Tiangang Yin

• PhD
• Researcher at NASA Goddard Space Flight Center / University of Maryland

Light Detection And Ranging (LiDAR) devices are increasingly used to provide data on Earth’s landscapes structures and atmosphere constituents. Their developments, especially with scanning and multi-beam systems require accurate modeling tools to analyze existing data and to design future systems. A few radiative transfer models (RTMs) can simulate...

Comparison of actual and simulated remotely sensed data is difficult since simulated data are not realistic in terms of both radiometry and geometry. This paper presents a modeling approach that considers the multi-directional acquisition within sensor field of view (FOV) in order to simulate realistic images of Earth surfaces, as acquired by passi...

In radiative transfer modeling, the angular variable Ω discretization can strongly influence the radiative transfer simulation, especially with small numbers of discrete directions. Most radiative transfer models use discrete ordinate method or finite volume method for solving the transport equation. Both of the methods have their own algorithms to...

Satellite and airborne optical sensors are increasingly used by scientists, and policy makers, and managers for studying and managing forests, agriculture crops, and urban areas. Their data acquired with given instrumental specifications (spectral resolution, viewing direction, sensor field-of-view, etc.) and for a specific experimental configurati...

Submission Website: https://www.mdpi.com/journal/remotesensing/special_issues/3AOYBN74YJ Dear Colleagues, Quantitative remote sensing has revolutionized the way we monitor and manage agricultural landscapes and vegetation. With advancements in sensor technology, data processing, and modelling techniques, remote sensing offers unprecedented opport...

Advances in artificial intelligence (AI) and Earth observation (EO) have transformed urban studies. This paper provides a commentary on how the AI-EO integration offers advancements in urban studies and applications. We conclude that AI will provide a deeper interpretation and autonomous identification of urban issues and the creation of customized...

Urban landscapes are highly heterogeneous but possess recurrent, distinguishable features known as urban landscape types, which exhibit distinct social and environmental performance, and collectively form an urban landscape typology (ULT). ULT is useful as they can aid decision-making in urban planning, predicting the impact of various development...

Coarse spatial resolution of Thermal Infrared (TIR) satellites hampers measuring the temperature and emissivity of scene elements from space that improves our understanding of land surfaces' thermal behavior. The stringent conditions of current TIR unmixing methods hinder the production of extensive component temperature and emissivity products. To...

We integrate the time series simulation capability of the maize model within Extended L-system (ELSYS) using the growth equations from a 4D maize and a leaf breakpoint model. These models simulate maize growth from emergence to male anthesis, accounting for 3D architecture during the vegetative season. We employ two methods to achieve time series s...

Airborne Light Detection And Ranging (LiDAR) data often suffer from noisy returns hovering in empty space within the collected 3D point clouds. This can be attributed to system-induced factors, such as timing jitter and range walk error, or instantaneous air conditions, such as smoke, rain, clouds, etc. These floating points are indeed outliers, wh...

Unmanned Aerial Vehicle (UAV) based hyperspectral imaging offers a flexible method for monitoring urban trees. However, its effect on estimating biochemical and biophysical parameters is still unknown. This study examines how spatial and spectral resolution, solar zenith angle (SZA), and diffuse solar irradiance (SKYL) affect chlorophyll content (C...

The demand for accurate airborne LiDAR point cloud classification has increased with improved resolutions of land cover map products. Although existing deep learning-based methods are capable of classifying airborne LiDAR point clouds, these methods indeed have a limited capability to extract the local features and suffer from global and local info...

As a powerful tool for simulating bi-directional reflectance and radiative transfer (RT) in complex canopies, the radiosity graphics model (RGM) suffers from a reduced runtime speed or even crashes when facing considerable computation load of the view factor for fine-grained simulation of heterogeneous canopy. In this work, the RGM model at pixel s...

The capability of spaceborne stereogrammetry using very high-resolution (VHR, <2 m) imagery with various environmental, experimental, and sensor configurations for characterizing forest canopy surfaces has not been completely explored. Existing archives of VHR imagery include a limited subset of potential stereo image acquisition configurations and...

The 2-band enhanced vegetation index (EVI2) was developed as an alternative to the enhanced vegetation index (EVI) for sensors that lack a blue band or for observing bright targets such as thick clouds, snow, and ice. However, research has indicated that EVI2 exhibits inconsistencies with the EVI when applied to non-moderate-resolution imaging spec...

Recent studies have demonstrated the potential of using bidirectional reflectance distribution function (BRDF) signatures captured by multi-angle observation data to enhance land cover classification and retrieve vegetation architectures. Considering the diversity of crop architectures, we proposed that crop mapping precision may be enhanced by usi...

The three-dimensional (3D) geometry of cities greatly influences their radiation regime and, consequently, their temperature. However, current remote sensing algorithms often treat urban pixels as Lambertian planes. 3D radiative transfer models such as DART that simulate the radiative budget as well as sensor images of cities (short and long waves)...

Heat released from the energy consumption in buildings (QB) is an important component of anthropogenic heat, which is a major contribution to the urban heat island (UHI) phenomenon. However, it is still a challenge to integrate all the available data to improve the estimation of QB due to inconsistences among multiple data sources. This paper prese...

Optical canopy models that connect land surface properties and satellite observed radiance must be validated before being used. These models include bi-directional reflectance distribution function (BRDF) models in the visible and near infrared domains, and directional brightness temperature (DBT) models in the thermal infrared domain. Near-surface...

With the recent progresses in lidar technology for Earth remote sensing, the development of a reliable lidar simulator is becoming central in order to define specifications for new sensors, perform inter-comparisons, train machine learning algorithms and help transferring information from one scale to another. The Discrete Anisotropic Radiative Tra...

Heat released from the energy consumption in buildings (QB) is an important component of anthropogenic heat, which is a major contribution to the urban heat island (UHI) phenomenon. However, it is still a challenge to integrate all the available data to improve the estimation of QB due to inconsistencies among multiple data sources. This paper pres...

Recent advances in instruments and retrieval methods enable measurements of solar-induced chlorophyll fluorescence (SIF) across a wide range of scales. Radiative transfer (RT) models for simulating scattering and (re-)absorption of SIF provide a powerful tool to study the upscaling of SIF signal from leaf level to terrestrial ecosystems. Based on t...

Light Detection And Ranging (LiDAR) is a developed technology that has been widely used to measure the Earth's surface by acquiring accurate three-dimensional (3D) information. LiDAR radiative transfer (RT) models provide physical-based simulation tools for interpreting LiDAR signal and estimating surface characteristics by model inversion. DART (D...

Light Detection And Ranging (LiDAR) remote sensing is increasingly needed to assess the 3D architecture of Earth's surface. Physically-based LiDAR radiative transfer (RT) models are essential tools for interpreting LiDAR signals, designing LiDAR systems, and validating information retrieval methods. Discrete Anisotropic Radiative Transfer (DART) is...

Current thermal infrared satellite images are full of mixed pixels. This work is a quantitative analysis, based on radiative transfer modelling, of the distribution of mixed pixels and their impact on the use of TES. TES was applied to radiance images of the cities of Basel and Heraklion simulated at different spatial resolutions by the DART radiat...

Airborne laser scanning (ALS) has been widely used to map gap probability and leaf area index (LAI) distribution at plot and landscape scales. As an indirect measurement, most ALS methods to estimate LAI combine waveform or point density information with supporting field measurements such as the leaf angle distribution, gap probability, or direct L...

Although remote sensing (RS) of solar-induced chlorophyll fluorescence (SIF) is increasingly used as a valuable source of information about vegetation photosynthetic activity, the RS SIF observations are significantly influenced by canopy-specific structural features (i.e., canopy architecture including leaf area index and presence of woody compone...

Solar-induced fluorescence (SIF) is a subtle but informative optical signal of vegetation photosynthesis. Remotely sensed SIF integrates environmental, physiological and structural changes that alter photosynthesis at leaf, plant and canopy scales. Radiative transfer models are ideally suited to investigate the complex sources of variability in the...

DART calibration is an iterative inversion method that is applied to shortwave (SW) satellite images to get maps of spectral signatures (SS) of city materials at the satellite spatial resolution. Therefore, it is potentially a handy spectral unmixing tool. However, up to now, it has only been validated by comparing the time series of SW radiative b...

The microclimatic conditions of the urban environment influence significantly the thermal comfort of human beings. One of the main human biometeorology parameters of thermal comfort is the Mean Radiant Temperature (Tmrt), which quantifies effective radiative flux reaching a human body. Simulation tools have proven useful to analyze the radiative be...

Saturation effects limit the application of vegetation indices (VIs) in dense vegetation areas. The possibility to mitigate them by adopting a negative soil adjustment factor X is addressed. Two leaf area index (LAI) data sets are analyzed using the Google Earth Engine (GEE) for validation. The first one is derived from observations of MODerate res...

The fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where th...

In response to the comment on our paper “High‐resolution, multilayer modeling of Singapore's urban climate incorporating local climate zones,” we provide detailed response to each of the incorrect accusations with scientifically based evidence. We have evaluated our model using all the available observational data, and the results showed good agree...

Remote sensing (RS) dedicated to the study of land surfaces benefits from more and more advanced sensors. However, the interpretation of RS data is often is often inaccurate due to the complexity of the observed land surfaces. Therefore, RS models, in particular physical models, that simulate RS observations of the three-dimensional (3D) landscapes...

Field measurements of leaf area density (LAD) and leaf area index (LAI) for individual trees have increased in importance and relevance with the advent of high spatial resolution remote sensing for the urban landscape. However, indirect field measurements of LAD/LAI for widely dispersed individual trees have not been comprehensively evaluated. The...

Radiative transfer models (RTMs) of vegetation canopies can be applied for the retrieval of numerical values of vegetation properties from satellite data. For such retrieval, it is necessary first to apply atmospheric correction to translate the top-of-atmosphere (TOA) satellite data into top-of-canopy (TOC) values. This atmospheric correction typi...

Methods to retrieve urban surface temperature (Ts) from remote sensing observations with sub-building scale resolution are developed using the Discrete Anisotropic Radiative Transfer (DART, Gastellu-Etchegorry et al., 2012) model. Corrections account for the emission and absorption of radiation by air between the surface and instrument (atmospheric...

Airborne lidar point clouds of vegetation capture the 3-D distribution of its scattering elements, including leaves, branches, and ground features. Assessing the contribution from vegetation to the lidar point clouds requires an understanding of the physical interactions between the emitted laser pulses and their targets. Most of the current method...

Three-dimensional (3D) radiative transfer models are the most accurate remote sensing models. However, presently the application of 3D models to heterogeneous Earth scenes is a computationally intensive task. A common approach to reduce computation time is abstracting the landscape elements into simpler geometries (e.g., ellipsoid), which, however,...

Increased urbanization and climate change have resulted in the intensification of the urban heat island (UHI) effect, particularly in tropical cities. One of the main causes of UHI is the man-made urban surfaces influencing the radiation budget by absorbing, reflecting, and emitting radiation at various wavelengths. The radiative budget of a city i...

We applied Weather Research and Forecasting (WRF) model's Multilayer Urban Canopy Model (MLUCM) to simulate the urban climate of Singapore during a hot period in April 2016. The high‐resolution local climate zone (LCZ) map was used as urban land use/land cover data in order to study the intraurban variability in different LCZ classes. The LCZ map f...

The anisotropic scattering behavior of land surface is characterized by its bidirectional reflectance-distribution function (BRDF). However, a physically consistent BRDF definition is still lacking for heterogeneous and rugged terrain that accounts for approximately 24% of Earth's land surface. In this study, we revisited current BRDF definitions a...

Three-dimensional (3D) radiative transfer modeling of the transport and interaction of radiation through earth surfaces is challenging due to the complexity of the landscapes as well as the intensive computational cost of 3D radiative transfer simulations. To reduce computation time, current models work with schematic landscapes or with small-scale...

Abstract We applied Weather Research and Forecasting (WRF) model’s Multilayer Urban Canopy Model (MLUCM), including Building Effect Parameterization and Building Energy Model (BEP-BEM) schemes, to simulate the urban climate of Singapore during April 2016, when a series of heat wave events occurred. The absence of high-resolution urban landscape da...

Topographic effects on canopy reflectance play a pivotal role in the retrieval of surface biophysical variables over rugged terrain. In this paper, we proposed a new canopy anisotropic reflectance model for discrete forests, Geometric Optical and Mutual Shadowing and Scattering-from-Arbitrarily-Inclined-Leaves model coupled with Topography (GOSAILT...

Urban geometry and materials combine to create complex spatial, temporal and directional patterns of longwave infrared (LWIR) radiation. Effective anisotropy (or directional variability) of thermal radiance causes remote sensing (RS) derived urban surface temperatures to vary with RS view angles. Here a new and novel method to resolve effective the...

The advantage of using remote sensing data in urban climatology study is to obtain simultaneous synoptic view of the full urban surface. Remotely-sensed data can be utilized to derive important parameters for numerical models to improve model's prediction accuracy. One such example is the local climate zone (LCZ) proposed by Stewart and Oke (2012),...

A semi-empirical multilayer urban canopy model is developed to estimate the vertical dispersion of traffic emissions in high density urban areas. It is motivated by the heterogeneity of urban morphology in real urban cities and the need of quick urban design and planning. The urban canopy is divided into multiple layers, to include the impact of bu...

Canopy radiation and scattering signals contain abundant vegetation information. Many biophysical parameters can be quantitatively retrieved with the help of canopy radiation and scattering models. Joint simulation of three-dimensional (3-D) models for multiband that combines the advantages of different spectral (frequency) domains could be a usefu...

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 Ear...

The 3D distribution of plant material is a key parameter to describe vegetation structure, which influences several processes such as radiation interception and ecosystem functioning. Vegetation covers are often described using Leaf Area Index (LAI) or Plant Area Index (PAI) for monitoring or modeling purposes. Characterizing vegetation 3D structur...

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...

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 Radia...

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 method...

Sentinel-2 (S2) earth observation satellite mission, launched in 2015, is foreseen to promote within-field decisions in Precision Agriculture (PA) for both: (1) optimizing crop production; and (2) regulating environmental impacts. In this second scope, a set of Leaf Area Index (LAI) derived from S2 type time-series (2006-2010, using Formosat-2 sate...

In the frame of the H2020 project, URBANFLUXES (http://urbanfluxes.eu/), new modeling is developed to improve the efficiency of the study of urban canopies with remote sensing, with the modeling of satellite and in- situ acquisitions (reflectance, albedo, brightness temperature), and also 3D radiative and energy budgets. The 3D radiative transfer m...

Physically-based radiative transfer modeling is the key to remote sensing of forest ecosystems. To scale spectral information from the leaf to the sensor level, the canopy architecture of a forest, illumination conditions and the viewing geometry have to be taken into account. Therefore, a new airborne image simulation approach is being developed f...

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 cla...

Nowadays, several optical space-borne systems with high resolution, high temporal revisit frequency and constant viewing angles are preparing to be be launched: Venμs, Sentinel-2, etc. The usefulness of these data will be limited due to for instance cloud coverage over the scene. Image fusion techniques with other satellite products of even higher...

A DART based data processing chain was developed for assessing the potential of a high spatial resolution geostationary satellite. It simulates time series of TOA and BOA radiance values and their spatial variability at any satellite spatial resolution, for any experimental, instrumental and view configuration (e.g., geosynchronous orbit). Account...

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 lands...

Lusi is a mud volcano in East Java, Indonesia, which started its eruption on 29th May 2006 and never stopped. To study this volcano, we used SAR interferometry with ALOS/Palsar satellite images from 2006 to 2010. By creation of a set of interferograms, and suppression of unwanted components, such as Earth curvature and elevation, we were able to co...

On September 30th, 2009, a major earthquake of magnitude 7.6 occurred near the west coast of Sumatra close to the city of Padang. On October 1st a significant aftershock (magnitude 6.6) occurred 270 km away. The casualties are estimated at 1200. This earthquake comes at a time when seismic activity in the region is particularly high. The purpose of...

Baseline calibration is needed in most of SAR interferometry processing. An iterative optimization of baseline with constrain of relative platform position is presented in this paper. The SAR passes which gives inaccurate platform position is successfully detected and calibrated using this algorithm. After processing, new estimated baseline improve...