A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications

被引:68
作者
Broich, Mark [1 ,2 ]
Huete, Alfredo [2 ]
Paget, Matt [3 ]
Ma, Xuanlong [2 ]
Tulbure, Mirela [1 ]
Coupe, Natalia Restrepo [2 ]
Evans, Bradley [4 ]
Beringer, Jason [5 ]
Devadas, Rakhesh [2 ]
Davies, Kevin [2 ]
Held, Alex [3 ]
机构
[1] Univ New S Wales, Sch Biol Earth & Environm Sci, Sydney, NSW 2052, Australia
[2] Univ Technol Sydney, Plant Funct Biol & Climate Change Cluster, AusCover TERN Sydney Node, Sydney, NSW 2007, Australia
[3] CSIRO, Marine & Atmospher Res, AusCover TERN, Pye Lab, Canberra, ACT 2600, Australia
[4] Macquarie Univ, Dept Biol Sci, N Ryde, NSW 2109, Australia
[5] Univ Western Australia, Sch Earth & Environm, Nedlands, WA 6009, Australia
关键词
Remote sensing; MODIS; AusCover TERN; Climate variability; Time-series; VEGETATION PHENOLOGY; HIGH-LATITUDES; CLIMATE-CHANGE; MODIS; FIRE; VARIABILITY; DYNAMICS; PATTERNS; COVER; MODEL;
D O I
10.1016/j.envsoft.2014.11.017
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Land surface phenology (LSP) characterizes episodes of greening and browning of the vegetated land surface from remote sensing imagery. LSP is of interest for quantification and monitoring of crop yield, wildfire fuel accumulation, vegetation condition, ecosystem response and resilience to climate variability and change. Deriving LSP represents an effort for end users and existing global products may not accommodate conditions in Australia, a country with a dry climate and high rainfall variability. To fill this information gap we developed the Australian LSP Product in contribution to AusCover/Terrestrial Ecosystem Research Network (TERN). We describe the product's algorithm and information content consisting of metrics that characterize LSP greening and browning episodes of the vegetated land surface. Our product allows tracking LSP metrics over time and thereby quantifying inter- and intraannual variability across Australia. We demonstrate the metrics' response to ENSO-driven climate variability. Lastly, we discuss known limitations of the current product and future development plans. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:191 / 204
页数:14
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