Arid
DOI10.1080/17538947.2017.1319975
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
ISSN1753-8947
EISSN1753-8955
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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