This paper presents a workflow capitalizing Google Earth’s High-resolution Imagery (GEHRI) to detect and monitor Artificial Waterway (AW) in a tropical peat forest. The workflow applies an Object-Based approach derived from concepts and techniques for indexing visual semantics in a ten-levels of visual structures. Three sequential stages are proposed as simplification of complex various object-based analysis. First stage, the ground characteristics of AW were summarized based on ground observations and local knowledge. Second stage, object-based semantics were predicted using the summarized characteristics and on-screen digitization was conducted. In the third stage, the data were transferred and analyzed using a GIS application. A case study was conducted in Sebubus Forest of West Kalimantan Province, Indonesia. Seven images of GEHRI were found for the study area. From the analysis, it was found that since 2009 until 2017, artificial waterways had entered deep into the peat forest area. There were 66 objects allegedly as artificial waterways reaching 166.5 km in length which from the pattern was thought to be a part of the farming of local people. This study concluded that improvement of conservation in peat forest management and detection model and monitoring by using simplified object basis approach. It is conducted to strengthen monitoring peatland in a participatory manner where high-skilled labor is not necessary. Keywords: Artificial Waterway, Tropical Peat, GEHRI, GEOBIA. Abstrak Penelitian ini menampilkan model pendeteksian dan monitoring perkembangan saluran air buatan di kawasan hutan gambut tropis dengan memanfaatkan citra satelit resolusi tinggi dari Google Earth (GEHRI). Pendekatan yang digunakan adalah analisis citra berbasis objek yang diilhami dari konsep dan teknik pengindeksan Visual Semantic berdasarkan sepuluh tingkat visual struktur. Dalam penelitian ini, tiga tahap proses dirumuskan sebagai penyederhanaan berbagai proses analisis berbasis objek yang biasanya sangat rumit. Tahap pertama, ikhtisar karakter objek dilapangan dengan metode observasi dan survey lapangan. Tahap kedua, identifikasi semantik objek dan digitalisasi pada tingkat citra, dan tahap yang ketiga adalah analisis menggunakan aplikasi GIS. Penelitian ini menggunakan studi kasus yang dilakukan di kawasan Hutan Gambut Sebubus di Kabupaten Sambas, Kalimantan Barat, dan ditemukan tujuh citra dari GEHRI yang digunakan sebagai kawasan studi. Dari hasil analisis didapati bahwa sejak 2009 sampai dengan 2017, saluran air buatan telah masuk jauh kedalam kawasan hutan gambut. Terdapat 66 objek yang diduga kuat sebagai saluran air buatan dengan panjang mencapai 166,5 km, yang dari polanya diduga bagian dari pertanian masyarakat lokal. Studi ini menyimpulkan bahwa diperlukan perbaikan manajemen konservasi kawasan hutan gambut dan model deteksi dan monitoring dengan menggunakan pendekatan berbasis objek yang disederhanakan. Hal ini dilakukan untuk memperkuat monitoring kawasan gambut secara partisipatif, dimana tenaga dengan keahlian tinggi tidak terlalu diperlukan. Kata Kunci: Saluran Air Buatan, Hutan Gambut, GEHRI, GEOBIA
Despite its potential use for earth observation and GIS-based analysis, Public Administrative Data (PAD) has been neglected in the spatial big data discussions. For instance, linking unaggregated public databases to the smallest administrative units for mining spatial data currently absents from literature. In this study, a neighborhood association base map was developed and the usability as a platform for linking PAD in Indonesia was investigated. The base map is proposed as a new feature in Indonesia's SDI. A data model was developed, and data accuracy and reliability were assessed by a case study. Four unaggregated databases obtained from public institutions were examined using common structured query language. The results show that from 1.3 million records, more than 95% can be directly linked to the base map. Finally, it is concluded that despite the existence of challenges, linking PAD with the base map is feasible and beneficial for GIS-based analysis.
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