Verification and recalibration of HY-2A microwave radiometer brightness temperature

HY-2A is the first one of the Chinese HY-2 ocean satellite series carrying a microwave radiometer(RM)to measure sea surface temperature,sea surface wind speed,atmospheric water vapor,cloud liquid water content,and rain rate.We verified the RM level 1B brightness temperature(T B)to retrieve environmental parameters.In the verification,TB that simulated using the ocean-atmosphere radiative transfer model(RTM)was used as a reference.The total bias and total standard deviation(SD)of the RM level 1B TB,with reference to the RTM simulation,ranged-20.6-4.38 K and 0.7-2.93 K,respectively.We found that both the total bias and the total SD depend on the frequency and polarization,although the values for ascending and descending passes are different.In addition,substantial seasonal variation of the bias was found at all channels.The verification results indicate the RM has some problems regarding calibration,e.g.,correction of antenna spillover and antenna physical emission,especially for the 18.7-GHz channel.Based on error analyses,a statistical recalibration algorithm was designed and recalibration was performed for the RM level 1B TB.Validation of the recalibrated TB indicated that the quality of the recalibrated RM level 1B TB was improved significantly.The bias of the recalibrated T B at all channels was reduced to<0.4 K,seasonal variation was almost eradicated,and SD was diminished(i.e.,the SD of the 18.7-GHz channel was reduced by more than 0.5K).     

"资源一号"02C卫星影像土地利用变化检测能力分析

“资源一号”02C卫星自成功发射以来,被广泛应用于土地资源、矿产资源、地质环境调查,以及国土资源、地质灾害应急监测等应用领域。“资源一号”02C卫星是一颗填补我国高分辨率遥感数据空白的卫星,是根据国土资源主体业务需求定制的第一颗国产高分辨率业务卫星。本文以吉林省和浙江省某试验区“资源一号”02C卫星数据为例,对“资源一号”02C卫星数据融合影像进行了土地利用遥感监测变化信息检测能力的方法试验。根据试验区数据变化信息提取试验结果,对“资源一号”02C卫星影像在土地利用动态遥感监测中的变化检测能力和适用性开展了试验、分析和评价工作。     

加权整体最小二乘EIV模型与算法——与"加权整体最小二乘EIO模型与算法"一文的讨论

加权整体最小二乘方法是一种能同时顾及EIV（errors-in-variables）模型中系数矩阵和观测向量误差的参数估计方法。根据不同的应用场景,EIV模型则表现出不同的结构特征。"加权整体最小二乘EIO模型与算法"一文采用EIO模型处理EIV模型中的结构化问题^*。为了将其与现有方法进行对比,本文罗列出4种处理EIV模型结构特征的方法,并归纳了8种参数估计公式。同时从精度评定的角度讨论了整体最小二乘解的一阶及更高阶精度近似评定方法。需要强调的是,针对EIV模型及其参数估计理论可以从函数模型、随机模型和参数估计方法3个方面展开研究,但各方法殊途同归。     

A density-based approach for detecting network-constrained clusters in spatial point events

Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future.     

Temporal and Spatial Dynamics Analysis of Grassland Ecosystem Pressure in Kazakhstan

Affected by climate change and policy factors, Kazakhstan is the country with the most severe ecological degradation and grassland conflicts in Central Asia. Therefore, studying the state of grassland carrying resources in Kazakhstan is particularly important for understanding the responses of grassland ecosystems to climate change and human activities. Based on Kazakhstan's remote sensing data and animal husbandry statistics, this study analyzes the patterns of changes in grassland ecosystems in Kazakhstan based on the supply and consumption of these ecosystems. The results show that: 1) From 2003 to 2017, the number of livestock raised in Kazakhstan showed a trend of sustained and steady growth. Due to freezing damage, the scale of livestock farming decreased in 2011, but a spatial difference in the livestock farming structure was not obvious. 2) The fluctuation of grassland supply in Kazakhstan has increased, while the consumption due to animal husbandry has also continued to increase, resulting in an increasing pressure on the grassland carrying capacity. 3) Between 2003 and 2017, the overall grassland carrying status of Kazakhstan have been abundant, but the grassland carrying pressure index has shown a steadily increasing trend, the grassland carrying pressure is growing, and it is mainly determined by grassland productivity. The greater pressure in lower Kyzylorda state, the southern Kazakhstan state of the cultivated land and the northern Kazakhstan state has gradually expanded to include the agro-pastoral zone and the semi-desert zone.     

140kaBP以来南海西南部上升流影响区沉积记录及其古海洋环境变化

对南海西南部现代上升流区沉积物柱样BIS-187-61孔有机碳、生物蛋白石、碳酸盐等各沉积组分进行了详细的分析,试图探讨末次间冰期(MIS 5)以来南海西南部夏季上升流影响区沉积过程及其所反映的海洋环境变化过程。研究结果发现,140kaBP以来该孔沉积记录期总体表现为:碳酸盐百分含量冰期低间冰期高,主要受周边陆源物质输入稀释的控制,为典型的"大西洋型碳酸盐旋回",有机碳、生物蛋白石、碳酸钙以及陆源沉积物的堆积速率均在MIS 2期、MIS 4期和MIS 5e期出现高值。其中,MIS 2期和MIS 4期生源和陆源沉积堆积速率增加可能与冰期时冬季风增强及海平面下降导致陆源营养物质输入增加对初级生产力的刺激有关,也可能与陆源物质输入增加对海洋生源颗粒物输出的压载作用增强有关。而MIS 5e期南海海平面高度与现代相仿,间冰期较强的夏季风引起的越南沿岸上升流增强是导致该时段本研究区域表层初级生产力增强,沉积物总堆积速率及各组分堆积速率都相应增加的主要原因。     

耦合土地利用回归与人口加权模型的PM2.5暴露风险评估

PM_2.5已成为人群健康的重要威胁之一,科学精准的暴露评估是PM_2.5风险防控的前提,为提升PM_2.5暴露精准评估,本文利用土地利用数据、道路数据、气象数据等构建PM_2.5土地利用回归反演模型,实现了2013年12月1日-2014年2月8日（冬季）广佛都市区PM_2.5时空动态演变监测,在此基础上将PM_2.5反演结果与人口密度数据耦合,分别从PM_2.5污染浓度与人口加权PM_2.5浓度2个方面,评估广佛都市区PM_2.5污染暴露风险。研究结果表明：① 土地利用回归模型能够较好的反映研究区域内PM_2.5的空间分布特征,R²大于0.78;② 2013年12月1日-2014年2月8日,广佛都市区PM_2.5浓度平均值呈现波动变化趋势,研究时段内,最高平均浓度为97.91 μg/m³ （12月29日-1月11日）,最低平均浓度为53.40 μg/m³ （1月26日-2月8日）,全时段PM_2.5浓度超WHO健康标准的面积占比达99.8%;③ 广佛都市区PM_2.5的空间分布具有异质性规律,其高值区分别位于广州市天河区、越秀区、番禺区北部、花都区北部及佛山市禅城区、南海区中部、三水区中部,低值区主要位于广州市白云区、番禺区东南部及佛山市顺德区南部。人口加权暴露风险存在2个高值中心,分别位于广州市和佛山市的主城区;④ 耦合人口加权模型前后,广佛都市区PM_2.5暴露风险高风险区空间分布发生变化,未考虑人口加权模型时,广佛深高值区较为分散,主要位于南海区、天河区、越秀区、禅城区,考虑人口加权模型后,高值区更加集中于广州市和佛山市的主城区。     

捷联式海洋重力数据的小波阈值滤波

基于捷联式海洋重力测量数据,对比不同小波、阈值及施加方式对滤波效果的影响。结果表明,db6、db7、db8、db9、db10、sym6、sym7、sym8、sym9、sym10、coif3、coif4和coif5小波较适用于海洋重力测量,小波分解层次可取至8层或9层,采用史坦无偏风险阈值滤波效果较好;小波分解至第8、9层时,阈值滤波结果与截止频率为0.005 Hz和0.003 3 Hz的Butterworth低通滤波器的滤波结果吻合较好,但小波阈值滤波结果更加平滑,两者差值的RMSE在0.25 mGal以内,且小波阈值滤波更容易分解出噪声成分,可以更有效地消除重力畸变。     

基于TCP-InSAR的采动区铁路动态沉降监测与时序分析

为高效获取采动区长时间序列形变,监控煤炭开采对矿区铁路的影响,研究一种基于TCP-InSAR(temporarily coherent point interferometric synthetic aperture radar)的采动区铁路形变监测方法。该方法根据时间序列SAR影像间的相干性,选取临时相干点构建Delaunay三角网,并通过离群值探测去除具有相位模糊度的TCP间的弧段,最后采用最小二乘解算得到区域地表变形。实验使用2016-10～2017-04时间段内的15景Sentinel-1A数据,利用TCP-InSAR技术获得某矿区的铁路形变。结果表明,受采动影响,该时间段内铁路最大下沉值为95mm,最大倾斜坡度为0.37‰。利用TCP-InSAR技术可实现采动区内铁路长时间的动态形变监测。     

GRACE时变信号恢复方法对比分析

针对利用GRACE重力数据反演地表质量变化过程中产生的时变信号削弱和泄露现象,分别采用尺度因子法和迭代恢复法对信号进行恢复,并选用CSR Mascon产品从时间序列变化和空间分布两个角度对两种恢复方法的效果进行对比分析。结果表明:1)尺度因子法虽实现上较为简单,但其计算结果完全依赖于所选的先验模型,当所选模型的可靠性较差时,会影响到GRACE反演结果的可靠性。2)迭代恢复法的恢复过程仅受GRACE原始观测值的约束,能较好地恢复研究区域的长期趋势信号和周期信号,但在部分区域可能存在信号过量恢复的现象。建议采用迭代恢复法进行GRACE时变信号恢复。