全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

青藏高原典型植被生长季遥感模型提取分析

DOI: 10.3724/SP.J.1047.2014.00815, PP. 815-823

Keywords: 青藏高原,生长季,对比分析,时空变化,遥感提取模型,物候学

Full-Text   Cite this paper   Add to My Lib

Abstract:

物候变化是衡量全球气候变化最直接、敏感的指示器,针对青藏高原这个独特地域单元上特殊的高寒植被进行关键物候期遥感提取模型及植被物候时空变化的研究具有重要的意义。本文首先以反距离加权空间插值算法与Savitzky-Golay滤波算法相结合的数据重建模型获得高质量2003-2012年青藏高原MODIS归一化植被指数(NDVI)数据。在此数据基础上,分别利用动态阈值法、最大变化斜率法、logistic曲线拟合法3种遥感植被生长季提取模型,对青藏高原地区两种典型植被的生长季(SOS生长季开始期,EOS生长季结束期,LOS生长季长度)进行提取。通过对3种模型提取结果的对比分析,并结合日均温模型对提取结果的验证发现,动态阈值法为青藏高原地区典型植被生长季的最优遥感提取模型。该模型对近10a的高分辨率典型高寒植被物候参量的反演及时空变化特征分析表明,受青藏高原水热及海拔梯度的影响,青藏高原植被物候变化呈现出从东南向西北的空间分异规律,随春季温度的升高,近10a来青藏高原高寒草地总体呈现生长季开始期(SOS)提前(0.248d/a)的趋势。

References

[1]  Tucker C J, Slayback D A, Pinzon J E, et al. Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999[J]. International Journal of Biometeorology, 2001,45(4):184-190.
[2]  Yu F, Price K P, Ellis J, et al. Response of seasonal vegetation development to climatic variations in eastern central Asia[J]. Remote sensing of environment, 2003,87(1):42-54.
[3]  Chen X, Tan Z, Schwartz M D, et al. Determining the growing season of land vegetation on the basis of plant phenology and satellite data in Northern China[J]. International Journal of Biometeorology, 2000,44(2):97-101.
[4]  Wen G. Seasonal phenological characteristics in East China monitor with AVHRR normalized difference vegetation index[J]. Journal of Remote Sensing,1998,2(4):270-275.
[5]  White M A, Beur S D, Kirsten M, et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006[J]. Global Change Biology, 2009,15(10):2335-2359.
[6]  Song C Q,You S C, Ke L H, et al. Spatio-temporal variation of vegetation phenology in the Northern Tibetan Plateau as detected by MODIS remote sensing[J]. Chinese Journal of Plant Ecology, 2011,35(8):853-863.
[7]  Ding M, Zhang Y, Sun X, et al. Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009[J]. Chinese Science Bulletin, 2013,58(3):396-405.
[8]  Jin Z, Zhuang Q, He J-S, et al. Phenology shift from 1989 to 2008 on the Tibetan Plateau: An analysis with a process-based soil physical model and remote sensing data[J]. Climatic Change, 2013,119(2):435-449.
[9]  Viovy N, Arino O, Belward A. The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series[J]. International Journal of Remote Sensing, 1992,13(8):1585-1590.
[10]  Lovell J, Graetz R. Filtering pathfinder AVHRR land NDVI data for Australia[J]. International Journal of Remote Sensing, 2001,22(13):2649-2654.
[11]  Park J, Tateishi R, Matsuoka M. A proposal of the Temporal Window Operation (TWO) method to remove high-frequency noises in AVHRR NDVI time series data[J]. Journal of the Japan Society of Photogrammetry and Remote Sensing, 1999,38(5):36-47.
[12]  Savitzky A, Golay M J. Smoothing and differentiation of data by simplified least squares procedures[J]. Analytical chemistry, 1964,36(8):1627-1639.
[13]  Cihlar J. Identification of contaminated pixels in AVHRR composite images for studies of land biosphere[J]. Remote sensing of environment, 1996,56(3):149-163.
[14]  Roerink G, Menenti M, Verhoef W. Reconstructing cloudfree NDVI composites using Fourier analysis of time series[J]. International Journal of Remote Sensing, 2000,21(9):1911-1917.
[15]  Wang D, Jiang X G, Tang L L, et al. The application of time-series fourier analysis to reconstructing cloud-free NDVI images[J]. Remote Sensing For Land & Resources, 2005,64(2):29-32.
[16]  Chen J, J?nsson P, Tamura M, et al. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter[J]. Remote sensing of environment, 2004,91(3):332-344.
[17]  Bian J, Li A, Song M, et al. Reconstruction of NDVI time-series datasets of MODIS based on Savitzky-Golay filter[J]. Journal of Remote Sensing, 2010,14(4):22-27.
[18]  Montandon L, Small E. The impact of soil reflectance on the quantification of the green vegetation fraction from NDVI[J]. Remote sensing of environment, 2008,112(4):1835-1845.
[19]  顾娟,李新,黄春林.基于时序 MODIS NDVI 的黑河流域土地覆盖分类研究[J].地球科学进展, 2010,25(3):317-326.
[20]  J?nsson P, Eklundh L. TIMESAT-a program for analyzing time-series of satellite sensor data[J]. Computers & Geosciences, 2004,30(8):833-845.
[21]  Zhang X, Friedl M A, Schaaf C B, et al. Monitoring vegetation phenology using MODIS[J]. Remote sensing of environment, 2003,84(3):471-475.
[22]  李英年,赵新全,曹广民,等.海北高寒草甸生态系统定位站气候、植被生产力背景的分析[J].高原气象,2004,23(4):558-567.
[23]  Shen M. Spring phenology was not consistently related to winter warming on the Tibetan Plateau[J]. Proceedings of the National Academy of Sciences, 2011,108(19):E91-E92.
[24]  Liu L, Liu L, Hu Y. Response of spring phenology to climate change across Tibetan Plateau[C]. Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on. IEEE, 2012: 1-4.
[25]  You S C, Song C Q, Ke L H, et al. Spatial distribution characteristics of vegetation phenology in northern Tibetan Plateau based on MODIS enhanced vegetation index[J]. Chinese Journal of Ecology, 2011,30(7):1513-1520.
[26]  Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems[J]. Nature, 2003,421(6918):37-42.
[27]  Moulin S, Kergoat L, Viovy N, et al. Global-scale assessment of vegetation phenology using NOAA/AVHRR satellite measurements[J]. Journal of Climate, 1997,10(6):1154-1170.
[28]  Mo Shenguo,Zhang Baiping,Cheng Weiming, et al. Major environment effects of the Tibetan Plateau[J]. Progress in Geograph, 2004, 23(2):88-96.
[29]  Lloyd D. A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery[J]. TitleREMOTE SENSING, 1990,11(12):2269-2279.
[30]  Zhou L, Tucker C J, Kaufmann R K, et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999[J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2001,106(D17):20069-20083.
[31]  Reed B C, Brown J F, VanderZee D, et al. Measuring phenological variability from satellite imagery[J]. Journal of Vegetation Science, 1994,5(5):703-714.
[32]  Schwartz M D, Reed B C, White M A. Assessing satellite-derived start-of-season measures in the conterminous USA[J]. International Journal of Climatology, 2002,22(14):1793-1805.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133