Relationship between forest void structure and microclimate
This study evaluated the impact of the “void”, a non-tangible space in the forest, on the microclimate, rather than tangible objects such as trees and understory vegetation. A terrestrial laser was used to measure the forest void space in three dimensions and compact meteorological sensors were used...
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| Published in | Journal of the Japanese Society of Revegetation Technology Vol. 50; no. 1; pp. 1 - 6 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | Japanese |
| Published |
Tokyo
JAPANESE SOCIETY OF REVEGETATION TECHNOLOGY
31.08.2024
Japan Science and Technology Agency |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0916-7439 1884-3670 0916-7439 |
| DOI | 10.7211/jjsrt.50.1 |
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| Abstract | This study evaluated the impact of the “void”, a non-tangible space in the forest, on the microclimate, rather than tangible objects such as trees and understory vegetation. A terrestrial laser was used to measure the forest void space in three dimensions and compact meteorological sensors were used to measure the temperature and humidity inside the forest. The relationship between the number of voxels for the tangible and non-tangible objects showed that the distribution of forest void structure was different by different height layer. The correlation analysis between the number of voxels and meteorological data showed that forest voids have a significant influence on minimum temperature. The previous study showed the presence or absence of forest canopy influences microclimate, however this study shows the relationships between forest structure and microclimate was obtained from the spatial distribution of forest void. |
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| AbstractList | This study evaluated the impact of the “void”, a non-tangible space in the forest, on the microclimate, rather than tangible objects such as trees and understory vegetation. A terrestrial laser was used to measure the forest void space in three dimensions and compact meteorological sensors were used to measure the temperature and humidity inside the forest. The relationship between the number of voxels for the tangible and non-tangible objects showed that the distribution of forest void structure was different by different height layer. The correlation analysis between the number of voxels and meteorological data showed that forest voids have a significant influence on minimum temperature. The previous study showed the presence or absence of forest canopy influences microclimate, however this study shows the relationships between forest structure and microclimate was obtained from the spatial distribution of forest void. |
| Author | NAKAJIMA, Fumio AOYAGI, Kantaro SETOGUCHI, Hiroaki KATO, Akira UEHARA, Koichi |
| Author_xml | – sequence: 1 fullname: SETOGUCHI, Hiroaki organization: Graduate School of Human and Environmental Studies, Kyoto University – sequence: 1 fullname: NAKAJIMA, Fumio organization: Denbei Farm – sequence: 1 fullname: KATO, Akira organization: Graduate School of Horticulture, Chiba University – sequence: 1 fullname: UEHARA, Koichi organization: Graduate School of Global and Transdisciplinary Studies, Chiba University – sequence: 1 fullname: AOYAGI, Kantaro organization: CTI Engineering Co., Ltd |
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| Cites_doi | 10.1016/j.foreco.2016.09.003 10.3390/rs12203457 10.1016/j.foreco.2016.09.036 10.2307/1931034 10.1016/j.agrformet.2013.09.005 10.1111/j.1538-4632.1992.tb00261.x 10.1111/ecog.03836 10.1016/j.agrformet.2017.04.012 10.1109/TGRS.2006.881743 10.1111/geb.12991 |
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| References | 10) Zellweger, F., Coomes, D., Lenoir, J., Depauw, L., Maes, S. L., Wulf, M., Kirby, K. J., Brunet, J., Kopecký, M., Máliš, F., Schmidt, W., Heinrichs, S., den Ouden, J., Jaroszewicz, B., Buyse, G., Spicher, F., Verheyen, K. and De Frenne, P. (2019) Seasonal drivers of understory temperature buffering in temperate deciduous forests across Europe. Global Ecology and Biogeography, 28: 1774-1786. 7) Hosoi, F. and Omasa, K. (2006) Voxel-based 3D modeling of individual trees for estimating leaf area density using high-resolution portable scanning lidar. IEEE Transactions on Geoscience and Remote Sensing, 44: 3610-3618. 4) Ehbrecht, M., Schall, P., Juchheim, J., Ammer, C. and Seidel, D. (2016) Effective number of layers: A new measure for quantifying three-dimensional stand structure based on sampling with terrestrial LiDAR. Forest Ecology and Management, 380: 212-223. 5) Ehbrecht, M., Schall, P., Ammer, C. and Seidel, D. (2017) Quantifying stand structural complexity and its relationship with forest management, tree species diversity and microclimate. Agricultural and Forest Meteorology, 242: 1-9. 1) Béland, M., Baldocchi, D. D., Widlowski, J-L., Fournier, R. A. and Verstraete, M. M. (2014) On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR. Agricultural and Forest Meteorology, 184: 82-97. 9) Wang, Y. and Fang, H. (2020) Estimation of LAI with the technology: A Review. Remote Sensing, 12: 3457. 3) Davis, K. T., Dobrowski, S. Z., Holden, Z. A., Higuera, P. E. and Abatzoglou, J. T. (2019) Microclimatic buffering in forests of the future: the role of local water balance. Ecography, 42: 1-11. 6) Getis, A. and Ord, J. K. (1992) The analysis of spatial association by use of distance statistics. Geographical Analysis, 24: 189-206. 2) Clark, P. J. and Evans, F. C. (1954) Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology, 4: 445-453. 8) Seidel, D., Ehbrecht, M. and Puettmann, K. (2016) Assessing different components of three-dimensional forest structure with single-scan terrestrial laser scanning: a case study. Forest Ecology and Management, 381: 196-208. 1 2 3 4 5 6 7 8 9 10 |
| References_xml | – reference: 1) Béland, M., Baldocchi, D. D., Widlowski, J-L., Fournier, R. A. and Verstraete, M. M. (2014) On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR. Agricultural and Forest Meteorology, 184: 82-97. – reference: 4) Ehbrecht, M., Schall, P., Juchheim, J., Ammer, C. and Seidel, D. (2016) Effective number of layers: A new measure for quantifying three-dimensional stand structure based on sampling with terrestrial LiDAR. Forest Ecology and Management, 380: 212-223. – reference: 5) Ehbrecht, M., Schall, P., Ammer, C. and Seidel, D. (2017) Quantifying stand structural complexity and its relationship with forest management, tree species diversity and microclimate. Agricultural and Forest Meteorology, 242: 1-9. – reference: 2) Clark, P. J. and Evans, F. C. (1954) Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology, 4: 445-453. – reference: 8) Seidel, D., Ehbrecht, M. and Puettmann, K. (2016) Assessing different components of three-dimensional forest structure with single-scan terrestrial laser scanning: a case study. Forest Ecology and Management, 381: 196-208. – reference: 9) Wang, Y. and Fang, H. (2020) Estimation of LAI with the technology: A Review. Remote Sensing, 12: 3457. – reference: 10) Zellweger, F., Coomes, D., Lenoir, J., Depauw, L., Maes, S. L., Wulf, M., Kirby, K. J., Brunet, J., Kopecký, M., Máliš, F., Schmidt, W., Heinrichs, S., den Ouden, J., Jaroszewicz, B., Buyse, G., Spicher, F., Verheyen, K. and De Frenne, P. (2019) Seasonal drivers of understory temperature buffering in temperate deciduous forests across Europe. Global Ecology and Biogeography, 28: 1774-1786. – reference: 6) Getis, A. and Ord, J. K. (1992) The analysis of spatial association by use of distance statistics. Geographical Analysis, 24: 189-206. – reference: 3) Davis, K. T., Dobrowski, S. Z., Holden, Z. A., Higuera, P. E. and Abatzoglou, J. T. (2019) Microclimatic buffering in forests of the future: the role of local water balance. Ecography, 42: 1-11. – reference: 7) Hosoi, F. and Omasa, K. (2006) Voxel-based 3D modeling of individual trees for estimating leaf area density using high-resolution portable scanning lidar. IEEE Transactions on Geoscience and Remote Sensing, 44: 3610-3618. – ident: 4 doi: 10.1016/j.foreco.2016.09.003 – ident: 9 doi: 10.3390/rs12203457 – ident: 8 doi: 10.1016/j.foreco.2016.09.036 – ident: 2 doi: 10.2307/1931034 – ident: 1 doi: 10.1016/j.agrformet.2013.09.005 – ident: 6 doi: 10.1111/j.1538-4632.1992.tb00261.x – ident: 3 doi: 10.1111/ecog.03836 – ident: 5 doi: 10.1016/j.agrformet.2017.04.012 – ident: 7 doi: 10.1109/TGRS.2006.881743 – ident: 10 doi: 10.1111/geb.12991 |
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| Title | Relationship between forest void structure and microclimate |
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