DOI: 10.3390/rs12030426
论文题名: Landsat analysis ready data for global land cover and land cover change mapping
作者: Potapov P. ; Hansen M.C. ; Kommareddy I. ; Kommareddy A. ; Turubanova S. ; Pickens A. ; Adusei B. ; Tyukavina A. ; Ying Q.
刊名: Remote Sensing
ISSN: 20724292
出版年: 2020
卷: 12, 期: 3 语种: 英语
英文关键词: Analysis ready data
; Global analysis
; Image compositing
; Land cover
; Land cover change
; Land surface phenology
; Landsat
; Multi-temporal metrics
; Surface reflectance
; Time-series analysis
Scopus关键词: Data handling
; Forestry
; Land use
; Mapping
; Reflection
; Analysis ready data
; Global analysis
; Image compositing
; Land cover
; Land surface phenology
; Land-cover change
; LANDSAT
; Multi-temporal
; Surface reflectance
; Time series analysis
英文摘要: The multi-decadal Landsat data record is a unique tool for global land cover and land use change analysis. However, the large volume of the Landsat image archive and inconsistent coverage of clear-sky observations hamper land cover monitoring at large geographic extent. Here, we present a consistently processed and temporally aggregated Landsat Analysis Ready Data produced by the Global Land Analysis and Discovery team at the University of Maryland (GLAD ARD) suitable for national to global empirical land cover mapping and change detection. The GLAD ARD represent a 16-day time-series of tiled Landsat normalized surface reflectance from 1997 to present, updated annually, and designed for land cover monitoring at global to local scales. A set of tools for multi-temporal data processing and characterization using machine learning provided with GLAD ARD serves as an end-to-end solution for Landsat-based natural resource assessment and monitoring. The GLAD ARD data and tools have been implemented at the national, regional, and global extent for water, forest, and crop mapping. The GLAD ARD data and tools are available at the GLAD website for free access. © 2020 by the authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159392
Appears in Collections: 气候变化与战略
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作者单位: Department of Geographical Sciences, University of Maryland, College Park, MD 20742, United States
Recommended Citation:
Potapov P.,Hansen M.C.,Kommareddy I.,et al. Landsat analysis ready data for global land cover and land cover change mapping[J]. Remote Sensing,2020-01-01,12(3)