Reliable time series of vegetation optical properties are needed to improve the modeling of the terrestrial carbon budget with remote sensing data. This paper describes the development of an automatic spectral system able to collect continuous long-term in-field spectral measurements of spectral down-welling and surface reflected irradiance. The paper addresses the development of the system, named hyperspectral irradiometer (HSI), describes its optical design, the acquisition, and processing operations. Measurements gathered on a vegetated surface by the HSI are shown, discussed and compared with experimental outcomes with independent instruments.

Recent investigations have induced relevant advancements of imaging interferometry, which is becoming a viable option for Earth remote sensing. Various research programs have chosen the Sagnac configuration for new imaging interferometers. Due to the growing diffusion of this technique, we have developed a self-contained theory for describing the signal produced by triangular FTSs and its optimal processing. We investigate the relevant disadvantages of multiplexing, and compare dispersive with FTS instruments. The paper addresses some methods for correcting the phase error, and the non-unitary transformation performed by a Sagnac interferometer. The effect of noise on spectral estimations is discussed.

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We discuss the appearance of systematic spatial and spectral patterns of noise in remotely sensed images as well as the possibility of mitigating the effects of these patterns on the data. We describe the structure of two simple theoretical models that predict the appearance of patterns of noise (mainly stripe noise). Moreover, two new algorithms that have been specifically developed to mitigate the noise patterns are described. The performance of the two algorithms is assessed by use of some hyperspectral images acquired by different kinds of airborne sensor. The algorithms show an unexpected ability to reject these noise patterns.