Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests
Global forests face severe challenges owing to climate change, making dynamic and accurate monitoring of forest conditions critically important. Forests in Japan, covering approximately 70% of the country's land area, play a vital role yet often overlooked in global forestry. Japanese forests a...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Science of Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017224000282 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850247136343490560 |
|---|---|
| author | Hantao Li Xiaoxuan Li Tomomichi Kato Masato Hayashi Junjie Fu Takuya Hiroshima |
| author_facet | Hantao Li Xiaoxuan Li Tomomichi Kato Masato Hayashi Junjie Fu Takuya Hiroshima |
| author_sort | Hantao Li |
| collection | DOAJ |
| description | Global forests face severe challenges owing to climate change, making dynamic and accurate monitoring of forest conditions critically important. Forests in Japan, covering approximately 70% of the country's land area, play a vital role yet often overlooked in global forestry. Japanese forests are unique, with approximately 50% comprising artificial forests, predominantly coniferous forests. Despite the Japanese government's extensive use of airborne Light Detecting and Ranging (LiDAR) to assess forest conditions, these data need more availability and frequency. The Global Ecosystem Dynamics Investigation (GEDI), the first Spaceborne LiDAR data explicitly designed for vegetation monitoring, is expected to provide significant value for high-frequency and high-accuracy forest monitoring. To assess the accuracy of GEDI data in Japanese artificial coniferous forests, the reference data were gathered from 53,967,770 artificial coniferous trees via airborne LiDAR data in Aichi Prefecture, Japan. This data was then compared to the corresponding GEDI-derived terrain elevations, canopy heights (GEDI RH98), and aboveground biomass density (AGBD) estimates to assess the accuracy of GEDI data. This research also explored how different factors influence the accuracy of GEDI terrain elevation estimates, including the type of beam, time of acquisition (day or night), beam sensitivity, and terrain slope. Additionally, the effects of various forest structural parameters, such as the height-to-diameter ratio, crown length ratio, and the number of trees on the accuracy of the GEDI canopy height and AGBD, were investigated. The results showed that GEDI terrain elevation demonstrated high accuracy across various slope conditions, with rRMSE ranging from 2.28% to 3.25% and RMSE ranging from 11.68 m to 16.54 m. After geolocation adjustment, the comparison of canopy height estimates derived from GEDI to airborne LiDAR-derived canopy height also showed high accuracy, exhibiting a rRMSE of 22.04%. In contrast, the GEDI AGBD product showed moderate accuracy, with a rRMSE of 52.79%. The findings also indicated that the accuracy of GEDI RH98 was influenced by terrain slope and crown length ratio, whereas the accuracy of GEDI AGBD was mainly impacted by the number of trees and crown length ratio. This study provided the first baseline accuracy assessment of GEDI terrain elevation, RH98, and AGBD estimates in Japanese artificial forests. Furthermore, this study provided valuable insights into the accuracy of GEDI metrics by examining potential factors. |
| format | Article |
| id | doaj-art-4577ca1d5fc3464f88033fa61e5323c4 |
| institution | OA Journals |
| issn | 2666-0172 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Science of Remote Sensing |
| spelling | doaj-art-4577ca1d5fc3464f88033fa61e5323c42025-08-20T01:59:00ZengElsevierScience of Remote Sensing2666-01722024-12-011010014410.1016/j.srs.2024.100144Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forestsHantao Li0Xiaoxuan Li1Tomomichi Kato2Masato Hayashi3Junjie Fu4Takuya Hiroshima5Graduate School of Agriculture and Life Sciences, The University of Tokyo, Tokyo, 113-8657, JapanDepartment of Geography and Geoinformation Science, George Mason University, Fairfax, VA, 22030, United StatesResearch Faculty of Agriculture, Hokkaido University, Sapporo, Hokkaido, 060-8589, Japan; Global Center for Food, Land, and Water Resources, Research Faculty of Agriculture, Hokkaido University, Sapporo, Hokkaido, 060-8589, JapanEarth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Tsukuba, Ibaraki, 305-8505, JapanGraduate School of Global Food Resources, Hokkaido University, Sapporo, Hokkaido, 060-0809, JapanGraduate School of Agriculture and Life Sciences, The University of Tokyo, Tokyo, 113-8657, Japan; Corresponding author.Global forests face severe challenges owing to climate change, making dynamic and accurate monitoring of forest conditions critically important. Forests in Japan, covering approximately 70% of the country's land area, play a vital role yet often overlooked in global forestry. Japanese forests are unique, with approximately 50% comprising artificial forests, predominantly coniferous forests. Despite the Japanese government's extensive use of airborne Light Detecting and Ranging (LiDAR) to assess forest conditions, these data need more availability and frequency. The Global Ecosystem Dynamics Investigation (GEDI), the first Spaceborne LiDAR data explicitly designed for vegetation monitoring, is expected to provide significant value for high-frequency and high-accuracy forest monitoring. To assess the accuracy of GEDI data in Japanese artificial coniferous forests, the reference data were gathered from 53,967,770 artificial coniferous trees via airborne LiDAR data in Aichi Prefecture, Japan. This data was then compared to the corresponding GEDI-derived terrain elevations, canopy heights (GEDI RH98), and aboveground biomass density (AGBD) estimates to assess the accuracy of GEDI data. This research also explored how different factors influence the accuracy of GEDI terrain elevation estimates, including the type of beam, time of acquisition (day or night), beam sensitivity, and terrain slope. Additionally, the effects of various forest structural parameters, such as the height-to-diameter ratio, crown length ratio, and the number of trees on the accuracy of the GEDI canopy height and AGBD, were investigated. The results showed that GEDI terrain elevation demonstrated high accuracy across various slope conditions, with rRMSE ranging from 2.28% to 3.25% and RMSE ranging from 11.68 m to 16.54 m. After geolocation adjustment, the comparison of canopy height estimates derived from GEDI to airborne LiDAR-derived canopy height also showed high accuracy, exhibiting a rRMSE of 22.04%. In contrast, the GEDI AGBD product showed moderate accuracy, with a rRMSE of 52.79%. The findings also indicated that the accuracy of GEDI RH98 was influenced by terrain slope and crown length ratio, whereas the accuracy of GEDI AGBD was mainly impacted by the number of trees and crown length ratio. This study provided the first baseline accuracy assessment of GEDI terrain elevation, RH98, and AGBD estimates in Japanese artificial forests. Furthermore, this study provided valuable insights into the accuracy of GEDI metrics by examining potential factors.http://www.sciencedirect.com/science/article/pii/S2666017224000282LiDARGEDIForest structural parametersJapanese artificial forestCanopy heightAGBD |
| spellingShingle | Hantao Li Xiaoxuan Li Tomomichi Kato Masato Hayashi Junjie Fu Takuya Hiroshima Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests Science of Remote Sensing LiDAR GEDI Forest structural parameters Japanese artificial forest Canopy height AGBD |
| title | Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests |
| title_full | Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests |
| title_fullStr | Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests |
| title_full_unstemmed | Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests |
| title_short | Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests |
| title_sort | accuracy assessment of gedi terrain elevation canopy height and aboveground biomass density estimates in japanese artificial forests |
| topic | LiDAR GEDI Forest structural parameters Japanese artificial forest Canopy height AGBD |
| url | http://www.sciencedirect.com/science/article/pii/S2666017224000282 |
| work_keys_str_mv | AT hantaoli accuracyassessmentofgediterrainelevationcanopyheightandabovegroundbiomassdensityestimatesinjapaneseartificialforests AT xiaoxuanli accuracyassessmentofgediterrainelevationcanopyheightandabovegroundbiomassdensityestimatesinjapaneseartificialforests AT tomomichikato accuracyassessmentofgediterrainelevationcanopyheightandabovegroundbiomassdensityestimatesinjapaneseartificialforests AT masatohayashi accuracyassessmentofgediterrainelevationcanopyheightandabovegroundbiomassdensityestimatesinjapaneseartificialforests AT junjiefu accuracyassessmentofgediterrainelevationcanopyheightandabovegroundbiomassdensityestimatesinjapaneseartificialforests AT takuyahiroshima accuracyassessmentofgediterrainelevationcanopyheightandabovegroundbiomassdensityestimatesinjapaneseartificialforests |