A nonlinear unmixing method in the infrared domain.

This paper presents the physical principle of a new (to our knowledge) unmixing method to retrieve optical properties (reflectance and emissivity) and surface temperatures over a heterogeneous and a folded landscape using hyperspectral and multiangular airborne images acquired with high spatial resolution. In fact, over such a complex scene, the linear mixing model of the reflectance commonly used in the reflective domain is no longer valid in the IR range for the two following reasons: multiple reflections due to the three-dimensional (3D) structure and the radiative phenomenon introduced by the temperature by way of the black body law. Thus, to solve this nonlinear unmixing problem, a new physical model of aggregation is used. Our model requires as inputs knowledge of the 3D scene structure and the spatial contribution of each material in the scene. Each elementary scene element is characterized by its optical properties, and its temperature, spectral, and multiangular acquisitions are required. This paper focuses only on the theoretical feasibility of such a method. In addition, an analysis is conducted evaluating the impact of the misregistration between the radiometric image and its digital terrain model, estimating a threshold of the relative importance of every elementary material to retrieve its corresponding optical properties and temperature. The results show that the 3D geometry must be accurately known (accuracy of 1 m for a spatial resolution of 20 m), and the relative contribution of material in the mixed area must be above 15% to retrieve its surface temperature with an accuracy better than 1 K. So, this method is applied on three different landscapes (heterogeneous flat surface, V shape, and urban canyon), and the results exhibit performances better than 1% for optical properties and 1 K for surface temperatures.

Aggregation process of optical properties and temperature over heterogeneous surfaces in infrared domain.

We propose a modeling of the aggregation processes of optical properties and temperature over the heterogeneous landscape in the infrared domain (3-14 microm). The main objectives of the modeling are to understand how these parameters aggregate and to study their links at different spatial scales. As the landscape is described at each scale by its radiative parameters, general equations linking the radiative parameters at a given high spatial scale to those at a rough scale are proposed. Then these equations are applied to several synthetic landscapes. An analysis based on a design of experiments is conducted to point out the influence of each of the input factors. The results show the importance of the intrinsic parameters (reflectance, emissivity, and surface temperature) of each surface element and also the directional and spectral behaviors of the aggregated parameters.

Thermal infrared radiance simulation with aggregation modeling (TITAN): an infrared radiative transfer model for heterogeneous three-dimensional surface--application over urban areas.

The thermal infrared radiance simulation with aggregation modeling (TITAN) model, presented here, is an innovative transfer radiative code in the infrared domain (3-14 microm). It takes into account the three-dimensional (3D) structure of the landscape and simulates all the radiative components introduced by this 3D structure, which are due to the reflection and emission of walls and sloping roofs. Examples are given to illustrate the new opportunities offered by TITAN over urban areas. First, a phenomenological study is conducted at four wavelengths analyzing the relative effect of all the radiative contributors to the total signal. The same analysis is performed at bottom of atmosphere, which reveals an error occurring when a flat assumption is made (between 1% and 5%). In a second example, the directional effects at sensor level are simulated and show that the radiative temperature can vary by up to 10 K.