LandTrendr smoothed spectral profiles enhance woody encroachment monitoring
| dc.contributor.author | Gelabert Vadillo, Pere Joan | |
| dc.contributor.author | Rodrigues Mimbrero, Marcos | |
| dc.contributor.author | De la Riva, Juan | |
| dc.contributor.author | Améztegui González, Aitor | |
| dc.contributor.author | Sebastià, Ma. T. | |
| dc.contributor.author | Vega García, Cristina | |
| dc.date.accessioned | 2021-09-01T10:46:42Z | |
| dc.date.available | 2021-09-01T10:46:42Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Secondary succession (SS) is one of the main consequences of the abandonment of agricultural and forestry practices in rural areas, causing -among other processes- woody encroachment on former pastures and croplands. In this study we model and monitor the spatial evolution of SS over semi-natural grassland communities in the mountain range of the Pyrenees in Spain, during the last 36 years (1984-2019). Independent variables for ‘annual-based’ and ‘period-based’ modeling were drawn from a suite of Surface Reflectance Landsat images, LandTrendr (LT)-algorithm-adjusted images and LT outputs. Support vector machine (SVM) classifiers were trained and tested using all possible variable combinations of all the aforementioned datasets. The best modeling strategy involved yearly time series of LT-adjusted Tasseled Cap Brightness (TCB) and Wetness (TCW) axes as predictors, attaining a F1-score of 0.85, a Matthew Correlation Coefficient (MCC) of 0.67 and an AUC 0.83. Woodlands encroached above 480,000 ha of grasslands and crops during the study period. A model using LT outputs for the whole period also denoted good performance (F1-score = 0.85, MCC = 0.75) and estimated a similar area of woodland expansion (~509,000 ha), but this ‘period’ approach was unable to provide temporal information on the year or the encroachment dynamics. Our results suggest an overall proportion of 66% for the Pyrenees being affected by SS, with higher intensity in the west-central part, decreasing towards the eastern end. | ca_ES |
| dc.description.sponsorship | This work was supported by project IMAGINE [CGL2016-80400-R] funded by the Spanish Science Foundation (FECYT) and by the research grant program Ajuts UdL, Jade Plus i Fundació Bancària La Caixa [Agreement 79/2018 of the Governing Council of the University of Lleida]. | ca_ES |
| dc.identifier.doi | https://doi.org/10.1016/j.rse.2021.112521 | |
| dc.identifier.idgrec | 031562 | |
| dc.identifier.issn | 0034-4257 | |
| dc.identifier.uri | http://hdl.handle.net/10459.1/71779 | |
| dc.language.iso | eng | ca_ES |
| dc.publisher | Elsevier | ca_ES |
| dc.relation.isformatof | Reproducció del document publicat a https://doi.org/10.1016/j.rse.2021.112521 | ca_ES |
| dc.relation.ispartof | Remote Sensing of Environment, 2021, vol. 262, 112521 | ca_ES |
| dc.rights | cc-by-nc-nd (c) Gelabert et al., 2021 | ca_ES |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | Landsat | ca_ES |
| dc.subject | LandTrendr | ca_ES |
| dc.subject | Land abandonment | ca_ES |
| dc.subject | SVM | ca_ES |
| dc.title | LandTrendr smoothed spectral profiles enhance woody encroachment monitoring | ca_ES |
| dc.type | info:eu-repo/semantics/article | ca_ES |
| dc.type.version | info:eu-repo/semantics/publishedVersion | ca_ES |