TY - GEN
T1 - Forest vertical structure from MODIS BRDF shape indicators
AU - Cui, Lei
AU - Jiao, Ziti
AU - Dong, Yadong
AU - Zhang, Xiaoning
AU - Sun, Mei
AU - Yin, Siyang
AU - Chang, Yaxuan
AU - He, Dandan
AU - Ding, Anxing
N1 - Publisher Copyright:
© 2018 IEEE
PY - 2018/10/31
Y1 - 2018/10/31
N2 - It has been a hot study field to extract forest structure parameter using Airborne LiDAR. Since footprints of Airborne LiDAR data are discontinuously distributed with small data coverage, therefore, it is impossible to obtain the forest structure information of continuous region using Airborne LiDAR data alone. The MODIS BRDF shape indicators contain the information regarding 3-D structure of forest and have the possibility to retrieve the structural parameters of forest. In this study, we select Howland Forest, Harvard Forest, La Selva Forest and Bartlett Forest as experimental areas, and aim to construct a canopy height estimation model from the airborne Laser Vegetation Imaging Sensor (LVIS) data and MODIS BRDF shape indicators. Firstly, H100 canopy height was extracted from the LVIS data and the MODIS BRDF shape indicators were calculated based on MODIS data. Secondly, using the Random Forest algorithm to develop a canopy height estimation model with H100 canopy height data and MODIS BRDF shape indicators. Finally, 10-fold cross-validation method is used to evaluate the accuracy of the model, and the validation results show that the MODIS BRDF shape indicators can be estimated forest canopy heights in high accuracy.
AB - It has been a hot study field to extract forest structure parameter using Airborne LiDAR. Since footprints of Airborne LiDAR data are discontinuously distributed with small data coverage, therefore, it is impossible to obtain the forest structure information of continuous region using Airborne LiDAR data alone. The MODIS BRDF shape indicators contain the information regarding 3-D structure of forest and have the possibility to retrieve the structural parameters of forest. In this study, we select Howland Forest, Harvard Forest, La Selva Forest and Bartlett Forest as experimental areas, and aim to construct a canopy height estimation model from the airborne Laser Vegetation Imaging Sensor (LVIS) data and MODIS BRDF shape indicators. Firstly, H100 canopy height was extracted from the LVIS data and the MODIS BRDF shape indicators were calculated based on MODIS data. Secondly, using the Random Forest algorithm to develop a canopy height estimation model with H100 canopy height data and MODIS BRDF shape indicators. Finally, 10-fold cross-validation method is used to evaluate the accuracy of the model, and the validation results show that the MODIS BRDF shape indicators can be estimated forest canopy heights in high accuracy.
KW - BRDF shape indicators
KW - LVIS
KW - The Kernel-driven model
KW - Vegetation height
UR - https://www.scopus.com/pages/publications/85063164715
U2 - 10.1109/IGARSS.2018.8517831
DO - 10.1109/IGARSS.2018.8517831
M3 - Conference contribution
AN - SCOPUS:85063164715
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 5911
EP - 5914
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -