TY - GEN
T1 - Estimating winter wheat biomass based on LANDSAT TM and MODIS data
AU - Bao, Yansong
AU - Gao, Wei
AU - Gao, Zhiqiang
PY - 2008
Y1 - 2008
N2 - Biomass can indicate plant growth status, so it is an important index for plant growth monitoring. This paper focused on the methodology of estimating winter wheat biomass based on LANDSAT TM and EOS MODIS images. In order to develop the method of retrieving wheat biomass from remote sensing data, field measurements were conducted when LANDSAT satellite passed over the study region. In the experiments, five LANDSAT TM images were acquired respectively at early erecting stage, jointing stage, earing stage, flowering stage and grain-filling stage of winter wheat, and experiment sites' wheat biomass was measured at each stage. Based on the TM and MODIS images, spectral indices such as NDVI, RDVI, EVI, MSAVI, SIPI and NDWI were calculated. Then the correlation coefficients between wheat biomass and spectral indices of the experiment sites were computed. According to the correlation coefficients, the optimal spectral indices for estimating wheat biomass were determined. The best-fitting method was employed to build the relationship models between wheat biomass and the optimal spectral indices. Finally, the models were used to estimate wheat biomass based on TM and MODIS data. The RMSE of estimated biomass was not more than 66.403 g/m2.
AB - Biomass can indicate plant growth status, so it is an important index for plant growth monitoring. This paper focused on the methodology of estimating winter wheat biomass based on LANDSAT TM and EOS MODIS images. In order to develop the method of retrieving wheat biomass from remote sensing data, field measurements were conducted when LANDSAT satellite passed over the study region. In the experiments, five LANDSAT TM images were acquired respectively at early erecting stage, jointing stage, earing stage, flowering stage and grain-filling stage of winter wheat, and experiment sites' wheat biomass was measured at each stage. Based on the TM and MODIS images, spectral indices such as NDVI, RDVI, EVI, MSAVI, SIPI and NDWI were calculated. Then the correlation coefficients between wheat biomass and spectral indices of the experiment sites were computed. According to the correlation coefficients, the optimal spectral indices for estimating wheat biomass were determined. The best-fitting method was employed to build the relationship models between wheat biomass and the optimal spectral indices. Finally, the models were used to estimate wheat biomass based on TM and MODIS data. The RMSE of estimated biomass was not more than 66.403 g/m2.
KW - Biomass retrieval
KW - EOS MODIS
KW - LANDSAT TM
KW - Spectral indices
UR - https://www.scopus.com/pages/publications/56249129770
U2 - 10.1117/12.806210
DO - 10.1117/12.806210
M3 - 会议稿件
AN - SCOPUS:56249129770
SN - 9780819473035
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Remote Sensing and Modeling of Ecosystems for Sustainability V
T2 - Remote Sensing and Modeling of Ecosystems for Sustainability V
Y2 - 13 August 2008 through 13 August 2008
ER -