The boundaries of the cities are not immutable, they can be changed. With the development of the economies and societies, the population and pollution of cities are increasing. Some urban areas are expanding with more population or other dynamics of urbanization, while other urban areas are reducing with the changing of the dynamics. Therefore, detecting urban areas or delineating the boundaries of the cities is one of the most important steps for urban studies, which is closely related to human settlements and human activities. Remote sensing data (RS) is widely used to monitor and detect land use and land cover on the surface of the earth. But the extraction of urban areas from the ordinary RS data is not easy work. The Operational Linescan System (OLS) is the sensors of the Defense Meteorological Satellite Program (DMSP). The nighttime lights from the DMSP/OLS provide worldwide remotely sensed data to analyze long-term light emissions which are closely related to human activities. But the nighttime lights imagery data contains inherent errors. Therefore, the approaches to calibrate the data and extract the urban areas from the data are complicated. The long-term objective of this thesis is to delineate the boundaries of the natural cities of the continental United States of America (USA) from 1992 to 2010 of nightlight imagery data with all the different satellites. In this thesis, the coefficients for the intercalibration of the nightlight imagery data have been calculated based on the method developed by Elvidge, et al. (2009), but the coefficients are new and available. The approach used to determine the most appropriate threshold value is very important to eliminate the possible data error. The method to offset this possible error and delineate the boundaries of the cities from nightlight imagery data is the head/tail breaks classification, which is proposed by Jiang (2012b). The head/tail breaks classification is also useful for finding the ht-index of the extracted natural cities which is developed by Jiang and Yin (2013). The ht-index is an indicator of the underlying hierarchy of the data. The results of this study can be divided into two categories. In the first, the achieved coefficients for the intercalibration of nightlight images of the continental USA are shown in a table, and the achieved data of the urban areas are stored in a data archive. In the second, the different threshold values of the uncalibrated images and the individual threshold value of the calibrated images are shown in tables, and the results of the head/tail breaks classification and power law test are also drawn. The results show that the acquired natural cities obey the power law distribution. And the results also confirm that the head/tail breaks classification is available for finding a suitable threshold value for the nightlight imagery data. Key words: cities’ boundaries; DMSP/OLS; head/tail breaks classification; nighttime lights; power law; urban areas

Inadequate economic data makes it more difficult for its incorporation in security-policy related prediction and there is a need for alternative datasets. Satellite data, more specifically nighttime lights data, can be used as a proxy for the economy. In this project, the correlation between nighttime lights and the economy between 1992 and 2018 is explored for five countries in Africa: Nigeria, Libya, the Central African Republic, the Republic of the Congo and Ghana. Data from two different satellite series, DMSP-OLS and VIIRS-DNB are used, and the extracted datasets are calibrated for the differences or intercalibrated. There was found to be a high correlation for two of the countries, the Republic of the Congo and Ghana. The biggest improvement can be made by developing the intercalibration method. A pitfall of the method is that it is not generally applicable as unique circumstances seen for Nigeria show in the correlation results.