Land use/land cover change detection and urban sprawl analysis

• Autor(a) principal: Viana, Cláudia M.
• Data de Publicação: 2019
• Outros Autores: Oliveira, Sandra, Oliveira, Sérgio, Rocha, Jorge
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/38912
• topic: Urban sprawl; Land use/cover change; Remote sensing; Time-Weighted Dynamic Time Warping; Time-series

This study presents a proposed application of the Time-Weighted Dynamic Time Warping (TWDTW) method for urban sprawl analysis. Four spectral indices were computed from a long time-series of Landsat satellite imagery, corresponding to 48 scenes acquired between 2006 and 2018. The spectral indices were the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built Index (NDBI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Bareness Index (NDBaI), which when processed resulted in 192 different images. The R package dtwSat was used for image processing, since it represents one of the few open source software programs available for processing large time-series datasets. The method was tested applied in the Alentejo Region of Southern Portugal; traditionally a rural region, where urban sprawl presents risks for the preservation of agricultural systems and for ecosystem sustainability. The sprawl analysis was integrated in a Geographic Information System (GIS), in which we computed an Expansion Index to quantitatively assess the three main urban land expansion types: infill, extension, and leapfrog. The results show that, between 2007 and 2012, the main changes are due to extension (50 ha), but with a significant amount of infill (36 ha) and leapfrog growth (4 ha), with this latter being the worst-case scenario. However, in the subsequent period, 2012-2017, urban growth decreased to about 10 ha, comprising both infill and extension, but notably leapfrog expansion disappeared. Our methodology proved to be flexible for managing irregular sampling and an out-of-phase time-series. The procedure offers a quantitative means of assessing urban sprawl dynamics and represents a potential strategy for defining sustainable urban development.