Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Spatio-temporal analysis of female breast cancer incidence in Shenzhen,2007-2012

Introduction:Breast cancer is a leading tumor with a high mortality in women.This study examined the spatio-temporal distribution of the incidence of female breast cancer in Shenzhen between 2007 and 2012.Methods:The data on breast cancer incidence were obtained from the Shenzhen Cancer Registry System.To describe the temporal trend,the average annual percentage change(AAPC) was analyzed using a pinpoint regression model.Spatial autocorrelation and a retrospective spatio-temporal scan approach were used to detect the spatio-temporal cluster distribution of breast cancer cases.Results:Breast cancer ranked first among different types of cancer in women in Shenzhen between 2007 and 2012 with a crude incidence of 20.0/100,000 population.The age-standardized rate according to the world standard population was 21.1/100,000 in 2012,with an AAPC of 11.3%.The spatial autocorrelation analysis showed a spatial correlation characterized by the presence of a hotspot in south-central Shenzhen,which included the eastern part of Luohu District(Donghu and Liantang Streets) and Yantian District(Shatoujiao,Haishan,and Yantian Streets).Five spatio-temporal cluster areas were detected between 2010 and 2012,one of which was a Class 1 cluster located in southwestern Shenzhen in 2010,which included Yuehai,Nantou,Shahe,Shekou,and Nanshan Streets in Nanshan District with an incidence of 54.1/100,000 and a relative risk of 2.41;the other four were Class 2 clusters located in Yantian,Luohu,Futian,and Longhua Districts with a relative risk ranging from 1.70 to 3.25.Conclusions:This study revealed the spatio-temporal cluster pattern for the incidence of female breast cancer in Shenzhen,which will be useful for a better allocation of health resources in Shenzhen.

Land use change in Bohai Rim: a spatial-temporal analysis

Based on RS and GIS methods, land use information for 1985 and 1995 was acquired from TM images and analyzed. Then on both spatial and temporal aspects, this paper analyzes land use change in three provinces of Hebei, Shandong and Liaoning and two municipalities of Beijing and Tianjin in the Bohai Rim covering the period of 1985 to 1995. The extent, rate, areal difference and trend of various types of land use changes in the region, as well as spatial changes of major types of land use, their distribution characteristics and regional orientation are revealed. The regional characteristics of land use are elaborated, so as to provide effective policy support for sustainable land use in the area around the Bohai Bay.

Spatiotemporal Property Analysis of Birth Defects in Wuxi,China

Objective To describe the temporal trends and spatial patterns of birth defects occurring in Wuxi, a developed region of China. Methods Wavelet analysis was used to decompose the temporal trends of birth defect prevalence based on the birth defect rates over the past 16 years. Birth defect cases with detailed personal and family information were geo-coded and the relative risk in each village was calculated. General G statistic was used to test the spatial property with different scales. Results Wavelet analysis showed an increasing temporal trend of birth defects in this region. Clustering analysis revealed that changes continued in the spatial patterns with different scales. Conclusion Wuxi is confronted with severe challenges to reduce birth defect prevalence. The risk factors are stable and show no change with spatial scale but an increasing temporal trend. Interventions should be focused on villages with a higher prevalence of birth defects.

Spatio-Temporal Air Pollutant Characterization for Urban Areas

Urban pollution has now become increasingly recognized as an important determinant of air pollution in developed countries. The effect of urban air pollution in developing countries, on the other hand, has not been adequately addressed in the data Spatio-temporal time series. Thus, this study was intended to characterize the effect of urbanization on air pollution for an urbanized Klang Valley, Malaysia using Spatio-temporal data from 2008 to 2017. The Air Pollution Index (API) data and local pollutant concentration were employed to establish the links between urban air pollution. The analysis will be supported by determining the source of pollutants during the study period using Principal Component Analysis (PCA). The study identified that Carbon monoxide (CO), Nitrogen Dioxide (NO2), and Ozone (O3) are the major air pollution that has contributed to degrading air quality in the Klang Valley due to the vehicles, combustion process, and industries.

面向源-目的地流的多元时空数据可视分析

交通智能(IC)卡可以记录居民的移动出行,反映居民的源-目的地(OD)信息;但智能卡记录的OD流数据规模大,直接可视化空间分布容易导致视觉杂乱,并且多元数据类型多,更难以和流数据结合对比分析。首先,针对直接可视化大规模OD数据的空间分布容易视觉遮挡的问题,提出基于正交非负矩阵分解(ONMF)的流聚类方法。所提方法对源-目的地数据聚类后再可视化,可以减少不必要的遮挡。然后,针对多元时空数据类型多难以结合对比分析的问题,设计了公交站点多元时序数据视图。该可视化方法将公交站点的流量大小和空气质量、空气温度、相对湿度、降雨量这四类多元数据在同一时间序列上编码,提高了视图的空间利用率并且可以对比分析。再次,为了辅助用户探索分析,开发了基于OD流和多元数据的交互式可视分析系统,并设计了多种交互操作提升用户探索效率。最后,基于新加坡交通智能卡数据集,从聚类效果和运行时间对该聚类方法评估。结果显示,在用轮廓系数评估聚类效果上,所提方法比原始方法提升了0.028,比用K均值聚类方法提升了0.253;在运行时间上比聚类效果较好的ONMFS(ONMF through Subspace exploration)方法少了254 s。通过案例分析和系统功能对比验证了系统的有效性。

1971-2022年河南省水汽压与能见度的时空分布及其关联

为探究河南省水汽压和能见度的时空分布特征和相关性,利用1971-2022年河南省118个国家级气象站的日最高水汽压和日最小能见度数据,分析了河南省年平均最高水汽压和最小能见度的时空变化特征及二者的相关性。结果表明:(1)年平均最高水汽压呈显著上升趋势,其气候倾向率达0.25 hPa/10a;最高水汽压在1998年发生由低到高的突变;豫中南、豫东及豫北水汽压上升最为显著;最高水汽压变化幅度大值区主要位于豫中南大部、豫西南部分县市。(2)年平均最小能见度呈显著下降趋势,其气候倾向率为-0.56 km/10a;最小能见度在2014年出现下降突变;豫西、豫西南、豫北部分县市及商丘、信阳局部能见度下降显著,变化幅度较大。(3)河南省大部分地区年平均最高水汽压与最小能见度存在显著的负相关(区域平均相关系数约为-0.41),水汽压升高(降低)易引起能见度降低(升高)。

基于组合权重-TOPSIS模型的贵州省水资源承载力评价

以贵州省为研究对象,基于2010—2020年水资源公报、统计年鉴数据等相关数据,从水资源、社会、经济、生态环境4个方面选取16项指标,构建水资源承载力评价指标体系,采用组合权重-TOPSIS模型对研究区88个县进行水资源承载力评价分析。结果表明:1)贵州省2020年县域水资源承载变化范围为0.329~0.716,总体水资源承载状况差异显著,较2010年水资源承载力有明显提升,且2020年水资源承载力呈现黔中区域的水资源承载力较低、周边区域较高的变化趋势,黔东区域水资源承载力最高。2)利用ArcGIS对贵州省县域的水资源承载指数进行全局莫兰指数分析,贵州省县域水资源承载力的莫兰指数为0.515,z值显著大于临界值2.58,p值小于显著性水平,贵州省水资源承载指数呈现空间集聚趋势。3)通过地理探测器分析可知,单因子对水资源承载力影响解释力最大的是人均水资源占有量;双因子交互作用下对水资源承载力的影响程度结果显示,人均水资源占有量是水资源承载力的主导因子。

基于耦合协调分析的火灾-经济-环境时空演化研究

为探究火灾、经济、环境的时空演化特征,基于2000—2019年中国火灾、经济、环境数据,建立火灾-经济-环境耦合协调模型,研究火灾、经济、环境系统的耦合发展水平;结合探索性空间数据分析(ESDA)方法研究我国31个省域各子系统时空演变特征及聚集性,并基于Moran'I检验开展火灾、经济、环境空间相关性分析。研究结果表明:2000—2019年火灾、经济和环境综合发展耦合良好。从时间维度上,2000—2019年耦合度和协调度呈上升趋势,耦合度受火灾综合得分影响,协调度受经济子系统影响;从空间维度上,经济发展是影响31个省域耦合协调度的主要因素。从耦合关系时空演变分析看,省域耦合度随时间呈聚集状态,耦合协调度在空间聚集中呈随机性。火灾、经济和环境对耦合协调的不同影响,导致协调类型及空间聚集状态不同。

重庆市渝中区长江-嘉陵江流域自动监测站2022年水质时空变化分析

采用地表水环境质量标准中的单因子法分析评价重庆市渝中区长江、嘉陵江流域内4个水质自动监测站2022年水质数据,选取水温、溶解氧、高锰酸盐指数、氨氮、总磷5个因子研究水质时空变化特征,使用Pearson相关系数法对8个水质监测参数相关性进行研究,分析了降雨对水质的影响及强降雨期间渝中区污水预处理厂溢流对下游水质自动监测站的影响。结果表明:长江、嘉陵江的出境断面均略优于入境断面,表明渝中区段水质未受到影响;从时间变化来看,4个水质自动监测站月变化趋势基本一致,高锰酸盐指数、氨氮、总磷3种污染物均呈现明显的“双峰”现象,高值基本出现在5—6月、9—10月;通过Pearson相关系数分析,降雨量与高锰酸盐指数呈负相关,与总磷呈正相关,但相关性均不显著;通过对8个水质监测参数进行相关性分析得知,高锰酸盐指数与总磷是影响我区两江水质的重要因素。

1990-2018年中国生态系统水源涵养功能时空格局与演变

探明生态系统水源涵养服务格局演变对中国生态系统水源涵养保护和管理具有重要意义。采用水量平衡模型,探明1990—2018年中国生态系统水源涵养分布特征,从全国、分区和栅格3个尺度揭示中国水源涵养演变规律。结果表明:(1)中国生态系统水源涵养时空异质性显著,整体南高北低、东高西低。不同植被水源涵养服务差异显著,以常绿阔叶林最高,草地最低。(2)中国水源涵养服务随高程升高呈阶梯式下降,随坡度变化因坡度梯度而不同,平坡区随坡度升高而升高,缓坡—陡坡区随坡度升高而降低。(3)中国多年平均水源涵养量为1.54×10^(12)m^(3)/a,以热带-亚热带季风区为主导,约占总量的77.9%。水源涵养服务演变全国尺度显著下降,分区尺度仅温带大陆气候区显著下降。(4)栅格尺度仅16.0%栅格变化显著,主要为极显著降低和显著降低,约占栅格总数的7.61%和5.30%,主要分布于藏东南、云贵高原西部、冀东北、浑善达克沙地、天山东麓和中国台湾省等地,它们是中国水源涵养保护与建设的重点区域。

2001-2018年华北平原森林面积变化及影响因素分析

探讨华北平原森林转型缓慢的影响因素,可以为国家制定促进华北平原森林转型的政策措施提供科学依据.利用2001-2018年土地利用/覆被数据,分析华北平原森林变化时空特征.基于华北平原248个样本区县的自然与社会经济数据,构建线性回归模型,分析森林转型缓慢的影响因素.结果表明:(1) 18年间,华北平原森林转型进入面积净增加阶段,但进程仍然缓慢.林地面积增长的主要来源和流失的主要去向均为耕地和草地,林地与耕地两者之间转换频繁.(2)森林净增加的热点区域主要分布在山东中部丘陵地区、山东半岛沿海地区,森林净增加的冷点区域主要集中在淮北平原一带.(3)经济发展路径和国家森林政策路径在华北平原森林转型过程中作用不明显,其降水少而蒸发量大的自然条件、竞争性土地利用情况以及农业机械化发展是制约华北平原森林转型的主要原因.建议优化农田防护林带布局,实施更具针对性的林业政策和精细化的管理措施,加强对江苏黄淮平原一带林草一体保护,合理推动平原地区林业产业发展,协调好农、林业结构关系,实现粮食生产与生态环境建设的共同发展.

Analysis of spatio-temporal pattern and driving force of land cover change using multi-temporal remote sensing images

Landuse and land cover change is regarded as a good indicator that represents the impact of human activities on earth’s environment.When the large collection of multi-temporal satellite images has become available,it is possible to study a long-term historical process of land cover change.This study aims to investigate the spatio-temporal pattern and driving force of land cover change in the Pearl River Delta region in southern China,where the rapid development has been witnessed since 1980s.The fast economic growth has been associated with an accelerated expansion of urban landuse,which has been recorded by historical remote sensing images.This paper reports the method and outcome of the research that attempts to model spatio-temporal pattern of land cover change using multi-temporal satellite images.The classified satellite images were compared to detect the change from various landuse types to built-up areas.The trajectories of land cover change have then been established based on the time-series of the classified land cover classes.The correlation between the expansion of built-up areas and selected economic data has also been analysed for better understanding on the driving force of the rapid urbanisation process.The result shows that,since early 1990s,the dominant trend of land cover change has been from farmland to urban landuse.The relationship between economic growth indicator(measured by GDP)and built-up area can well fit into a linear regression model with correlation coefficients greater than 0.9.It is quite clear that cities or towns have been sprawling in general,demonstrating two growth models that were closely related to the economic development stages.

Video Analysis Based on Volumetric Event Detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television （CCTV） data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today＇s approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called ＂pre-suspicion＂ mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.

Application of the Distance to Natural (D2N) Index and Statistical Analysis of Different Anthropic Uses of the Río Grande De Comitán Watershed, Chiapas, México

The intensification of anthropic uses (i.e., increase of the hemerobic condition) threatens the remnants of native vegetation due to the reduction of its self-regulation capacity. In this research, the Distance to Nature (D2N) index for land use and land cover was applied in the Río Grande de Comitán watershed (Southern Mexico) to answer the following questions: 1) What were the land use dynamics observed in the Rio Grande de Comitán watershed in the trajectory through 1999, 2009 and 2019? 2) Does the subcategorization of the D2N allow one to identify which anthropic uses influence more the territorial expression of the watershed? To answer these questions, we performed a supervised classification of land use and land cover was performed in this watershed, and for the D2N index, the classification was simplified to three-category scale for the subcategorization of the anthropic component. Through Principal Component Analysis (PCA), we identified that agricultural anthropogenic use had the greatest influence on territorial expression. The reported scenario indicates a trend of gradual and continuous reduction of naturalness over the last 20 years. Additionally, the D2N index proved to be a useful tool to demonstrate both the anthropic impact, with the simplified scale, and the component that most influences the territory, by subcategorizing the anthropic scale.

1980—2020年全球重大洪灾时空特征探析

为充分理解全球洪涝灾害的时空演变规律,基于长时间序列全球历史洪灾数据,运用数理统计和GIS空间分析方法,在不同空间尺度和年代际、年际的时间尺度上,全面分析了1980—2020年重大洪涝灾害的时空特征。结果表明:①全球洪灾次数在21世纪前10 a达到峰值,死亡和影响人口在1990s达到峰值,累计经济损失在2010s达到峰值,次均经济损失在1990s和2010s最高;②洪灾发生次数及造成的经济损失在1980—2020年期间呈显著上升趋势,每次洪灾造成的人口损失呈现下降趋势;③亚洲洪涝灾害严重,洪灾的发生次数、死亡人数、影响人口及经济损失的累计值分别占全球总数的41%、68%、95%和63%,然而包括中国在内的亚洲诸多国家的洪灾人口损失呈下降趋势;④全球重大洪灾呈东西向分布,灾害重心有南移趋势,洪灾由集中趋于分散,影响区域逐渐变广。

晋中地区2001-2020年水资源时空演化特征分析

晋中是一个水资源严重缺乏的地区,1956年以来水资源总量和人均占有水资源量双双大幅下降,水资源短缺问题亟待解决。本文基于晋中地区2001—2020年气候和水资源数据,采用逐年法与系列法、行政与流域、地表水和地下水三位一体的方式分析其水资源时空演化特征。结果表明,晋中气候向暖湿化方向发展,水资源上升趋势显著,但地表水和地下水变化不尽相同。水资源时空分布不均,按区域西缺东丰;按流域海河流域较黄河流域更丰富;按空间地表水西少东多,地下水西多东少;按时序地表水较地下水旱涝急转现象更突出。

1971-2020年广西喀斯特地区高温灾害时空变化特征

利用线性趋势分析和GIS空间插值等方法,对广西喀斯特地区1971—2020年≥35℃高温日数、≥35℃有效积温进行分析,初步探究其时空分布规律。结果表明,1971—2020年广西喀斯特地区年平均≥35℃高温日数、≥35℃有效积温均呈上升变化趋势,气候倾向率分别2.8 d·(10a)^(-1)、3.5℃·(10a)^(-1);7—8月高温更为集中。空间分布上,≥35℃高温日数和≥35℃有效积温南北差异明显,呈现西南高、东北低的特点,崇左市为主要的高值区。从高温变化趋势空间分布来看,西南和东北均呈增多变化趋势,崇左市和桂林市增多趋势明显。

基于注意力特征融合时空图网络的超短期风电功率预测

为提高风电功率的预测精度,综合考虑时间和空间多维度因素的影响,提出了一种基于注意力机制和多阶段特征融合的时空图神经网络(Spatio-temporal graph neural network with attention mechanism and multistage feature fusion,AMF-STGNN)的超短期风电功率预测方法。首先基于Pearson相关系数法对数据特征进行降维,确定影响风电功率的关键因素。然后构建AMF-STGNN预测模型。该模型主要由时空关联网络构建模块和多维度时空特征抽取模块组成。通过时空关联网络构建模块构建时空图,以揭示风电气象因素的空间连接关系。通过多维度时空特征抽取模块应用时间卷积和图卷积挖掘数据的时空特征,并利用注意力机制学习重要特征。此外,该方法还引入残差结构和多阶段特征融合结构提高模型的表达能力。最后以宁夏3个风电场真实数据为例,验证了所提方法在提升风电功率预测精度方面的有效性。