几种新型的星载多光谱和成像光谱仪

近几年出现了几种新型的星载多光谱和成像光谱仪,例如:Landsat-7卫星的有效载荷增强型主题测绘仪+（ETM+）;EOS AM-1卫星的有效载荷多角度成像光谱仪（MISR）和先进空间热发射和反射辐射计（ASTER）;特殊探测器紫外成像光谱仪（SSUSI）。文章从结构、性能参数等方面综述了这几种星载成像光谱仪。     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

Satellite-observed biological variability in the equatorial Pacific during the 2009–2011 ENSO cycle

The event of 2009–2011 El Niño Southern Oscillation (ENSO) provides an opportunity to gain insight into the biological variability of the equatorial Pacific Ocean for an entire ENSO cycle with satellite and in situ observations. Even though El Niño and La Niña in general led to respectively weakened and enhanced chlorophyll-a concentration and net primary production (NPP) along the equatorial Pacific Ocean during the 2009–2011 ENSO cycle, biological responses were highly disparate along the equator and attributed to different driving mechanisms. In the eastern equatorial Pacific east of 150°E, the El Niño-La Niña biological change was in general small except for the transition period even though sea surface temperature (SST) showed over ∼5 °C drop from El Niño to La Niña. In the central-eastern (170°W–140°W) equatorial Pacific, moderate change of biological activity is attributed to the changes of thermocline driven by the eastward propagating equatorial Kelvin waves and changes of zonal currents and undercurrents. Highest biological response in this ENSO cycle was located in the central (170°E–170°W) and central-western (150°E–170°E) equatorial Pacific with quadruple chlorophyll-a concentration and over ∼400 mg C m⁻² d⁻¹ increase of NPP from El Niño in 2009 to La Niña in 2010. However, spatial pattern of ENSO biological variability as represented with NPP is not exactly the same as chlorophyll-a variability. Wind-driving mixing of nutrients and eastward advection of the oligotrophic warm pool waters are attributed to this significant biological variability in this region.     

Experiment for mapping land cover and it’s change in southeastern Sri Lanka utilizing 250 m resolution MODIS imageries

Utilizing freely available MODIS NDVI and Natural color imageries of 250 m spatial resolution produced by NASA, an experiment was made to map land-cover and its change with an emphasis on vegetation cover in southeastern Sri Lanka, which plays a vital role for control of green house gas. For the change detection purpose, 1987 land cover map made by present authors from Landsat MSS image and extensive ground truth survey data was used as the base map. The result of the experiment shows that MODIS data are useful to make a land cover map of 250 m spatial resolution for tropical areas with high cloud coverage like Sri Lanka. It was found that the forest cover decrease amounted as large as 21% in 19 years time span in southeastern Sri Lanka, the prominent forest region of the country. On the other hand homestead/vegetation and mixed vegetation/scrub dominant categories increased by 13.7% and 7.1%, respectively. These changes are considered due to a large clearance of forest areas for agriculture and building houses to accommodate increasing inhabitants.     

Developing a dust storm detection method combining Support Vector Machine and satellite data in typical dust regions of Asia

Enhancing the dust storm detection is a key part for the environmental protection, human healthy and economic development. The goal of this paper is to propose a new Support Vector Machine (SVM)-based method to automatically detect dust storms using remote sensing data. Existing methods dealing with this problem are usually threshold-based that are of great complexity and uncertainty. In this paper we propose a simple and reliable method combining SVM with MODIS L1 data and explore the optimal band combinations used as the feature vectors of SVM. The developed method was evaluated by MODIS and OMI data qualitatively and quantitatively on three study sites located in the Arabian Desert, Gobi Desert and Taklimakan Desert, and it was also compared to three other traditional methods based on their accuracy, complexity, reliability and sensitivity to thresholds. The detection results demonstrated that the combination of (Band7 − Band3)/(Band7 + Band3) ((B7 − B3)/(B7 + B3)), Band20 − Band31 (B20 − B31), and Band31/Band32 (B31/B32) can detect the dust storms more precisely than other individual bands or their combination. The comparison among those cases indicated that the proposed automatic method exhibited an advantage of minimizing the uncertainty and complexity, which were the limits of defining thresholds based on the threshold-based methods. The conclusions can provide references for studies that focus on statistical-based dust storm detection.     

Satellite Observations of Natural and Anthropogenic Aerosol Effects on Clouds and Climate

Anthropogenic aerosols affect the climate system and the hydrological cycle. The net effect of aerosols is to cool the climate system, directly by reflecting sunlight to space, and indirectly by increasing the brightness and cover of clouds that in turn also reflect more sunlight to space. The uncertainty in the aerosol effect on climate is 5 times greater than that of the greenhouse gases. The reason for this is the short aerosol lifetime and chemical complexity, that makes it difficult to represent the global aerosol budget from surface or aircraft measurements. Satellites provide daily global information about the aerosol content, generating large statistics with excellent regional and global representation of the aerosol column concentration, and differentiating fine from coarse aerosol. Here we use observations performed with the MODIS instrument onboard the Terra and Aqua satellites to differentiate natural from anthropogenic aerosols, and to measure the aerosol effect on cloud properties and on the reflectivity of sunlight.     

基于DSP的固态功率控制器的设计

以提高某型飞机配电系统可靠性及灵活性为目的,设计了一种以DSP为控制内核,以μC/OS-Ⅱ实时嵌入式操作系统为软件平台的固态功率控制器。硬件选择上,系统主控制单元采用TI公司的DSP芯片TMS320F2808;功率开关芯片选用具有自保护功能的BTS724G,以期提高系统可靠性和降低功耗;采用ACS756电流传感器替代传统采样电阻。软件实现上,给出了详细的软件设计思路和系统程序设计。系统调试表明,设计的基于DSP的固态功率控制器很好地满足了负载通断要求,开关准确度和灵敏度比较高。     

嵌入式系统的组成、设计与调试

嵌入式系统是将先进的计算机技术、半导体技术和电子技术相结合的产物。本文介绍了嵌入式系统的组成,并针对嵌入式系统自身的特点,深入地阐述了设计和调试方面的一些关键技术。     

Sensor calibration impacts on dust detection based on MODIS and VIIRS thermal emissive bands

Dust detection using remotely sensed measurements has been one of the challenging problems encountered by atmospheric scientists. MODerate Resolution Imaging Spectroradiometer (MODIS) on the Terra (T) and Aqua (A) platforms have been a versatile sensor for well over 21 and 18 years respectively, and have been extremely useful in the retrieval of aerosol information over the entire globe. The MODIS radiances from the Level 1B in general are expected to be within 5% accuracy in the reflective wavelengths and within 1% in the thermal emissive wavelengths. In this paper, we evaluate the sensitivity of previously developed dust detection technique based on thermal emissive wavelengths, which correspond to MODIS bands 20, 29, 31, and 32 respectively. The Thermal Emissive Dust Index (TEDI) performed very comparably to the traditional Aerosol Optical Thickness (AOT) retrievals by MODIS reflective channels. Since the MODIS Thermal Emissive Bands (TEB) are well calibrated on-orbit using a BlackBody (BB) source, the calibration of these long wave infrared bands is quite robust. As A-MODIS continues to perform well beyond its designed lifetime of 6 years, the instrument has undergone various levels of degradation during its mission time. As a consequence, it is imperative to check the impacts of calibration on the higher-level retrievals. In this paper, we rigorously analyze the sensitivity of TEDI due to the impact of calibration by the afore-mentioned TEB. The perturbation of the dominant (linear) calibration term demonstrated the following: first, there was a correlation in the sensitivity of the TEDI due to the uncertainty in the linear calibration term. Based on a perturbation in the linear calibration term for all aforementioned bands over a range of ±5% yielded the TEDI sensitivity to vary from approximately ?3.2% to about ?3.6%. When considering the uncertainty in each individual band significant changes were observed. The least change was observed for the perturbation in the calibration of band 20 with the TEDI sensitivity and the largest sensitivity in TEDI was observed in the perturbation of band 31 calibration. Thus, in the case of TEDI, noticeable sensitivity due to calibration uncertainty was observed in bands 29, 31, and 32, reiterating the importance of the TEB calibration in these bands. Also, the dust detection scheme based on A-MODIS was successfully transferred to the follow-on sensors such as Suomi (SNPP) and NOAA 20 (N20) VIIRS. The results presented in this paper would be extremely helpful in understanding impacts of calibration on the higher-level products for both current and future missions based on the MODIS heritage. Finally, the work also identifies the importance of radiometric fidelity in maintaining the accuracy of the dust detection. Results presented will show drastic improvement of the Saharan dust detection after the reduction of the electronic crosstalk in the 8.5 µm channel of T-MODIS.     

Investigations of the Krasnoyarsk Reservoir waters based on the multispectral satellite data

In this work historical investigations and modern results of classification of the Krasnoyarsk Reservoir are presented. The paper presents results of studying the dynamics of phytopigments and other optically active components, using multispectral satellite data. Several approaches to interpreting satellite data for optically complex inland water bodies are offered. Based on results of historical investigations it is shown that the spatial distribution of phytoplankton in the reservoir stems back to the time of its formation. Color index in the red spectral region (CIR) is introduced. A relationship between the color index and chlorophyll concentration is investigated. The CIR, derived from the AVHRR data, has been found to be related to chlorophyll concentration. Based on MODIS data, the waters of the Krasnoyarsk Reservoir have been classified in accordance with their optical spectral variability, using the technique of unsupervised IsoData classification. An empirical relationship between multispectral MODIS data and the ground-truth measurements of chlorophyll concentration has been found.