Estimation of canopy cover in dense mixed-species forests using airborne lidar data
Airborne laser scanning (ALS) data and digital hemispherical photos (DHP) from 93 sample plots in Laeva test site, Estonia, were used to study effects of phenology and scan angle on the ALS-based canopy cover (CCALS) estimates. The relative share of first returns (P1/A) for 6185 forest stands was an...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2018-01-01
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| Series: | European Journal of Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/22797254.2017.1411169 |
| _version_ | 1818252482428534784 |
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| author | Tauri Arumäe Mait Lang |
| author_facet | Tauri Arumäe Mait Lang |
| author_sort | Tauri Arumäe |
| collection | DOAJ |
| description | Airborne laser scanning (ALS) data and digital hemispherical photos (DHP) from 93 sample plots in Laeva test site, Estonia, were used to study effects of phenology and scan angle on the ALS-based canopy cover (CCALS) estimates. The relative share of first returns (P1/A) for 6185 forest stands was analysed. The CCALS was calculated using different height thresholds and echoes, and was compared with the CC estimates based on DHP (CCDHP) and crown model (CCRCrown). The first of many echoes-based canopy cover estimate (CCALS,1.3_1) saturated at values greater than 80%. The strongest correlation of CCDHP was found with CCALS,1.3_A using all echoes and a 1.3 m height break (R2 = 0.81, RMSE = 11.8%). Correcting the estimate for view nadir angle did not improve the correlation of CCALS,1.3_A with CCDHP. The CCRCrown had a weak correlation (R2 < 0.25) with CCALS and with CCDHP. The P1/A was not influenced by tree species composition, but by phenology, stand relative density and forest height; however, CCALS was not dependent on stand height. Foliage phenology had a substantial effect on CCALS and CCDHP. In dense mixed-species forests, we recommend to use all returns for canopy cover estimation. |
| first_indexed | 2024-12-12T16:24:53Z |
| format | Article |
| id | doaj.art-18dc085058a045e09006cfd14eae6955 |
| institution | Directory Open Access Journal |
| issn | 2279-7254 |
| language | English |
| last_indexed | 2024-12-12T16:24:53Z |
| publishDate | 2018-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | European Journal of Remote Sensing |
| spelling | doaj.art-18dc085058a045e09006cfd14eae69552022-12-22T00:18:53ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542018-01-0151113214110.1080/22797254.2017.14111691411169Estimation of canopy cover in dense mixed-species forests using airborne lidar dataTauri Arumäe0Mait Lang1Estonian University of Life SciencesEstonian University of Life SciencesAirborne laser scanning (ALS) data and digital hemispherical photos (DHP) from 93 sample plots in Laeva test site, Estonia, were used to study effects of phenology and scan angle on the ALS-based canopy cover (CCALS) estimates. The relative share of first returns (P1/A) for 6185 forest stands was analysed. The CCALS was calculated using different height thresholds and echoes, and was compared with the CC estimates based on DHP (CCDHP) and crown model (CCRCrown). The first of many echoes-based canopy cover estimate (CCALS,1.3_1) saturated at values greater than 80%. The strongest correlation of CCDHP was found with CCALS,1.3_A using all echoes and a 1.3 m height break (R2 = 0.81, RMSE = 11.8%). Correcting the estimate for view nadir angle did not improve the correlation of CCALS,1.3_A with CCDHP. The CCRCrown had a weak correlation (R2 < 0.25) with CCALS and with CCDHP. The P1/A was not influenced by tree species composition, but by phenology, stand relative density and forest height; however, CCALS was not dependent on stand height. Foliage phenology had a substantial effect on CCALS and CCDHP. In dense mixed-species forests, we recommend to use all returns for canopy cover estimation.http://dx.doi.org/10.1080/22797254.2017.1411169Airborne lidar datacanopy covertree crown modelslive crown base heightphenology |
| spellingShingle | Tauri Arumäe Mait Lang Estimation of canopy cover in dense mixed-species forests using airborne lidar data European Journal of Remote Sensing Airborne lidar data canopy cover tree crown models live crown base height phenology |
| title | Estimation of canopy cover in dense mixed-species forests using airborne lidar data |
| title_full | Estimation of canopy cover in dense mixed-species forests using airborne lidar data |
| title_fullStr | Estimation of canopy cover in dense mixed-species forests using airborne lidar data |
| title_full_unstemmed | Estimation of canopy cover in dense mixed-species forests using airborne lidar data |
| title_short | Estimation of canopy cover in dense mixed-species forests using airborne lidar data |
| title_sort | estimation of canopy cover in dense mixed species forests using airborne lidar data |
| topic | Airborne lidar data canopy cover tree crown models live crown base height phenology |
| url | http://dx.doi.org/10.1080/22797254.2017.1411169 |
| work_keys_str_mv | AT tauriarumae estimationofcanopycoverindensemixedspeciesforestsusingairbornelidardata AT maitlang estimationofcanopycoverindensemixedspeciesforestsusingairbornelidardata |