Tiangang Yin

DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence

To better understand the life-essential cycles and processes of our planet and to further develop remote sensing (RS) technology, there is an increasing need for models that simulate the radiative budget (RB) and RS acquisitions of urban and natural landscapes using physical approaches and considering the three-dimensional (3-D) architecture of Earth surfaces. Discrete anisotropic radiative transfer (DART) is one of the most comprehensive physically based 3-D models of Earth-atmosphere radiative transfer, covering the spectral domain from ultraviolet to thermal infrared wavelengths. It simulates the optical 3-D RB and optical signals of proximal, aerial, and satellite imaging spectrometers and laser scanners, for any urban and/or natural landscapes and for any experimental and instrumental configurations. It is freely available for research and teaching activities. In this paper, we briefly introduce DART theory and present recent advances in simulated sensors (LiDAR and cameras with finite field of view) and modeling mechanisms (atmosphere, specular reflectance with polarization and chlorophyll fluorescence). A case study demonstrating a novel application of DART to investigate urban landscapes is also presented.

Simulating satellite waveform Lidar with DART model

DART model was extended for simulating satellite Lidar data of 3D Earth scenes with Monte Carlo based methods. 2 major modeling methods were developed. (1) Monte Carlo method for efficiently handling complex phase functions: once scattering directions with close occurrence probabilities are grouped within classes, a 1st random pulling gives the class of scattering directions, and a 2nd random pulling gives the scattering direction within the class. (2) A so-called RayCarlo method combines the classical Monte Carlo forward photon tracing method and the flux tracking method, which allows one to decrease computer time of classical Monte Carlo method by factors that can reach 108. Simulation results are very encouraging. Validation tests are being conducted.

Lidar radiative transfer modeling in the Atmosphere

DART model was extended for simulating satellite lidar signal of Earth-Atmosphere systems. The adopted approach combines Monte Carlo and flux tracking methods. It improves a lot signal to noise ratios of simulated waveforms. For accurate simulation of atmosphere photon tracing, the atmosphere modelling was modified for obtaining continuous vertical distribution of extinction coefficients. It leads to a much better accuracy than the use of atmosphere layers with constant extinction coefficients. This improvement is valid with any type of atmosphere, exponential or not.

Atmospheric correction of ground-based thermal infrared camera through dart model

We introduced an approach to simulate and separate atmospheric contribution in ground-based thermal-infrared (TIR) camera measurements. Different from the traditional approach which uses the look-up table built from 1-D radiative transfer model (RTM), this approach directly simulates 3-D ray propagations and interactions in the heterogeneous urban environment by using the Discrete Anisotropic Radiative Transfer (DART) model. The atmospheric turbid cells that occupy every part of the urban scene are created using the vertical constituent distribution and the optical property profiles in the existing databases or from the actual meteorological measurements. The two components of atmospheric effects on the TIR at-sensor radiance are attenuated transmission and path thermal emission. Taking both into account, the at-surface radiance corresponding to the signal emitted only from the urban surface can be derived.

Recent advances of modeling lidar data using dart and radiometric calibration coefficient from LVIS waveforms comparison

The fast development of the light detection and ranging (LiDAR) technique, especially with scanning and multi-beam systems that launch pulses along different directions, requires efficient and accurate simulation tools to analyze existing data and to design future systems. This work presents the recent advantages of the discrete anisotropic radiative transfer (DART) model in LiDAR data simulation. A more comprehensive comparison between DART-simulated waveforms and Laser Vegetation Imaging Sensor (LVIS) over Howland forest, Maine is presented. Results show that in addition to waveform shape simulation, radiometric calibration coefficients could be inferred from the comparison. This new discovery could provide an approach for possible radiometric modeling of LiDAR data, that convert the digital number of the waveform into actual energy.

Dart: Radiative Transfer modeling for simulating terrain, airborne and satellite spectroradiometer and LIDAR acquisitions and 3D radiative budget of natural and urban landscapes

The need of better accuracy for analyzing remote sensing (RS) data of complex Earth surfaces explains the increasing need of models that simulate RS data with physical approaches. Similarly, the study of Earth surfaces functioning requires physical models that simulate the 3D radiative budget (RB) of these surfaces. DART (Discrete Anisotropic Radiative Transfer is one of the most comprehensive physically based 3D models that model the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It simulates optical signals at the entrance of terrain/airborne/satellite imaging radiometers and laser scanners, as well as the 3D RB, of urban/natural landscapes for any experimental and instrumental configurations. Its licenses are free for research and teaching activities. Here, we present its major recent advances.

DAta simulation and fusion of imaging spectrometer and LiDAR multi-sensor system through dart model

Multi-sensor systems are increasingly demanding in recent remote sensing (RS) applications. Combination of LiDAR and imaging spectrometers is an emerging technique used by several recent airborne systems. The combined data provide both functional and structural information, which makes this technique a unique tool for understanding and management of the Earths ecosystems. The rapid development of this technique demands the simulation and validation of the combined data. In this paper, we introduce a new method to simulate data fusion of multi-sensor system which combined LiDAR and imaging spectrometer, with any experimental, instrumental, and geometrical configurations of systems. This method is implemented in the latest release of discrete anisotropic radiative transfer (DART) model.

Modeling specular reflectance and polarization in DART model for simulating remote sensing images of natural and urban landscapes

The need of better accuracy to analyze remote sensing (RS) data and radiative budget (RB) of Earth surfaces explains the demand of physical models of RS and RB data. DART (Discrete Anisotropic Radiative Transfer) model is probably the most comprehensive three-dimensional (3D) physical model. Indeed, with original ray tracking and Monte Carlo methods for tracking radiation in the Earth and atmosphere from visible to thermal infrared wavelengths, it simulates the 3D RB and acquisitions of terrain / RS imaging radiometers and laser scanners, for any urban / natural landscape and any experimental / instrumental configuration. Paul Sabatier delivers free licenses for research and teaching activities. After introducing DART theory, we present recent advances: simulation of LiDAR and airborne sensors, and modeling of specular interaction and polarization.

Remote Sensing Studies of Urban Canopies: 3D Radiative Transfer Modeling

Need for better understanding and more accurate estimation of radiative fluxes in urban environments, specifically urban surface albedo and exitance, motivates development of new remote sensing and three‐dimensional (3D) radiative transfer (RT) modeling methods. The discrete anisotropic radiative transfer (DART) model, one of the most comprehensive physically based 3D models simulating Earth/atmosphere radiation interactions, was used in combination with satellite data (e.g., Landsat‐8 observa‐ tions) to better parameterize the radiative budget components of cities, such as Basel in Switzerland. After presenting DART and its recent RT modeling functions, we present a methodological concept for estimating urban fluxes using any satellite image data.

Direction discretization for radiative transfer modeling: An introduction to the new direction model of dart

Many radiative transfer (RT) models combine exact kernel and discrete ordinate techniques for solving the transport equation. They discretize the 4π space into a finite number of angular sectors, with directions along which radiation propagates. They can be more or fewer and equally spaced or not. RT model improvement is usually focused on 3D landscapes simulation and RT mathematical modeling. The angular variable Ω discretization is a much less addressed problem, although it can strongly influence the simulation of satellite signals, especially with small numbers of discrete directions. Here, we present a new Ω discretization that improves the accuracy of simulated result.