Nighttime Light Monitoring

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Product Category

• Land use
• Land cover
• Natural Disaster
• Climate Change
• Coast Management 

• Marine
• Earth's Surface Motion

Financial Domains

• Investment management 
• Risk Analysis 
• Insurance management 
• Green finance

User requirements 

UN16: Nighttime light monitoring.

Description

Nighttime light plays a crucial role in various Earth science studies and practical applications. By filtering out unwanted sources like moonlight and other interferences, we can effectively track and analyse artificial lights from human activities, such as street and building lighting. Hence, monitoring nighttime lights can serve various purposes, including measuring the extent and characteristics of urbanization processes, estimating economic growth at both national and subnational scales, mapping global poverty, and population density, and evaluating access to electricity and electrification. Generally, there are three remote sensing sensors for nighttime light, and each of them has advantages and disadvantages. DMSP OLS provides long-term data from the early 1970s until 2011, however, it has low spatial (2.7km) and radiometric (6bits) resolutions. The VIIRS Day/Night Band (DNB) represents an enhancement over the previous DMSP OLS system, offering improved spatial and radiometric resolution. VIIRS provides spatial resolutions of 375 and 750 meters (depending on the band), and daily temporal resolution, and delivers more comprehensive global coverage with higher-quality data. In addition, there is NASA’s Black Marble product which is an enhancement product of DNB by applying atmospheric and angular corrections and applying an algorithm to remove moonlight contribution. One of the advantages of using DMSP-OLS and VIIRS-DNB is that the World Bank provides a data archive called The Light Every Night dataset that is published on Amazon Web Services including tutorials about using the dataset. The last product is Luojia 1-01 which was produced by Wuhan University in 2018 and has the advantage of higher spatial resolution (130m) but it lacks the high temporal resolution of DNB by having data every 15 days. Furthermore, there is inconsistency in the data available on the portal, as the most recent observations are only up to March 2019, and in certain regions of the world, the data is even earlier. Finally, using land cover data can be useful to concentrate the service for urban areas only.

Spatial Coverage Target

Regional

Data Throughput

Rapid tasking 

Data availability

• High
• High

• Low
• Low

PRODUCT SPECIFICATIONS

Main processing steps

The dynamic change of nighttime light is the main indicator of the change in human activities. Therefore, time series nighttime light data is essential for related applications. Apply masks and filters to remove unwanted data or sources of interference. This may involve masking out areas with heavy cloud cover or masking out natural sources of light, such as moonlight, to focus on artificial light sources. Conduct calibration processes to convert the digital numbers in the nighttime light imagery to radiance or reflectance values, making the data suitable for quantitative analysis.  Generate time series data by compiling and comparing nighttime light data over various periods. This enables the monitoring of changes in artificial light patterns over time. Conduct statistical and spatial analyses to interpret the data and derive insights related to urbanization, economic activities, energy consumption, and other factors. Create visualizations and maps to present the nighttime light data in a clear and informative manner.

Input data sources

Optical:   DMSP OLS, VIIRS DNB, Luojia 1-01

Radar: N.A

Satellite-based products: N.A

Supporting data:  Land cover data such as ESA CCI Land cover (20m resolution)

Accessibility

DMSP OLS, VIIRS DNB: freely and publicly available from NASA.

Luojia 1-01: available from Wuhan university

Spatial resolution

Luojia 1-01: 130m

VIIRS DNB: 750m

DMSP OLS: 2700m

Frequency (Temporal resolution)

Luojia 1-01: 15 days

VIIRS DNB: Daily

DMSP OLS: Annual

Latency

Luojia 1-01: NA

VIIRS DNB: Daily

DMSP OLS: Archive

Geographical scale coverage

Globally

Delivery/ output format

Data type: Raster/Vector/Charts

File format: GeoTIFF/Shapefile /PDF

Accuracies

Thematic accuracy: N.A

Spatial accuracy: 1.5-2 pixels of input data

Constraints and limitations

• Cloud presence
• The lower spatial resolution of the products
• Natural light sources like moonlight can interfere with the detection of artificial nighttime light.
• May not be sensitive enough to detect low-intensity light sources accurately, which can lead to underestimation of nighttime light in less densely populated areas.

User's level of knowledge and skills to extract information and perform further analysis on the EO products.

Skills: Ample

Knowledge: Ample

P20: Nighttime light monitoring

Download the product sheet gap analysis 

Maturity score

Mean: 2.5

STD: 0.66

Constraints and limitations

·  Cloud presence

·  Natural light sources like moonlight can interfere with the detection of artificial nighttime light.

·  May not be sensitive enough to detect low-intensity light sources accurately, which can lead to underestimation of nighttime light in less densely populated areas.

Relevant user needs

UN37: Projection of risk to portfolio assets into the future.

R&D gaps

·  The lower spatial resolution of the products

Potential improvements drivers

·  New missions with higher spatial resolution

Utilisation level review

Utilisation score

Mean: 2.68

STD: 1.12

No utilisation

Unawareness of the existence of this EO product

Low utilisation

·  The product is already satisfying the technical and usability requirements.

·  Unawareness of the existence of commercial EO products with better specifications,

Awareness of its use as a proxy for economic activity. Would be good for the FM community to check if it has other use cases within the industry.

Medium utilisation

High utilisation

Critical gaps related to relevant user needs