geography

Visualize Satellite images with Mapbox API

Accessing to satellite images based on geolocalization has many applications in data visualization and data sciences. There are several alternative of services which provide API interfaces which can be integrated in notebooks or articles, for instance : Google Maps, Bings Maps, OpenStreetMap, … You can find free, freemium or premium services. In this post we are going to illustrate a short demo of mapbox satellite API. Mapbox present itself as the “location data platform for mobile and web applications”.

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China mainland population density

In an earlier post we mapped the urbanization rate of China at province level. In this post we will go futher by visualizing where Chinese people are living using a gridded population map. We will use the NASA dataset (Population Density Grid, v3 (1990, 1995, 2000)) which consists of estimates of human population by 2.5 arc-minute grid cells. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells.

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Getting and cleaning data, example of Chinese airports - Part 4/5

One of the big problem for anybody interested in China and data science is the availability of data sets. There are limited free resources available and they are often incomplete or inaccurate. Getting data and especially cleaning data becomes one of the biggest pain of data science applied to China. The objective of this series of post is to illustrate the problem and associated process on a specific example: plot a map of the airports of mainland China.

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Getting and cleaning data, example of Chinese airports - Part 3/5

Introduction Objective One of the big problem for anybody interested in China and data science is the availability of data sets. There are limited free resources available and they are often incomplete or inaccurate. Getting data and especially cleaning data becomes one of the biggest pain of data science applied to China. The objective of this group of post is to illustrate the problem and associated process on a specific example: plot a map of the airports of mainland China.

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Getting and cleaning data, example of Chinese airports - Part 2/5

Introduction Objective One of the big problem for anybody interested in China and data science is the availability of data sets. There are limited free resources available and they are often incomplete or inaccurate. Getting data and especially cleaning data becomes one of the biggest pain of data science applied to China. The objective of this group of post is to illustrate the problem and associated process on a specific example: plot a map of the airports of mainland China.

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Getting and cleaning data, example of Chinese airports - Part 1/5

Introduction Objective One of the big problem for anybody interested in China and data science is the availability of data sets. There are limited free resources available and they are often incomplete or inaccurate. Getting data and especially cleaning data becomes one of the biggest pain of data science applied to China. The objective of this group of post is to illustrate the problem and associated process on a specific example: plot a map of the airports of mainland China.

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China Urbanisation & Large cities

Objective In this article we are going to plot a map of China urbanization rate per provinces together with Chinese cities with at least 2 millions population. In a nutshell : 1 - Get rural and urban population data from official China statistic bureau, clean the data, same two steps for Chinese largest cities 2 - Prepare a map of China with provinces 3 - Get data for the main Chinese cities, population, names and longitude, latitude 4 - Plot China base map with provincial subdivisions, choropleth of urbanization rate, add main cities

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