Fecha/hora: 03/06/2024 14:32:42

Biblioteca(s): | INIA Las Brujas.
Tipo de la producción científica: | Artículos en Revistas Indexadas Internacionales
Circulación/Nivel: | Internacional - --
Fecha corriente: | 27/09/2022
Fecha de la última actualización: | 27/09/2022
Autoria: | BAEZA, S.; VÉLEZ-MARTIN, E.; DE ABELLEYRA, D.; BANCHERO, S.; GALLEGO, F.; SCHIRMBECK, J.; VERON, S.; VALLEJOS, M.; WEBER, E.; OYARZABAL, M.; BARBIERI, A.; PETEK, M.; GUERRA LARA, M.; SARRAILHÉ, S.S.; BALDI, G.; BAGNATO, C.; BRUZZONE, L.; RAMOS, S.; HASENACK, H.
Afiliación: | SANTIAGO BAEZA, Departamento de Sistemas Ambientales, Facultad de Agronomía, UdelaR, Montevideo, Montevideo, 12900, Uruguay; E. VÉLEZ-MARTIN, GeoKarten Consultoria em Tecnologia da Informação Ltda. Roca Sales, Rio Grande do Sul, 95735-000, Brazil; D. DE ABELLEYRA, Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA) Hurlingham, Buenos Aires, 1686, Argentina; S. BANCHERO, Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA) Hurlingham, Buenos Aires, 1686, Argentina; F. GALLEGO, Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, UdelaR, Montevideo, Montevideo, 11400, Uruguay; J. SCHIRMBECK, GeoKarten Consultoria em Tecnologia da Informação Ltda. Roca Sales, Rio Grande do Sul, 95735-000, Brazil; S. VERON, Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA) Hurlingham, Bs. As., Argentina;Departamento de Métodos Cuantitativos y Sistemas de Información, LART, IFEVA, Facultad de Agronomía, UBA/CONICET, Bs. As., Argentina; MARÍA VALLEJOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; E. WEBER, Departamento Interdisciplinar e Programa de Pós-Graduação em Sensoriamento Remoto, Universidade Federal do Rio Grande do Sul, Campus Litoral Norte. Tramandaí, Rio Grande do Sul, 95590-000, Brazil; M. OYARZABAL, Departamento de Métodos Cuantitativos y Sistemas de Información, LART, IFEVA, Facultad de Agronomía, UBA/CONICET, Buenos Aires, Buenos Aires, 1417, Argentina; A. BARBIERI, Departamento de Geografía, Facultad de Ciencias, UdelaR, Montevideo, Montevideo, 11400, Uruguay; M. PETEK, Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA) Hurlingham, Buenos Aires, 1686, Argentina; M. GUERRA LARA, Instituto de Matemática Aplicada San Luis, Universidad Nacional de San Luis y CONICET, San Luis, San Luis, 5700, Argentina; S. S. SARRAILHÉ, Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA) Hurlingham, Buenos Aires, 1686, Argentina; G. BALDI, Instituto de Matemática Aplicada San Luis, Universidad Nacional de San Luis and CONICET, San Luis, San Luis, 5700, Argentina; C. BAGNATO, IRNAD, UNRN, CONICET, Río Negro, San Carlos de Bariloche, 8400, Argentina; L. BRUZZONE, Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, UdelaR, Montevideo, Montevideo, 11400, Uruguay; S. RAMOS, Departamento de Geografía, Facultad de Ciencias, UdelaR, Montevideo, Montevideo, 11400, Uruguay; H. HASENACK, Departamento de Ecologia, IB e Programa de Pós-Graduação em Agronegócios, CEPAN, Universidade Federal do Rio Grande do Sul. Porto Alegre, Rio Grande do Sul, 91501-970, Brazil.
Título: | Two decades of land cover mapping in the Río de la Plata grassland region: The MapBiomas Pampa initiative.
Año de publicación: | 2022
Fuente/Imprenta: | Remote Sensing Applications: Society and Environment, 2022, Volume 28, Article 100834. doi: https://doi.org/10.1016/j.rsase.2022.100834
ISSN: | 2352-9385
DOI: | 10.1016/j.rsase.2022.100834
Idioma: | Inglés

Notas:

Article history: Received 26 April 2022; Received in revised form 29 August 2022; Accepted 3 September 2022; Available online 8 September 2022.
Corresponding author: Baeza, S.; Departamento de Sistemas Ambientales, Facultad de Agronomía, UdelaR, Montevideo, Montevideo, Uruguay; email:sbaeza@fagro.edu.uy  -- This work has been also partially funded by ANII INNOVAGRO projects FSA_PI_2018_1_149022 and FSA_PI_2018_1_148811; CSIC I+D 2020_358, FMV_3_2020_1_162279, and FMV_1_2021_1_167032.

Contenido: | ABSTRACT.- The Río de la Plata Grasslands (RPG) region is the largest area of the temperate humid and sub-humid grasslands biome in South America and one of the largest in the world. The region is located on fertile soils, generally very suitable for agricultural development, so it is undergoing an intense land cover change process. Our knowledge of these changes remains incomplete. Most regional-scale studies have been conducted over specific periods, limited subsets of the RGP, coarse resolution and, in general, used land cover classes that are not readily compatible. In this work we described and analyzed the land cover changes in the entire RPG region for the first two decades of the 21st century, especially those related to grasslands loss. We generated annual land cover maps with 30-m resolution that discriminate between 8 categories: native woody formation, forest plantation, swampy areas and flooded grassland, grassland, farming, non-vegetated area, water and non-observed. The map series was evaluated for the years 2001 and 2018 using a completely independent dataset, selected by stratified randomized sampling. Overall accuracy was 73.5% and 77.8% for 2001 and 2018, respectively, with user and producer accuracies that varied between classes and years. In 20 years, RPG region lost, at least, 2.4 million ha of grassland (9% of the remaining grassland area in 2001). Most of these losses are concentrated in Brazil and Uruguay and are associated with new agricultural or forestry areas that increased by 5% and 100%, respectively. Our maps allow a comprehensive understanding of the transformation processes that RPG are undergoing and provide the context on which to explore a large set of hypotheses related to ecosystem structure and functioning. It will also contribute to improving decision-making at both the regional and national levels. © 2022 Elsevier B.V.
Palabras-Clave: | Classification; Grasslands; Land use change; Landsat; Time series.
Categoría del tema: | F01 Cultivo
Registro original: | INIA Las Brujas (LB)
Ejemplares: | LB - (103179-1) - PXI - AP - DD - Remote Sensing Applications/2022 -  -  - DIS