RAPID: A Radiosity Applicable to Porous IndiviDual Objects for directional reflectance over complex vegetated scenes

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Yunnan pine shoot beetles (PSB), Tomicus yunnanensis and Tomicus minor have spread through southwestern China in the last five years, leading to millions of hectares of forest being damaged. Thus, there is an urgent need to develop an effective approach for accurate early warning and damage assessment of PSB outbreaks. Remote sensing is one of the most efficient methods for this purpose. Despite many studies existing on the mountain pine beetle (MPB), very little work has been undertaken on assessing PSB stress using remote sensing. The objective of this paper was to develop a spectral linear mixing model aided by radiative transfer (RT) and a new Yellow Index (YI) to simulate the reflectance of heterogeneous canopies containing damaged needles and quantitatively inverse their PSB stress. The YI, the fraction of dead needles, is a physically-explicit stress indicator that represents the plot shoots damage ratio (plot SDR). The major steps of this methods include: (1) LIBERTY2 was developed to simulate the reflectance of damaged needles using YI to linearly mix the green needle spectra with the dead needle spectra; (2) LIBERTY2 was coupled with the INFORM model to scale the needle spectra to the canopy scale; and (3) a look-up table (LUT) was created against Sentinel 2 (S2) imagery and inversed leaf chlorophyll content (LCC), green leaf area index (LAI) and plot SDR. The results show that (1) LIBERTY2 effectively simulated the reflectance spectral values on infested needles (mean relative error (MRE) = 1.4-18%), and the YI can indicate the degrees of needles damage; (2) the coupled LIBERTY2-INFORM model is suitable to estimate LAI (R 2 = 0.73, RMSE = 0.17 m m −2 , NRMSE = 11.41% and the index of agreement (IOA) = 0.92) and LCC (R 2 = 0.49, RMSE = 56.24 mg m −2 , NRMSE = 25.22% and IOA = 0.72), and is better than the original LIBERTY model (LAI: R 2 = 0.38, RMSE = 0.43 m m −2 , NRMSE = 28.85% and IOA = 0.68; LCC: R 2 = 0.34, RMSE = 76.44 mg m −2 , NRMSE = 34.23% and IOA = 0.57); and (3) the inversed YI is positively correlated with the measured plot SDR (R 2 = 0.40, RMSE = 0.15). We conclude that the LIBERTY2 model improved the reflectance simulation accuracy of both the needles and canopies, making it suitable for assessing PSB stress. The YI has the potential to assess PSB damage.

Section: Lcc Lai and Plot Shoots Damage Ratio Estimation (Sdr) Perfmentioning

confidence: 99%

Detection of Shoot Beetle Stress on Yunnan Pine Forest Using a Coupled LIBERTY2-INFORM Simulation

Qiu

Huang

et al. 2018

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“…A forward dataset generated by the RAPID model was used to examine the precision of the estimated effective emissivity and to explore the performance of the inversion algorithm. The RAPID model is a novel computer graphics-based radiosity model applicable to porous individual thin objects [26]. In the GCI algorithm, the sources of error in the retrieved results were mainly from the clumping index and the LAI.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…This algorithm was evaluated against both simulated and measured surface temperatures over several small-scale scenes. We selected a novel radiosity model, i.e., radiosity applicable to porous individual objects (RAPID) proposed by Huang et al [26], as the benchmark for forward simulations. The measured dataset was collected by the wide-angle infrared dual mode line/area array scanner (WIDAS) sensor over orchard, maize and wheat canopies.…”

Section: Introductionmentioning

confidence: 99%

A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index

Bian

Cao

et al. 2017

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Abstract:The inversion of land surface component temperatures is an essential source of information for mapping heat fluxes and the angular normalization of thermal infrared (TIR) observations. Leaf and soil temperatures can be retrieved using multiple-view-angle TIR observations. In a satellite-scale pixel, the clumping effect of vegetation is usually present, but it is not completely considered during the inversion process. Therefore, we introduced a simple inversion procedure that uses gap frequency with a clumping index (GCI) for leaf and soil temperatures over both crop and forest canopies. Simulated datasets corresponding to turbid vegetation, regularly planted crops and randomly distributed forest were generated using a radiosity model and were used to test the proposed inversion algorithm. The results indicated that the GCI algorithm performed well for both crop and forest canopies, with root mean squared errors of less than 1.0 • C against simulated values. The proposed inversion algorithm was also validated using measured datasets over orchard, maize and wheat canopies. Similar results were achieved, demonstrating that using the clumping index can improve inversion results. In all evaluations, we recommend using the GCI algorithm as a foundation for future satellite-based applications due to its straightforward form and robust performance for both crop and forest canopies using the vegetation clumping index.

“…To simulate the combined effects of heterogeneous terrain and complex vegetation composition on MODIS or MISR BRDF products, RT models are expected to contend with a domain (or scene) size greater than 0.5 km. Although many 3D models may simulate such a large scene, there are very few that are specifically optimized to cope RAPID is a radiosity-based model using computer graphics methods to compute RT within and above 3D vegetated scenes from visible/near infrared (VNIR, 0.47-2.5 µm) [16] to thermal infrared (TIR, 8-14 µm) [32], and microwave (MV, 2.5-30 cm) parts [33] of the electromagnetic spectrum [16,33].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the faster version RAPID3 is developed in this paper to specifically accelerate the simulation for km-scale scenes. A typical 3D forest scene defined in RAPID [16]; each tree is represented by porous crowns, solid stems and soil polygons; each crown is composed of a few porous objects, which look similar to planar objects but will be dynamically projected into sub-leaves during runtime.…”

Section: Introductionmentioning

confidence: 99%

Accelerated RAPID Model Using Heterogeneous Porous Objects

Huang

2018

Self Cite

Abstract:To enhance the capability of three-dimensional (3D) radiative transfer models at the kilometer scale (km-scale), the radiosity applicable to porous individual objects (RAPID) model has been upgraded to RAPID3. The major innovation is that the homogeneous porous object concept (HOMOBJ) used for a tree crown scale is extended to a heterogeneous porous object (HETOBJ) for a forest plot scale. Correspondingly, the radiosity-graphics-combined method has been extended from HOMOBJ to HETOBJ, including the random dynamic projection algorithm, the updated modules of view factors, the single scattering estimation, the multiple scattering solutions, and the bidirectional reflectance factor (BRF) calculations. Five cases of the third radiation transfer model intercomparison (RAMI-3) have been used to verify RAPID3 by the RAMI-3 online checker. Seven scenes with different degrees of topography (valleys and hills) at 500 m size have also been simulated. Using a personal computer (CPU 2.5 GHz, memory 4 GB), the computation time of BRF at 500 m is only approximately 13 min per scene. The mean root mean square error is 0.015. RAPID3 simulated the enhanced contrast of BRF between backward and forward directions due to topography. RAPID3 has been integrated into the free RAPID platform, which should be very useful for the remote sensing community. In addition, the HETOBJ concept may also be useful for the speedup of ray tracing models.