globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2013.02.004
Scopus记录号: 2-s2.0-84880084883
论文题名:
Differentiation of plant age in grasses using remote sensing
作者: Knox N; M; , Skidmore A; K; , van der Werff H; M; A; , Groen T; A; , de Boer W; F; , Prins H; H; T; , Kohi E; , Peel M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 24, 期:1
起始页码: 54
结束页码: 62
语种: 英语
英文关键词: Grassland ; Hyperspectral ; Phenology ; Plant age ; Savanna ; Spectro-radiometry ; SWIR ; VNIR
Scopus关键词: accuracy assessment ; age structure ; ecosystem approach ; grass ; grassland ; growth response ; microtopography ; NDVI ; phenology ; plant ; radiometer ; savanna ; spatial variation ; spectral reflectance ; vegetation index
英文摘要: Phenological or plant age classification across a landscape allows for examination of micro-topographical effects on plant growth, improvement in the accuracy of species discrimination, and will improve our understanding of the spatial variation in plant growth. In this paper six vegetation indices used in phenological studies (including the newly proposed PhIX index) were analysed for their ability to statistically differentiate grasses of different ages in the sequence of their development. Spectra of grasses of different ages were collected from a greenhouse study. These were used to determine if NDVI, NDWI, CAI, EVI, EVI2 and the newly proposed PhIX index could sequentially discriminate grasses of different ages, and subsequently classify grasses into their respective age category. The PhIX index was defined as: (An VNIR+log(An SWIR2))/(An VNIR - log(An SWIR2)), where An VNIR and An SWIR2 are the respective normalised areas under the continuum removed reflectance curve within the VNIR (500-800 nm) and SWIR2 (2000-2210 nm) regions. The PhIX index was found to produce the highest phenological classification accuracy (Overall Accuracy: 79%, and Kappa Accuracy: 75%) and similar to the NDVI, EVI and EVI2 indices it statistically sequentially separates out the developmental age classes. Discrimination between seedling and dormant age classes and the adult and flowering classes was problematic for most of the tested indices. Combining information from the visible near infrared (VNIR) and shortwave infrared region (SWIR) region into a single phenological index captures the phenological changes associated with plant pigments and the ligno-cellulose absorption feature, providing a robust method to discriminate the age classes of grasses. This work provides a valuable contribution into mapping spatial variation and monitoring plant growth across savanna and grassland ecosystems. © 2013 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79808
Appears in Collections:气候变化事实与影响

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作者单位: Faculty for Geo-information Science and Earth Observation (ITC), University of Twente, PO Box 217, 7500 AE Enschede, Netherlands; Earth Observation Division, South African National Space Agency (SANSA), PO Box 484, Silverton, 0127, South Africa; University of KwaZulu-Natal, School of Agricultural, Earth and Environmental Sciences, Private Bag X01, Scottsville 3209, Pietermaritzburg, South Africa; Resource Ecology Group, Wageningen University, Droevendaalsesteeg 3a, 6708 PB Wageningen, Netherlands; Amarula Elephant Research Programme, Biological and Conservation Sciences, Westville Campus, University of KwaZulu-Natal, Private Bag X54001, Durban 4000, South Africa; Tanzania Wildlife Research Institute, PO BOX 661, Arusha, Tanzania; ARC-Animal Production Institute, PO Box 7063, Nelspruit, 1206, South Africa

Recommended Citation:
Knox N,M,, Skidmore A,et al. Differentiation of plant age in grasses using remote sensing[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,24(1)
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