Abstract

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 configuration (surface and atmosphere conditions, sun direction, etc.) are commonly translated into qualitative and quantitative Earth surface parameters. However, atmosphere properties and Earth surface 3D architecture often confound their interpretation. Radiative transfer models capable of simulating the Earth and atmosphere complexity are, therefore, ideal tools for linking remotely sensed data to the surface parameters. Still, many existing models are oversimplifying the Earth-atmosphere system interactions and their parameterization of sensor specifications is often neglected or poorly considered. The Discrete Anisotropic Radiative Transfer (DART) model is one of the most comprehensive physically based 3D models simulating the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It has been developed since 1992. It models optical signals at the entrance of imaging radiometers and laser scanners on board of satellites and airplanes, as well as the 3D radiative budget, of urban and natural landscapes for any experimental configuration and instrumental specification. It is freely distributed for research and teaching activities. This paper presents DART physical bases and its latest functionality for simulating imaging spectroscopy of natural and urban landscapes with atmosphere, including the perspective projection of airborne acquisitions and LIght Detection And Ranging (LIDAR) waveform and photon counting signals.

Highlights

  • Remote sensing (RS) observations facilitate global studies of the land surface and biophysical properties of vegetation

  • The objective of this paper is to present the latest advances in Discrete Anisotropic Radiative Transfer (DART) (DART 5 version) modeling of airborne and satellite IS as well as LIght Detection And Ranging (LIDAR) data of architecturally complex natural and urban landscapes

  • During more than 20 years of development, DART has reached the stage of a reference Radiative transfer (RT) model in the field of optical RS

Read more

Summary

Introduction

Remote sensing (RS) observations facilitate global studies of the land surface and biophysical properties of vegetation (e.g., leaf biomass, soil moisture). Spectroscopy (IS) and LIght Detection and Ranging (LIDAR) RS techniques that are mapping the Earth landscapes from the visible to the thermal infrared spectral domains (between 0.3 μm and 50 μm). Imaging spectroradiometers measure fluxes (radiance) as two-dimensional (2D) arrays (images). Radiance fluxes can be transformed into landscape reflectance (ratio of reflected and incident radiation) of visible (VIS) and near infrared (NIR) wavelengths, and into landscape brightness temperature TB in the case of thermal infrared (TIR) acquisitions. LIDAR sensors use a laser beam as a photon source and measure the travel time between the laser pulse emission and its reflected return to calculate the range (distance) to the objects encountered by the emitted pulse. The combination of range measurements with knowledge of platform location and attitude provides a three-dimensional (3D)

Objectives
Methods
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call