[1]
Dj.M. Maric, P.F. Meier and S.K. Estreicher: Mater. Sci. Forum Vol. 83-87 (1992), p.119.
Google Scholar
[1]
F.M. Danson*, P. Bowyer. Estimating live fuel moisture content from remotely sensed reflectance [J ] . Remote Sensing of Environment 92 (2004) 309–321.
DOI: 10.1016/j.rse.2004.03.017
Google Scholar
[2]
F. M. Danson , M. D. Steven , T. J . Malthus &J . A. Clark. High spectral resolution data for determining leaf water content [J ] . International Journal of Remote sensing , 1992 , 13 (3) : 461~470.
DOI: 10.1080/01431169208904049
Google Scholar
[3]
Ceccato , P. , Flasse , S. , Tarantola , S. , Jacquemound , S. , & Gregoire , J . 2M. . Detecting vegetation leaf water content using reflectance in the optical domain[J ] . Remote Sensing of Environment , 2001 (77) : 22~33.
DOI: 10.1016/s0034-4257(01)00191-2
Google Scholar
[4]
Ceccato , P. , Nadine Gobron , Stephane Flasse , Bernard Pinty , & Stefano Tarantola. Designing a spectral index to esstimate vegetation water content from remote sensing data : Part 1. Theoretical approach[J ] . Remote Sensing of Environment , 2002 (82) : 188~197.
DOI: 10.1016/s0034-4257(02)00037-8
Google Scholar
[5]
Ceccato , P. , Stephane Flasse , Jean Marie Gregoire. Designing a spectral index to esstimate vegetation water content from remote sensing data Part 2. Validation and applications[J ] . Remote Sensing of Environment , 2002 (82) : 198~207.
DOI: 10.1016/s0034-4257(02)00036-6
Google Scholar
[6]
Paltridge , G. W. , and Barber , J . Monitoring grassland dryness and fire potential in Australia with NOAA/ AVHRR data[J ] . Remote Sensing of Environment , 1988 (25) : 381~394.
DOI: 10.1016/0034-4257(88)90110-1
Google Scholar
[7]
E. Chuvieco , D. Rian , I. Aguado and D. Cocero. Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data : applications in fire danger assessment [J ] . International Journal of Remote sensing , 2001 , 23 (11) : 2145~2162.
DOI: 10.1080/01431160110069818
Google Scholar
[8]
Marta Yebra , Emilio Chuvieco , David Riano. Estimation of live fuel moisture content from MODIS images for fire risk assessment. [J ]agri –culturaland forest meteorology 2008 (48): 523 – 536.
DOI: 10.1016/j.agrformet.2007.12.005
Google Scholar
[9]
Ceccato , P. , Flasse , S. , Tarantola , S. , Jacquemound , S. , & Gregoire , J . 2M. . Detecting vegetation leaf water content using reflectance in the optical domain[J ] . Remote Sensing of Environment , 2001 (77) : 22~33.
DOI: 10.1016/s0034-4257(01)00191-2
Google Scholar
[10]
Gao, B.C., 1996. NDWI: a normalized difference water index forremote sensing of vegetation liquid water from space. Remote Sens. Environ. 58, 257–266.
DOI: 10.1016/s0034-4257(96)00067-3
Google Scholar
[11]
Moghaddam , M. , & Saatchi , S. S. Monitoring tree moisture using an estimation algorithm applied to SAR data from BOREAS[J ] . IEEE Transactions on Geoscience and Remote Sensing , 1999 , 17 (2) , 901~916.
DOI: 10.1109/36.752209
Google Scholar
[12]
Liuchuang, Ge chenghui . U.S. Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) Features and Applications of remote sensing data. [J] REMOTE SENSING INFORMATION, 2000 (3) : 45~48.
Google Scholar
[13]
Liuchuang, Ge chenghui . U.S. AQUA Earth Observing System satellite data policy, the main technical indicators and data sharing issues Localization, [J] REMOTE SENSING INFORMATION, 2002 (6) : 38~42.
Google Scholar