Segmentation and distribution of watershed using K-Modes clustering algorithm and Davies-Bouldin index based on geographic information system (GIS)

2016 ◽  
Author(s):  
Muhammad Farid Fahmi ◽  
Yoyon K. Suprapto ◽  
Wirawan
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Clustering Algorithm ◽  
Geographic Information

scholarly journals Identifying Urban Road Black Spots with a Novel Method Based on the Firefly Clustering Algorithm and a Geographic Information System

2020 ◽  
Vol 12 (5) ◽  
pp. 2091 ◽  
Author(s):  
Tengfei Yuan ◽  
Xiaoqing Zeng ◽  
Tongguang Shi
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Euclidean Distance ◽  
Clustering Algorithm ◽  
Rapid Development ◽  
Geographic Information ◽  
Sustainable Urban Development ◽  
Urban Road ◽  
Cost Distance ◽  
Black Spots

With the rapid development of urban road traffic, there are a certain number of black spots in an urban road network. Therefore, it is important to create a method to effectively identify the urban road black spots in order to quickly and accurately ensure the safety of residents and maintain the sustainable development of a city. In this study, a GIS (geographic information system) and the Firefly Clustering Algorithm are combined. On the one hand, a GIS can accurately extract the distance between accident points through its spatial analysis function, overcoming the disadvantage of the accident data not usually including the specific location data. On the other hand, the Firefly Clustering Algorithm can be used to comprehensively extract the characteristics of accident points, which is particularly suitable for the identification of black spots. In order to verify the feasibility of the proposed method, this research compares the identification effect between the OD (origin–destination) cost distance calculated by GIS and the Euclidean distance. The results show that the Euclidean distance is smaller than the OD cost distance and that the accident search method based on the Euclidean distance can overestimate the number of black spots, especially for intersections. Therefore, the proposed method based on the Firefly Clustering Algorithm and GIS can not only contribute to identifying urban road black spots but also plays an auxiliary role in reducing urban road crashes and maintaining sustainable urban development.

PEMANFAATAN WEBGIS DALAM MENDUKUNG PROGRAM DESA BERSAUDARA DI KABUPATEN MAGELANG

2018 ◽  
Vol 2 ◽  
pp. 223
Author(s):  
Humam Zarodi
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographic Information

<p>Erupsi Gunungapi Merapi tahun 2010 mengakibatkan banyak korban jiwa, kerusakan aset dan kerugian di berbagai bidang. Untuk meminimalkan korban jiwa, kerusakan dan kerugian, diperlukan upaya pengurangan risiko bencana (PRB). Salah satu upaya yang dilakukan adalah program desa bersaudara (<em>sister village</em>) yang digagas oleh Pemerintah Kabupaten Magelang melalui Badan Penanggulangan Bencana Daerah (BPBD). Program desa bersaudara ini bertujuan agar ada kepastian tempat pengungsian, mengurangi kesemrawutan proses pengungsian serta memudahkan pelayanan pengungsi. Program ini dapat memanfaatan Sistem Informasi Geografis/<em>Geographic Information System</em> (GIS) yang berbasis web (<em>WebGIS</em>). <em>WebGIS</em> mampu mendiseminasikan peta yang dihasilkan dalam program desa bersaudara, misalnya peta jalur evakuasi. Makalah ini bertujuan untuk mendiskripsikan pemanfataan <em>WebGIS</em> dalam mendukung program desa bersaudara, dengan mengambil kasus di Desa Ngargomulyo (desa rawan bencana) dan Desa Tamanagung (desa penyangga/ penerima pengungsi). Metodenya adalah memaparkan proses pemetaan jalur evakuasi. Proses penyusunan peta tersebut terbagi empat tahap:   survei lapangan, penyiapan data spasial, coding dan publikasi. Hasilnya adalah tampilan peta jalur evakuasi yang bisa diakses oleh siapapun tanpa menggunakan aplikasi GIS yang memudahkan masyarakat pengungsi, penerima pengungsi, pemerintah maupun parapihak, mengetahui asal pengungsi, jalur evakuasi dan titik pengungsian. Penelitian ini menyimpulkan bahwa pemetaan <em>WebGIS</em> dapat mendukung upaya PRB dengan keunggulan bisa dijangkau pengguna secara sangat luas.<strong></strong></p><p><strong>Kata kunci</strong>: desa bersaudara, <em>sister village</em>, pemetaan jalur evakuasi, <em>gis</em>, <em>webgis</em></p>

Implementation of A-Star Algorithm for Searching Routes Near the Tsunami Evacuation Shelter Point

2020 ◽  
Vol 4 (2) ◽  
pp. 254-259
Author(s):  
Renita Astri ◽  
Sularno
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Distance Estimation ◽  
Geographic Information ◽  
High Population

District of West Padang which is the area closest to the coast and has a high population. Therefore a geographic information system was created using the A-Star Algorithm method. The A-Star algorithm uses the closest distance estimation to reach a goal and has a heuristic value that is used as a basis for consideration. In this system there are alternative paths and show the amount of capacity and distance from the shelter to be addressed.

Geographic information system development in the CARETS project

1977 ◽  
Author(s):  
William B. Mitchell ◽  
Robin G. Fegeas ◽  
Katherine A. Fitzpatrick ◽  
Cheryl A. Hallam
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
System Development ◽  
Geographic Information ◽  
Information System Development
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