Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

DMSP-OLS与NPP-VIIRS夜间灯光遥感影像数据整合

DMSP-OLS夜间灯光遥感数据截至2013年,现已被NPP-VIIRS夜间灯光数据取代。因此,要获得长时间序列且稳定的夜间灯光数据集,需要整合两类夜间灯光数据。基于此,本文提出了基于重采样的两类数据整合方法,对2013—2020年NPP-VIIRS数据进行模拟,最终建立了1992—2020年长时间序列校正—模拟DMSP-OLS夜光遥感数据集。结果表明,基于重采样的整合方法效果良好(城市区域Pearson相关系数ρ=0.9852,RMSE=3.4607),整合数据集与相关社会经济参考量高度契合(影像DN值总和与GDP的相关系数ρ=0.946,与人口的相关系数ρ=0.971,二次多项式模型拟合R²≈0.98,RMSE<5.55),优于已有研究。因此,利用该方法整合后的数据集能更好地支撑基于夜间灯光影像的长时间序列研究。     

最佳小波包基的矿区植被及红边位置提取

小波包变换能同时对植被光谱信息的低频和高频分量进行分解,并能克服小波变换时间分辨率高而频率分辨率低的缺陷从而具有能够探测植被细微变化的优势。实验利用Hyperion高光谱影像对云南省普朗铜矿区植被像元的光谱进行最佳小波包基参量获取与植被信息识别,并在此基础上提出一种提取重金属污染下植被红边位置的最佳小波包基系数应用模型。研究结果表明基于最佳小波包基参量的植被信息识别及基于最佳小波包基系数的重金属污染探测具有可行性与一定优越性。     

高分辨率遥感影像滤波算法综述

高分辨率卫星影像空间分辨率高,地物结构纹理信息突出,常用于土地利用监测、自然灾害预报等领域,但其所含的背景噪声影响了影像识别和分析的有效性和可靠性,因此,选取合适的滤波方法消除各种噪声成为遥感影像处理的首要任务。在遥感技术发展的几十年中,研究者们针对各种噪声类型已发展了多种滤波方法。本文分析了高分辨率遥感影像噪声的特点,介绍了一些传统的滤波算法和近年来广泛应用的新型滤波方法,并深入探讨各种滤波器的性能及其优缺点,为今后选择合适的算法消除高分辨率遥感影像噪声提供参考,最后对遥感影像滤波方法的发展前景进行了展望。     

地理国情监测在城市化发展中的应用研究——以汕头市为例

开展地理国情监测工作的目的是为了获取自然与人类社会经济活动引起的地表变化信息,为政府、企业和公众提供地理国情信息服务。城市化发展、变迁是地理国情监测的重要应用方面之一,本文以广东省汕头市为例,基于遥感技术（ RS）,利用多时相影像数据提取不同时期建成区变化信息,并有针对性地对比分析,直观反映了汕头市三十多年的城市化发展的特点和进展情况。     

MODIS MAIAC高分辨率气溶胶光学厚度产品在干旱区的适用性研究

The Multiangle Implementation of Atmospheric Correction (MAIAC) is a new generic algorithm applied to MODIS measurements to retrieve Aerosol Optical Depth (AOD) over land at high spatial resolution (1 km). It is expected to have good potential in improving the AOD inversion of dark and bright surfaces of land. The high spatial resolution of the MAIAC retrievals enhances the capability to distinguish aerosol sources and determine subtle aerosol features. Retrieval of satellite aerosol properties is therefore often challenging due to considerable seasonal variations in surface reflectance and aerosol properties. To date, MAIAC AOD over arid regions under data-scarce environments has been evaluated. Considering these uncertainties, a systematic effort was made to evaluate the MAIAC AOD over arid areas using Aerosol Robotic Network (AERONET) ground-based AOD from 2000 to 2019. Considerable MAIAC-AERONET AOD matchups demonstrate the capability of MAIAC to retrieve AOD over varied ground surfaces and temporal scales. We employed a broader perspective and evaluated MAIAC performance under varying aerosol loading, aerosol types, surface coverage, and viewing geometry. The results show that (1) MAIAC performed well over various temporal scales, including monthly, seasonal and annual scales. Although underestimation is prevalent, MAIAC AOD in the spring and winter months correspond to the highest and lowest retrieval accuracies, respectively. (2) MAIAC performed well over four different typical land surface land surfaces, showing the highest retrieval accuracy over grassland, yet it slightly overestimated AOD. Construction land is most affected by the aerosol model, and farmland is strongly disturbed by surface reflectance and underestimated most obviously (Below EE = 46.5%). (3) The accuracies of the MAIAC AOD observations of Terra and Aqua are similar; R2 is more than 0.75, but both are underestimated, especially for Aqua. In general, MAIAC’s ability to provide AOD at high spatial resolution appears promising over arid areas and is expected to be helpful to study the characteristics of fine aerosols in arid areas and promote the study of local air quality. © 2023 Science Press. All rights reserved.     

北极海域SAR海浪方向谱反演及其与中法海洋卫星CFOSAT/SWIM数据的比较

The interaction between ocean waves and sea ice in the Arctic ocean has received significant attention. However, the study on this issue is significantly limited due to the lack of observation data. Synthetic Aperture Radar (SAR) plays an important role in the research of ocean wave and sea-ice interaction because of its unique capability of imaging sea surface in two dimensions. Sentinel-1 (S1), which consists of Sentinel-1A (S1A) and Sentine-1B (S1B), can cover the entire Arctic Area within 2 days. The Interferometric Wide Swath (IW) mode, one of the main imaging modes of S1 in the Arctic, has been providing SAR images with a high resolution of 10 m. The ocean wave spectra are derived using the S1 IW data. The spectra are likely to provide vital observation for studying the interaction between sea-ice and waves as they present the distribution of wave energy and their variations in different frequencies and directions. Meanwhile, the retrieved ocean wave spectra are an excellent validation data source for SWIM, which is onboard the China-France Oceanography Satellite and provides measurements of ocean wave spectra in the global ocean.In this study, we use the sub-images from the S1 IW image with a size of 1024 pixels × 1024 pixels (10.24 km × 10.24 km) to retrieve ocean wave spectra by using a nonlinear retrieval method (i.e., MPI scheme). The retrieved ocean wave spectra and wave parameters are compared with SWIM measurements acquired at an incidence angle of 10°, and the Significant Wave Height (SWH) is measured at nadir. The SWIM spectrum covers a large area by approximately 70 km × 90 km. To make a comparison, all the SAR sub-image spectra within a SWIM beam coverage are averaged to calculate a new observed SAR spectrum, which is inputted into the MPI inversion scheme. Then, the retrieved SAR ocean wave spectrum is compared with the SWIM spectrum. The footprint size of the SWIM nadir beam is 18 km, which is comparable to the S1 sub-image size. Accordingly, a SAR sub-image is extracted at SWIM nadir, and the corresponding ocean wave spectrum is retrieved. The SWH is calculated by integrating the retrieved wave spectra to compare with the SWIM nadir measurements of SWH. The experiment was carried out using the data acquired in September 2020 in the Greenland Sea and Norwegian Sea, where the ocean waves generated in the North Atlantic and propagating vast distances to the ice-covered area in the Arctic ocean can be frequently observed. Fifty-four ocean wave spectra were retrieved from 25 IW data and are compared with the SWIM slope spectra. The comparison shows that the SAR-retrieved spectra are consistent with SWIM spectra in terms of structure and energy distribution. Good agreements are also found between the integral parameters of the SAR ocean wave spectra and SWIM slope spectra. The comparison yields a bias and an RMSE of 0.11 and 0.71 m for SWH and a bias and an RMSE of -0.52 s and 0.62 s for mean wave period. The comparison of the dominant wave parameters yield a bias of -7.74° and an RMSE of 15.75° for the dominant wave direction and a bias of -0.56 m and an RMSE of 52.73 m for the dominant wavelength. Furthermore, 5075 data pairs of S1-retrieved SWH and SWIM nadir SWH were collocated and compared. The comparison result yields a bias of 0.03 m, an RMSE of 0.48 m, and a correlation of 0.95. The comparison between the S1 retrieved results and the SWIM measurements suggests that ocean wave information can be effectively retrieved from S1 IW data by using the MPI method in the Arctic ocean. Although the MPI method relies on prior information, it is still an effective method for obtaining ocean wave spectra in high resolution. The spectra retrieved from S1 are likely to show the energy attenuation of ocean waves in different frequencies and directions when propagating toward an ice-covered area. This finding will be of great support for the further study on the interaction between sea ice and ocean waves. © 2023 National Remote Sensing Bulletin. All rights reserved.     

利用稀疏分解的高分辨率遥感图像线状特征检测

目的 线状特征检测是利用遥感数据开展地物目标自动识别的重要步骤。利用高分辨率遥感图像的高度细节化特点,针对现有线状特征检测方法存在的问题,提出了一种基于稀疏分解的高分辨率遥感图像线状特征检测方法。采用 K-SVD字典学习算法获取线状特征表达所需的过完备字典,基于稀疏分解模型,从高分辨率遥感图像中分离出高频成分,实现遥感图像线状特征的初步检测;用曲波分层自适应阈值法对分离后的高频成分作降噪处理,以提高线状特征检测的效果。利用 QuickBird图像进行实验的结果显示,该方法在线段连续性、低对比度线段检测与椒盐噪声消除方面均有一定优势。     

一种基于GEO星间链路的导航系统时间同步新体制

设计提出了一种时间同步新体制即在GEO卫星上放置高精度氢钟并在GEO卫星间建立高精度星间链路以进行高精度时间维持利用两种方案进行了仿真比较研究 仿真结果表明本文提出的方案切实可行可以显著提升时间同步精度尤其是自主时间同步精度并得出了时间同步精度与星间链路精度和星载钟的精度关系 仿真结果表明星载钟精度对新体制时间同步精度的影响相对于星间链路精度的影响较小.     

利用方向纹理特征从影像上搜索道路中心线

针对遥感影像道路中心线提取问题,提出利用方向纹理特征辅助道路中心线匹配搜索的思想,以人工给出的道路种子点和初始搜索方向为基础,运用方向纹理特征直接从遥感影像上匹配搜索道路的中心线。算法通过预测道路的宽度、弯曲等情况来自动调整纹理窗口的大小,因而能够很好地搜索到道路中心线,此外算法针对树木遮挡、车辆压盖设计了相应的处理策略。实验表明:该方法对遥感影像上不同类型道路均有很好的提取效果,且提取效率高于现有的道路提取算法。