南海西沙海槽地区的海底热流测量

为了解南海西沙海槽区的地热特征,利用Ewing型地热探针在该区开展了地热测量,并利用TK04热导率仪测量了相关站位表层沉积物样品的热导率,获得了7个站位的热流数据。结果表明,研究区7个站位的热导率变化范围为0.88~1.06 W/m.K,平均为0.96 W/m.K,地温梯度变化范围为85~120℃/km,热流值变化范围为83~112 mW/m2,平均达到95 mW/m2。分析表明测量结果与20世纪80年代中美合作在西沙海槽的地热测量结果一致性较好,说明研究区仍具有高热流特征,推测高热流特征可能与本区高热背景、莫霍面埋深较浅、断裂发育、晚期岩浆活动和基底起伏等有关。     

温差能驱动的水下滑翔器设计与实验研究

论文设计开发了一种新型的温差能驱动的水下滑翔器,并对它做了水域实验研究。文章讨论了温差能驱动的滑翔器运动机理及其在垂直剖面的运动分析,得到稳态运动的参数解。结合能够把水域温差能转变为机械能的热机设计以及滑翔器的主要机械结构和控制硬件系统设计,完成了滑翔器的初步设计与开发。滑翔器在千岛湖进行了水域实验,实验结果表明,此水下滑翔器完全能够利用温差能实现预定的滑翔运动。     

热红外波段大气透过率和程辐射的估算方法

文中对M ONTRAN模型内嵌6种大气模式的主要特性差异进行分析,并以中纬度夏季大气模式为例,分析了主要参数(如水汽、臭氧以及气温等)对估算热红外波段大气透过率和程辐射的影响。论文最后对利用探空数据构造完整大气模式进行了研究。     

全球气候变化下南海诸岛保护优先区识别分析

全球变化下,珊瑚礁保护区是保护生物多样性、增强珊瑚礁对气候变暖抵抗力的有效方式,而维持珊瑚礁弹性是其核心内容。针对珊瑚礁最具有威胁性的热压力因子,基于南海1982—2009年卫星观测海表面温度（SST）数据和CMIP5加拿大地球系统模式CanESM2模型预估的2006—2100年南海SST数据构建热压力强度模型,从维持珊瑚礁弹性的角度识别IPCC RCP 4.5和RCP 8.5情景下南海诸岛保护优先区。结果表明：RCP 4.5和RCP 8.5情景下13%左右的南海诸岛珊瑚礁识别为保护优先区。根据热压力强度与珊瑚抵抗力及避难所关系,西沙群岛七连屿和晋卿岛近年观测与未来预估的热压力强度均比较低,在保障其服务功能的基础上建议实施完全保护;东沙群岛东沙环礁和中沙环礁排洪滩近年观测急性热压力强度较高但未来预估热压力强度较低,建议实施50%禁止利用保护;中沙群岛黄岩岛近年观测和未来预估的急性热压力强度均比较低,建议实施50%多用途保护。南沙群岛有14%左右的珊瑚礁识别为保护优先区,根据其热压力强度可实施30%~100%禁止利用保护或30%~50%多用途保护。RCP 4.5和RCP 8.5情景下的南海诸岛保护优先区及保护对策,可为维持珊瑚礁生态弹性及应对全球气候变化提供重要的参考价值。     

The thermal maturity of sedimentary basins as revealed by magnetic mineralogy

The thermal evolution of sedimentary basins is usually constrained by maturity data, which is interpreted from Rock-Eval pyrolysis and vitrinite reflectance analytical results on field or boreholes samples. However, some thermal evolution models may be inaccurate due to the use of elevated maturities measured in samples collected within an undetected metamorphic contact aureole surrounding a magmatic intrusion. In this context, we investigate the maturity and magnetic mineralogy of 16 claystone samples from Disko-Svartenhuk Basin, part of the SE Baffin Bay volcanic margin. Samples were collected within thermal contact metamorphic aureoles near magma intrusions, as well as equivalent reference samples not affected by intrusions. Rock-Eval pyrolysis (T_max), and vitrinite reflectance (Ro) analysis were performed to assess the thermal maturity, which lies in the oil window when 435°C ≤ T_max ≤ 470°C and 0.6%–0.7% ≤ Ro ≤ 1.3%. In addition, we performed low- (<300K) and high-temperature (>300K) investigations of isothermal remanent magnetization to assess the magnetic mineralogy of the selected samples. The maturity results (0.37% ≤ Ro ≤ 2%, 22°C ≤ T_max ≤ 604°C) show a predominance of immature to early mature Type III organic matter, but do not reliably identify the contact aureole when compared to the reference samples. The magnetic assemblage of the immature samples consists of iron sulphide (greigite), goethite and oxidized or non-stoichiometric magnetite. The magnetic assemblage of the early mature to mature samples consists of stoichiometric magnetite and fine-grained pyrrhotite (<1 μm). These results document the disappearance of the iron sulphide (greigite) and increase in content of magnetite during normal burial. On the other hand, magnetite is interpreted to be the dominant magnetic mineral inside the contact aureole surrounding dyke/sill intrusions where palaeotemperatures indicate mature to over-mature state. Interestingly, the iron sulphide (greigite) is still detected in the contact aureole where palaeotemperatures exceeded 130°C. Therefore, the magnetic mineralogy is a sensitive method that can characterize normal burial history, as well as identify hidden metamorphic contact aureoles where the iron sulphide greigite is present at temperatures beyond its stability field.     

Terrestrial heat flow and lithospheric thermal structure in the Chagan Depression of the Yingen-Ejinaqi Basin,north central China

The Chagan Depression in the Yingen-Ejinaqi Basin, located at the intersection of the Paleo-Asian Ocean and the Tethys Ocean domains is an important region to gain insights on terrestrial heat flow, lithospheric thermal structure and deep geodynamic processes. Here, we compute terrestrial heat flow values in the Chagan Depression using a large set of system steady-state temperature data from four representative wells and rock thermal conductivity. We also estimate the “thermal” lithospheric thickness, mantle heat flow, ratio of mantle heat flow to surface heat flow and Moho temperature to evaluate the regional tectonic framework and deep dynamics. The results show that the heat flow in the Chagan Depression ranges from 66.5 to 69.8 mW/m², with an average value of 68.3 ± 1.2 mW/m². The Chagan Depression is characterized by a thin “thermal” lithosphere, high mantle heat flow, and high Moho temperature, corresponding to the lithospheric thermal structure of “cold mantle and hot crust” type. We correlate the formation of the Yingen-Ejinaqi Basin to the Early Cretaceous and Cenozoic subduction of the western Pacific Plate and the Cenozoic multiple extrusions. Our results provide new insights into the thermal structure and dynamics of the lithospheric evolution in central China.     

高分五号热红外传感器多通道SST反演

2018-05高分五号（GF-5）卫星发射升空,其上搭载的全谱段成像仪在热红外8—13 μm谱段范围内具有4个温度反演通道（B09,B10,B11,B12）,空间分辨率设计优于40 m,在国内民用传感器领域实现了由单通道向多通道、中空间分辨率向高空间分辨率的跨越式突破,使得GF-5卫星热红外数据在地表热环境遥感领域具有极其重要应用价值。本研究基于GF-5的4个热红外通道的通道响应函数,利用全球742条TIGR（Thermodynamic Initial Guess Retrieval）探空廓线数据,进行不同观测角度、水汽含量和海表发射率条件下的MODTRAN4.0（Moderate resolution atmospheric Transmittance and Radiance code4.0)辐射传输过程模拟,基于模拟结果分别对两通道、三通道和四通道劈窗算法海表温度SST（ Sea Surface Temperature）反演系数进行修订,并分析观测角度、水汽含量和海表发射率对不同通道组合的精度影响,并通过GF-5卫星实际反演的SST结果进行验证。GF-5全谱段成像仪SST反演两通道劈窗算法组合共有6种,即B09-B10、B09-B11、B09-B12、B10-B11、B10-B12、B11-B12;三通道劈窗算法组合共有4种,即B09-B10-B11、B09-B10-B12、B09-B11-B12、B10-B11-B12;四通道劈窗算法组合1种,即B09-B10-B11-B12。通过对不同通道组合形式研究发现,水汽含量对SST反演精度有较大的影响,且温度反演的精度随着水汽含量的增加而降低;其次是观测角度,SST反演精度随着观测天顶角的增大而降低;最后是发射率的影响,两通道、三通道和四通道劈窗算法SST反演精度随着发射率的变化总体在0.1 K以内变化。最后以大亚湾核电站周围海域为验证区,用GF-5热红外遥感影像进行SST的反演并做误差分析,结果表明B09-B10通道SST反演实际误差为0.57 K,反演精度较高,实际误差与理论模拟误差相差0.24 K,差异的来源主要包括辐射定标和传感器噪声等要素影响,其他通道形式反演精度有待于传感器响应稳定后进一步验证。     

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.     

基于城市地表温度与归一化植被指数对北京市建成区热环境分析

针对研究城市热环境的过程中,利用归一化植被指数(NDVI)进行地表温度(LST)反演,再将LST和NDVI结合说明地物变迁与城市热环境的影响的现状,利用Landsat-8多时相遥感影像、高分辨率影像、公开GIS等多源数据,通过人工交互判读和量化统计分析,实现了2013—2017年北京建成区NDVI变化及其对地表热环境影响分析,再对分析结果进行差值拟合评价。对NDVI阈值分割按照大小为LC1、LC2、LC3、LC4,对LST分为高温区(TH)、常温区(TR)和低温区(TL)。结果表明,2013年至2017年:1)建成区的平均NDVI增加0.03,其中LC1增加1.0%,LC2减少11.6%,LC3区域减少1.7%,LC4区域增加12.3%。2)建成区平均LST增加2.55 K,TH百分比增加0.6%;TR百分比减少1.1%,TL百分比增加0.5%。3)NDVI相对增加,地表温度相对下降以及NDVI相对减少,地表温度相对上升占60%,NDVI相对下降,地表温度相对下降以及NDVI相对增加,地表温度相对上升的占40%。     

基于热红外图像的海面油膜面积的测算方法

针对现有油膜检测技术难以准确测算油膜面积且检测精度受天气条件影响大的问题,本文提出了一种基于热红外图像的海面油膜面积测算方法。采用波段为 8耀14 滋m 的红外热像仪获取海面油膜的热红外图像,对采集的油膜图像进行预处 理 （灰度化、中值滤波和锐化）;基于图像灰度分布特征分割油膜区域 （感兴趣区域,ROI）,采用形态学操作对 ROI 进行填充、腐蚀与膨胀,并对 ROI 进行数学表征;通过像素面积法计算 ROI 实际物理面积。实验结果表明：在不同的外界天气环境下 （如海浪、海风、海雾、不同光照等环境）,该方法对不同黏度的石油样品在海面形成的油膜均有良好的检测精度, ROI 面积计算平均误差为 3.77%。