Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Calbi, Mariasole; Clerici, Nicola (2021): Aerial images dataset for Reconstructing Long Term High Andean Forest Dynamics Using Historical Aerial Imagery: A Case Study in Colombia [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.932909

Always quote citation above when using data! You can download the citation in several formats below.

Published: 2021-06-22 • DOI registered: 2021-08-05

RIS CitationBibTeX Citation ShareShow MapGoogle Earth

Abstract:
To unveil the long-term dynamics of peri-urban high Andean forest cover, and provide valuable information on historical vegetation changes in a highly dynamic landscape, we gathered and analyzed aerial imagery spanning the years 1940 to 2007 from nine administrative localities in the Eastern Andean Cordillera of Colombia. The aerial images were obtained from the Colombian Geographical Institute Agustín Codazzi (IGAC) where they were scanned in high resolution. Subsequently the images were georeferenced in two consecutive steps using QGIS 2.18, using the thin plate spline as a transformation method for data interpolation, since it led to the highest precision among all the methods tested (first and second order polynomials).
Keyword(s):
aerial imagery; altiplano cundiboyacense; Colombia
Related to:
Calbi, Mariasole; Clerici, Nicola; Thomas, Borsch; Brokamp, Grischa (2020): Reconstructing Long Term High Andean Forest Dynamics Using Historical Aerial Imagery: A Case Study in Colombia. Forests, 11(8), 788, https://doi.org/10.3390/f11080788
Coverage:
Latitude: -20.000000 * Longitude: -65.000000
Event(s):
Central_Andes * Latitude: -20.000000 * Longitude: -65.000000 * Location: Andes
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1Binary ObjectBinaryCalbi, Mariasole
2Binary Object (Media Type)Binary (Type)Calbi, Mariasole
3Binary Object (File Size)Binary (Size)BytesCalbi, Mariasole
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
41 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML