Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1080/17538947.2017.1319975 |
Isolating type-specific phenologies through spectral unmixing of satellite time series | |
Nagol, Jyoteshwar R.1; Sexton, Joseph O.1; Anand, Anupam1; Sahajpal, Ritvik1; Edwards, Thomas C.2 | |
通讯作者 | Nagol, Jyoteshwar R. |
来源期刊 | INTERNATIONAL JOURNAL OF DIGITAL EARTH
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ISSN | 1753-8947 |
EISSN | 1753-8955 |
出版年 | 2018 |
卷号 | 11期号:3页码:233-245 |
英文摘要 | Vegetation phenology is commonly studied using time series of multi-spectral vegetation indices derived from satellite imagery. Differences in reflectance among land-cover and/or plant functional types are obscured by sub-pixel mixing, and so phenological analyses have typically sought to maximize the compositional purity of input satellite data by increasing spatial resolution. We present an alternative method to mitigate this ’mixed-pixel problem’ and extract the phenological behavior of individual land-cover types inferentially, by inverting the linear mixture model traditionally used for sub-pixel land-cover mapping. Parameterized using genetic algorithms, the method takes advantage of the discriminating capacity of calibrated surface reflectance measurements in red, near infrared, and short-wave infrared wavelengths, as well as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index. In simulation, the unmixing procedure reproduced the reflectances and phenological signals of grass, crop, and deciduous forests with high fidelity (RMSE < 0.007 NDVI); and in empirical tests, the algorithm extracted the phenological characteristics of evergreen trees and seasonal grasses in a semi-arid savannah. The approach shows potential for a wide range of ecological applications, including detection of differential responses to climate, soil, or other factors among vegetation types. |
英文关键词 | Spectral unmixing land-surface phenology NDVI genetic algorithms |
类型 | Article |
语种 | 英语 |
国家 | USA |
收录类别 | SCI-E |
WOS记录号 | WOS:000428620000001 |
WOS关键词 | REFLECTANCE FUSION MODEL ; SPRING PHENOLOGY ; VEGETATION PHENOLOGY ; MULTITEMPORAL MODIS ; SURFACE REFLECTANCE ; RESOLUTION DATA ; CLIMATE-CHANGE ; NORTH-AMERICA ; PLANT-GROWTH ; LAND-SURFACE |
WOS类目 | Geography, Physical ; Remote Sensing |
WOS研究方向 | Physical Geography ; Remote Sensing |
来源机构 | United States Geological Survey |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/210176 |
作者单位 | 1.Univ Maryland, Dept Geog Sci, Global Land Cover Facil, College Pk, MD 20742 USA; 2.Utah State Univ, Coll Nat Resources, Dept Wildland Resources, USGS Utah Cooperat Fish & Wildlife Res Unit, Logan, UT 84322 USA |
推荐引用方式 GB/T 7714 | Nagol, Jyoteshwar R.,Sexton, Joseph O.,Anand, Anupam,et al. Isolating type-specific phenologies through spectral unmixing of satellite time series[J]. United States Geological Survey,2018,11(3):233-245. |
APA | Nagol, Jyoteshwar R.,Sexton, Joseph O.,Anand, Anupam,Sahajpal, Ritvik,&Edwards, Thomas C..(2018).Isolating type-specific phenologies through spectral unmixing of satellite time series.INTERNATIONAL JOURNAL OF DIGITAL EARTH,11(3),233-245. |
MLA | Nagol, Jyoteshwar R.,et al."Isolating type-specific phenologies through spectral unmixing of satellite time series".INTERNATIONAL JOURNAL OF DIGITAL EARTH 11.3(2018):233-245. |
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