialised staff. “ “ Conclusion This research proposes a strategy involving adjustments and supplements to current institutional arrangements to address GIS implementation challenges. Recommendations include implementing a shared data dictionary system and conducting pilot projects to test inter-sector instruments. Budget constraints hinder GIS implementation, particularly at the local authority level, where geospatial data tasks are often assigned to non-specialised sta . Ensuring the success of GIS implementation requires considering all identified critical factors. GIS has the potential to transform public sector operations, significantly impacting government activities and public information quality. E ective GIS implementation will enhance service delivery and optimise resource utilisation. REFERENCES; [1] A. Yaakup, (2001) GIS as tools for monitoring the urban development in metropolitan region: A case of Klang Valley Region, Peninsular Malaysia [2] Azad, B., (1993), “Organizational Aspects of GIS Implementation: Preliminary Results from a Dozen Cases, Paper presented at the Urban and Regional Information Systems Association Conference, Atlanta, Georgia [3] Bernhardsen, T. (1992), Geographic Information Systems. Norway: Viak TI. [4] Buyong, T. (1995), GIS for Local Authorities, Penerbitan Fakulti Ukur dan Tanah, Universiti Teknologi Malaysia [5] Croswell, P. (1991), Obstacles to GIS Implementation and Guidelines to Increase the Opportunities for Success. Journal of the Urban and Regional Information Systems Association, 3(1), 43-56 [6] Couclelis, H. (1991), Requirements for planning relevant GIS: a spatial perspective. Papers in Regional Science, 70(1), 9-19 [7] Carr, J. L. (1994), The strengths and weaknesses of quantitative and qualitative research. TEKNIKAL
11 Kepentingan Infrastruktur Data Geospatial dalam Pembangunan Bandar Pintar (The importance of Geospatial Data Infrastructure in Smart City Development) Pengenalan Matlamat utama inisiatif bandar pintar (smart city) adalah untuk mewujudkan persekitaran bandar yang mampan, boleh didiami dan berdaya tahan yang memberikan kualiti hidup yang tinggi kepada rakyat sambil memacu pertumbuhan ekonomi dan pembangunan mampan (Halegoua, 2020). Pembangunan bandar pintar diperkukuhkan lagi dengan pembangunan teknologi termaju seperti Internet of Things (IoT), Kepintaran Buatan (Artificial Intelligence, AI) dan Analitik Data Raya “ “ Pembangunan bandar pintar sangat bergantung pada ketersediaan dan kebolehcapaian data geospatial, yang dijana oleh Infrastruktur Data Geospatial (GDI) DR ZAKRI TARMIDI Pensyarah, Jabatan Geoinformasi, Fakulti Alam Bina dan Ukur, Universiti Teknologi Malaysia zakritarmidi@utm.my (big data analytics). Penggunaan pelbagai teknologi termaju ini dapat meningkatkan penyampaian perkhidmatan awam dan pengalaman secara keseluruhan (Silva et al., 2018). Pembangunan bandar pintar sangat bergantung pada ketersediaan dan kebolehcapaian data geospatial, yang dijana oleh Infrastruktur Data Geospatial (GDI). GDI merupakan satu kerangka melibatkan polisi, standard, data geospatial dan teknologi yang membantu dalam capaian dan perkongsian maklumat geospatial (Rajabifard & Williamson, 2002). GDI membolehkan pihak yang terlibat dengan inisiatif bandar pintar untuk mengumpul, membuat analisis, memapar dan mengedar data geospatial yang berkaitan melalui pelbagai sistem yang menyokong penyampaian perkhidmatan bandar seperti pengangkutan, tenaga, air dan pengurusan sisa. Dengan menggunakan GDI, bandar pintar dapat membangunkan model geospatial yang mengintegrasikan data spatial untuk mengenal pasti corak, trend dan perspektif yang dapat membantu dalam membuat keputusan serta membangunkan polisi. Kajian ini bertujuan menilai kepentingan GDI dalam pembangunan bandar pintar dengan mengenal pasti isu-isu dan langkah-langkah untuk mengintegrasi GDI dalam pembangunan bandar pintar. Kepentingan integrasi GDI dalam pembangunan bandar pintar boleh dilihat daripada beberapa kajian terdahulu. Ia boleh dibahagikan kepada beberapa fokus utama iaitu; integrasi data spatial, strategi pentadbiran, keselamatan data spatial, carian dan analisis metadata, integrasi sensor, polisi dan interoperabiliti data. Terdapat beberapa isu utama yang telah diketengahkan oleh kajian-kajian terdahulu berkaitan integrasi GDI dalam inisiatif bandar pintar. Antara isu utama yang dinyatakan adalah berkaitan (1) data geospatial, (2) integrasi sensor berkaitan, (3) pengurusan data geospatial, (4) keperluan untuk menambah baik metadata dan (5) isu berkaitan institusi dan pentadbiran. Kepentingan GDI dalam Pembangunan Bandar Pintar Isu-isu Integrasi dalam Bandar Pintar
12 Buletin Geospatial Sektor Awam TEKNIKAL Rajah 1 Lima (5) isu utama integrasi GDI dalam bandar pintar Data geospatial Integrasi sensor berkaitan Pengurusan data geospatial Keperluan untuk menambahbaik metadata Isu berkaitan institusi dan pentadbiran Bagi isu berkaitan data geospatial, perhatian perlu diberikan terlebih dahulu kepada isu format, kualiti dan interoperabiliti data (Ghosh & Mukherjee, 2022; Moshrefzadeh et al., 2017; Nagaraja et al., 2020). Format data yang berbeza dan kualiti data yang tidak terjamin merupakan cabaran utama yang perlu diatasi bagi memperbaiki integrasi GDI dalam inisiatif bandar pintar. Selain itu, interoperabiliti data perlu ditingkatkan kerana inisiatif bandar pintar ini memerlukan pelbagai jenis data termasuk data spatial dan data bukan spatial yang harus berfungsi secara saling melengkapi. Bagi isu integrasi sensor pula, data spatial yang digunakan, sepatutnya boleh diintegrasikan secara tidak langsung dengan pelbagai sensor lain seperti kamera litar tertutup (CCTV), sensor lampu trafik dan sensor-sensor berkaitan (Bhattacharya & Painho, 2017; Iban & Aksu, 2020; Rabelo et al., 2017). Kebolehan untuk mengintegrasikan sensor-sensor terkini dengan data spatial akan meningkatkan lagi kebolehcapaian dan kemas kini data yang sedia ada. Selain itu, isu berkaitan pengurusan data geospatial turut dibangkitkan khususnya berkaitan garis panduan atau prosedur untuk pengumpulan, penyimpanan, pemprosesan, analisis dan pengedaran atau visualisasi data spatial (Ghosh & Mukherjee, 2022; Moshrefzadeh et al., 2017). Dengan adanya garis panduan dan prosedur yang baik dapat membantu pihak pengurusan bandar pintar dalam meningkatkan kualiti, kebolehcapaian, keselamatan serta interoperabiliti data (Chaturvedi et al., 2019). Isu metadata juga sering dibincangkan di mana terdapat keperluan untuk menambah baik metadata supaya lebih dinamik untuk memudahkan proses carian dan analisis (Rajaram et al., 2018). Penambahbaikan ini boleh dilaksanakan dengan memasukkan topik peta dan hipergraf bagi melihat hubungan antara topik dalam metadata yang sedia ada. Ini akan memudahkan lagi proses carian dan analisis topik secara lebih mendalam. Akhir sekali, isu institusi dan pentadbiran GDI dalam bandar pintar turut diketengahkan (Iban & Aksu, 2020; Kim et al., 2019). Pelaksanaan GDI bandar pintar melibatkan pelbagai agensi, jabatan dan bahagian. Ini memerlukan pengurusan rentas-institusi yang melibatkan undang-undang, dasar dan kerangka kerja organisasi untuk memastikan komunikasi dan kerjasama yang berkesan. Format data yang berbeza dan kualiti data yang tidak terjamin merupakan cabaran utama yang perlu diatasi bagi memperbaiki integrasi GDI dalam inisiatif bandar pintar. “ “ Ke Arah Integrasi GDI dalam Bandar Pintar Berdasarkan isu-isu yang telah dikenal pasti, perancangan untuk menambah baik integrasi GDI dalam bandar pintar boleh dilaksanakan dengan lebih strategik. Kajian ini mengetengahkan beberapa cadangan inisiatif yang merangkumi tiga (3) hala tuju utama, iaitu menambah baik integrasi data geospatial, mempertingkatkan kemajuan teknologi dan pembaharuan institusi (rujuk Rajah 2). Menambah baik Integrasi Data Geospatial Mempertingkatkan Kemajuan Teknologi Pembaharuan Institut Rajah 2 Hala tuju integrasi GDI dalam bandar pintar
13 Integrasi data geospatial boleh ditambah baik melalui pemudahcaraan dan pengaktifan data geospatial. Ini termasuk meningkatkan interoperabiliti dan kemudahan capaian data daripada pelbagai sumber serta memastikan data yang dihasilkan tepat, relevan dan terkini. Untuk meningkatkan penggunaan teknologi, adaptasi terhadap teknologi terkini dan akan datang yang berkaitan dengan GDI perlu dilaksanakan. Contohnya, teknologi seperti pembelajaran mendalam, pembelajaran mesin dan kecerdasan buatan dapat membantu meningkatkan keupayaan pengurusan data geospatial dan pemetaan pintar dalam bandar. Pembaharuan institusi pula perlu diberi tumpuan bagi memperkasa kerjasama dan kolaborasi antara agensi yang terlibat dalam pembangunan bandar pintar. Ini termasuk memperbaiki komunikasi dan meningkatkan penglibatan aktif semua pihak supaya pengurusan bandar pintar akan lebih efisien melalui sokongan dan koordinasi yang lebih baik antara institusi. Secara keseluruhannya, untuk memastikan kejayaan pelaksanaan bandar pintar, integrasi yang efektif terhadap data khususnya data geospatial, pengurusan data yang cekap, keselamatan data yang kukuh serta pengurusan institusi yang baik adalah amat diperlukan. Integrasi GDI dalam inisiatif pembangunan bandar pintar bukanlah satu perkara baru, namun terdapat beberapa isu berkaitan integrasi perlu dilihat dan ditambah baik. Kajian ini mengenal pasti lima (5) isu dan menggariskan tiga (3) hala tuju utama untuk menambah baik integrasi GDI dalam inisiatif bandar pintar, iaitu: menambah baik integrasi data geospatial, mempertingkatkan kemajuan teknologi dan pembaharuan institusi. Kajian ini menunjukkan kepentingan untuk melihat semula asas bagi pelaksanaan integrasi GDI dalam inisiatif bandar pintar bagi memudahkan pengumpulan, pemprosesan, analisis serta visualisasi dan pengagihan data geospatial di antara agensi-agensi utama dalam inisiatif bandar pintar. Kesimpulan Penulis merakamkan ucapan terima kasih kepada Universiti Teknologi Malaysia (UTM) kerana membiayai projek ini di bawah Geran Penyelidikan Galakan UTM (UTMER), nombor vote 31J77. Penghargaan Kajian ini menunjukkan kepentingan untuk melihat semula asas bagi pelaksanaan integrasi GDI dalam inisiatif bandar pintar “ “ RUJUKAN; Bhattacharya, D., & Painho, M. (2017). Smart cities intelligence system (smacisys) integrating sensor web with spatial data infrastructures (sensdi). ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 4, 21–28. Chaturvedi, K., Matheus, A., Nguyen, S. H., & Kolbe, T. H. (2019). Securing spatial data infrastructures for distributed smart city applications and services. Future Generation Computer Systems, 101, 723–736. Ghosh, S., & Mukherjee, A. (2022). STROVE: Spatial data infrastructure enabled cloud–fog–edge computing framework for combating COVID-19 pandemic. Innovations in Systems and Software Engineering, 1–17. Halegoua, G. (2020). 1 AN INTRODUCTION TO SMART CITIES. Iban, M. C., & Aksu, O. (2020). A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach. Land Use Policy, 91, 104376. Kim, M., Gwak, I., & Koh, J. (2019). The strategies of advanced local spatial data infrastructure for Seoul Metropolitan Government. International Journal of Urban Sciences, 23(3), 352–368. Moshrefzadeh, M., Chaturvedi, K., Hijazi, I., Donaubauer, A., & Kolbe, T. H. (2017). Integrating and managing the information for smart sustainable districts-the Smart District data infrastructure (SDDI). In Geoinformationssysteme 2017–Beiträge zur 4. Münchner GI-Runde. Wichmann Verlag. Nagaraja, G. S., Koundinya, A. K., Thippeswamy, G., & Hegde, V. V. (2020). Spatial Data Infrastructures for Urban Governance Using High-Performance Computing for Smart City Applications. Smart Intelligent Computing and Applications: Proceedings of the Third International Conference on Smart Computing and Informatics, Volume 2, 585–592. Rabelo, A. C. S., Oliveira, I. L., & Lisboa-Filho, J. (2017). An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures. International Conference on Smart Cities and Green ICT Systems, 2, 242–249. Rajabifard, A., & Williamson, I. P. (2002). Spatial Data Infrastructures: an initiative to facilitate spatial data sharing. Global Environmental DBs- Present Situation and Future Directions. ISPRS-WG IV/8. Rajaram, G., Karnatak, H. C., Venkatraman, S., Manjula, K. R., & Krithivasan, K. (2018). A novel computational knowledge-base framework for visualization and quantification of geospatial metadata in spatial data infrastructures. GeoInformatica, 22, 269–305. Silva, B. N., Khan, M., & Han, K. (2018). Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society, 38, 697–713.
TEKNIKAL 14 Buletin Geospatial Sektor Awam Introduction The Potential of Geospatial Technique in Mapping the Uncharted Reefs in Malaysia Abstract Coral reefs in Malaysia are vital ecosystems that support marine biodiversity, protect coastlines, and contribute to local economies. However, many reefs remain uncharted due to the logistical and technological challenges of traditional mapping methods. This study explores the application of advanced geospatial techniques for mapping uncharted coral reefs in Malaysia, focusing on the Pahang coastal region. The integration of satellite imagery, Geographic Information System (GIS), and underwater photogrammetry enhances the resolution and scope of mapping e orts. This research highlights the potential of geospatial techniques to revolutionise reef exploration and conservation in Malaysia, promoting sustainable management of marine resources. “ “ By dissipating wave energy, coral reefs help protect coastal communities from flooding and property damage, thus safeguarding human lives and infrastructure. MUHAMMAD FAIZ MOHD HANAPIAH Advanced Coastal Research and Innovation, Kulliyyah of Science, International Islamic University Malaysia faizhanapiah@iium.edu.my Coral reefs, often referred to as the "rainforests of the sea," are among the most vital marine habitats. Despite covering only 1% of the ocean floor, they support approximately 25% of all marine life, making them one of the most biodiverse ecosystems on the planet. This remarkable biodiversity is crucial for the health and stability of marine environments, as coral reefs provide habitat, food, and breeding grounds for a wide variety of marine species, including fish, invertebrates, and algae. The importance of coral reefs extends beyond their ecological value. They play a critical role in coastal protection, acting as natural barriers that reduce the impact of waves, storms, and erosion on shorelines. By dissipating wave energy, coral reefs help protect coastal communities from flooding and property damage, thus safeguarding human lives and infrastructure. This protective function is particularly vital in regions prone to hurricanes, typhoons, and other severe weather events. Figure 1 Nearshore reef exploration in Pahang coastal waters since 2020
15 Furthermore, coral reefs are a cornerstone of marine tourism, attracting millions of visitors worldwide who engage in activities such as snorkelling, scuba diving, and wildlife observation. The vibrant colours and diverse marine life of coral reefs create unique and mesmerizing underwater landscapes that draw tourists, contributing significantly to local economies. In many coastal regions, tourism generated by coral reefs provides employment and income for communities, supporting hotels, restaurants, tour operators, and other businesses. In addition to tourism, coral reefs are integral to fisheries. They serve as nurseries for numerous fish species, many of which are commercially important. The complex structures of coral reefs o er shelter and feeding grounds for juvenile fish, enhancing their survival rates and contributing to the productivity of nearby fisheries as shown in Figure 2. Small-scale and subsistence fishers rely heavily on the abundance of fish associated with coral reefs for their livelihoods and food security. Figure 2 Some of the benthic communities’ structure found in Kuantan coastal waters
Nearshore Reefs Exploration in Pahang Coastal Area Nearshore reefs exploration in Pahang coastal waters has evolved significantly over the past decade as shown in Figure 3. Between 2012 and 2020, coral video transect surveys were conducted, providing valuable visual insights into reef health, species diversity, and coral coverage. From 2021 to 2023, more advanced methods such as Single Beam Echo Sounders (SBES) and 3D photogrammetry were introduced, enabling detailed mapping of reef topography and structural complexity. These technologies allowed for a more precise understanding of reef distribution and morphology. In 2024, exploration e orts took another leap forward with the deployment of multibeam echo sounders and ROV-based surveys, providing high-resolution bathymetric data and the ability to investigate reef ecosystems in greater detail and depth, ultimately advancing conservation and management strategies for these critical habitats. Geospatial Application on Coral Reef Mapping The use of geospatial technologies in coral reef mapping represents a transformative approach to understanding and conserving these vital marine ecosystems at multiple scales (Figure 4). By leveraging advanced tools and techniques such as satellite imagery, remote sensing, GIS, and underwater photogrammetry, researchers can obtain comprehensive, high-resolution data on coral reef structures, health, and dynamics. These technologies not only enhance the accuracy and e ciency of mapping e orts but also enable the continuous monitoring and assessment of coral reefs, which is crucial for e ective conservation and management. Coral Video Transect Survey SBES and 3D Photogrammetry ROV and MBES Figure 3 Nearshore reefs exploration in Pahang coastal area between 2012-2024. TEKNIKAL 16 Buletin Geospatial Sektor Awam
Satellite imagery is one of the most powerful geospatial tools for coral reef mapping. High-resolution satellites, such as Sentinel-2A, Landsat, and WorldView, provide extensive spatial coverage, allowing for the mapping of large and often remote reef areas that are otherwise di cult to access. These satellites can capture images with resolutions as fine as 10 meters, o ering detailed views of reef structures and the surrounding marine environment. One of the significant advantages of satellite imagery is its ability to monitor changes over time. By analysing time-series data, researchers can detect trends and anomalies, such as coral bleaching events, sedimentation, and algal overgrowth. This temporal monitoring is essential for understanding the impacts of environmental stressors and human activities on coral reefs and for implementing timely conservation interventions. Figure 5 highlights such approaches as reported by Lutzenkirchen et al., 2024. Satellite Imagery Figure 4 Advanced geospatial technologies o er varying levels of resolution from coarse-scale satellite imagery to high-resolution underwater photogrammetry (Lutzenkirchen et al., 2024). Figure 5 Satellite imagery of the Neulka Islands (New Caledonia) by Lutzenkirchen et al., 2024 17
TEKNIKAL 18 Buletin Geospatial Sektor Awam GIS is integral to coral reef mapping, providing a platform for storing, analysing, and visualising geospatial data. GIS allows researchers to integrate various data sources, including satellite imagery, remote sensing data, and field observations, to create comprehensive maps and models of coral reef ecosystems. Through GIS, spatial analyses can be conducted to assess reef health, biodiversity, and habitat extent. For example, GIS can be used to identify areas of high coral cover, detect changes in reef morphology, and evaluate the impacts of human activities such as coastal development and pollution (da Silveira et al., 2021). Additionally, GIS facilitates Geographic Information System (GIS) Figure 6 Coral reef mapping in Pernambuco State, Brazil by da Silveira et al. (2021) Underwater photogrammetry is a technique that involves capturing multiple overlapping photographs of reef structures from di erent angles and processing them with specialised software to generate detailed 3D models as shown in Figure 7. These models provide accurate representations of the reef’s physical features, enabling precise measurements of coral colonies, reef rugosity, and other structural attributes. The use of underwater photogrammetry is particularly valuable for fine-scale mapping and monitoring of coral reefs. It Underwater Photogrammetry Figure 7 3D photogrammetry survey to visualise coral reef ecosystem in Kuantan coastal water the creation of predictive models that can forecast future changes in reef conditions under di erent environmental scenarios, aiding in proactive conservation planning. allows researchers to document changes in coral cover, growth rates, and structural complexity over time, providing critical data for assessing reef health and resilience. The high level of detail obtained through photogrammetry also supports habitat classification and species identification, contributing to a deeper understanding of reef biodiversity.
As we continue to develop and refine these technologies, it is crucial to prioritise collaboration and data sharing to maximise their impact. By leveraging the power of geospatial techniques, we can uncover the hidden treasures of our marine ecosystems and ensure their protection for future generations. The journey towards comprehensive coral reef mapping is challenging, but with the right tools and collaborative e orts, it is an achievable goal that will benefit both nature and humanity. 19 Despite the advancements in geospatial technologies, several challenges remain in coral reef mapping. Data accuracy can be a ected by environmental factors such as water clarity, depth, and weather conditions. Additionally, the high cost of advanced mapping tools and the need for specialised expertise can limit their accessibility, particularly in developing regions. Future directions in coral reef mapping involve the integration of multiple geospatial techniques to overcome these challenges. Combining satellite imagery, remote sensing, GIS, and underwater photogrammetry can provide a more comprehensive and multi-scale understanding of coral reef ecosystems. Advances in machine learning and artificial intelligence (AI) are also set to revolutionise coral mapping, enabling automated image analysis and pattern recognition to process vast amounts of data more e ciently. Moreover, the increasing availability of high-resolution satellite imagery and a ordable drone technology is democratising coral reef mapping, making it accessible to a broader range of stakeholders. Collaborative e orts and open data initiatives will further enhance our ability to map and monitor coral reefs globally, fostering international cooperation in marine conservation. In conclusion, the mapping of uncharted coral reefs in Malaysia is a vital endeavour for preserving marine biodiversity and supporting local communities. Current methods have provided valuable insights but are limited by various constraints. The integration of advanced geospatial techniques o ers a promising future for coral reef mapping, enabling comprehensive and e cient assessments at multiple scales. Combining satellite imagery, remote sensing, GIS, and underwater photogrammetry can provide a more comprehensive and multi-scale understanding of coral reef ecosystems. “ “ Challenges and Future Directions Conclusion “ “ By leveraging the power of geospatial techniques, we can uncover the hidden treasures of our marine ecosystems and ensure their protection for future generations.
Enhancing Open Geospatial Data Services in Malaysia: A Comparative Analysis of Best Practices in the United States, Canada, and Switzerland MAS JULIZA BINTI ALIAS Pusat Geospatial Negara (PGN), Ministry of Natural Resources and Environment Sustainability (NRES) masjuliza@nres.gov.my Abstract This research study explores the valuable insights from a comparative analysis of open geospatial data best practices observed in the United States, Canada, and Switzerland. The objective is to identify e ective strategies for enhancing Malaysia's current geospatial data services. The study investigates open file-based geospatial data variety and policies in the three (3) countries. Despite certain limitations in making direct comparisons, the findings provide essential preliminary insights by learning from the best practices. This study contributes to the groundwork for more comprehensive and e cient open geospatial data services in Malaysia, fostering enhanced accessibility of geospatial information for diverse stakeholders. Introduction “ “ Open data initiatives are transforming geospatial information access globally by offering free and unrestricted geographic datasets that drive innovation and decision-making. Keywords : Geospatial data, open data services, data variety, policies, national geospatial agency Figure 1 Landsat Data Citations in Scopus versus the Data Price Source of image: Landsat Missions (2023) TEKNIKAL 20 Buletin Geospatial Sektor Awam
Geospatial data is tied to specific Earth locations, represented by geographic coordinates (Dinkins, 2023), and supports various applications. This study focuses on three (3) main types of geospatial data: Topographic Data: Details the Earth's surface, including natural and artificial features, crucial for urban planning, environmental analysis, and infrastructure development. Elevation Data: Provides vertical height information, essential for flood modelling, slope analysis, and precision agriculture. Boundary Data: Defines administrative and political divisions, important for governance, land management, and electoral planning. “ “ Despite the benefits, Malaysia has not fully adopted open geospatial data due to concerns over balancing accessibility with revenue and navigating legal and policy complexities. Geospatial data can be in vector (discrete features) or raster (grid cells) formats, with common file types like Shapefile and GeoTIFF. Providing data in diverse formats enhances accessibility and utility across applications. Most countries have a government agency that coordinates, manages, and promotes geospatial data, referred to in this study as the national geospatial organisation. In the United States, the USGS handles extensive geospatial data and collaborates widely to ensure data quality and accessibility. In Canada, the Earth Sciences Sector (ESS) of Natural Resources Canada (NRCan) oversees the Canadian Geospatial Data Infrastructure (CGDI), facilitating nationwide data sharing. In Switzerland, Swisstopo manages topographic data and promotes open data initiatives, working with various authorities to ensure data availability for multiple applications. These organisations play key roles in advancing open geospatial data accessibility and use in their respective countries. 21 Open data initiatives are transforming geospatial information access globally by o ering free and unrestricted geographic datasets that drive innovation and decision-making. Recognizing geospatial data as public property, governments play a crucial role in ensuring accessibility and transparency, which aligns with principles of democratic governance and citizen empowerment (Craglia et al., 2012; Vancauwenberghe et al., 2019). Open data initiatives can significantly boost data usage and return on investment. As illustrated in Figure 1, the United States Geological Survey (USGS) Landsat data saw a marked increase in citations after the data was made openly available in 2010. Despite the benefits, Malaysia has not fully adopted open geospatial data due to concerns over balancing accessibility with revenue and navigating legal and policy complexities. This research examines the open data practices of the United States, Canada, and Switzerland to gather insights for enhancing Malaysia's geospatial data services, focusing on the types of data o ered and the policies in place.
Data and Methods Open Geospatial Data Service Data Variety Topographic Data Product Type Format Scale Product Type Format Resolution Product Type Format Extent Elevation Data Boundaries Data Download Limits Coyright & Restrictions Liability on Accuracy Policies Figure 2 Comparison framework of open geospatial data services between best practice countries This study examines open geospatial data practices in the U.S., Canada, and Switzerland, focusing on data variety and open data policies. Information is collected from the o cial websites: USGS (U.S.), NRCan (Canada), and Swisstopo (Switzerland). Platforms analysed include TopoView and The National Map by the USGS, GeoGratis by the NRCan, and Swisstopo’s main site. QGIS Desktop Version 3.28.3 is used for viewing the downloaded datasets. The study uses the comparison framework in Figure 2 to evaluate common practices in data variety and policies. The variety of topographic, elevation, and boundary data is evaluated considering the product, type, format, and scale/resolution/extent of the open data. In term of policies, the study investigates the download limits, copyright and restrictions, and liability on accuracy of the open geospatial data. Insights from this analysis aim to improve Malaysia’s open geospatial data services. TEKNIKAL 22 Buletin Geospatial Sektor Awam
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