To state that one railway station is “Good” can be done in different aspects. There are no absolute criteria and this ranges between scales. To a passenger, “Good” station is, perhaps, the one that is well lightened, clean, and have clear signage; or the one that has restaurants, convenience store, and safe. To the businessmen, “Good” station is the one that attracts most traffic as the probability for their purchase in the stations' increases. To the operators, the “Good” station is the one that delivers the most cash flow and has a low maintenance cost. …
Hands-on Tutorials
How is Bandung City’s public transportation service coverage? Which regions are yet to be served by the public transportation network in Bandung City?
Introduction
Bandung City is the capital of West Java Province in Indonesia and it has its own transportation sector problem. At one time, it is considered to be one of the most congested cities in Indonesia, and the 14th in Asia (ADB, 2019). This is shocking because it is expected that Jakarta to be the most congested city, as Jakarta is the capital city and also is popular for its congestion, but Jakarta is second (for instance, Coconuts Jakarta (2019), Detik (2019), and many more). Bandung City is even worse than Mumbai. This makes me, a resident of Bandung City, think…
Python exercise for computer vision
A question popped up in my head. Images are basically raster files. As a raster file, naturally, an image consists of rows and columns filled by colour values. You can see this by opening a picture in Photoshop and zoom in. Or just open the picture and zoom in, you’ll see it’ll get pixelated. So technically, an image can be converted into an excel file that also consists of rows and columns.
How to convert an image into an excel file
Diving into computer vision (CV) science, there is a way by utilising Python and VBA for Excel. In CV…
Hands-on Tutorials
How do you observe the relationship between the two variables? A scatter plot for non-spatial data, bivariate choropleth for spatial data.
Introduction
Are the Covid-19 cases correlate with Urban Density? Does Population Density correlate with Gross Economic Output? What is the relationship between GDRP and Pollution? Are cities more productive than rural?
These questions can be answered by analyzing two spatial datasets. A simple scatter plot might answer it quickly. but in this article, I want to put heavy emphasis on the spatial aspect. This is because these questions rely on the geographical aspect of the elements. Truncating the aspect with a scatter plot might hide strategical or impactful insight regarding the actual nature of the data. …
To understand how cities behave and make better policies, first, we must understand the spatial interactions inside the cities. This is impossible if the cities do not have data with spatial elements. Some Cities have spatial elements in their datasets, but unfortunately, some are not computable. These spatial elements must be computable, as being computable reduces the analysis cost and provides robust results. GeoDataFrame is a simple computable and intuitive “data format” that I propose to be the solution and such data should be procured by cities in Indonesia.
Introduction
Geographic Information System (GIS) is an essential skill an urban planner must-have. With GIS, urban planners may manage, publish, and analyze spatial data. The spatial data is distinct to ordinary data as spatial data has a spatial element that sometimes people overlook. The awareness and intuition about the “spatial” are what makes an urban planner, or geographer powerful.
As an Indonesian Urban Planner, I deal with spatial data every day, and this essay is inspired by a dataset that is published by Jakarta City, Indonesia. I must say, Jakarta City’s spatial data repository impresses me! It is structured, readable, processable…
Geographic Information System
In some cases, you might need to see the relationship between 2 raster datasets. Doing so with GUI applications might be infuriating because of the lag, and inconsistency, and many more. Even worse when dealing with large resolution rasters. Scripting in Python might be an alternative solution that provides you with reliable, fast, automated, and consistent results. This article guides you to display a scatter plot of two raster datasets using basic and popular Python libraries.
Introduction
Raster data is basically an image or matrix. As an image or matrix, it is consisted of arrays and can be formed as data frames or spreadsheets. You can even visualize raster data in Adobe Photoshop or Ms. Excel! Each raster cell holds a single numeric value that can mean anything as it depends on the context. This value can be elevation, land cover index, NDVI (Normalized Difference vegetation Index) all depending on the context.
In some cases, we might want to see the relationship between rasters. For example, does slope affect greeneries? What is the relationship between NDVI and…
DS in Real World
With limited stamina, people are only able to walk to some duration or distance. To promote public transportation usage, the accessibility of public transportation service should be within this distance. Using Geographical Information System, we are able to identify which regions that are not within the walking distance and infer the unserved citizens.
Summary: Jakarta City is among the worst congested city in the world. Public transportation usage must be promoted by first widening the service coverage to the residents. This covering distance should be within 700 m based on the standard walking distance as humans have limited stamina to walk. So,
has Jakarta’s 700 m public transportation range of service reached all of its residents?
The answer is no. There are around (approximated) 827.594 (out of 10 million) citizens that live beyond current public transportation walking distance. 9160.16 out of 64,752 hectares (around 14%) are not covered by the service range. …
