DOI: 10.1016/j.jag.2016.06.019
Scopus记录号: 2-s2.0-84997682850
论文题名: Mapping Brazilian savanna vegetation gradients with Landsat time series
作者: Schwieder M ; , Leitão P ; J ; , da Cunha Bustamante M ; M ; , Ferreira L ; G ; , Rabe A ; , Hostert P
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 52 起始页码: 361
结束页码: 370
语种: 英语
英文关键词: Cerrado
; Land surface phenology
; Landsat time series
; Physiognomy mapping
Scopus关键词: cerrado
; Landsat
; mapping
; phenology
; remote sensing
; savanna
; Sentinel
; time series analysis
; Brazil
英文摘要: Global change has tremendous impacts on savanna systems around the world. Processes related to climate change or agricultural expansion threaten the ecosystem's state, function and the services it provides. A prominent example is the Brazilian Cerrado that has an extent of around 2 million km2 and features high biodiversity with many endemic species. It is characterized by landscape patterns from open grasslands to dense forests, defining a heterogeneous gradient in vegetation structure throughout the biome. While it is undisputed that the Cerrado provides a multitude of valuable ecosystem services, it is exposed to changes, e.g. through large scale land conversions or climatic changes. Monitoring of the Cerrado is thus urgently needed to assess the state of the system as well as to analyze and further understand ecosystem responses and adaptations to ongoing changes. Therefore we explored the potential of dense Landsat time series to derive phenological information for mapping vegetation gradients in the Cerrado. Frequent data gaps, e.g. due to cloud contamination, impose a serious challenge for such time series analyses. We synthetically filled data gaps based on Radial Basis Function convolution filters to derive continuous pixel-wise temporal profiles capable of representing Land Surface Phenology (LSP). Derived phenological parameters revealed differences in the seasonal cycle between the main Cerrado physiognomies and could thus be used to calibrate a Support Vector Classification model to map their spatial distribution. Our results show that it is possible to map the main spatial patterns of the observed physiognomies based on their phenological differences, whereat inaccuracies occurred especially between similar classes and data-scarce areas. The outcome emphasizes the need for remote sensing based time series analyses at fine scales. Mapping heterogeneous ecosystems such as savannas requires spatial detail, as well as the ability to derive important phenological parameters for monitoring habitats or ecosystem responses to climate change. The open Landsat and Sentinel-2 archives provide the satellite data needed for improved analyses of savanna ecosystems globally. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80048
Appears in Collections: 气候变化事实与影响
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作者单位: Humboldt-Universität zu Berlin, Geography Department, Unter den Linden 6, Berlin, Germany; Universidade de Brasília—UNB, Campus Universitário Darcy Ribeiro, Asa Norte, Brasília, DF, Brazil; Universidade Federal de Goiás—UFG, Campus II, LAPIG, Goiânia, GO, Brazil; Humboldt-Universität zu Berlin, Integrated Research Institute on Transformations of Human-Environment Systems (IRI THESys), Unter den Linden 6, Berlin, Germany
Recommended Citation:
Schwieder M,, Leitão P,J,et al. Mapping Brazilian savanna vegetation gradients with Landsat time series[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,52