4.7 Article

Understanding multi-temporal urban forest cover using high resolution images

Journal

URBAN FORESTRY & URBAN GREENING
Volume 29, Issue -, Pages 106-112

Publisher

ELSEVIER GMBH
DOI: 10.1016/j.ufug.2017.10.020

Keywords

Urban forestry; Image processing; Object-based classification

Funding

  1. CAPES (Coordination for the Improvement of Higher Education Personnel)
  2. Embrapa Forestry (Brazilian Agricultural Research Corporation)

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Urban forests offer city residents a better quality of life. They also act as barrier and filter to pollutants resulting from human activities. Mapping the distribution of forests in urban areas is therefore important for good urban planning. Currently, high resolution images are considered useful tools to quantify forested urban areas for large scale urban development. The objective of this work was to evaluate multi-temporal urban forest area changes over different land-use classes, using available high-resolution images obtained from different satellites. The municipality of Araucaria (Parana State) was chosen as study area because it is a large industrial zone of southern Brazil. The effects on the forests within this municipality caused by the increase in human activities between 2005 and 2012 were determined using high resolution images (5 m). We recorded a reduction of 22.8% in the forests surrounding urban areas of the municipality, as a result of deforestation of 791 ha and plantation of only 251 ha. The utility, commercial and residential zones which are more crowded the areas of highest population density were those which showed the greatest loss of tree cover. Object-based classification accuracy using images from different satellites was sufficient to quantify the evolution of tree-cover over the studied period.

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