Integration of hyperspectral and LiDAR data for mapping small water bodies

Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.     

The 2019 Brumadinho tailings dam collapse: Possible cause and impacts of the worst human and environmental disaster in Brazil

On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed catastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13 × 10⁶ m²), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream.     

利用BDS与无人船进行污染源分析及处理

在大数据的背景下,充分利用北斗卫星导航系统（BDS）的定位功能,以无人船作为用户端,在水质数据采集和污染源位置的问题中积极探索新的实践方案,迅速、准确地找到污染源,减少河流污染物污染的时间,且无人船上装有净化模块,在发现污染时可作简易处理。在无人船上安装水质分析仪,水质分析仪的传输模块中安装经给防水处理的北斗卫星定位芯片和WiFi数据传输器,进而对河流的污染物种类及浓度进行分析,并采用大数据的计算方法,计算出污染源位置,向云平台反映污染源位置分析结果与污染物处理方法。通过BDS,将数据按照位置区域划分,并将能到达污染源的最短路径发送到处理人的移动设备上。本文通过对基于BDS定位的水质污染监测可视化系统进行分析,以期迅速找出污染源,减少水质污染现象的发生。     

ASTER数据的煤矿区水体信息提取

为实现多光谱数据对煤矿区水体信息提取,以萍乡市芦新岭及周边煤矿为试验区,在国内外学者对水体指数法提取水体信息和应用的启发下,对试验区不同地物的波谱特征进行分析。本文首先利用数学统计方法建立一种ASTER数据综合归一化差异水体指数模型SWI ASTER_xy,然后利用这一模型对试验区进行水体信息提取。试验表明,该模型能够有效地提取矿区各类水体,还可以运用在ASTER数据（或其他多光谱数据）对不同区域不同地物的提取,在遥感地物定量提取上具有很好的效果和潜力,具有一定的推广价值。     

黄河中下游沿线城市水资源利用效率的时空演变及影响因素

采用超效率DEA模型、GIS空间分析方法、动态面板的系统GMM估计方法对2010—2017年黄河中下游沿线城市水资源利用效率时空格局及影响因素进行分析,结果表明：① 黄河中下游沿线城市水资源利用效率整体由2010年的0.70波动下降为2017年的0.67,且区域内70%以上的城市水资源利用效率变动趋势与其一致;② 黄河中下游沿线城市水资源利用效率呈“U”型区域两侧相对较高,中间区域相对较低的空间分布态势,且空间分布重心始终位于地理重心的北方;③ 环境规制、经济发展水平、产业结构优化、技术水平对水资源利用效率呈显著正向影响,农田水利设施建设、城镇化对水资源利用效率呈显著负向影响。研究结论可为黄河流域生态保护与高质量发展的推进提供决策支持。     

中国区域水资源系统韧性与效率的发展协调关系评价

在界定水资源系统韧性概念的基础上,综合应用赋权法、SBM-DEA模型及发展协调度模型对2000—2016年全国31个省区的区域水资源系统的效率、韧性以及两者之间的发展协调关系进行评价。结果如下：① 中国区域水资源系统效率整体上处于非有效区,在研究期间呈现出在波动中上升的趋势。② 中国区域水资源系统韧性的平均值为0.39,总体水平较低,研究期间整体上呈波动上升趋势。③ 中国区域水资源系统效率与韧性的发展度总体呈现平稳上升—较快上升—急剧下降—上升的趋势,呈倒“U”型发展;协调度在研究期间呈现波动中上升趋势,大部分省区的发展度较好,而协调度较弱。④ 2000—2016年,水资源效率与韧性的发展协调度一直维持着“东?中?西”阶梯式递减格局,失调省区的数量降低,初级协调、中级协调、良好协调省区的数量逐渐提升,整体向协调趋势发展;空间格局上呈现由2000年倒“E”型对称式分布格局向如今北部围绕天津、中部围绕上海、南部围绕广东的三级格局演变,格局分布与中国三大经济区基本吻合,可知中国水资源系统效率与韧性的发展协调水平与经济发展水平之间有明显的关系。     

环塔里木盆地绿洲城市发展与水环境质量协调度

解决好新疆环塔里木盆地绿洲城市发展与水环境质量之间的关系,对"一带一路"倡议顺利实施及新疆社会稳定具有十分重要的作用。基于2004-2017年环塔里木盆地绿洲城市发展与水环境变化状况,构建城市发展与水环境质量的综合评价模型及二者的协调度模型,以探讨环塔里木盆地绿洲城市发展、水环境质量变化及二者的协调关系。结果表明：2004-2017年,（1）环塔里木盆地绿洲城市发展综合指数呈现出逐年稳定上升的趋势,经济发展和城镇空间规模扩大是环塔里木盆地绿洲城市发展的主要形式;（2）环塔里木盆地绿洲城市的水环境质量综合指数呈现出逐年降低的趋势,水环境质量形势严峻;（3）环塔里木盆地绿洲城市发展-水环境质量系统的协调度呈现倒U型的稳定发展趋势,但总体上两者的协调度较低,城市发展和水环境质量之间的矛盾日益突出。     

生物土壤结皮对风沙土和黄绵土膨胀特性的影响

作为重要的土壤物理性质,膨胀性在影响土壤导水性、持水性、抗蚀性以及土壤结构的形成和发育等方面发挥着重要作用。为了探讨生物土壤结皮（BSCs）土壤的膨胀特性及其主要影响因素,针对黄土高原风沙土和黄绵土两种典型土壤,利用膨胀仪测定并比较了有、无藓结皮及其在不同因素（初始含水量、干湿循环、冻融循环、温度）下膨胀率的差异,分析了BSCs对土壤膨胀性的影响及其与环境因素和BSCs性质的关系。结果显示：风沙土上藓结皮的膨胀率为1.93%,较无结皮增加了8.65倍;而黄绵土上藓结皮的膨胀率为2.05%,与无结皮相比降低了76.68%。藓结皮的生物量和厚度与其膨胀率在风沙土上均呈线性正相关关系（P < 0.05）,在黄绵土上分别呈二次函数（P=0.02）和线性正相关关系（P=0.02）。初始含水量同时影响了土壤最大膨胀率和稳定膨胀时间,影响程度风沙土远大于黄绵土（包括藓结皮和无结皮）;干湿循环次数对无结皮土壤膨胀率的影响程度大于藓结皮土壤,其中风沙土和黄绵土上无结皮的膨胀率分别是50.00%~620.00%和-2.28%~10.81%,而两种土壤上藓结皮的膨胀率分别是-5.70%~10.88%和-10.24%~-21.46%;冻融循环下4种土壤的膨胀率均有不同程度的降低,降幅为0~18.54%。黄绵土无结皮的膨胀率受温度影响程度较大,50℃下黄绵土无结皮的膨胀率分别是25℃和35℃下的1.17倍和1.21倍。BSCs显著地改变了风沙土和黄绵土表层的膨胀性,其影响的程度和方向取决于土壤类型。同时,BSCs的膨胀性受含水量、温度、干湿以及冻融循环等关键因素影响。     

贵州夜郎湖表层水体地球化学昼夜变化及其影响因素

为探究岩溶水库水文地球化学行为过程,对贵州普定夜郎湖表层水体进行了为期3 d的高分辨率昼夜监测。结果表明：1）多变的天气和水文条件叠加导致水体离子指标昼夜变化不显著,规律性较差。而水温、DO、pH值、SpC、SIc、pCO₂等常规理化指标受水温变化和生物作用表现出明显的昼夜波动。2）利用亨利常数和主成分分析,得到温度变化、生物作用、人类活动、水库的蓄水与放水对夜郎湖水库水文地球化学特征变化的贡献率分别为21.66%、17.28%、14.08%和10.22%,说明作用于水库水文地球化学行为的因子具有多元性。3）δ ¹⁸O表现出与DO一致的波动趋势,即白天上升,晚上下降,反映在短时间尺度上,氢氧稳定同位素变化受控于生物过程（主要是呼吸作用过程）;而对比水库水体和大气降水的d-excess（d值）发现,水库水体的d值（8.21‰）显著偏低于当地大气降水的d值（9.64‰）,说明在长时间尺度上,主要受蒸发效应引起的不平衡分馏影响。     

毛乌素沙地植被水分利用效率的时空格局

水分利用效率（WUE）是衡量生态系统碳水循环耦合程度的重要指标,明晰其动态变化规律有助于判断区域植被生态建设是否与当地的自然条件相适应。利用基于CASA（Carnegie-Ames-Stanford Approach）模型得到的植被净初级生产力（NPP）数据和MODIS系列产品中的蒸散发（ET）数据,估算了2001—2016年毛乌素沙地植被的WUE,并探讨了其时空演变特征及与气象因子的关系。结果显示：（1）WUE的多年平均值为0.62 gC·mm^-1·m^-2,空间上自东向西递减,在不同植被类型间表现为栽培植物>灌丛>草甸>草原>荒漠;（2）WUE以0.009 gC·mm^-1·m^-2·a^-1的速率上升,东部地区变化尤为显著,NPP的快速增长是WUE呈增加趋势的主要原因;（3）WUE与各气象因子的相关程度由大至小依次为太阳辐射、降水量、风速和气温,分布在西部地区的荒漠植被WUE受气象因子影响最小。经过一系列生态建设工程的治理,毛乌素沙地大部分地区自2001年以来NPP和WUE均呈增加趋势,即生态系统在变“绿”的同时还实现了水分的高效利用,有利于当地生态环境的健康发展;但在水热条件较差的中西部地区,新建设的植被生长缓慢且导致蒸散发产生强烈变化,使WUE呈减少趋势,暴露出植被建设规模与水资源承载能力不匹配的问题,需引起格外重视。