Updated: Jul 28
In general, road density in Indonesia is relatively low compared to developed countries. According to data from the Central Statistics Agency (BPS) of Indonesia in 2019, the total length of road networks in Indonesia was approximately 563,278 kilometers. With a land area of around 1.9 million square kilometers, this results in a road density of approximately 0.29 kilometers per square kilometer. The rapid urban growth in Indonesia, driven by urbanization and population migration to major cities, has affected the level of road density. The influx of population migrating to urban areas creates pressure on existing road infrastructure.
Road density refers to the level of road network density in a specific area. Typically, road density is measured by calculating the total length of roads within a given area and comparing it to the area's size. The resulting measurement of road density provides an indication of the extent to which the road network has been developed and reflects the level of accessibility to that area. In this article, we will discuss the concept of road density, commonly used measurement methods, and the important implications of road density within Geographic Information Systems (GIS).
Spatial analysis plays a crucial role in examining road density and its spatial distribution using GIS. GIS technology allows for the integration of road network data with other spatial datasets, such as population density, land use, and transportation patterns. By overlaying and analyzing these datasets, GIS can provide valuable insights into the relationship between road density and various socio-economic factors.
Determining the boundary of the Area Using Grid.
Grid is one of the features available in the iDesktop SuperMap software. Grid is used to divide a specific study area or region into uniformly sized square cells. Grid can be used in various spatial analyses, such as availability analysis, density analysis, or interpolation analysis. For example, you can calculate the number of features or feature density in each grid cell, or perform spatial data interpolation based on values within grid cells.
The utilization of spatial queries in iDesktop SuperMap allows you to identify, extract, and analyze relevant road data in creating road density. By using spatial queries, you can identify and extract the necessary road data to calculate road density within a specific area.
The use of a 2D monitoring dashboard using Geoportal SuperMap offers several advantages that can enhance the user experience and improve efficiency in spatial data monitoring.