Who needs our help?
In an ever more transparent world, China continues to mystify. A lack of reliable data has forced our previous analysis of the world’s most populous country to be based on anecdotal evidence and disparate reports. Orbital Insight’s China Economic Index finally helps investors, governments, think-tanks and NGOs to achieve the clarity they need to make decisions.
Assessing Economic Development through Multiple Macro Signals
Application of Orbital Insight’s proprietary machine vision and data science algorithms in China can shed new light on its economic development, in terms of import/export volume, commodity production and consumption, agricultural output, expansion and utilization of energy infrastructure, relative poverty and wealth levels, adherence to national regulatory frameworks, and geopolitical developments (South China Sea reclamation), and more.
Cities of interest
Tianjin, Chongqing, Hangzhou, Nanjing, Wuhan, Chengdu, Xi’an, Changsha, Fuzhou, Jinan, Hefei, Zhengzhou, Hohhot, Haikou, Guiyang, Suzhou, Shanghai, Kunming, Dalian, Xiamen, Ningbo, Dongguan, Wuxi, Qingdao, Wenzhou, Changzhou, Tangshan, Xuzhou, Huizhou, Yichang, Zhenjiang, Huainan, Huai’an
City Economic Development, e.g., car density, truck density, building construction, electricity consumption through nighttime illumination, road building
Import and Export, e.g.,port activity (ship count and sizes) , rail throughput, aircraft count in airports, commodity stockpiles at ports
Industrial and Rural Output, e.g., multi-granularity agricultural yields, crop health, pit mining activity, factory activity as indicated by trucking activity
Energy, e.g., oil storage (commercial and SPR), development of coal plants, solar cell farms, and wind farms
Policy, determine with unprecedented transparency China’s policy efficacy related to population migration, infrastructure construction, economic activity, ghost-city occupancy, etc. Glean insights about Beijing’s policy efficacy on specific or national projects
Tracking, Gross Floor Area (GFA) of buildings is one of Orbital Insight’s development indicators. Using a convolutional neural network satellite imagery is classified in terms of building shadows, see Figure 1, which are interpreted in terms of trigonometry to yield a time series of GFA for each city of interest, see Figures 2 and 3. Shadows are indicative of building heights.
A section of Nanjing algorithmically segmented in terms of building shadow by a convolutional neural network
Source: DigitalGlobe Inc.