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A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images

Chapa, Fernando ; Hariharan, Srividya ; Hack, Jochen (2019)
A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images.
In: Sustainability, 2019, 11 (19)
doi: 10.25534/tuprints-00009656
Artikel, Zweitveröffentlichung

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Kurzbeschreibung (Abstract)

Urbanization nowadays results in the most dynamic and drastic changes in land use/land cover, with a significant impact on the environment. A detailed analysis and assessment of this process is necessary to take informed actions to reduce its impact on the environment and human well-being. In most parts of the world, detailed information on the composition, structure, extent, and temporal changes of urban areas is lacking. The purpose of this study is to present a methodology to produce high-resolution land use/land cover maps by the use of free software and satellite imagery. These maps can help to understand dynamic urbanizations processes to plan, design, and coordinate sustainable urban development plans, especially in areas with limited resources and advancing environmental degradation. A series of high-resolution true color images provided by Google Earth Pro were used to do initial classifications with the Semi-Automatic Classification Plug-in in QGIS. Afterwards, a new methodology to improve the classification by the elimination of shadows and clouds, and a reduction of misclassifications through superimposition was applied. The classification was carried out for three urban areas in León, Nicaragua, with different degrees of urbanization for the years 2009, 2015, and 2018. Finally, the accuracy of the classification was analyzed using randomly defined validation polygons. The results are three sets of high-resolution land use/land cover maps of the initial and the improved classification, showing the detailed structures and temporal dynamics of urbanization. The average accuracy of classification reaches 74%, but up to 85% for the best classification. The results clearly identify advancing urbanization, the loss of vegetation and riparian zones, and threats to urban ecosystems. In general, the level of detail and simplicity of our methodology is a valuable tool to support sustainable urban management, although its application is not limited to these areas and can also be employed to track changes over time, providing therefore, relevant information to a wide range of decision-makers.

Typ des Eintrags: Artikel
Erschienen: 2019
Autor(en): Chapa, Fernando ; Hariharan, Srividya ; Hack, Jochen
Art des Eintrags: Zweitveröffentlichung
Titel: A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images
Sprache: Englisch
Publikationsjahr: 2019
Publikationsdatum der Erstveröffentlichung: 2019
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Sustainability
Jahrgang/Volume einer Zeitschrift: 11
(Heft-)Nummer: 19
DOI: 10.25534/tuprints-00009656
URL / URN: https://tuprints.ulb.tu-darmstadt.de/9656
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Herkunft: Zweitveröffentlichung aus gefördertem Golden Open Access
Kurzbeschreibung (Abstract):

Urbanization nowadays results in the most dynamic and drastic changes in land use/land cover, with a significant impact on the environment. A detailed analysis and assessment of this process is necessary to take informed actions to reduce its impact on the environment and human well-being. In most parts of the world, detailed information on the composition, structure, extent, and temporal changes of urban areas is lacking. The purpose of this study is to present a methodology to produce high-resolution land use/land cover maps by the use of free software and satellite imagery. These maps can help to understand dynamic urbanizations processes to plan, design, and coordinate sustainable urban development plans, especially in areas with limited resources and advancing environmental degradation. A series of high-resolution true color images provided by Google Earth Pro were used to do initial classifications with the Semi-Automatic Classification Plug-in in QGIS. Afterwards, a new methodology to improve the classification by the elimination of shadows and clouds, and a reduction of misclassifications through superimposition was applied. The classification was carried out for three urban areas in León, Nicaragua, with different degrees of urbanization for the years 2009, 2015, and 2018. Finally, the accuracy of the classification was analyzed using randomly defined validation polygons. The results are three sets of high-resolution land use/land cover maps of the initial and the improved classification, showing the detailed structures and temporal dynamics of urbanization. The average accuracy of classification reaches 74%, but up to 85% for the best classification. The results clearly identify advancing urbanization, the loss of vegetation and riparian zones, and threats to urban ecosystems. In general, the level of detail and simplicity of our methodology is a valuable tool to support sustainable urban management, although its application is not limited to these areas and can also be employed to track changes over time, providing therefore, relevant information to a wide range of decision-makers.

URN: urn:nbn:de:tuda-tuprints-96563
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 500 Naturwissenschaften und Mathematik > 550 Geowissenschaften
Fachbereich(e)/-gebiet(e): 11 Fachbereich Material- und Geowissenschaften
11 Fachbereich Material- und Geowissenschaften > Geowissenschaften
Hinterlegungsdatum: 08 Dez 2019 20:55
Letzte Änderung: 06 Dez 2023 07:16
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