Discrimination of sugarcane varieties in southeastern brazil with EO-1 hyperion data

被引:211
作者
Galvao, LS [1 ]
Formaggio, AR [1 ]
Tisot, DA [1 ]
机构
[1] INPE, Div Sensoriamento Remoto, BR-12227010 Sao Jose Dos Campos, SP, Brazil
关键词
hyperspectral remote sensing; sugarcane varieties; hyperion; discriminant analysis; agriculture; crops;
D O I
10.1016/j.rse.2004.11.012
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Hyperspectral data acquired by the Hyperion instrument, on board the Earth Observing-1 (EO-I) satellite, were evaluated for the discrimination of five important Brazilian sugarcane varieties(RB72-454, SP80-1816, SP80-1842, SP81-3250, and SP87-365). The radiance values were converted into surface reflectance images by a MODTRAN4-based technique. To discriminate varieties with similar reflectance values, multiple discriminant analysis (MDA) was applied over the data. To obtain an adequate discriminant function, a stepwise method was used to select the best variables among surface reflectance values, ratios of reflectance, and several spectral indices potentially sensitive to changes in chlorophyll content, leaf water, and lignin-cellulose. Results showed that the five Brazilian sugarcane varieties were discriminated using EO-I Hyperion data. Differences in canopy architecture affected sunlight penetration and reflectance, resulting in a higher reflectance for planophile (e.g., SP81-3250) than erectophile (e.g., SP80-1842) sugarcane plants. The variety SP80-1842 presented lower reflectance values, deeper lignin-cellulose absorption bands at 2103 nm and 2304 nm, shallower leaf liquid water absorption bands at 983 nm and 1205 rim, and lower leaf liquid water content than the other sugarcane varieties. To discriminate this cultivar, a single near-infrared (NIR) band threshold was used. To discriminate the other four sugarcane varieties with similar reflectance values, MDA was used producing a classification accuracy of 87.5% for a hold-out set of pixels. The comparison between the ground truth data and the MDA-derived classification image confirmed the model' capacity to differentiate the varieties accurately. The best results were obtained for the cultivar SP87-365 that presented the lowest spectral variability in the discriminant space. Some misclassified areas were associated with the cultivars SP80-1816 and SP81-3250 that showed the highest spectral variability. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:523 / 534
页数:12
相关论文
共 45 条
  • [1] Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery
    Apan, A
    Held, A
    Phinn, S
    Markley, J
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2004, 25 (02) : 489 - 498
  • [2] Imaging spectroscopy for desertification studies: Comparing AVIRIS and EO-1 Hyperion in Argentina drylands
    Asner, GP
    Heidebrecht, KB
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (06): : 1283 - 1296
  • [3] Badaloo G. H., 1999, Proceedings of the Third Annual Meeting of Agricultural Scientists, Reduit, Mauritius, 17-18 November 1998, P47
  • [4] Family x environment and genotype x environment interactions for sugarcane across two contrasting marginal environments in Mauritius
    Bissessur, D
    Tilney-Bassett, RAE
    Chong, LCYLS
    Domaingue, R
    Julien, MHR
    [J]. EXPERIMENTAL AGRICULTURE, 2000, 36 (01) : 101 - 114
  • [5] Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leaves
    Blackburn, GA
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 1998, 19 (04) : 657 - 675
  • [6] Validation of a hyperspectral curve-fitting model for the estimation of plant water content of agricultural canopies
    Champagne, CM
    Staenz, K
    Bannari, A
    McNairn, H
    Deguise, JC
    [J]. REMOTE SENSING OF ENVIRONMENT, 2003, 87 (2-3) : 148 - 160
  • [7] REFLECTANCE SPECTROSCOPY - QUANTITATIVE-ANALYSIS TECHNIQUES FOR REMOTE-SENSING APPLICATIONS
    CLARK, RN
    ROUSH, TL
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH, 1984, 89 (NB7): : 6329 - 6340
  • [8] *CTR TECN COP AC A, 2004, COP
  • [9] Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes
    Datt, B
    McVicar, TR
    Van Niel, TG
    Jupp, DLB
    Pearlman, JS
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (06): : 1246 - 1259
  • [10] Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance
    Daughtry, CST
    Walthall, CL
    Kim, MS
    de Colstoun, EB
    McMurtrey, JE
    [J]. REMOTE SENSING OF ENVIRONMENT, 2000, 74 (02) : 229 - 239