TY - JOUR
T1 - Utilization of online geospatial data sources for oikonym study
T2 - 4th International Geography Seminar 2020, IGEOS 2020
AU - Susilo, B.
AU - Cahyono, A.
N1 - Publisher Copyright:
© 2022 Institute of Physics Publishing. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Oikonym is a part of toponym that focus the study on the name given to inhabited place. In the past, availability of data was one of the obstacles in the study of toponym as well as oikonym. Now days, the development of digital mapping and information technology particularly internet enables oikonym data obtained from a variety of sources. This study aimed to explore the typology of housing names as well as the geographical characteristic of the housing location by means of mapping and spatial analysis. Data required for mapping and analysis were obtained via internet therefore referred as online geospatial data sources. Housing names were analyzed based on their generic and specific elements and language of origin used for naming. Spatial analyses i.e., 3D analysis and network analysis were performed to obtain geographical characteristic of the housing location. This study shows, about 57% of housings which have generic name, use indigenous element i.e., local language. In addition to this, about 80% of housings use indigenous element for their specific names. Housings mostly located in low land and gentle slope. On average, distance of housings to the center of capital area is 3.3 km and road density is 6.6 km/km2.
AB - Oikonym is a part of toponym that focus the study on the name given to inhabited place. In the past, availability of data was one of the obstacles in the study of toponym as well as oikonym. Now days, the development of digital mapping and information technology particularly internet enables oikonym data obtained from a variety of sources. This study aimed to explore the typology of housing names as well as the geographical characteristic of the housing location by means of mapping and spatial analysis. Data required for mapping and analysis were obtained via internet therefore referred as online geospatial data sources. Housing names were analyzed based on their generic and specific elements and language of origin used for naming. Spatial analyses i.e., 3D analysis and network analysis were performed to obtain geographical characteristic of the housing location. This study shows, about 57% of housings which have generic name, use indigenous element i.e., local language. In addition to this, about 80% of housings use indigenous element for their specific names. Housings mostly located in low land and gentle slope. On average, distance of housings to the center of capital area is 3.3 km and road density is 6.6 km/km2.
UR - http://www.scopus.com/inward/record.url?scp=85142495234&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/1089/1/012030
DO - 10.1088/1755-1315/1089/1/012030
M3 - Conference article
AN - SCOPUS:85142495234
SN - 1755-1307
VL - 1089
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012030
Y2 - 29 September 2020 through 30 September 2020
ER -