Forest volume estimation based on spectral and textural information from the Landsat 8 satellite

WANG Yueting; ZHANG Xiaoli; YANG Huiqiao; WANG Shuhan; BAI Jinting

doi:10.11833/j.issn.2095-0756.2015.03.008

Volume 32 Issue 3

May 2015

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Article Navigation > Journal of Zhejiang A&F University > 2015 > 32(3): 384-391

YU Bao. Characteristics and impact factors of self-pruning in natural Larix gmelinii forest[J]. Journal of Zhejiang A&F University, 2023, 40(1): 209-216. DOI: 10.11833/j.issn.2095-0756.20220220

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WANG Yueting, ZHANG Xiaoli, YANG Huiqiao, et al. Forest volume estimation based on spectral and textural information from the Landsat 8 satellite[J]. Journal of Zhejiang A&F University, 2015, 32(3): 384-391. DOI: 10.11833/j.issn.2095-0756.2015.03.008

Forest volume estimation based on spectral and textural information from the Landsat 8 satellite

DOI: 10.11833/j.issn.2095-0756.2015.03.008

1.
Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China;
2.
Forestry College, Beijing Forestry University, Beijing 100083, China

Received Date: 2014-07-17
Rev Recd Date: 2014-11-03
Publish Date: 2015-06-20

Abstract

On the Jiangle State Forest Farm of Fujian Province forest volume was obtained by field investigation and by Landsat 8 observations that utilized band spectral values, vegetation indexes, derivatives of bands, and optimal textural measurements derived from the panchromatic band using varied window sizes. Through multiple regression analysis, volume estimation models were produced with independent variables of 1） only spectral factors and 2） combined spectral factors and textural volume. Then, validation was conducted using field survey data to test and compare model prediction accuracy. Experimental results showed R2 = 0.727 6 for the spectrally based volume estimation model and R2 = 0.857 5 for the combined model. Model prediction accuracy was 79.8% for the single spectral based volume estimation model and 86.0% for the combined model. Therefore, the improved prediction accuracy using textural information from the panchromatic band with images of Landsat 8 for forest volume estimation and application of this procedure should be considered when determining forest volume.［Ch, 3 fig. 6 tab. 22 ref.］
- forest mensuration,
- forest volume,
- Landsat 8 images,
- band spectra,
- texture information,
- estimation models

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

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Forest volume estimation based on spectral and textural information from the Landsat 8 satellite

1. Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China;

2. Forestry College, Beijing Forestry University, Beijing 100083, China

Received Date: 2014-07-17

Rev Recd Date: 2014-11-03

Publish Date: 2015-06-20

Key words:

Abstract: On the Jiangle State Forest Farm of Fujian Province forest volume was obtained by field investigation and by Landsat 8 observations that utilized band spectral values, vegetation indexes, derivatives of bands, and optimal textural measurements derived from the panchromatic band using varied window sizes. Through multiple regression analysis, volume estimation models were produced with independent variables of 1） only spectral factors and 2） combined spectral factors and textural volume. Then, validation was conducted using field survey data to test and compare model prediction accuracy. Experimental results showed R2 = 0.727 6 for the spectrally based volume estimation model and R2 = 0.857 5 for the combined model. Model prediction accuracy was 79.8% for the single spectral based volume estimation model and 86.0% for the combined model. Therefore, the improved prediction accuracy using textural information from the panchromatic band with images of Landsat 8 for forest volume estimation and application of this procedure should be considered when determining forest volume.［Ch, 3 fig. 6 tab. 22 ref.］

Forest volume estimation based on spectral and textural information from the Landsat 8 satellite

DOI: 10.11833/j.issn.2095-0756.2015.03.008

Abstract

References

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Cited by

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Other cited types(1)

通讯作者: 陈斌, bchen63@163.com

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