区域性森林大火的真正成因

森林大火真正起因于地球排气中易燃还原性气体在腐殖层的临界积聚(气体体积分数大约为5%~6%)。现场气体(H2,CO)系统测量结果证实了这一点。测量结果显示,该林区腐殖层中H2、CO质量分数分别为(10~170)×10-6(本底值为0·5×10-6)和(2~60)×10-6(本底值为0·5×10-6),二者均远高于大气本底值数十到数百倍,而且未燃区的测值显然高于1998年燃区。     

Stream formation in W Serpentis-type binaries

By the method proposed by Nazarenko (1993) and using observational data obtained by different authors, the physical conditions in the stream in the neighbourhood of the inner Lagrangian point L₁ were calculated for three interacting binary systems of W Ser-type: β Lyr, V367 Cyg, RY Sct. It is shown, that as a result of the evolutional expansion of the mass losing component the deep layers of its atmosphere reach the neighbourhood of the first Lagrangian point L₁ and a stream of axial symmetric shape is formed. Its radius is comparable to the dimension of the mass losing component. The rate of the mass transfer increases up to 10⁻⁵ M_⊙/yr. The calculated parameters of the stream in the neighbourhood of the point L₁ explain the main observational properties of the investigated systems (existence of extended circumstellar matter with a developed structure, high mass transfer rate).     

基于对等网络技术的气象数据共享服务应用

气象数据共享业务广泛采用了单一资料源向各个目标节点分发的方式,针对这种共享业务的特点,设计并实现了一种基于对等网络技术的气象数据共享应用,提供资料源的共享发布以及节点间的共享访问功能。该应用通过搭建的仿真平台模拟实际业务应用,验证了在全国气象宽带网络上实现共享传输的可行性。在随后的小范围业务试验中进一步证明了该应用能够在特定的业务场景中不增加中心节点资源消耗而提升数据共享的传输效率。     

BDS-3新频点信号双频精密单点定位精度分析

北斗卫星导航系统(BeiDou navigation satellite System, BDS)已于2020年7月正式建成并开通, 北斗三号(BDS-3)在旧信号B1I和B3I的基础上, 增加了B1C、B2a新信号. 为了全面评估BDS-3的新信号B1C、B2a的定位性能, 试验了GPS (Global Positioning System)、BDS-3、BDS-2/BDS-3新旧信号的定位性能和BDS系统不同频点与GPS组合定位性能, 对BDS (B1I+B3I、B1C/B2a)+GPS (L1+L2)组合静态PPP (Precise Point Positioning)定位性能进行分析, 并与单卫星系统对比分析. 试验结果表明: BDS-3 (B1C/B2a)在East (E)、\lk North (N)、Up (U)方向的定位精度优于1.25cm、0.89cm、1.67cm, BDS-3新旧频点在E、N方向上定位精度与GPS L1/L2在同一水平上, U方向上新频点定位精度高于GPS L1/L2和BDS-3旧频点, 较旧频点定位精度提升了34.2%, 新频点收敛时间25.9min比旧频点提升了12.7%; 相较于BDS、GPS单系统, 组合系统BDS/GPS定位精度和收敛时间有了明显的提高, BDS-3 (B1C/B2a)+GPS在E、N方向上与BDS-3 (B1I/B3I)+GPS定位精度相当, 在U方向上定位精度前者较后者有了明显的提升, 提升了17.2%, 组合系统新频点收敛时间20.1min比旧频点提升了17.6%.     

Cu2+对序批式反应器中活性污泥胞外聚合物产量及其组分的影响

研究了长期暴露条件下Cu2+对序批式反应器(SBR)性能及其活性污泥胞外聚合物(EPS)特性的影响。结果表明,进水中加入10 mg·L-1的Cu2+后,在SBR运行的第16~55天,COD和NH+4-N的去除率保持稳定;在第56~75天,COD和NH+4-N的平均去除率与进水Cu2+浓度为0 mg·L-1时相比分别下降了3.88%和6.41%。浓度为10 mg·L-1的Cu2+长期作用下,活性污泥中EPS、松散附着EPS(LB-EPS)和紧密附着EPS(TB-EPS)产量及LB-EPS和TB-EPS中蛋白质(PN)含量增加。傅里叶变换红外光谱分析表明10 mg·L-1 Cu2+的长期暴露导致TB-EPS中PN的C=O键、N-H键和C-O键相对含量降低。X射线光电子能谱(XPS)测试结果显示在10 mg·L-1 Cu2+长期暴露条件下,LB-EPS和TB-EPS中元素Cu和O百分含量增加。     

Targeting rare earth element bearing mine tailings on Bangka Island,Indonesia, with Sentinel-2 MSI

A laboratory study on rare earth element bearing mine tailings, collected from Bangka Island, Indonesia, reported a new spectral absorption feature at 674 nm associated with Erbium. The present study aims to evaluate the capability of the European Space Agency’s Sentinel-2 MSI sensors to detect this absorption feature from space. An arithmetic band operation is performed on selected visible and near-infrared spectral bands of a Sentinel-2 image. The results show that Sentinel-2 MSI is capable of detecting the 674 nm Erbium-related absorption feature within the particular environmental setting of the study area.     

Mapping wetland characteristics using temporally dense Sentinel-1 and Sentinel-2 data: A case study in the St. Lucia wetlands,South Africa

Wetlands have been determined as one of the most valuable ecosystems on Earth and are currently being lost at alarming rates. Large-scale monitoring of wetlands is of high importance, but also challenging. The Sentinel-1 and -2 satellite missions for the first time provide radar and optical data at high spatial and temporal detail, and with this a unique opportunity for more accurate wetland mapping from space arises. Recent studies already used Sentinel-1 and -2 data to map specific wetland types or characteristics, but for comprehensive wetland characterisations the potential of the data has not been researched yet. The aim of our research was to study the use of the high-resolution and temporally dense Sentinel-1 and -2 data for wetland mapping in multiple levels of characterisation. The use of the data was assessed by applying Random Forests for multiple classification levels including general wetland delineation, wetland vegetation types and surface water dynamics. The results for the St. Lucia wetlands in South Africa showed that combining Sentinel-1 and -2 led to significantly higher classification accuracies than for using the systems separately. Accuracies were relatively poor for classifications in high-vegetated wetlands, as subcanopy flooding could not be detected with Sentinel-1’s C-band sensors operating in VV/VH mode. When excluding high-vegetated areas, overall accuracies were reached of 88.5% for general wetland delineation, 90.7% for mapping wetland vegetation types and 87.1% for mapping surface water dynamics. Sentinel-2 was particularly of value for general wetland delineation, while Sentinel-1 showed more value for mapping wetland vegetation types. Overlaid maps of all classification levels obtained overall accuracies of 69.1% and 76.4% for classifying ten and seven wetland classes respectively.     

Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots,UAV-LiDAR data and Sentinel-2 imagery

The mangrove forests of northeast Hainan Island are the most species diverse forests in China and consist of the Dongzhai National Nature Reserve and the Qinglan Provincial Nature Reserve. The former reserve is the first Chinese national nature reserve for mangroves and the latter has the most abundant mangrove species in China. However, to date the aboveground ground biomass (AGB) of this mangrove region has not been quantified due to the high species diversity and the difficulty of extensive field sampling in mangrove habitat. Although three-dimensional point clouds can capture the forest vertical structure, their application to large areas is hindered by the logistics, costs and data volumes involved. To fill the gap and address this issue, this study proposed a novel upscaling method for mangrove AGB estimation using field plots, UAV-LiDAR strip data and Sentinel-2 imagery (named G∼LiDAR∼S2 model) based on a point-line-polygon framework. In this model, the partial-coverage UAV-LiDAR data were used as a linear bridge to link ground measurements to the wall-to-wall coverage Sentinel-2 data. The results showed that northeast Hainan Island has a total mangrove AGB of 312,806.29 Mg with a mean AGB of 119.26 Mg ha⁻¹. The results also indicated that at the regional scale, the proposed UAV-LiDAR linear bridge method (i.e., G∼LiDAR∼S2 model) performed better than the traditional approach, which directly relates field plots to Sentinel-2 data (named the G∼S2 model) (R² = 0.62 > 0.52, RMSE = 50.36 Mg ha⁻¹<56.63 Mg ha⁻¹). Through a trend extrapolation method, this study inferred that the G∼LiDAR∼S2 model could decrease the number of field samples required by approximately 37% in comparison with those required by the G∼S2 model in the study area. Regarding the UAV-LiDAR sampling intensity, compared with the original number of LiDAR plots, 20% of original linear bridges could produce an acceptable accuracy (R² = 0.62, RMSE = 51.03 Mg ha⁻¹). Consequently, this study presents the first investigation of AGB for the mangrove forests on northeast Hainan Island in China and verifies the feasibility of using this mangrove AGB upscaling method for diverse mangrove forests.     

Winter cover crops in Dutch maize fields: Variability in quality and its drivers assessed from multi-temporal Sentinel-2 imagery

Planting a cover crop between the main cropping seasons is an agricultural management measure with multiple potential benefits for sustainable food production. In the maize production system of the Netherlands, an effective establishment of a winter cover crop is important for reducing nitrogen leaching to groundwater. Cover crop establishment after maize cultivation is obliged by law for sandy soils and consequently implemented on nearly all maize fields, but the winter-time vegetative ground cover varies significantly between fields. The objectives of this study are to assess the variability in winter vegetative cover and evaluate to what extent this variability can be explained by the timing of cover crop establishment and weather conditions in two growing seasons (2017–2018). We used Sentinel-2 satellite imagery to construct NDVI time series for fields known to be cultivated with maize within the province of Overijssel. We fitted piecewise logistic functions to the time series in order to estimate cover crop sowing date and retrieve the fitted NDVI value for 1 December (NDVI_Dec). We used NDVI_Dec to represent the quality of cover crop establishment at the start of the winter season. The Sentinel-2 estimated sowing dates compared reasonably with ground reference data for eight fields (RMSE = 6.6 days). The two analysed years differed considerably, with 2018 being much drier and warmer during summer. This drought resulted in an earlier estimated cover crop sowing date (on average 19 days) and an NDVI_Dec value that was 0.2 higher than in 2017. Combining both years and all fields, we found that Sentinel-2 retrieved sowing dates could explain 55% of the NDVI_Dec variability. This corresponded to a positive relationship (R² = 0.50) between NDVI_Dec and the cumulative growing degree days (GDD) between sowing date and 1 December until reaching 400 GDD. Based on cumulative GDD derived from two weather stations within Overijssel, we found that on average for the past three decades a sowing date of 19 September (± 7 days) allowed to attain these 400 GDD; this provides support for the current legislation that states that from 2019 onwards a cover crop should be sown before 1 October. To meet this deadline, while simultaneously ascertaining a harvest-ready main crop, in practice implies that undersowing of the cover crop during spring will gain importance. Our results show that Sentinel-2 NDVI time series can assess the effectiveness and timing of cover crop growth for small agricultural fields, and as such has potential to inform regulatory frameworks as well as farmers with actionable information that may help to reduce nitrogen leaching.     

基于2 m格网点云数据的高精度DEM制作第三次国土调查坡度图

地形地貌随着时间的推移时刻发生变化,以高精度数字高程模型（EDE）数据制作坡度图,进而计算田坎系数,更精准地进行耕地面积计算及统计。以2 m格网点云数据生成的DEM数据为基础,按照第三次全国国土调查的相关技术要求,根据耕地坡度分级要求进行分级,生成坡度分级栅格数据图。对坡度分级栅格数据图进行矢量化,生成坡度分级矢量化数据。对矢量化数据进行图斑综合、界线平滑、拓扑重建、数据裁切等处理,制作完成调查区域坡度图及相关属性数据制作。并对生产的坡度图成果进行分析,找出不同尺度格网生产的坡度图的技术差异,并对高精度坡度的应用进行了展望。