Information analysis of hyperspectral images from the hyperion satellite

被引:0
|
作者
Yu. G. Puzachenko
R. B. Sandlersky
A. N. Krenke
M. Yu. Puzachenko
机构
[1] Russian Academy of Sciences,Severtsov Institute of Ecology and Evolution
[2] Russian Academy of Sciences,Institute of Geography
来源
Doklady Earth Sciences | 2017年 / 475卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
A new method of estimating the outgoing radiation spectra data obtained from the Hyperiоn EO-1 satellite is considered. In theoretical terms, this method is based on the nonequilibrium thermodynamics concept with corresponding estimates of the entropy and the Kullbak information. The obtained information estimates make it possible to assess the effective work of the landscape cover both in general and for its various types and to identify the spectrum ranges primarily responsible for the information increment and, accordingly, for the effective work. The information is measured in the frequency band intervals corresponding to the peaks of solar radiation absorption by different pigments, mesophyll, and water to evaluate the system operation by their synthesis and moisture accumulation. This method is assumed to be effective in investigation of ecosystem functioning by hyperspectral remote sensing.
引用
收藏
页码:784 / 787
页数:3
相关论文
共 50 条
  • [21] From hyperspectral satellite images to decision processus: a user-oriented approach
    Minghelli-Roman, A
    Cauneau, F
    Marni, S
    Petit, M
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 2386 - 2388
  • [22] Hyperion provides information from on high
    Segal, CC
    Carman, S
    LASER FOCUS WORLD, 2002, 38 (08): : 149 - +
  • [23] Improve the Flooding Analysis Result from Low Resolution DEMs using Medium Resolution Satellite Hyperspectral Images
    Ruiz Lozano, Oscar A.
    Sanchez Espeso, Javier
    Alvarez Diaz, Cesar
    PROCEEDINGS OF THE 39TH IAHR WORLD CONGRESS, 2022, : 5359 - 5366
  • [24] Preprocessing of Hyperspectral Images - a Comparative Study of Destriping Algorithms for EO-1 Hyperion
    Scheffler, Daniel
    Karrasch, Pierre
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XIX, 2013, 8892
  • [25] Multistage Hybrid Denoising Network for Satellite Hyperspectral Images
    Ren, Kai
    Sun, Weiwei
    Yang, Gang
    Meng, Xiangchao
    Peng, Jiangtao
    Li, Huiyang
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62
  • [26] A novel approach to combine spatial and spectral information from hyperspectral images
    Gaci, Belal
    Abdelghafour, Florent
    Ryckewaert, Maxime
    Mas-Garcia, Silvia
    Louargant, Marine
    Verpont, Florence
    Laloum, Yohana
    Bendoula, Ryad
    Chaix, Gilles
    Roger, Jean-Michel
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2023, 240
  • [27] Filter Banks for Hyperspectral Pixel Classification of Satellite Images
    Rajadell, Olga
    Garcia-Sevilla, Pedro
    Pla, Filiberto
    PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, PROCEEDINGS, 2009, 5856 : 1039 - 1046
  • [28] Reconstruction of Hyperspectral Data From RGB Images With Prior Category Information
    Yan, Longbin
    Wang, Xiuheng
    Zhao, Min
    Kaloorazi, Maboud
    Chen, Jie
    Rahardja, Susanto
    IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2020, 6 : 1070 - 1081
  • [29] A model on achieving higher performance in the classification of hyperspectral satellite data: A case study on Hyperion data
    Chutia D.
    Bhattacharyya D.K.
    Kalita R.
    Goswami J.
    Singh P.S.
    Sudhakar S.
    Applied Geomatics, 2014, 6 (3) : 181 - 195
  • [30] Analysis of the efficiency of classification of hyperspectral satellite images of natural and man-made areas
    Borzov S.M.
    Potaturkin A.O.
    Potaturkin O.I.
    Fedotov A.M.
    Optoelectronics, Instrumentation and Data Processing, 2016, 52 (1) : 1 - 10