A study on Extraction of Natural Cities from the Nightlight Imagery Using Head/tail breaks method

University essay from Högskolan i Gävle/Avdelningen för Industriell utveckling, IT och Samhällsbyggnad


With the high development of economic and demand for city research, an issue of detecting city boundaries plays an extremely important role in urbanization that promotes the progress of human civilization. Some critical applications such as land use, urban planning and city sprawl have been constantly discussed, which rely on the acquisition of city areas. For the better acquisition of city areas, choosing a proper method to capture city boundaries becomes significant where it greatly improves the value of city study. Although conventional data can be used to define the city boundaries, some drawbacks still exist when measuring the city boundaries in a global scale.

Remote sensing (RS) data of nightlight imagery (2010) by Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) acquired from National oceanic and atmospheric administration's National Geoscience Data Center (NOAA/NOGA) is applied to extract the city boundaries in fifty countries, of which these countries are chosen followed by the Gross Domestic Product that are ranked in top 50. In this case, the data distribution of nightlight imagery followed by heavy-tailed distribution. Head/tail break algorithm poses a possibility of calculating reasonable threshold and extracting the natural cities with the help of software based on the Geomatics information system (GIS). An extended study of power law is made by using of power law estimator from previous studies to check whether the extracted natural cities can match the power law distribution.

Result shows that combination of the nightlight imagery data and the head/tail break is capable of extracting the city boundaries and a set of possible thresholds with visual inspection by using the head/tail break are executed. There is only one country, namely Belgium, cannot be processed due to its data properties. Result also address how well the natural cities of the fifty countries can be extracted in terms of visual inspection, among the chosen cities, 33 of countries boundaries can be better matched and 13 countries can fundamentally match the city boundaries. Meanwhile, an extended study of power law is provided and four countries have to be found that do not follow the power law distribution. From the result obtained, the study expects that integration of support data will efficiently increase the accuracy of extraction and more useful information can be acquired in further study. On the other hand, a comparative study of threshold decision needs to be verified, put it differently, whether using head/tail break with visual inspection on extracted city boundaries is helpful or not.

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