Leaf area index mapping in northern Canada

被引:19
作者
Abuelgasim, Abdelgadir A. [1 ]
Leblanc, Sylvain G. [2 ]
机构
[1] Canada Ctr Remote Sensing, Earth Observat & Geosolut Div, Ottawa, ON K1A 0Y7, Canada
[2] Canadian Space Agcy, Ctr Spatial John H Chapman, Canada Ctr Remote Sensing, St Hubert, PQ J3Y 8Y9, Canada
关键词
CYCLOPES GLOBAL PRODUCTS; VEGETATION; LAI; NORMALIZATION; VALIDATION; PARAMETERS; DYNAMICS; EXCHANGE; FAPAR; TM;
D O I
10.1080/01431161.2010.494636
中图分类号
TP7 [遥感技术];
学科分类号
080201 [机械制造及其自动化];
摘要
Leaf area index (LAI) is an important structural vegetation parameter that is commonly derived from remotely sensed data. It has been used as a reliable indicator for vegetation's cover, status, health and productivity. In the past two decades, various Canada-wide LAI maps have been generated by the Canada Centre for Remote Sensing (CCRS). These products have been produced using a variety of very coarse satellite data such as those from SPOT VGT and NOAA AVHRR satellite data. However, in these LAI products, the mapping of the Canadian northern vegetation has not been performed with field LAI measurements due in large part to scarce in situ measurements over northern biomes. The coarse resolution maps have been extensively used in Canada, but finer resolution LAI maps are needed over the northern Canadian ecozones, in particular for studying caribou habitats and feeding grounds. In this study, a new LAI algorithm was developed with particular emphasis over northern Canada using a much finer resolution of remotely sensed data and in situ measurements collected over a wide range of northern arctic vegetation. A statistical relationship was developed between the in situ LAI measurements collected over vegetation plots in northern Canada and their corresponding pixel spectral information from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. Furthermore, all Landsat TM and ETM+ data have been pre-normalized to NOAA AVHRR and SPOT VGT data from the growing season of 2005 to reduce any seasonal or temporal variations. Various spectral vegetation indices developed from the Landsat TM and ETM+ data were analysed in this study. The reduced simple ratio index (RSR) was found to be the most robust and an accurate estimator of LAI for northern arctic vegetation. An exponential relationship developed using the Theil-Sen regression technique showed an R-2 of 0.51 between field LAI measurement and the RSR. The developed statistical relationship was applied to a pre-existing Landsat TM 250 m resolution mosaic for northern Canada to produce the final LAI map for northern Canada ecological zones. Furthermore, the 250 m resolution LAI estimates, per ecological zone, were almost generally lower than those of the CCRS Canada-wide VGT LAI maps for the same ecozones. Validation of the map with LAI field data from the 2008 season, not used in the derivation of the algorithm, shows strong agreement between the in situ LAI measurement values and the map-estimated LAI values.
引用
收藏
页码:5059 / 5076
页数:18
相关论文
共 34 条
[1]
Evaluation of national and global LAI products derived from optical remote sensing instruments over Canada [J].
Abuelgasim, Abdelgadir A. ;
Fernandes, Richard A. ;
Leblanc, Sylvain G. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2006, 44 (07) :1872-1884
[2]
LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION -: Part 1:: Principles of the algorithm [J].
Baret, Frederic ;
Hagolle, Olivier ;
Geiger, Bernhard ;
Bicheron, Patrice ;
Miras, Bastien ;
Huc, Mireille ;
Berthelot, Beatrice ;
Nino, Fernando ;
Weiss, Marie ;
Samain, Olivier ;
Roujean, Jean Louis ;
Leroy, Marc .
REMOTE SENSING OF ENVIRONMENT, 2007, 110 (03) :275-286
[3]
LAI and fAPAR mapping at global scale by model inversion against spaceborne POLDER data [J].
Bicheron, P ;
Leroy, M ;
Hautecoeur, O .
IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, :1228-1230
[4]
Grassland modeling and monitoring with SPOT-4 VEGETATION instrument during the 1997-1999 SALSA experiment [J].
Cayrol, P ;
Chehbouni, A ;
Kergoat, L ;
Dedieu, G ;
Mordelet, P ;
Nouvellon, Y .
AGRICULTURAL AND FOREST METEOROLOGY, 2000, 105 (1-3) :91-115
[5]
Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements [J].
Chen, JM ;
Pavlic, G ;
Brown, L ;
Cihlar, J ;
Leblanc, SG ;
White, HP ;
Hall, RJ ;
Peddle, DR ;
King, DJ ;
Trofymow, JA ;
Swift, E ;
Van der Sanden, J ;
Pellikka, PKE .
REMOTE SENSING OF ENVIRONMENT, 2002, 80 (01) :165-184
[6]
Retrieving leaf area index of boreal conifer forests using landsat TM images [J].
Chen, JM ;
Cihlar, J .
REMOTE SENSING OF ENVIRONMENT, 1996, 55 (02) :153-162
[7]
CHEN W., 2009, REMOTE SENS IN PRESS
[8]
LAND PROCESSES IN CLIMATE MODELS [J].
DICKSON, RE .
REMOTE SENSING OF ENVIRONMENT, 1995, 51 (01) :27-38
[9]
Parametric (modified least squares) and non-parametric (Theil-Sen) linear regressions for predicting biophysical parameters in the presence of measurement errors [J].
Fernandes, R ;
Leblanc, SG .
REMOTE SENSING OF ENVIRONMENT, 2005, 95 (03) :303-316
[10]
Landsat-5 TM and Landsat-7 ETM+ based accuracy assessment of leaf area index products for Canada derived from SPOT-4 VEGETATION data [J].
Fernandes, R ;
Butson, C ;
Leblanc, S ;
Latifovic, R .
CANADIAN JOURNAL OF REMOTE SENSING, 2003, 29 (02) :241-258