Estimation of actual carbon dioxide removal in burned forests using satellite data:A case study in South Korea

With the increasing impact of climate change,carbon emissions and removals have become major issues.Forests are major carbon pools,and forest fires are an essential part of the carbon cycle.This study introduces a model for estimating the detailed actual CO_(2)removal in burned forests using burn severity and tree survivability.Actual CO_(2)removal was estimated from empirical yield tables without using the standard carbon removal provided by the national inventory.The primary CO_(2)calculation method followed the guidelines of the International Panel on Climate Change.The burn severity was mapped using Sentinel-2 multispectral instrument data,and the survivability of each forest type was estimated according to burn severity.The survivability was applied to the pre-fire CO_(2)removal of each forest to estimate post-fire CO_(2)removal.In our case study,the burned forest area was 1,034 ha,and the CO_(2)removal before the fire was 8,615.3t/year.After the fire,removal decreased by 81.2%to 1,618.4 t/yr.In particular,the decrease in coniferous forests was high,more than 86%.The lack of survivability data on burned trees was a major limitation of our study.Systematically accumulating field monitoring data of post-fire forests will be necessary for future research and could serve as a reference for devising immediate countermeasures against forest fires.

Calibrating Remotely Sensed Ocean Chlorophyll Data: An Application of the Blending Technique in Three Dimensions (3D)

In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.

Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture(Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle(UAV), and a digital elevation model(DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include Quick Bird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km2, and the volume of the landslide was 7.70 ± 1.46 million m3. The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.

Remote Sensing Multitemporal Data for Geomorphological Analysis of the Murghab Alluvial Fan in Turkmenistan

Archaeological studies are ever more landscape-oriented, in order to study archaeological evidences in relation with their territorial contexts. In such a framework, reconstruction and understanding of ancient landscapes assume a crucial role for archaeological research. This study proposes a first morphological analysis of the whole Murghab alluvial fan in Turkmenistan, by means of the SRTM-DEM datum, and then the reconstruction of the ancient hydrography in the northeastern fringe of the fan, based on medium-high geometric resolution satellite data, and in continuity with previous studies. The importance to know historical fluvial network is due to the strict relationship between fresh water availability and human settlement distribution. SRTM-DEM, Corona, Soyouz KFA, Landsat, and Aster data were used, overlaying them in a GIS, and digitizing palaeochannels through photo-interpretation were done. Today, this is an almost desert area of the fan, and that is why it is easier to recognize buried forms by means of photo-interpretation, even though sometimes in a doubtful way. Despite the uncertainties, this model provided a useful tool for next and focused archaeological field surveys and excavations, aimed to find out human settlement evidences in correlation with ancient waterways.

Ocean surface currents estimated from satellite remote sensing data based on a global hexagonal grid

Global ocean surface currents estimated from satellite derived data based on a regular global grid are affected by the grid’s shape and placement.Due to different neighbourhood relationships,the rectangular lat/lon grids lose accuracy when interpolating andfitting elevation data.Hexagonal grids have shown to be advantageous due to their isotropic,uniform neighbourhood.Considering these merits,this paper aims to estimate global ocean surface current using a global isotropic hexagonal grid from satellite remote sensing data.First,gridded satellite altimeter data and wind data with different resolutions are interpolated into the centre of the global isotropic hexagonal grid.Then,geostrophic and Ekman currents components are estimated according to the Lagerlof Ocean currents theory.Finally,the inversion results are verified.By analyzing the results,we conclude that the ocean surface currents estimated based on the global isotropic hexagonal grid have considerable accuracy,with improvement over rectangular lat/lon grids.

Remote Efects of Tropical Cyclone Wind Forcing over the Western Pacific on the Eastern Equatorial Ocean

An ocean general circulation model （OGCM） is used to demonstrate remote effects of tropical cyclone wind （TCW） forcing in the tropical Pacific. The signature of TCW forcing is explicitly extracted using a locally weighted quadratic least=squares regression （called as LOESS） method from six-hour satellite surface wind data; the extracted TCW component can then be additionally taken into account or not in ocean modeling, allowing isolation of its effects on the ocean in a clean and clear way. In this paper, seasonally varying TCW fields in year 2008 are extracted from satellite data which are prescribed as a repeated annual cycle over the western Pacific regions off the equator （poleward of 10°N/S）; two long-term OGCM experiments are performed and compared, one with the TCW forcing part included additionally and the other not. Large, persistent thermal perturbations （cooling in the mixed layer （ML） and warming in the thermocline） are induced locally in the western tropical Pacific, which are seen to spread with the mean ocean circulation pathways around the tropical basin. In particular, a remote ocean response emerges in the eastern equatorial Pacific to the prescribed off-equatorial TCW forcing, characterized by a cooling in the mixed layer and a warming in the thermocline. Heat budget analyses indicate that the vertical mixing is a dominant process responsible for the SST cooling in the eastern equatorial Pacific. Further studies are clearly needed to demonstrate the significance of these results in a coupled ocean-atmosphere modeling context.

基于不同数据源的数字孪生小流域底板模型精度检验

为解决小流域综合治理规划设计中基础地形数据获取困难等问题,基于合成孔径雷达卫星遥感影像、倾斜摄影影像、光探测测距影像等3种主流遥感数据源,分别建立栖龙湾小流域数字孪生底板模型,进而提取主沟道纵断面、2块梯田样地边界、10个林地样区的郁闭度,与人工解译和实测结果对比进行精度检验,结果表明:以光探测测距影像为数据源的提取精度最高,以倾斜摄影影像为数据源的提取精度次之,以孔径雷达卫星遥感影像为数据源的提取精度最低。鉴于3种数据源小流域底板模型各有优缺点,可根据实际工作需要进行多源数据融合,以改善数字孪生技术在小流域综合治理规划设计中的应用效果。在栖龙湾小流域内选择石坎梯田地块进行合成孔径雷达卫星遥感影像与倾斜摄影影像数据融合、选择科普展览馆进行倾斜摄影影像与光探测测距影像数据融合,均取得良好的效果。

降雨监测与预报技术在防洪减灾中的应用进展

洪水灾害突发性强,成灾速度快,对人民生命和财产安全造成较大的威胁。降雨作为洪水灾害致灾因子,数据的精确度对防洪减灾具有重要意义。以降雨监测与预报技术为切入点,对雨量站点观测、天气雷达降雨估计及预报、降雨数值预报、卫星遥感反演的现状进行了总结,通过分析时空降尺度方法及多源数据融合技术在降雨监测与预报中的应用,揭示了其在提升降雨数据“量”与“型”准确度方面的效果。研究表明:降雨监测与预报技术在当前取得了显著进展,但在山丘区和城市环境空间的复杂地形方面仍面临分辨率受到限制及精确性、时效性不足的问题。多源数据融合能提高降雨数据精度、时空覆盖能力和预测准确性,优化算法模型、融合“空-天-地”多源数据形成高分辨率预报是未来的研究方向。

区块链技术赋能卫星产业:优势、挑战与对策

作为数字货币的底层技术,区块链具有去中心化、集体维护、数据不可篡改和可追溯等特性,被认为在很多领域具有广泛的应用前景。卫星产业作为战略性新兴产业,其安全可靠、互联互通和隐私保护等需求,与区块链的核心特性天然吻合。当前区块链技术在卫星产业中的应用尚处于起步阶段,鲜有学者对区块链技术和卫星产业的集成应用进行探讨。通过系统阐述区块链技术的基本原理,对区块链技术当前在卫星产业中的研究现状进行了全面的总结。分析了区块链技术在卫星产业中最有潜力的3个应用场景,重点阐述了区块链在其中所发挥的功能和优势。提出了区块链技术应用于卫星产业需面临的挑战,并给出了解决思路,以为将来区块链技术在卫星产业中的深入应用提供参考。

乌梁素海湖冰完整生消过程的数值模拟

为探究气候变暖背景下乌梁素海湖冰的冰厚、冰温和冰物候特征的变化,利用ERA5-Land和MERRA-2再分析数据作为大气强迫场,结合多源卫星遥感反演得到的初始模拟日期,通过一维高分辨率热力学雪冰(HIGHTSI)模型模拟了2015—2016年乌梁素海湖冰的完整生消过程。结果显示:①研究期内,最大冰厚达到41.7 cm,初冰日和终冰日分别为2015年11月21日和2016年3月25日,冰期为126 d。②对于水深较浅而冬季日照充足的乌梁素海,气温是影响冰厚的主要因素,太阳辐射次之,两者的昼夜周期循环显著影响冰层的厚度和温度;当冰面有雪覆盖时,积雪的低导热和高反照率会明显削弱气温和太阳辐射对冰层的影响。③即使缺失现场观测数据,采用气象数据和遥感反演的初始模拟日期仍能准确地表征现场真实冰雪的完整演变过程。该研究可为中纬度干旱区季节性冰封浅水湖冰的计算和湖冰生消的年际变化研究奠定基础。

异构卫星遥感数据融合的水深反演模型

为探究影像分辨率和水深反演模型对异构卫星数据融合水深反演结果的影响,本文将ICESat-2激光测高数据分别与多时相Landsat 8、Sentinel-2及WorldView-3卫星数据相融合,利用对数比值模型、多波段模型、BP神经网络、支持向量机、随机森林和极限梯度提升进行水深反演。试验结果表明,影像空间分辨率对水深反演结果精度影响不显著,且综合考虑反演结果的精度和分辨率,Sentinel-2卫星数据性能最佳,同时极限梯度提升相较于其他模型的反演性能最优,其在东沙环礁试验区域的水深反演结果RMSE最优可达0.51 m。该结果对基于异构遥感卫星数据融合的近岸区域水深测量具有很好的参考价值。

EASE-Grid投影风云卫星产品地理信息写入方法

风云卫星遥感数据服务网的卫星遥感产品数据集中,风云三系列气象卫星遥感产品数据集中很多采用的是等面积可伸缩地球网格(EASE-Grid)投影方式进行处理,实际应用中对使用者具有较高的数据处理能力要求,不利于遥感产品数据集的省级应用。基于数据集使用中的这些问题,该文以FY3D雪水当量数据集产品为例,采用程序化方法对EASE-Grid投影产品数据集的地理信息进行写入,通过构建地理坐标系参考对象和地理信息目录,将数据矩阵中写入地理信息并以GeoTiff格式文件输出。结果表明,经过该方法处理过的产品数据可与矢量文件实现准确的经纬度信息的匹配,降低了数据分析处理的难度。该方法具有较好的适用性,对于EASE-Grid的三种不同的投影方式均适用,可在一定程度上提高卫星遥感产品数据集的省级科研与应用水平。

高分卫星影像遥感指数批量处理系统设计与实现

针对日益增长的高分卫星影像数据文件量和批量化计算处理其遥感指数的需求,采用交互式数据语言IDL,基于分层架构和事件驱动模型,设计和开发具有图形用户界面、不依赖ENVI软件、可跨平台独立运行的高分卫星影像遥感指数批量处理系统,实现影像读取、指数计算、数据输出的批量化、可视化、流程化处理,简化从繁芜复杂的高分影像数据文件中提取多种遥感指数的手工操作过程。在农业遥感业务中的实践应用结果表明:本系统能够稳定运行,高效地处理大批量的高分卫星影像文件,精准计算多种遥感指数,避免了传统方法存在的操作繁琐、重复劳动、频繁等待等问题,不仅极大提升了农业遥感业务的工作效率,而且对遥感数据分析处理和相关软件的开发应用也具有重要的参考意义。本系统的成功设计实现与应用,显示出了分层架构、事件驱动模型与IDL语言的结合对农业遥感领域信息系统开发和实践的有效性。

基于人工智能的多源遥感数据融合在电网勘测应用研究

随着卫星遥感、空间科技等技术的不断发展,通过卫星采集多源遥感数据已被广泛应用到诸多行业。将多源数据进行融合,生成信息更丰富、质量更高的图像,能更清晰地分析地物地貌地形情况,已成为近年来图像智能处理领域的技术研究前沿方向。文章基于人工智能卷积网络和注意力机制,提出一种统一融合网络,将不同光谱和空间属性的遥感源数据进行有效融合,生成具有精确光谱信息和清晰空间细节的高分辨率图像,为电网勘测选址选线等业务提供了辅助支撑的有效手段。实验结果表明,文章研究结果比现有典型方法具备更好的融合效果。

基于多源遥感数据的省域XCO_(2)变化与分析

利用卫星监测XCO_(2)变化已成为一种有效手段。根据2009—2021年的GOSAT卫星数据并结合夜光遥感数据、净初级生产力遥感数据,探究辽宁省近13年XCO_(2)变化趋势,获取XCO_(2)变化的影响因素及XCO_(2)变化造成的影响。研究表明,自2009年起辽宁省XCO_(2)便处于稳定增长趋势,且辽东地区XCO_(2)总体高于辽西地区;通过相关系数计算得,夜光遥感数据与GOSAT数据相关系数较高,说明人类活动与XCO_(2)变化关系密切;NPP数据与XCO_(2)相关系数较低,说明植物的固碳能力并不是影响XCO_(2)变化的主要因素。相关研究可为省域范围的大气CO_(2)排放监测与治理提供一定的决策支持。

基于卫星通导遥的AI生态大模型智能服务系统研究

文章对基于卫星通导遥的AI生态大模型智能服务系统进行了研究。该系统依托卫星数据资源构建了100亿+数字生态样本库工厂,打造了基于华为遥感处理算力、空天院遥感应用算法、无人机航空拍摄影像的多数字场景遥感大模型,重点覆盖太行山生态保护、农业示范区监测、“遥感+”金融生态信贷、期货交易预估等领域创新应用,实现了遥感数据的AI智能化加工处理,为推动卫星通导遥和信息产业的融合发展提供了有力支撑。

我国遥感卫星服务应急减灾问题分析与建议

随着航天技术的进步,国产遥感卫星已成为我国应急管理体系中不可或缺的部分。文章对国产遥感卫星在灾害响应中的需求特性进行了总结,分析了遥感卫星资源应急观测和应用服务能力,针对遥感卫星观测能力不足、协同机制不健全、产品服务不佳等问题,提出了探索民商卫星应急服务模式、多源数据综合应用、建全应急产品服务体系和数据处理智能化等方面建议,可以为相关决策以及后续卫星研制提供参考,推进我国应急减灾能力的现代化进程。

基于地理模型和多源遥感的林草生态综合监测方法——以日照市莒县为例

随着生态系统保护工作的不断推进,林草生态系统成为人们关注的重点问题。分析林草生态监测现状可确定目前林草生态监测存在的问题。针对当前林草生态综合监测过程,由于遥感图像分析能力不足,造成监测结果精度不足等问题,提出基于地理模型和多源遥感的林草生态综合监测方法。采集遥感图像,完成3D标定及预处理工作。通过纹理特征提取与支持向量机算法,对林草生态环境遥感影像进行判读。应用多源遥感技术构建地理加权回归模型,实现林草地图斑监测。将图斑带入马尔科夫矩阵模型中,获取林草生态综合变化监测结果。至此,基于地理模型和多源遥感的林草生态综合监测方法设计完成。通过实验证实,此方法的遥感图像分类精度以及监测精度均优于当前方法。

基于原型校正时空网络的多步海表面高度时空预测

海表面高度作为一项重要的海洋观测指标,对海洋生态系统和气候变化研究具有重要影响。传统基于循环神经网络(recurrent neural network,RNN)的时空序列预测模型在更新记忆状态时,存在一个关键问题:旧的记忆状态会被立即刷新,模型无法有效地保留时间序列的长期依赖关系和变化趋势。这导致在多步海洋预测中,模型无法充分挖掘时间域的重要特征,从而使预测误差随着预测步长的增加而严重累积。为解决这个问题,设计一种原型校正时空网络(prototype corrected spatiotemporal network,PCST-Net)来实现准确的端到端多步海表面高度时空预测。PCST-Net采用基于RNN的网络结构,并设计记忆状态更新(memory state update,MSU)单元作为模型的核心构建单元。MSU单元利用原型校正模块(prototype correction module,PCM)来学习海表面高度样本的原型特征,从而提取时间域中的关键信息,并校正当前时间步的海表面高度高维特征,有效缓解多步预测中的严重误差累积问题。此外,提出一种多步信息输入策略,使模型能够从更广泛的时间步长中获得更全面准确的上下文信息,进而提高预测性能。通过对热带太平洋日平均海表面高度异常(sea surface height anomaly,SSHA)数据的多步时空预测验证了所提出的模型。结果表明:PCST-Net模型对未来5 d多步SSHA时空预测的平均均方根误差、平均绝对误差和皮尔逊相关系数分别为0.634 cm、0.488 cm和0.995。研究表明,PCST-Net模型可以准确地预测SSHA的时空变化趋势,这为多步海表面高度时空预测模型提供了一种可行性方法。

基于遥感卫星的极端气象观测数据安全预警系统设计

影响极端气象产生与演变的因素众多,给极端气象的预警工作带来较大难度,为及时对极端气象作出有效防御,利用遥感卫星观测数据设计并开发了极端气象观测数据安全预警系统;设计遥感卫星观测数据校准器、观测数据采集器、处理器、安全报警器,调整通信模块的连接方式,完成安全预警系统硬件的优化;通过遥感卫星、暴雨极端天气等数据库表的构建与连接,建立系统数据库;在系统硬件和数据库的支持下,利用遥感卫星观测数据获取气象观测数据,通过气象观测数据特征的提取,估算极端气象参数,将其与设置的安全阈值进行比对,综合极端气象强度和紧迫度参数,实现系统的安全预警功能;实验结果表明,所设计系统的平均预警时间偏差为0.18 h,误警率和漏警率平均值分别为2.8%和2.7%,响应时延平均值为16.4 ms。