Arid
DOI10.1371/journal.pone.0150808
Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region
Callister, Kate E.1; Griffioen, Peter A.2; Avitabile, Sarah C.1; Haslem, Angie1; Kelly, Luke T.3,4; Kenny, Sally A.1,2; Nimmo, Dale G.3,5; Farnsworth, Lisa M.1; Taylor, Rick S.1,6; Watson, Simon J.1; Bennett, Andrew F.1,2,3; Clarke, Michael F.1
通讯作者Callister, Kate E.
来源期刊PLOS ONE
ISSN1932-6203
出版年2016
卷号11期号:3
英文摘要

Understanding the age structure of vegetation is important for effective land management, especially in fire-prone landscapes where the effects of fire can persist for decades and centuries. In many parts of the world, such information is limited due to an inability to map disturbance histories before the availability of satellite images (similar to 1972). Here, we describe a method for creating a spatial model of the age structure of canopy species that established pre-1972. We built predictive neural network models based on remotely sensed data and ecological field survey data. These models determined the relationship between sites of known fire age and remotely sensed data. The predictive model was applied across a 104,000 km(2) study region in semi-arid Australia to create a spatial model of vegetation age structure, which is primarily the result of stand-replacing fires which occurred before 1972. An assessment of the predictive capacity of the model using independent validation data showed a significant correlation (r(s) = 0.64) between predicted and known age at test sites. Application of the model provides valuable insights into the distribution of vegetation age-classes and fire history in the study region. This is a relatively straightforward method which uses widely available data sources that can be applied in other regions to predict age-class distribution beyond the limits imposed by satellite imagery.


类型Article
语种英语
国家Australia
收录类别SCI-E
WOS记录号WOS:000373116500010
WOS关键词EASTERN IBERIAN PENINSULA ; NORTHWEST-TERRITORIES ; LANDSCAPE-PERSPECTIVE ; MALLEE ECOSYSTEMS ; NEURAL-NETWORKS ; TM IMAGERY ; AUSTRALIA ; FOREST ; AGE ; REGIMES
WOS类目Multidisciplinary Sciences
WOS研究方向Science & Technology - Other Topics
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/195609
作者单位1.La Trobe Univ, Dept Ecol Environm & Evolut, Bundoora, Vic, Australia;
2.Arthur Rylah Inst Environm Res, Dept Environm Land Water & Planning, Heidelberg, Vic, Australia;
3.Deakin Univ, Sch Life & Environm Sci, Burwood, Vic, Australia;
4.Univ Melbourne, Sch Biosci, ARC Ctr Excellence Environm Decis, Parkville, Vic 3052, Australia;
5.Charles Sturt Univ, Sch Environm Sci, Inst Land Water & Soc, Albury, NSW, Australia;
6.Anindilyakwa Land Council, Alyangula, NT, Australia
推荐引用方式
GB/T 7714
Callister, Kate E.,Griffioen, Peter A.,Avitabile, Sarah C.,et al. Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region[J],2016,11(3).
APA Callister, Kate E..,Griffioen, Peter A..,Avitabile, Sarah C..,Haslem, Angie.,Kelly, Luke T..,...&Clarke, Michael F..(2016).Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region.PLOS ONE,11(3).
MLA Callister, Kate E.,et al."Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region".PLOS ONE 11.3(2016).
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