<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Latin American cities are amongst those with the highest rates of urbanization in the world. This process has involved their territorial expansion as well as the densification of some of its neighborhoods, in mainly central areas. This is the case of the city of Santiago del Estero (Argentina) that increased its population by 33% between 1991 and 2010 with the consequent transformations of the local space. In this context, this study analyzes the evolution of vegetated areas and densification of the central area of the city using satellite data. We analyzed two indices: normalized difference vegetation index (NDVI) and Urban Index (UI) time-series data, for the 1992–2011 year period, using the Google Earth Engine for processing Landsat 5 TM images. We found that the NDVI showed a decreasing trend in the timelapse under consideration, while the UI performance registered the opposite trend. The mean NDVI decreased from 0.161 (1992) to 0.103 (2011) while the UI mean increased from 0.003 to 0.036 in the same timelapse. Further, the NDVI has a strong negative correlation with UI (R-squared = -0.862). The results are consistent with the census information that recorded an important demographic and housing growth for the entire city in this period.</p>
</abstract>

Latin American cities are amongst those with the highest rates of urbanization in the world. This process has involved their territorial expansion as well as the densification of some of its neighborhoods, in mainly central areas. This is the case of the city of Santiago del Estero (Argentina) that increased its population by 33% between 1991 and 2010 with the consequent transformations of the local space. In this context, this study analyzes the evolution of vegetated areas and densification of the central area of the city using satellite data. We analyzed two indices: normalized difference vegetation index (NDVI) and Urban Index (UI) time-series data, for the 1992–2011 year period, using the Google Earth Engine for processing Landsat 5 TM images. We found that the NDVI showed a decreasing trend in the timelapse under consideration, while the UI performance registered the opposite trend. The mean NDVI decreased from 0.161 (1992) to 0.103 (2011) while the UI mean increased from 0.003 to 0.036 in the same timelapse. Further, the NDVI has a strong negative correlation with UI (R-squared = -0.862). The results are consistent with the census information that recorded an important demographic and housing growth for the entire city in this period.

Relationship between densification and NDVI loss. A study using the Google Earth Engine at local scale

Environmental & Socio-economic Studies

This work is licensed under the Creative Commons Attribution 4.0 International License.

Latin American cities are amongst those with the highest rates of urbanization in the world. This process has involved their territorial expansion as well as...

Relationship between densification and NDVI loss. A study using the Google Earth Engine at local scale

Published Online: Sep 27, 2022

Page range: 33 - 42

Received: May 13, 2022

Accepted: Aug 25, 2022

DOI: https://doi.org/10.2478/environ-2022-0015

Keywords
vegetation cover loss, densification, NDVI, Google Earth Engine, Santiago del Estero, Argentina

© 2022 Juan Pablo Celemin et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Relationship between densification and NDVI loss. A study using the Google Earth Engine at local scale

Published Online: Sep 27, 2022

Page range: 33 - 42

Received: May 13, 2022

Accepted: Aug 25, 2022

DOI: https://doi.org/10.2478/environ-2022-0015

Keywordsvegetation cover loss, densification, NDVI, Google Earth Engine, Santiago del Estero, Argentina

© 2022 Juan Pablo Celemin et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
vegetation cover loss, densification, NDVI, Google Earth Engine, Santiago del Estero, Argentina