The mixed pixel effect in land surface phenology: A simulation study

被引:123
作者
Chen, Xiang [1 ,2 ]
Wang, Dawei [1 ]
Chen, Jin [1 ]
Wang, Cong [1 ]
Shen, Miaogen [3 ]
机构
[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
[2] Arkansas Tech Univ, Dept Emergency Management, Russellville, AR 72801 USA
[3] CAS Ctr Excellence Tibetan Plateau Earth Sci, Inst Tibetan Plateau Res, Key Lab Alpine Ecol & Biodivers, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
Green-up date (GUD); Land surface phenology; Mixed pixel effect; Spring phenology; Uncertainty; SPRING PHENOLOGY; CLIMATE-CHANGE; TIME-SERIES; VEGETATION; RESPONSES; DYNAMICS; ONSET; NDVI;
D O I
10.1016/j.rse.2018.04.030
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Because of the limited spatiotemporal resolutions in vegetation index (VI) products, land surface phenology (LSP) results may not well capture ground-based phonological changes. This is likely the result of the mixed pixel effect: (1) a pixel in VI products may contain an unknown composition of vegetation species or land cover types; and (2) these species differ in their sensitivity to climatic variations. The mixed pixel effect has induced inconsistent findings in LSP with in situ observations of spring phenology. To this end, this study has designed a series of simulation experiments to initiate the methodological exploration of how the green-up date (GUD) of a mixed pixel could be altered by the endmember GUDs and different non-GUD variables, including the end member composition, minimum and maximum normalized difference vegetation index (NDVI), and the length of the growth period. The study has also compared the sensitivity of two generally adopted GUD identification methods, the relative threshold method and the curvature method (also known as the inflection-point method). The simulations with two endmembers show that even if there is no change in the endmember GUDs, the GUD of the mixed pixel could be substantially altered by the changes in non-GUD variables. In addition, the study has also developed a simulation toolkit for the GUD identification with cases of three or more endmembers. The results of the study provide insights into effective strategies for analyzing spring phonology using VI products: the mixed pixel effect can be alleviated by selecting pixels that are relatively stable in the land cover or species composition. This simulation study calls for in situ phonological observations to validate the LSP, such as conducting climate-controlled experiments on few mixed species at a small spatial scale. The paper also argues for the necessity of isolating GUD trends caused by non-phenological changes in the study of spring phenology.
引用
收藏
页码:338 / 344
页数:7
相关论文
共 34 条
[1]  
ADAMS JB, 1986, J GEOPHYS RES-SOLID, V91, P8098, DOI 10.1029/JB091iB08p08098
[2]   Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS [J].
Ahl, Douglas E. ;
Gower, Stith T. ;
Burrows, Sean N. ;
Shabanov, Nikolay V. ;
Myneni, Ranga B. ;
Knyazikhin, Yuri .
REMOTE SENSING OF ENVIRONMENT, 2006, 104 (01) :88-95
[3]   UPSCALE INTEGRATION OF NORMALIZED DIFFERENCE VEGETATION INDEX - THE PROBLEM OF SPATIAL HETEROGENEITY [J].
AMAN, A ;
RANDRIAMANANTENA, HP ;
PODAIRE, A ;
FROUIN, R .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1992, 30 (02) :326-338
[4]   Responses of spring phenology to climate change [J].
Badeck, FW ;
Bondeau, A ;
Böttcher, K ;
Doktor, D ;
Lucht, W ;
Schaber, J ;
Sitch, S .
NEW PHYTOLOGIST, 2004, 162 (02) :295-309
[5]   Global phenological response to climate change in crop areas using satellite remote sensing of vegetation, humidity and temperature over 26 years [J].
Brown, M. E. ;
de Beurs, K. M. ;
Marshall, M. .
REMOTE SENSING OF ENVIRONMENT, 2012, 126 :174-183
[6]   Monitoring phenological key stages and cycle duration of temperate deciduous forest ecosystems with NOAA/AVHRR data [J].
Duchemin, B ;
Goubier, J ;
Courrier, G .
REMOTE SENSING OF ENVIRONMENT, 1999, 67 (01) :68-82
[7]   Optical-biophysical relationships of vegetation spectra without background contamination [J].
Gao, X ;
Huete, AR ;
Ni, WG ;
Miura, T .
REMOTE SENSING OF ENVIRONMENT, 2000, 74 (03) :609-620
[8]   Land surface phenology: What do we really 'see' from space? [J].
Helman, David .
SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 618 :665-673
[9]   Overview of the radiometric and biophysical performance of the MODIS vegetation indices [J].
Huete, A ;
Didan, K ;
Miura, T ;
Rodriguez, EP ;
Gao, X ;
Ferreira, LG .
REMOTE SENSING OF ENVIRONMENT, 2002, 83 (1-2) :195-213
[10]   TIMESAT -: a program for analyzing time-series of satellite sensor data [J].
Jönsson, P ;
Eklundh, L .
COMPUTERS & GEOSCIENCES, 2004, 30 (08) :833-845