C3连续的单位四元数插值样条曲线

目的 构造一类C³连续的单位四元数插值样条曲线,证明它的插值性和连续性,并把它应用于刚体关键帧动画设计中。方法 利用R³空间中插值样条曲线的5次多项式调配函数的累和形式构造了S³空间中单位四元数插值样条曲线,它不仅能精确通过一系列给定的方向,而且能生成C³连续的朝向曲线。结果 与Nielson的单位四元数均匀B样条插值曲线的迭代构造方法相比,所提方法避免了为获取四元数B样条曲线控制顶点对非线性方程组迭代求解的过程,提高了运算效率;与单位四元数代数三角混合插值样条曲线的构造方法（Su方法）相比,所提方法只用到多项式基,运算速度更快。本例中创建关键帧动画所需的时间与Nielson方法和Su方法相比平均下降了73%和33%。而且,相比前两种方法,所提方法产生的四元数曲线连续性更高,由C²连续提高到C³连续,这意味着动画中刚体的朝向变化更加自然。结论 仿真结果表明,本文方法对刚体关键帧动画设计是有效的,对实时性和流畅性要求高的动画设计场合尤为适用。     

数字孪生淮河防洪“四预”系统关键技术

聚焦淮河流域防洪减灾重大需求面临的预报、预警、预演、预案关键科技难题，利用无人机、激光雷达、卫星遥感等“空天地”一体化技术，研发基于多源多尺度信息的数据底板构建技术，构建高精度多要素数据底板；利用水文水动力数值模拟和并行计算技术，构建超大规模水文水动力学耦合模拟技术；基于高精度数据底板、高性能算力和高精准算法，建立数字孪生淮河防洪“四预”平台，并在 2020 年淮河流域性较大洪水复盘检视和 2021—2022 年淮河多场次暴雨洪水中进行了应用。结果表明：计算节点数量由原来的 9 个细化至 5 157 个，计算单元大小由原来的 9 648 km² 细化至 17 km²，模型平均效率系数为 0.8，淮河干流主要控制站最大流量预报相对误差基本在 10%以内，洪水预报预见期能达到 2~4 d，可实现全流域全要素的精细化模拟，为数字孪生流域、洪水预报及工程调度提供技术支撑。     

非局部加权邻域三角滤波TV-L1光流估计

目的 针对非刚性运动、运动遮挡与间断、大位移以及复杂边缘结构等困难场景图像序列光流计算的准确性与鲁棒性问题,提出一种基于加权邻域三角滤波的非局部TV-L¹光流计算方法。方法 首先设计非平方惩罚函数L¹模型与梯度守恒假设相结合的数据项,然后引入基于L¹模型与基于图像梯度自适应变化权重相结合的平滑项,并根据提出的鲁棒数据项与图像-光流联合控制平滑项建立TV-L¹光流计算能量函数模型。最后采用基于加权邻域三角的非局部约束项,通过引入图像金字塔分层变形计算策略,在每层图像光流计算时对光流计算结果进行基于加权邻域三角网格的中值滤波优化,提出基于加权邻域三角滤波的非局部TV-L¹光流计算模型。结果 分别采用MPI与Middlebury数据库测试图像序列对本文方法和LDOF、CLG-TV、SOF、Classic+NL等代表方法进行实验对比。本文方法光流计算结果的平均角误差（AAE）和平均端点误差（AEE）相对其他对比方法平均下降28.45%和28.42%,时间消耗相对传统方法增长5.16%。结论 相对于传统的光流计算方法,本文方法针对非刚体运动、运动遮挡与间断、大位移运动以及复杂边缘等困难场景具有较好的适用性,光流估计结果具有较高的精度和较好的鲁棒性。     

结合EMD-cl嵌入的多载体密图分存方法

目的 传统误差扩散或恢复函数的多载体密图分存会对嵌密载体视觉质量造成较大影响,同时恢复函数需单独设计,只适用于二值或灰度图像,且通过简单Arnold置乱或异或加密仅能提供有限的安全性。针对此问题,提出结合EMD-c^l嵌入的多载体密图分存方法。方法 采用双哈希MD5和SHA-1值产生多组与密图属性和用户密钥有关的置乱参数,驱动2维双尺度矩形映射来改变载体像素对应关系,然后将置乱后载体同位置像素构成向量,按扩展约瑟夫遍历映射分配基向量,通过EMD-c^l嵌入秘密像素,从而将密图分存到多张载体中。结果 采用EMD-c^l提高了嵌密载体视觉质量且不需额外设计恢复函数,可针对不同分辨率和灰度阶密图分存。所提方法载体像素位置和EMD-c^l基向量都与密图MD5和SHA-1值以及用户密钥紧密绑定,仅有正确用户密钥和密图MD5和SHA-1值才能对密图恢复,并可通过第三方公信方托管的参与者分存信息MD5和SHA-1值使得所述策略具备认证能力。所提方法密钥空间为1.193 6×10¹¹⁸,可抵抗暴力破解。实验结果表明,结合EMD-c^l,所提方法具有较好的嵌密载体视觉质量,NC趋近于1,对于EMD-3^l,嵌密载体PSNR均接近50 dB;对于EMD-5^l和EMD-7^l,PSNR分别达到45 dB和42 dB,而传统方法,PSNR最好仅为42 dB。所提方法可分存不同分辨率和灰度阶密图,可对参与者密钥分存信息的真实性进行检验且对密图哈希和用户密钥极度敏感。结论 所提方法具有较低复杂度,较高安全性和普适性及认证能力,在整体性能上优于传统误差扩散或恢复函数的多载体密图分存方法,适用于对嵌密载体视觉质量要求高和针对不同分辨率和灰度阶密图分存的安全场景中。     

利用距离与内能极小平滑链接Bézier曲线

目的 对于满足低阶连续的链接Bézier曲线,提高曲线之间的连续性以达到平滑的目的,需要对曲线的控制顶点进行相应调整。因此,可根据具体的目标对需要调整的控制顶点进行优化选取,使得平滑后的链接曲线满足相应的要求。针对这一问题,给出了3种目标下优化调整控制顶点的方法。方法 首先对讨论的问题进行描述,分别指出链接Bézier曲线从C⁰连续平滑为C¹连续和从C¹连续平滑为C²连续两种情形需调整的控制顶点;然后分别给出两种情形下,以新旧控制顶点距离极小为目标、曲线内能极小为目标、新旧控制顶点距离与曲线内能同时极小为目标,对链接Bézier曲线进行平滑的方法,最后对3种极小化方法进行对比,并指出了不同方法的适用场合。结果 数值算例表明,距离极小化方法调整后的控制顶点偏离原控制顶点的距离相对较小,适合于控制顶点取自于实物时的应用场合;内能极小化方法获得的链接曲线内能相对较小,适合于要求曲线能量尽可能小的应用场合;距离与内能同时极小化方法兼顾了新旧控制顶点的距离和链接曲线的内能,适合于对两个目标都有要求的应用场合。结论 提出的方法为链接Bézier曲线的平滑提供了3种有效手段,且易于实现,对其他类型链接曲线的平滑具有参考价值。     

数字孪生潭江流域先行先试建设与实践

数字孪生流域与数字孪生水网、数字孪生水利工程互联互通、信息共享、各有侧重,共同构成数字孪生水利系统核心,是推动新时代水利高质量发展的重要实施路径之一_[^1]。水利部于2022年2月启动了数字孪生流域建设先行先试工作,为切实其提高潭江流域水利工程防洪调度能力,江门市水利局按照水利部及广东省数字孪生流域试点建设工作要求_[^2],开展数字孪生潭江流域建设。数字孪生潭江面向流域防洪调度需求,以精细化调度22宗大中型水库、7宗梯级闸陂为目标,围绕四预核心功能,建设数据底板、模型平台、业务应用等内容,构建了流域LI级数据底板,流域重点区域及重点工程L2级数据底板,开发了五大类水利专业模型,初步构建了流域联合调度平台,并在2022年“龙舟水”、西北江洪水、台风暴雨防御期间投入实战,助力潭江流域水库水闸的群联合调度,取得防洪不受淹水资源不浪费的最佳效益。     

利用色调—亮度彩色分量的可见光植被指数

目的 无人机遥感具有高时效、高分辨率、低成本、操作简单等优势。但由于无人机通常只携带可见光传感器,无法计算由可见光-近红外波段组合所构造的植被指数。为解决这一问题,提出一种归一化色调亮度植被指数NHLVI （normalized hue and lightness vegetation index）。方法 通过分析HSL （hue-saturation-lightness）彩色空间模型,构建一种基于色调亮度的植被指数,将该植被指数以及其他常用的可见光植被指数,如归一化绿红差值指数NGRDI （normalized green-red difference index）、过绿指数ExG （excess green）、超绿超红差分指数ExGR （excess green minus excess red）等,分别与野外实测光谱数据和无人机多光谱数据的NDVI （normalized difference vegetation index）进行相关性比较;利用受试者工作特征曲线ROC （receiver operating characteristic curve）的特点确定阈值,并进行植被信息提取与分析。结果 NHLVI与NDVI相关性高（R²=0.776 8）,而其他可见光植被指数中,NGRDI与NDVI相关性较高（R²=0.687 4）;ROC曲线下面积大小作为评价不同植被指数区分植被与非植被的指标,NHLVI指数在ROC曲线下面积为0.777,小于NDVI （0.815）,但大于NGRDI （0.681）,区分植被与非植被能力较强。为进一步验证其精度,利用阈值法提取植被,NHLVI提取植被信息的总体精度为82.25%,高于NGRDI （79.75%）,尤其在植被稀疏区,NHLVI的提取结果优于NGRDI。结论 提出的归一化色调亮度植被指数,提取植被精度较高,适用于无人机可见光影像植被信息提取,为无人机可见光影像的应用提供了新方法。     

1993~2016年喜马拉雅山西段杰纳布流域冰川变化遥感监测

基于Landsat TM/ETM+及OLI遥感影像,对喜马拉雅山西段杰纳布流域冰川面积进行提取,对冰川时空分布特征及其变化分析,并结合周边气象台站及CRU再分析资料气温、降水量资料对研究区冰川变化原因进行讨论。结果表明：①1993~2016年杰纳布流域冰川面积萎缩了164.56±161.72 km²,占总面积的5.78%,年均萎缩率为0.25±0.25 %·a^-1,且在2000年后加快萎缩;②杰纳布流域冰川在各个朝向和海拔带上均呈萎缩趋势,其中S朝向冰川面积萎缩率最大,占研究区冰川萎缩总面积的24.35%; 4 600~4 800 m和4 800~5 000 m两个海拔高度带冰川面积近23 a分别减少了29.93 km²和30.91 km²,占流域冰川面积萎缩总量的17.72%和18.30%;③1993~2016年杰纳布流域共有28条冰川末端发生不同程度的前进现象;④对狮泉河和Srinagar气象站及CRU再分析资料气温、降水量变化分析表明,1993~2016年该区域年均气温呈显著上升是杰纳布流域冰川萎缩的主要原因。     

带形状控制的自由曲线曲面参数样条

目的 样条曲线曲面的构造是工程制图中的一个重要部分。针对双曲抛物面上参数样条曲线的构造,在已有的研究基础上提出了一种样条方法使曲线曲面可以任意地逼近一个多边形或者一个网格。方法 在标准四面体内构造一个双曲抛物面,在该曲面上以基函数参数化的方法定义一种带形状参数的参数样条曲线曲面,样条基函数通过将双曲抛物面的有理参数化进行限定,生成单参数有理样条基函数。详细研究了样条的保形性及其端点性质。结果 样条曲线具有一个可变的形状控制因子,可以对曲线进行调整,能以任意精度逼近这个控制四边形或网格。对空间节点列,利用该样条可以生成G²-连续空间曲线,同样对于空间网格可以构造G²-连续的拟合曲面,它所对应的基函数可以是有理形式。结论 实验结果表明,本文在笔者已有的研究基础上提出的参数样条曲线可以通过重心坐标系变换适应为任意的四边形,除了空间四面体内的样条曲线,四面体退化成四边形同样可实现。     

带法向约束的隐式T样条曲线重构

目的 隐式曲线能够描述复杂的几何形状和拓扑结构,而传统的隐式B样条曲线的控制网格需要大量多余的控制点满足拓扑约束。有些情况下,获取的数据点不仅包含坐标信息,还包含相应的法向约束条件。针对这个问题,提出了一种带法向约束的隐式T样条曲线重建算法。方法 结合曲率自适应地调整采样点的疏密,利用二叉树及其细分过程从散乱数据点集构造2维T网格;基于隐式T样条函数提出了一种有效的曲线拟合模型。通过加入偏移数据点和光滑项消除额外零水平集,同时加入法向项减小曲线的法向误差,并依据最优化原理将问题转化为线性方程组求解得到控制系数,从而实现隐式曲线的重构。在误差较大的区域进行T网格局部细分,提高重建隐式曲线的精度。结果 实验在3个数据集上与两种方法进行比较,实验结果表明,本文算法的法向误差显著减小,法向平均误差由10^-3数量级缩小为10^-4数量级,法向最大误差由10^-2数量级缩小为10^-3数量级。在重构曲线质量上,消除了额外零水平集。与隐式B样条控制网格相比,3个数据集的T网格的控制点数量只有B样条网格的55.88%、39.80%和47.06%。结论 本文算法能在保证数据点精度的前提下,有效降低法向误差,消除了额外的零水平集。与隐式B样条曲线相比,本文方法减少了控制系数的数量,提高了运算速度。     

Change in area of Ebinur Lake during the 1998–2005 period

Ebinur Lake is located in a typical arid region in the north‐west of China. It is an area with the lowest elevation in the Junggar Basin in the Province of Xinjiang. Recent monitoring indicates that the lake surface area has increased. To obtain a continuous record of the change in lake area, a radiometric analysis of SPOT/VEGETATION (VGT) imagery was carried out based on methodology developed for regional lake area mapping. Two indices, the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), were selected to identify the water body of Ebinur Lake. The indices are calculated based on the spectral reflectances in the red and near infrared bands of VGT sensor. If the NDVI is less than a critical value (0) and if the NDWI is larger than a critical value (0), the pixel is flagged as a water body. Validation indicates that the methodology to identify water bodies based on multi‐spectral VGT data is applicable in our study area achieving an overall accuracy of 91.4%. Independent monitoring results elicit that the lake surface area was at its lowest in 1998. The yearly average surface area is about 503 km². The lake area increased to 603 km² during 1999. In the period 1999–2001 the area changes are marginal. A large area increase occurred from 2001 to 2002 till the lake area reached a surface area of 791 km². The lake area peaks to 903 km² in 2003 and subsequently decreased to areas of 847 km² in 2004 and 746 km² in 2005. Similar area change dynamics are observed when applying the remote sensing based technique. Seasonally, the typical dynamics elicit a larger surface area in spring and winter and a smaller one during summer.     

A denoising–classification–retracking method to improve spaceborne estimates of the water level–surface–volume relation over the Urmia Lake in Iran

ABSTRACT

Decreasing the volume of the Urmia Lake, as the largest inland water body in Iran, is one of the current environmental and water resource management concerns. This study obtains a reliable spaceborne water level (WL)–area–volume relationship for the Urmia Lake using terrestrial, aerial and satellite-based data. The aim of this study is to improve Urmia Lake’s WL derived from satellite altimetry and, consequently, to more accurately estimate the volume of the lake for the last decade. To this end, improved WL is obtained from the Satellite with Argos and Altika (SARAL/AltiKa) and Jason-2 altimetry missions by performing a post-processing method. The post-processing method includes a denoising, a classification and appropriate retracking algorithms. The results are validated against in situ gauge data and also compared with results from Prototype Innovant de Système de Traitement pour les Applications Côtières et l’Hydrologie (PISTACH) and Prototype on AltiKa for Coastal, Hydrology and Ice (PEACHI) products. The Denoising–Classification–Retracking (DCR) method improves the root mean square error (RMSE) of WL with respect to those of PISTACH and PEACHI by 54% and 24%, respectively. The surface area of the lake is determined from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images based on calculating normalized difference water index (NDWI). The results are validated against the surface area obtained from aerial photogrammetry and Cartosat high resolution image. Moreover, based on bathymetric map a Look-up table including surface area and volume of the lake at specific levels are formed. The obtained surface area is then compared with the values of the Look-up table. The normalized root mean square error between surface extent obtained from proposed method and corresponding values is about 11%. The estimated lake’s volume is compared with the level-volume curve from the bathymetric data. The result showed the RMSE of this comparison is about 0.12 km³. Our validated results show that the lake has lost 75% of its volume from late 2008 to early 2016 but continued with an increase in its volume in May 2017 twice as much as in early 2016. Our results support urgent or long-term restoration plan of Lake Urmia and highlight the important role of spaceborne sensors for hydrological applications.     

Modelling spatial‐temporal change of Poyang Lake using multitemporal Landsat imagery

Poyang Lake is a seasonal lake, exchanging water with the lower branch of the Yangtze River. During the spring and summer flooding season it inundates a large area while in the winter it shrinks considerably, creating a large tract of marshland for wild migratory birds. A better knowledge of the water coverage duration and the beginning and ending dates for the vast range of marshlands surrounding the lake is important for the measurement, modelling and management of marshland ecosystems. In addition, the abundance of a special type of snail (Oncomelania hupensis), the intermediate host of parasite schistosome (Schistosoma japonicum) in this region, is also heavily dependent on the water coverage information. However, there is no accurate digital elevation model (DEM) for the lake bottom and the inundated marshland, nor is there sufficient water level information over this area. In this study, we assess the feasibility of the use of multitemporal Landsat images for mapping the spatial‐temporal change of Poyang Lake water body and the temporal process of water inundation of marshlands. Eight cloud‐free Landsat Thematic Mapper images taken during a period of one year were used in this study. We used the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) methods to map water bodies. We then examined the annual spatial‐temporal change of the Poyang Lake water body. Finally we attempted to obtain the duration of water inundation of marshlands based on the temporal sequence of water extent determined from the Landsat images. The results showed that although the images can be used to capture the snapshots of water coverage in this area, they are insufficient to provide accurate estimation of the spatial‐temporal process of water inundation over the marshlands through linear interpolation.     

Integration of Palmer Drought Severity Index and remote sensing data to simulate wetland water surface from 1910 to 2009 in Cottonwood Lake area, North Dakota

Spatiotemporal variations of wetland water in the Prairie Pothole Region are controlled by many factors; two of them are temperature and precipitation that form the basis of the Palmer Drought Severity Index (PDSI). Taking the 196 km² Cottonwood Lake area in North Dakota as our pilot study site, we integrated PDSI, Landsat images, and aerial photography records to simulate monthly water surface. First, we developed a new Wetland Water Area Index (WWAI) from PDSI to predict water surface area. Second, we developed a water allocation model to simulate the spatial distribution of water bodies at a resolution of 30 m. Third, we used an additional procedure to model the small wetlands (less than 0.8 ha) that could not be detected by Landsat. Our results showed that i) WWAI was highly correlated with water area with an R² of 0.90, resulting in a simple regression prediction of monthly water area to capture the intra- and inter-annual water change from 1910 to 2009; ii) the spatial distribution of water bodies modeled from our approach agreed well with the water locations visually identified from the aerial photography records; and iii) the R² between our modeled water bodies (including both large and small wetlands) and those from aerial photography records could be up to 0.83 with a mean average error of 0.64 km² within the study area where the modeled wetland water areas ranged from about 2 to 14 km². These results indicate that our approach holds great potential to simulate major changes in wetland water surface for ecosystem service; however, our products could capture neither the short-term water change caused by intensive rainstorm events nor the wetland change caused by human activities.     

Lake-area mapping in the Tibetan Plateau: an evaluation of data and methods

Lake area derived from remote-sensing data is a primary data source, because changes in lake number and area are sensitive indicators of climate change. These indicators are especially useful when the climate change is not convoluted with a signal from direct anthropogenic activities. The data used for lake-area mapping is important, to avoid introducing unnecessary uncertainty into long-term trends of lake-area estimates. The methods for identifying waterbodies from satellite data are closely linked to the quality and efficiency of surface-water differentiation. However, few studies have comprehensively considered the factors affecting the selection of data and methods for mapping lake area in the Tibetan Plateau (TP), nor of evaluating their consequences. This study tests the dominant data sets (Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data) and the methods for automated waterbody mapping on 14 large lakes (>500 km²) distributed across different climate zones of the TP. Seasonal changes in lake area and data availability from Landsat imagery are evaluated. Data obtained in October is optimal because in this month the lake area is relatively stable. The data window can be extended to September and November if insufficient data is available in October. Grouping data into three-year bins decreases the effects of year-to-year seasonal variability and provides a long-term trend that is suitable for time series analysis. The Landsat data (Multispectral Scanner, MSS; Thematic Mapper, TM; Enhanced Thematic Mapper Plus, ETM+; and Operational Land Imager, OLI) and MODIS data (MOD09A1) showed good performance for lake-area mapping. The Otsu method is used to determine the optimal threshold for distinguishing water from non-water features. Several water extraction indices, namely NDWI_McFeeters, NDWI_Xu, and AWEI_non-shadow, yielded high overall classification accuracy (92%), kappa coefficient (0.83), and user’s accuracy (~90%) for lake-water classification using Landsat data. The MODIS data using NDWI_McFeeters and NDWI_Xu showed consistent lake area (r² = 0.99) compared with Landsat data on the corresponding date with root mean square error (RMSE) values of 86.87 and 103.33 km² and mean absolute error (MAE) values of 25.7 and 29.04 km², respectively. The MODIS data is suitable for great lake mapping, which is the case for the large lakes in the TP. Although automated water extraction indices exhibited high accuracy in separating water from non-water, visual examination and manual editing are still necessary. Combined with recent Chinese high-resolution satellites, these remotely sensed imageries will provide a wealth of data for studies of lake dynamics and long-term lake evolution in the TP.     

Changes in snow and glacier cover in an arid watershed of the western Kunlun Mountains using multisource remote-sensing data

Snow and glaciers in the mountain watersheds of the Tarim River basin in western China provide the primary water resources to cover the needs of downstream oases. Remote sensing provides a practical approach to monitoring the change in snow and glacier cover in those mountain watersheds. This study investigated the change in snow and glacier cover in one such mountain watershed using multisource remote-sensing data, including the Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat (Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+)), Corona, and Google Earth^TM imagery. With 10 years’ daily MODIS snow-cover data from 2002 to 2012, we used two de-cloud methods before calculating daily snow-cover percentage (SCP), annual snow-cover frequency (SCF), and annual minimum snow-cover percentage (AMSCP) for the watershed. Mann–Kendall analysis showed no significant trend in any of those snow-cover characterizations. With a total of 22 Landsat images from 1967 to 2011, we used band ratio and supervised classification methods for snow classification for Landsat TM/ETM+ images and MSS images, respectively. The Landsat snow-cover data were divided into two periods (1976–2002 and 2004–2011). Statistical tests indicated no significant difference in either the variance or mean of SCPs between the two periods. Three glaciers were identified from Landsat images of 1998 and 2011, and their total area increased by 12.6%. In addition, three rock glaciers were also identified on both the Corona image of 1968 and the Google high-resolution image of 2007, and their area increased by 2.5%. Overall, based on multisource remote-sensing data sets, our study found no evidence of significant changes in snow and glacier cover in the watershed.     

Using Landsat imagery interpretation for underground water prospection around Qena Province,Egypt

Abstract

This work deals with visual interpretation of Landsat satellite images covering an area of 27 000 km² around Qena Province, Upper Egypt. Geological, structural lineaments and drainage density maps are constructed. From these maps the significant hydrogeological features are extracted, correlated and utilized in locating some areas of high underground water content.     

Remote-sensing monitoring for spatio-temporal dynamics of sand dredging activities at Poyang Lake in China

As the largest freshwater lake in China, Poyang Lake is suffering from declining water quality related to the excessive dredging of sand. Field supervision is difficult due to the size of the lake (>3000 km², wet season) and limited human resources. In this study, an approach is proposed to monitor sand-dredging activities using medium-resolution optical remote-sensing imagery, including 45 Landsat TM/ETM+ images from 2002 to 2012 and 140 HJ1A/B CCD images from 2009 to 2012. The procedure for detecting dredging vessels involves three steps. (1) The entire image is segmented into different homogeneous partitions to overcome water body heterogeneity, and ships in each partition with different levels of water clarity are detected using three types of contrast box architecture. (2) Dredging vessels are then identified based on a spatial overlay analysis of ships and dredging plumes, which are extracted from remote-sensing imagery. (3) False alarms (FAs) of dredging vessels are screened according to the distribution of the sandy lake bed. The results showed significant spatio-temporal variation in dredging activities; sand-dredging activities were concentrated at the northern part of Poyang Lake prior to 2008 and have expanded southwards since 2009. The northern part of the lake experienced persistent dredging operations throughout the year, whereas dredging was observed only during the wet seasons in the southern portion of the lake. A high intensity of illegal dredging was discovered based on two lines of evidence: dredging vessels were detected during the sand-dredging ban, and the estimated quantities of sand dredging were much higher than those planned by the authority. The sediment balance in Poyang Lake has continued to be disrupted, and the lake has become a sediment-exporting system. This study provides an effective solution for monitoring sand-dredging dynamics as well as useful information for managing sand dredging in fresh water environments and assessing its potential impacts on aquatic ecosystems.     

Permanent disappearance and seasonal fluctuation of urban lake area in Wuhan,China monitored with long time series remotely sensed images from 1987 to 2016

ABSTRACT

Lakes are important to the healthy functioning of the urban ecosystem. The urban lakes in Wuhan, China, which is known as ‘city of hundreds of lakes’, are facing substantial threats mainly due to rapid urbanization. This paper focused on detecting the spatial and temporal change of urban lakes in Wuhan, using a long time series of Landsat and HJ-1A remotely sensed data from 1987 to 2016. The permanent disappearance and seasonal fluctuation of 28 main urban lakes were analysed, and their relationships with climatic change and human activities were discussed. The results show that most lakes in Wuhan had shrunk over the past 30 years resulting in a permanent change from water to land. The shrinkage was also most apparent in the central region of the city. Seasonal fluctuations of lake area were evident for most lakes but the relative important driving variable of lake area change varied between sub-periods of time for different lakes. The explanatory power of impervious surface to five-year permanent water change is 91.75%, suggesting that urbanization – as increasing impervious surface – had led to the shrinkage of urban lakes in Wuhan. In all, 128.28 km² five-year permanent water disappeared from 1987 to 2016.