Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.  相似文献   

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

《International Journal of Applied Earth Observation and Geoinformation》2020

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.  相似文献   

广西土壤有机质空间变异特征及其影响因素研究   总被引：2，自引：0，他引：2  

钟聪  李小洁  何园燕  邱微文  李杰  张新英  胡宝清 《地理科学》2020,40(3):478-485

基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明：广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

秋季连续打捞蓝藻对水-气界面温室气体通量的影响     

荀凡  杜先  陈新芳  刘高飞  齐天赐  冯慕华 《湖泊科学》2020,32(6):1707-1722

在巢湖西北半湖近岸带设置大型围隔研究秋季连续打捞蓝藻对湖泊温室气体通量的影响，应用YL-1000型大型仿生式水面蓝藻清除设备进行原位打捞蓝藻，通过便携式温室气体分析仪-静态箱法对大型围隔内水-气界面CH₄、CO₂通量特征及其影响因素进行观测.结果表明：对比未打捞区，蓝藻连续打捞下打捞区水体中叶绿素a（Chl.a）、悬浮物（SS）浓度不断下降，两者削减率分别为72%、85%，Chl.a、SS浓度分别下降到29.6±2.5 μg/L、12.5±1.2 mg/L，打捞对围隔内颗粒态物质去除效果十分明显；打捞过程中水体溶解性有机物（DOM）中微生物代谢类腐殖质（C1）、类蛋白（C3）显著下降趋势，打捞区C1、C3组分（0.18±0.02、0.06±0.01 RU）强度明显低于未打捞区（0.26±0.05、0.12±0.03 RU），打捞能有效控制藻源性溶解性有机质释放.同时，打捞区水-气界面CH₄通量呈显著下降趋势，未打捞区CH₄通量平均值（17.473±1.514 nmol/（m²·s））为打捞区（7.004±4.163 nmol/（m²·s））近2倍，CH₄通量与Chl.a、C1、C3组分均呈显著正相关，水体中藻源性溶解态有机质对CH₄通量具有促进作用；打捞区CO₂释放通量呈显著上升趋势，打捞区CO₂吸收通量（-0.200±0.069 μmol/（m²·s））明显低于未打捞区（-0.344±0.017 μmol/（m²·s）），CO₂通量与Chl.a、温度均呈显著负相关.秋季打捞对CH₄、CO₂综合日平均通量减排量值为0.275±0.076 mol/（m²·d）（以CO₂当量计）.研究结果揭示了巢湖秋季连续打捞蓝藻过程对水-气界面温室气体具有显著减排作用，且能在一定程度上减缓蓝藻水华与湖泊富营养化、气候变暖之间的恶性循环，为湖泊碳循环和蓝藻水华灾害防控提供科学数据支撑和理论参考.  相似文献   

针铁矿对湖泊草、藻来源可溶有机质的非均质吸附     

章奇  居琪  李健欣  曹驰程  江和龙  张晖 《湖泊科学》2020,32(4):1041-1049

为探究富营养化湖泊中自生源可溶有机质(DOM)在泥水界面的吸附行为,以马来眼子菜(Potamogeton malaianus)和铜绿微囊藻(Microcystis aeruginosa)释放的DOM为代表,考察针铁矿对草、藻源DOM中不同组分的吸附特征.三维荧光平行因子分析表明类富里酸组分C1和类胡敏酸组分C4的含量很低,而类蛋白物质(类酪氨酸组分C2和类色氨酸组分C3)分别占草、藻源DOM荧光组成的70%和93%. 2种DOM均可被针铁矿吸附,吸附过程符合伪一级动力学.通过等温线拟合发现针铁矿吸附藻源DOM的非线性更强,饱和吸附量(23.77 mg/g)高于草源DOM(19.10 mg/g).特别地,类蛋白组分呈现非线性吸附,而类腐殖物质的吸附近似线性,且针铁矿对于DOM各荧光组分的吸附量顺序为:C3C2 C4 C1,此非均质吸附特征与DOM组分的初始含量、分子大小、芳香性及有效吸附位点有关.红外光谱证实氨基、羧基和羟基是吸附过程中的重要官能团.因此,草、藻源DOM显著改变了针铁矿表面的有机物质组成,影响湖泊沉积物的生物地球化学行为.  相似文献   

Effects of long-term cyclic horizontal loading on bucket foundations in saturated loose sand     

《Applied Ocean Research》2019

A 1-g model experimental study was conducted to investigate the accumulated rotations and unloading stiffness of bucket foundations in saturated loose sand. One-way horizontal cyclic loading was applied to model bucket foundations with embedment ratios 0.5 and 1.0. Up to 10⁴ cycles of loading were applied at a frequency of 0.2 Hz varying load amplitudes. The accumulated rotation of the bucket foundations increased with the number of cycles and the load amplitudes. Empirical equations were proposed to describe the accumulated rotation of the foundations. The unloading stiffness of foundations increased with the number of cycles but decreased with an increase in load amplitude. The initial unloading stiffness of L/D = 1.0 (L is skirt length; D is foundation diameter) was approximately twice that of L/D = 0.5. Excess pore water pressure difference of 50% was observed between L/D = 0.5 and 1.0. The suction and static capacity of the bucket increased with increase of bucket embedment ratio with a difference of 69.5% and 73.6% respectively between L/D = 0.5 and 1.0.  相似文献   

大气负荷对新疆地区地壳形变和地面重力变化的影响     

王海涛  王斌  王伟  章传银 《大地测量与地球动力学》2019,39(2):189-194

基于ECMWF全球大气模型和中国地面气候资料日值数据集中新疆及周边的气象站气压数据，根据弹性地壳形变理论，采用移去-恢复法，利用负荷格林函数法和球谐函数法，计算新疆及周边区域2011~2015年大气负荷变化对地壳垂直、水平形变的影响，同时采用大气导纳方法计算大气变化对地面重力的影响。结果表明，大气负荷对新疆地区垂直形变的影响达到cm级，对地面重力的影响可达10 μGal；大气负荷影响具有明显的季节性。  相似文献   

Drying increases organic colloidal mobilization in the karst vadose zone: Evidence from a 15-year cave-monitoring study     

Jin Liao  Chaoyong Hu  Xiuli Li  Jiaoyang Ruan 《水文研究》2021,35(4):e14163

Understanding the hydrological processes of colloids within the karst vadose zone is vital to the security of karst groundwater and providing appropriate paleohydrological explanations of colloid-facilitated metals in speleothem. This study addresses the mobilization mechanisms driving colloidal organic matter (COM) transport in the karst vadose zone using a 15-year long monthly monitoring dataset from a cave drip point (HS4) in Heshang Cave, Qingjiang Valley, China. Variations in COM concentrations were reported as the fluorescence difference values of raw and filtered (<0.22 μm) samples at an excitation wavelength of 320 nm and emission wavelength of ~400 nm. A fluorescence humification index (HIX) lower than 0.8 and an autochthonous index (BIX) higher than 1.2 indicated that the origin of COM was mainly from the karst vadose zone, rather than the soil zone. The COM concentration varied from 0.001 to 0.038 Raman Unit (RU), with evident seasonal fluctuations. Rising limbs for COM values occurred prior to rising limbs within a dripwater hydrograph; moreover, the COM peak values corresponding to the beginning of the increasing hydrograph generally suggested that the mobilization of COM reflected the movement of the air–water interface (AWI) in the karst vadose zone rather than rainfall intensity or flow velocity. COM peak values were positively correlated with the antecedent drying duration and negatively correlated with HIX values. These phenomena may be explained by the increased amount of organic matter that was aggregated and absorbed on the surface of carbonate in the karst vadose zone during a longer drying duration. Moreover, the longer drying duration was also beneficial to autochthonous biological activity, which subsequently decreased the HIX value of the organic matter in the karst vadose zone. The movement of AWI and the drying duration are both controlled by the outside weather conditions. This study is therefore conducive to evaluating the security of karst groundwater in response to climate change, and challenges prevailing paleoclimate interpretations of colloid-facilitated metal abundance timeseries reported from speleothems.  相似文献   

地震作用下纤维编织网增强钢筋混凝土柱的抗震性能分析          下载免费PDF全文

张童  雷真  朱争光  吴亚玲 《地震工程学报》2020,42(1):57-62,72

为了解地震作用下纤维编织网增强钢筋混凝土柱的抗震性能,采用钢筋、混凝土、纤维编织网浇筑纤维编织网增强钢筋混凝土柱,编织网主材为碳、玻璃纤维束;利用电液伺服加载系统为试件加载地震作用,监测相关数据,部分试件置入氯化钠溶液进行多次干湿循环。不同环境下的实验结果显示:纤维编织网层数越多,纤维编织网增强钢筋混凝土柱承载能力越强,抗震性能越好;配箍间距较大时,纤维编织网增强钢筋混凝土柱的抗震性能仅在地震作用的后期呈现较差状态;干湿循环次数越多,纤维编织网增强钢筋混凝土柱承载力越弱,抗震性能越差。对于氯盐环境而言,可增加纤维编织网增强钢筋混凝土柱的抗腐蚀措施改善抗震性能。适当增加纤维编织网的数量、降低配箍间距有利于提升纤维编织网增强钢筋混凝土柱的抗震性能。  相似文献