Top Description Format Spatial information Temporal information Provenance & quality Licensing & constraints Related records Correspondence Authors Additional metadata Funding Download/Access

Powell, P.A.; Gutierrez-Angonese, J.; Burslem, D.F.R.P.; Travis, J.M.J.; Jiménez, Y.G.; Montti, L.

Land cover maps of Sierra de San Javier, Tucumán, Argentina, 1986-2018

This dataset is under embargo and will be made available by 10 November 2025 at the latest Find out more »

Cite this dataset

This dataset is under embargo and will be made available by 10 November 2025 at the latest Find out more »

https://doi.org/10.5285/4d30e697-6a97-45ed-95e6-ac4d66247284

The data resource consists of a series of land cover maps built using raster and shapefiles to evaluate the expansion of the invasive Ligustrum lucidum forest cover in Sierra de San Javier (Yungas forest ecoregion). The classification was conducted to investigate the expansion of the invasion of non-native species Ligustrum at the landscape scale and to model future management strategies using RangeShifter software.
The data includes 4 maps with 8 classes of land used: Ligustrum forest; Subtropical montane forest; Dry forest; Montane grasslands; Anthropogenic grasslands and shrubland used for livestock and temporary agriculture, a mixed class including also herbaceous agriculture and low-density urban areas; Sugar cane; Citrus plantations, mostly lemon; high/medium-density urban and build up areas.
The work was carried out as part of NERC grant NE/S011641/1 Optimising the long-term management of invasive species affecting biodiversity and the rural economy using adaptive management

Publication date: 2024-06-12

883 views *

More information

View numbers valid from 12 June 2024 (information prior to this was not collected)

Formats

TIFF, Shapefile

Spatial information

Study area

Spatial representation types

Raster
Vector

Spatial reference system

WGS 84 / Pseudo-Mercator

Temporal information

Temporal extent

1986-01-01 to 2018-12-31

Provenance & quality

Land cover maps (LCM) were constructed by applying the machine learning algorithm Random Forest (RF), based on an ensemble of classification trees, fully run on the Google Earth Engine platform. For the classification of tree model runs, 315 points from Thematic Mapper (TM) were chosen by visual interpretation of satellite data. Training areas previously obtained and tested were used to build LCM series of the same study area. All data collected in training areas is recorded onto GPS in the field. For the Ligustrum class, 52 training points were collected during fieldwork in 2010 and spectrally verified using vegetation indices. A total of 367 points for the 8 categories were used and then were transferred into spreadsheets and exported as comma-separated value (CSV) files for deposit into the EIDC. To classify 1986 LCM a subset of training points of L. lucidum was used, including only 28 areas that were identified as source points of dispersion.
The land cover maps obtained were downloaded in raster (tif) format. All training points were presented as shape files.

Licensing and constraints

This dataset is under embargo and will be made available by 10 November 2025 at the latest Find out more »

This dataset will be available under the terms of the Open Government Licence

Cite this dataset as:

Powell, P.A.; Gutierrez-Angonese, J.; Burslem, D.F.R.P.; Travis, J.M.J.; Jiménez, Y.G.; Montti, L. (2024). Land cover maps of Sierra de San Javier, Tucumán, Argentina, 1986-2018. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/4d30e697-6a97-45ed-95e6-ac4d66247284

BibTeX RIS