LandTrendr smoothed spectral profiles enhance woody encroachment monitoring

Gelabert P.J. ; Rodrigues M. (Universidad de Zaragoza) ; de la Riva J. (Universidad de Zaragoza) ; Ameztegui A. ; Sebastià M.T. ; Vega-Garcia C.

Resumen: 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. © 2021 The Authors

Idioma: Inglés

DOI: 10.1016/j.rse.2021.112521

Año: 2021

Publicado en: Remote Sensing of Environment 262 (2021), 112521 [10 pp]
ISSN: 0034-4257

Factor impacto JCR: 13.85 (2021)

Categ. JCR: IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY rank: 2 / 28 = 0.071 (2021) - Q1 - T1
Categ. JCR: REMOTE SENSING rank: 2 / 34 = 0.059 (2021) - Q1 - T1
Categ. JCR: ENVIRONMENTAL SCIENCES rank: 10 / 279 = 0.036 (2021) - Q1 - T1

Factor impacto CITESCORE: 20.7 - Earth and Planetary Sciences (Q1) - Agricultural and Biological Sciences (Q1)

Factor impacto SCIMAGO: 3.862 - Geology (Q1) - Computers in Earth Sciences (Q1)

Financiación: info:eu-repo/grantAgreement/ES/FECYT/IMAGINE CGL2016-80400-R

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)