In desert steppe regions with sparse vegetation, there are discrepancies between vertical and oblique observations made by satellite-based sensors. In this study, we developed and deployed an online multiangle spectrometer in the desert steppe area of Inner Mongolia, China, to calibrate satellite-based vegetation indices. One of the key components of the device is a specially designed quarter-arc iron track that holds fixed view angles of 30°, 45°, 60°, 75° and 90° are fixed. These observation positions equipped with high-efficiency multichannel sensors can capture the reflectance of ground objects at visible and near-infrared wavelengths. Real-time experiments were conducted with multiple observation angles and an error-based view angle correction model was constructed to reconcile the differences between angular and vertical observations. The calculated results were subsequently applied to the bias-correction process of the Sentinel-2 vegetation index. Across all view angles, the daily distributions of the Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) exhibited a U-shaped pattern with the nadir occurring at noon. Among the data, RVI demonstrated superior overall stability compared to NDVI. However, with vegetation growth, the NDVI showed less sensitivity, resulting in a decrease in its coefficient of variation (CV) from 32.3% to 18.2%. To correct the bias in Sentinel-2 products, we initially applied path length correction (PLC) to eliminate the topographic influence on the Band4 and Band8 band reflectance. Our findings revealed that Band8 performed better than Band4 in mitigating the effects of topography, as evidenced by a decrease in the determination coefficient from 0.448 to 0.09. Additionally, we corrected the view angle error of the NDVI of Sentinel-2 by constructing a view angle correction model (R2=0.84, RMSE=0.03). The corrected images exhibited significant variation characteristics in areas with relatively large view angles. The results of this study provide valuable scientific support for the correction of satellite image products and the accurate detection of vegetation through remote sensing in regions with low vegetation coverage.

Model checking is considered one of the most practical applications of theoretical computer science in the verification of concurrent systems, and model checking tools are very important for such applications. This paper presents the model checking tool VERDS with the theoretical background, basic functionalities and modeling techniques with various examples. In particular, the tool includes an implementation of a bounded correctness checking approach which can be seen as an extension of bounded model checking and complementary to the traditional symbolic model checking. VERDS is also flexible for extension. We show how it is extended to handle discrete time models. We carry out case-studies of a kind of task scheduling problems, in which time specification is essential. The experimental results show that VERDS is not only feasible for solving practical problems but also with good performance in solving such problems.

Polarized light has been studied over the past four decades as a useful signal to enhance the information from a variety of remote sensing applications. In the measurement process, the Stokes parameters are usually used to describe the state of polarization of light reflected from target surfaces. However, there is no research concerning the influence of extinction of the polarizer on the polarization properties derived from the Stokes parameters when we perform the polarimetric measurements of target surfaces using a spectrometer. In this paper, we measured the Stokes parameters of six natural surfaces (two soil samples, three vegetation covers, and a single leaf) and two man-made targets over a wide range of viewing directions at different incident zenith angles in the laboratory under two measurement conditions: considering and without considering the extinction of the polarizer. The comparison of these measured results indicated that the extinction of the polarizer, which was taken from the Spectralon panel, decreased the I parameter and the bidirectional polarized reflectance factor of all the samples. Moreover, it is safe to use the I parameter to represent the total reflected intensity of all our samples when we considered the extinction of the polarizer. Thus, the polarimetric measurements of target surfaces can not only give us the polarization information but also provide a reliable intensity signal.