Fatemeh Ahmadi; yasser Ebrahimian Ghajari; Abbas Kiani
Abstract
Abstract: Remote sensing provides a powerful data source for mapping urban areas and monitoring urban dynamics on various scales. Among remote sensing data, images taken at night provide an effective way to monitor human activities on a global scale. Because the features and capabilities of these images ...
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Abstract: Remote sensing provides a powerful data source for mapping urban areas and monitoring urban dynamics on various scales. Among remote sensing data, images taken at night provide an effective way to monitor human activities on a global scale. Because the features and capabilities of these images can enable separating urban areas and other human activities, the main feature of which is the use of light at night by accurately measuring the location, from the background without light. Via providing uninterrupted and continuous monitoring from the night world perspective, these images provide valuable source and results of human activities from the past to the present; the time series analysis of this data is highly valuable for discovering, estimating and monitoring social and economic dynamics in countries, especially sub-regions where there are no official statistics. With the development of night data satellite sensors in recent years and new research conducted in the field of night-time data, this study aims to review the advances in night-time sensors, introduce the existing data and products, review and express the advantages and disadvantages of each one and review methods and solutions presented in previous research for solving the existing problems and limitations in order to improve these images. Therefore, according to the reviews of 225 articles on night light from various credible journals, the results demonstrated that 65% of the available articles were from night light data in the urban field (59% related to urban dynamics extracting and studying and 6% for population surveys) and 35% for non-urban field (17% for energy consumption, 13% for economic issues and 5% for other issues such as pollution) in a more detailed look. Articles that have tried to provide methods for correcting night images can be categorized as follows: in the DMSP-OLS data, 44% of the articles were urban surveys, 14% were for economic purposes, 38% for the general purpose of correction and 4% for other purposes. Visible and infrared imaging radiometer suite (VIIRS) data were 57% for economic purposes, 36% for urban surveys and 7٪ for other purposes. The results and findings of this study can provide a general overview for researchers to familiarize and understand the trends of various studies in the use of night light data. It can also help researchers choose the right data and algorithm according to their purpose and study field.
