TY - GEN
T1 - A multilevel slicing based coding method for tree detection
AU - Lin, Chien Yu
AU - Lin, Chinsu
AU - Chang, Chein I.
N1 - Publisher Copyright:
© 2018 IEEE
PY - 2018/10/31
Y1 - 2018/10/31
N2 - This paper proposed an efficient height slicing method for detecting trees using a canopy height model (CHM). A digital forest simulator was proposed to randomly generate trees by a 2-dimensional Gaussian probability density function. Details such as the location, crown radius, and height of a tree are automatically generated via the parameters of location, spread blob, and amplitude of a two-dimensional Gaussian function. An index of hit rate was used to evaluate the detection power of the algorithm and the indices RMSE and PRMSE were used to evaluate the estimation accuracy of tree height and crown radius. The proposed algorithm was able to detect trees at 100% and 80% hit rate at a stand density of less than 600 trees per hectare and this then gradually decreased to 85% and 70% as stand density increased to 1000 trees per hectare for artificial forest and natural forest respectively.
AB - This paper proposed an efficient height slicing method for detecting trees using a canopy height model (CHM). A digital forest simulator was proposed to randomly generate trees by a 2-dimensional Gaussian probability density function. Details such as the location, crown radius, and height of a tree are automatically generated via the parameters of location, spread blob, and amplitude of a two-dimensional Gaussian function. An index of hit rate was used to evaluate the detection power of the algorithm and the indices RMSE and PRMSE were used to evaluate the estimation accuracy of tree height and crown radius. The proposed algorithm was able to detect trees at 100% and 80% hit rate at a stand density of less than 600 trees per hectare and this then gradually decreased to 85% and 70% as stand density increased to 1000 trees per hectare for artificial forest and natural forest respectively.
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U2 - 10.1109/IGARSS.2018.8517654
DO - 10.1109/IGARSS.2018.8517654
M3 - Conference contribution
AN - SCOPUS:85063153359
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 7524
EP - 7527
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 -