Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes
To improve the simulation accuracy of vegetation canopy reflectance in optical bands, the Radiosity Applicable to Porous IndiviDual objects (RAPID) model has been upgraded to better deal with branches in the latest RAPID4. Previous versions of RAPID (RAPID1 and RAPID3) neglected branches in porous o...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
American Association for the Advancement of Science (AAAS)
2023-01-01
|
Series: | Journal of Remote Sensing |
Online Access: | https://spj.science.org/doi/10.34133/remotesensing.0039 |
_version_ | 1797837496820695040 |
---|---|
author | Huaguo Huang Jianbo Qi Linyuan Li |
author_facet | Huaguo Huang Jianbo Qi Linyuan Li |
author_sort | Huaguo Huang |
collection | DOAJ |
description | To improve the simulation accuracy of vegetation canopy reflectance in optical bands, the Radiosity Applicable to Porous IndiviDual objects (RAPID) model has been upgraded to better deal with branches in the latest RAPID4. Previous versions of RAPID (RAPID1 and RAPID3) neglected branches in porous objects in optical bands, while RAPID2 emphasized them in microwave bands. This inconsistency needed to be addressed to establish a unified radiosity-based simulation framework. By incorporating branches in RAPID4, we have improved several aspects of the model, including the random dynamic projection process, the equivalent reflectance or transmittance, the single scattering estimation, the multiple scattering solution, and the bidirectional reflectance factor (BRF) calculation. Three-dimensional trees from the fifth RAdiation transfer Model Intercomparison (RAMI-V) have been used to test the contribution of branches on BRF. Comparisons with a ray-tracing-based LESS model (the LargE-Scale remote sensing data and image Simulation framework) on RAMI-V scenes show a general agreement on BRF (R2 ≥ 0.96 and root mean square error ranging from 0.014 to 0.054). The major biases occur in a realistic scene (i.e., HET51_WWO_TLS) created from terrestrial laser scanning data. Sensitivity analysis has been conducted to show the branch contribution on BRF in optical domain. Without considering dense branches, the BRF error can exceed 0.1. |
first_indexed | 2024-04-09T15:26:44Z |
format | Article |
id | doaj.art-415c831dc3564de784cea51087d96c3a |
institution | Directory Open Access Journal |
issn | 2694-1589 |
language | English |
last_indexed | 2024-04-09T15:26:44Z |
publishDate | 2023-01-01 |
publisher | American Association for the Advancement of Science (AAAS) |
record_format | Article |
series | Journal of Remote Sensing |
spelling | doaj.art-415c831dc3564de784cea51087d96c3a2023-04-28T16:06:44ZengAmerican Association for the Advancement of Science (AAAS)Journal of Remote Sensing2694-15892023-01-01310.34133/remotesensing.0039Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI ScenesHuaguo Huang0Jianbo Qi1Linyuan Li2State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing 100083, People’s Republic of China.State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing 100083, People’s Republic of China.State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing 100083, People’s Republic of China.To improve the simulation accuracy of vegetation canopy reflectance in optical bands, the Radiosity Applicable to Porous IndiviDual objects (RAPID) model has been upgraded to better deal with branches in the latest RAPID4. Previous versions of RAPID (RAPID1 and RAPID3) neglected branches in porous objects in optical bands, while RAPID2 emphasized them in microwave bands. This inconsistency needed to be addressed to establish a unified radiosity-based simulation framework. By incorporating branches in RAPID4, we have improved several aspects of the model, including the random dynamic projection process, the equivalent reflectance or transmittance, the single scattering estimation, the multiple scattering solution, and the bidirectional reflectance factor (BRF) calculation. Three-dimensional trees from the fifth RAdiation transfer Model Intercomparison (RAMI-V) have been used to test the contribution of branches on BRF. Comparisons with a ray-tracing-based LESS model (the LargE-Scale remote sensing data and image Simulation framework) on RAMI-V scenes show a general agreement on BRF (R2 ≥ 0.96 and root mean square error ranging from 0.014 to 0.054). The major biases occur in a realistic scene (i.e., HET51_WWO_TLS) created from terrestrial laser scanning data. Sensitivity analysis has been conducted to show the branch contribution on BRF in optical domain. Without considering dense branches, the BRF error can exceed 0.1.https://spj.science.org/doi/10.34133/remotesensing.0039 |
spellingShingle | Huaguo Huang Jianbo Qi Linyuan Li Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes Journal of Remote Sensing |
title | Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes |
title_full | Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes |
title_fullStr | Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes |
title_full_unstemmed | Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes |
title_short | Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes |
title_sort | enhanced branch simulation to improve rapid in optical region using rami scenes |
url | https://spj.science.org/doi/10.34133/remotesensing.0039 |
work_keys_str_mv | AT huaguohuang enhancedbranchsimulationtoimproverapidinopticalregionusingramiscenes AT jianboqi enhancedbranchsimulationtoimproverapidinopticalregionusingramiscenes AT linyuanli enhancedbranchsimulationtoimproverapidinopticalregionusingramiscenes |