Vegetation Phenology Extraction and Analysis in Urban Area using Landsat Vegetation Fraction Time Series

被引:0
|
作者
Cai, Cai [1 ]
Li, Peijun [2 ]
Shi, Zhongkui [2 ]
机构
[1] Beijing Inst Surveying & Mapping, Beijing Municipal Key Lab Urban Spatial Informat, Beijing, Peoples R China
[2] Peking Univ, Sch Earth & Space Sci, Inst Remote Sensing & GIS, Beijing, Peoples R China
关键词
vegetation phenology; urban area; Landsat time series; vegetation fraction; global generic endmembers;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Considering diverse vegetation types and complex land cover changes in urban and surrounding areas, a new method was developed for phenology extraction in urban and surrounding areas using Landsat time series and global generic endmembers from standardized spectral mixing analysis. NDVI and EVI time series from Landsat images were also generated for comparison. Landsat time series images over Beijing area of three different years, i.e., 1990, 2000 and 2014, and total 83 scenes were used in this study. The results of phenology extraction from vegetation fraction showed slightly better than those from EVI, and much better than those from NDVI. It also showed that the characteristics of vegetation phenology in urban and surrounding areas have obvious differences in spatial distribution and among different vegetation types. The method provides an effective tool for phenology extraction and analysis in urban areas.
引用
收藏
页码:415 / 418
页数:4
相关论文
共 50 条
  • [1] Urban vegetation phenology analysis using high spatio-temporal NDVI time series
    Feng Li
    Guo Song
    Zhu Liujun
    Zhou Yanan
    Lu Di
    [J]. URBAN FORESTRY & URBAN GREENING, 2017, 25 : 43 - 57
  • [2] Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data
    Lu, Yuhao
    Coops, Nicholas C.
    Hermosilla, Txomin
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2017, 126 : 11 - 23
  • [3] A VEGETATION PHENOLOGY MODEL FOR FRACTIONAL VEGETATION COVER RETRIEVAL USING TIME SERIES DATA
    Liu, Yaokai
    Mu, Xihan
    Qian, Yonggang
    Tang, Lingli
    Li, Chuanrong
    [J]. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 3339 - 3342
  • [4] Wheat phenology extraction from time-series of SPOT/VEGETATION data
    Lu, Linlin
    Guo, Huadong
    [J]. CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 4, PROCEEDINGS, 2008, : 794 - 797
  • [5] Preparing Landsat Image Time Series (LITS) for Monitoring Changes in Vegetation Phenology in Queensland, Australia
    Bhandari, Santosh
    Phinn, Stuart
    Gill, Tony
    [J]. REMOTE SENSING, 2012, 4 (06) : 1856 - 1886
  • [6] ANALYSIS OF VEGETATION GROWTH TRENDS IN URBAN AREAS USING DENSE LANDSAT TIME SERIES: A CASE STUDY OF TIANJIN, CHINA
    Chai, Baohui
    Li, Peijun
    [J]. 2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 5921 - 5924
  • [7] PHENOLOGY PARAMETER EXTRACTION FROM TIME-SERIES OF SATELLITE VEGETATION INDEX DATA USING PHENOSAT
    Rodrigues, Arlete
    Marcal, Andre R. S.
    Cunha, Mario
    [J]. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 4926 - 4929
  • [8] Urban Vegetation Classification Based on Phenology using HJ-1A/B time series imagery
    Feng Li
    Zhu Liujun
    Liu Han
    Huang Yinyou
    Du Peijun
    Adaku, Ebenezer
    [J]. 2015 JOINT URBAN REMOTE SENSING EVENT (JURSE), 2015,
  • [9] A Bayesian hierarchical model for estimating spatial and temporal variation in vegetation phenology from Landsat time series
    Senf, Cornelius
    Pflugmacher, Dirk
    Heurich, Marco
    Krueger, Tobias
    [J]. REMOTE SENSING OF ENVIRONMENT, 2017, 194 : 155 - 160
  • [10] Evaluation of Urban Vegetation Phenology Using 250 m MODIS Vegetation Indices
    Zhang, Hongxin
    Wang, Xiaoyue
    Peng, Dailiang
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2022, 88 (07): : 461 - 467