Arid
DOI10.3390/rs8070540
Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?
Schumacher, Paul1; Mislimshoeva, Bunafsha1; Brenning, Alexander2; Zandler, Harald3; Brandt, Martin4; Samimi, Cyrus3,5; Koellner, Thomas1,5
通讯作者Schumacher, Paul
来源期刊REMOTE SENSING
ISSN2072-4292
出版年2016
卷号8期号:7
英文摘要

Remote sensing-based woody biomass quantification in sparsely-vegetated areas is often limited when using only common broadband vegetation indices as input data for correlation with ground-based measured biomass information. Red edge indices and texture attributes are often suggested as a means to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data. Model performance was evaluated based on cross-validation bias, standard deviation and Root Mean Square Error (RMSE) at the logarithmic and non-logarithmic scales. Both models achieved rather limited performances in wood volume prediction. Nonetheless, model performance increased with red edge indices and texture attributes, which shows that they play an important role in semi-arid regions with sparse vegetation.


英文关键词woody biomass wood volume estimation semi-arid RapidEye red edge texture
类型Article
语种英语
国家Germany ; Denmark
收录类别SCI-E
WOS记录号WOS:000382224800010
WOS关键词LEAF-AREA INDEX ; LAND-COVER CHANGES ; ABOVEGROUND BIOMASS ; HERBACEOUS BIOMASS ; VEGETATION INDEXES ; REMOTE ESTIMATION ; TROPICAL FOREST ; INNER-MONGOLIA ; NATIONAL-PARK ; TIME-SERIES
WOS类目Remote Sensing
WOS研究方向Remote Sensing
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/195963
作者单位1.Univ Bayreuth, Fac Biol Chem & Geosci, Ecol Serv, D-95440 Bayreuth, Germany;
2.Univ Jena, Dept Geog, D-07743 Jena, Germany;
3.Univ Bayreuth, Inst Geog, D-95440 Bayreuth, Germany;
4.Univ Copenhagen, Dept Geosci & Nat Resource Management, DK-1350 Copenhagen, Denmark;
5.Univ Bayreuth, BayCEER, D-95440 Bayreuth, Germany
推荐引用方式
GB/T 7714
Schumacher, Paul,Mislimshoeva, Bunafsha,Brenning, Alexander,et al. Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?[J],2016,8(7).
APA Schumacher, Paul.,Mislimshoeva, Bunafsha.,Brenning, Alexander.,Zandler, Harald.,Brandt, Martin.,...&Koellner, Thomas.(2016).Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?.REMOTE SENSING,8(7).
MLA Schumacher, Paul,et al."Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?".REMOTE SENSING 8.7(2016).
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