Visualization and damage assessment for flooded area

A practical method for visualizing flood area and evaluating damage is presented, which consists of two technical approaches: self-programming and adapting commercial GIS platforms. The low-cost and easy-to-use GIS-Based model developed by self-programming can meet current requirements of most local authorities, especially in developing countries. In this model, two cases, non-source flood and source flood, are distinguished and the Seed-spread algorithm suitable for source-flood is discussed; The flood damage is assessed by overlaying the flood area range with thematic maps and other related social and economic data. and all thematic maps are converted to raster format before overlay analysis. Two measures are taken to improve the operation efficiency of speed seed-spreed algorithm. The accuracy of the model mainly depends on the resolution and precision of the DEM data, and the accuracy of registering all raster layers and the quality of attribute data.     

Capturing Raster Data From Scanned Thematic Maps Using Desktop Graphics Software

Data capture from paper maps remain a slow and costly part of many Geographic Information System projects. In this paper a simple method is described which makes use of the facilities of desktop graphics software to capture raster data from scanned thematic maps. The first stage is to use the flood fill tool to identify the regions of the map that represent the data values and set them to a separate colour for each thematic category. This edited image is then imported into a GIS, where a specially written majority filter is used to classify any remaining pixels to produce a raster GIS layer. The technique is tested on samples from three maps, giving accuracy levels of over 90% in all cases when compared with digitising the same maps by hand. The technique could be useful for situations where a rapid and simple means of data capture is needed and could be developed further by drawing on techniques for contextual classification rather than relying on a general purpose flood fill algorithm.     

Multi-hazard assessment using machine learning and remote sensing in the North Central region of Vietnam

Natural hazards constitute a diverse category and are unevenly distributed in time and space. This hinders predictive efforts, leading to significant impacts on human life and economies. Multi-hazard prediction is vital for any natural hazard risk management plan. The main objective of this study was the development of a multi-hazard susceptibility mapping framework, by combining two natural hazards—flooding and landslides—in the North Central region of Vietnam. This was accomplished using support vector machines, random forest, and AdaBoost. The input data consisted of 4591 flood points, 1315 landslide points, and 13 conditioning factors, split into training (70%), and testing (30%) datasets. The accuracy of the models' predictions was evaluated using the statistical indices root mean square error, area under curve (AUC), mean absolute error, and coefficient of determination. All proposed models were good at predicting multi-hazard susceptibility, with AUC values over 0.95. Among them, the AUC value for the support vector machine model was 0.98 and 0.99 for landslide and flood, respectively. For the random forest model, these values were 0.98 and 0.98, and for AdaBoost, they were 0.99 and 0.99. The multi-hazard maps were built by combining the landslide and flood susceptibility maps. The results showed that approximately 60% of the study area was affected by landslides, 30% by flood, and 8% by both hazards. These results illustrate how North Central is one of the regions of Vietnam that is most severely affected by natural hazards, particularly flooding, and landslides. The proposed models adapt to evaluate multi-hazard susceptibility at different scales, although expert intervention is also required, to optimize the algorithms. Multi-hazard maps can provide a valuable point of reference for decision makers in sustainable land-use planning and infrastructure development in regions faced with multiple hazards, and to prevent and reduce more effectively the frequency of floods and landslides and their damage to human life and property.     

Application of frequency ratio,weights of evidence and evidential belief function models in landslide susceptibility mapping

The landslide hazard occurred in Taibai County has the characteristics of the typical landslides in mountain hinterland. The slopes mainly consist of residual sediments and locate along the highway. Most of them are in the less stable state and in high risk during rainfall in flood season especially. The main purpose of this paper is to produce landslide susceptibility maps for Taibai County (China). In the first stage, a landslide inventory map and the input layers of the landslide conditioning factors were prepared in the geographic information system supported by field investigations and remote sensing data. The landslides conditioning factors considered for the study area were slope angle, altitude, slope aspect, plan curvature, profile curvature, distance to faults, distance to rivers, distance to roads, normalized difference vegetation index, lithological unit, rainfall and land use. Subsequently, the thematic data layers of conditioning factors were integrated by frequency ratio (FR), weights of evidence (WOE) and evidential belief function (EBF) models. As a result, landslide susceptibility maps were obtained. In order to compare the predictive ability of these three models, a validation procedure was conducted. The curves of cumulative area percentage of ordered index values vs. the cumulative percentage of landslide numbers were plotted and the values of area under the curve (AUC) were calculated. The predictive ability was characterized by the AUC values and it indicates that all these models considered have relatively similar and high accuracies. The success rate of FR, WOE and EBF models was 0.9161, 0.9132 and 0.9129, while the prediction rate of the three models was 0.9061, 0.9052 and 0.9007, respectively. Considering the accuracy and simplicity comprehensively, the FR model is the optimum method. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.     

MapGIS 在地质制图中的应用研究

简要讨论了MapGIS的主要功能,阐述了利用MapGIS软件制作地质图设计与制作成图的过程,以及不同专题图专题内容的表示方法。 MapGIS制图技术简化了纷繁复杂的传统地质制图过程,而且美观精确;空间分析技术可以将矢量数据和栅格数据综合制作出各种图形和图像文件,方便分析。介绍了地质图制作的工作流程、图像处理方法,以及图像生成之后地质图的校正美化。     

Remote sensing and geoinformation center of Mongolia: A brief outlook

Abstract

A GIS based approach is proposed for the integration of three thematic maps viz. geomorphology, drainage density and slope using fuzzy logic for the assessment of ground water resource potential of a soft rock terrain of Midnapur District, West Bengal, India. The geomorphology and drainage density maps of the area are prepared from IRS‐1B LISS‐II data, and the slope map is obtained from the contours depicted on the topographic map of Survey of India. Each feature of all the thematic maps is assigned with individual fuzzy set values within a range between 0 to 1 according to their relative importance in the prediction of ground water occurrence. The maps are then integrated through fuzzy operation to model the ground water potential zone of the study area. The evolved model while verified with surface geophysical results is found to be in good agreement.     

Frequency ratio modelling using geospatial data to predict Kimberlite Clan of rock emplacement zones in Dharwar Craton,India

Kimberlite clan of rocks (KCR) comprising of mantle derived ultrabasic rocks such as Kimberlite and related Lamproites and Lamprophyres,are the primary source of diamond. Locating the KCR is first step in the diamond exploration, which is highly challenging in the field due to (i) very small spatial extent of KCR pipes (ii) high susceptibility of KCR to weathering and alteration on exposure to atmosphere, owing to their ultrabasic composition. Predictive statistical models using the geospatial data are often used to minimize the search and the present work attempts to apply the Frequency Ratio (FR) based predictive model in GIS to prepare KCR potential zone maps based on the relationship between the already explored KCR locations and the factors that favour their emplacement. Wajrakarur Kimberlite Field (WKF) in the Dharawar Craton of India, with more than 30 explored kimberlite pipes is selected as the study area. Geospatial technology has been used to generate thematic maps such as known KCR pipe locations, lineament density, lineament buffer zone, lineament intersection buffer zone, drainage anomaly buffer zone, geomorphology, and classified image showing distribution of mineral such as clay, iron oxide and calcrete, which are surface expression of KCR emplacement from various sources. Landsat 8 OLI satellite data, ASTER DEM were used in preparing the geomorphology, lineament map, and band ratio based mineral classified map. The thematic maps were converted to raster grid of 10 sq. m. FR values for each unit in each thematic map were obtained by correlating the spatial relationship between thematic map and the 25 locations of the 33 “known” KCR locations in WKF used for FR modelling. Cumulative FR value were obtained by carrying out overlay analysis of the thematic maps, which are classified into five classes by Natural Breaking method as (i)Very Low Favourable (VLF), (ii) Low Favourable (LF), (iii)Moderate favourable (MF), (iv)High Favourable (HF), and (v)Very High Favourable (VHF). The model was validated by ground verification at random sites and statistical method. During the ground visit, we observed KCR-like lithology’s at four new sites that have calcrete exposure at limited spatial extent and also some pieces of ultrabasic rocks similar to the explored sites. To ascertain their chemical composition of the samples were plotted in the MgO-K₂O-Al₂O₃ ternary diagram. All the four samples fall in the Kimberlite/Lamproite field confirming them to be KCR. The FR predictive model was also validated statistically. Total 13 locations, including 8 site out of 33 known KCR locations, one newly discovered pipe by GSI and the four locations discovered during this study were used for the validation. Statistical validation shows that 84% of model accuracy is achieved. The study reveals that Lineament Intersection, and circular drainage anomaly in 3rd order streams, lineament density are significant themes in predicting KCR emplacement zones. The study demonstrates the utility of statistical based model such as FR model in predicting the location of KCR emplacement, even with statistically insignificant distribution of KCRs and can be applied elsewhere in the world to locate the KCRs. In the process, we report discovery of four new KCR pipes in the WKF.     

武汉市地理国情监测更新方法研究与实践

第一次地理国情普查工作已经结束,地理国情数据动态更新将成为普查工作的重点内容。本文结合地理国情普查及数据更新工作,充分整合已有数据资源优势,面对武汉防汛抗灾的严峻形势,紧急制订出防汛应急测绘保障方案,完成渍水区域地表高程和排水管线专题地图及数据收集,为武汉市提供基础测绘应急保障和技术服务支撑。     

All Equal-Area Map Projections Are Created Equal,But Some Are More Equal Than Others

High-resolution regional and global raster databases are currently being generated for a variety of environmental and scientific modeling applications. The projection of these data from geographic coordinates to a plane coordinate system is subject to significant areal error. Sources of error include users selecting an inappropriate projection or incorrect parameters for a given projection, algorithmic errors in commercial geographic information system (GIS) software, and errors resulting from the projection of data in the raster format. To assess the latter type of errors, the accuracy of raster projection was analyzed by two methods. First, a set of 12 one-degree by one-degree quadrilaterals placed at various latitudes was projected at several raster resolutions and compared to the projection of a vector representation of the same quadrilaterals. Second, several different raster resolutions of land cover data for Asia were projected and the total areas of 21 land cover categories were tabulated and compared. While equal-area projections are designed to specifically preserve area, the comparison of the results of the one-degree by one-degree quadrilaterals with the common equal area projections (e.g., the Mollweide) indicates a considerable variance in the one-degree area after projection. Similarly, the empirical comparison of land cover areas for Asia among various projections shows that total areas of land cover vary with projection type, raster resolution, and latitude. No single projection is best for all resolutions and all latitudes. While any of the equal-area projections tested are reasonably accurate for most applications with resolutions of eight-kilometer pixels or smaller, significant variances in accuracies appear at larger pixel sizes.     

从栅格数据直接建立拓扑关系的算法研究

本文提出了从栅格数据直接建立拓扑关系的思想,用跟踪过程中容易获得的拓扑信息来优化拓扑生成的算法模型,借以提高拓扑生成的效率。本文还提出用连通性区域填充的方法处理各种任意复杂岛的思想。     

Modelling forest canopy gaps using LiDAR-derived variables

Remote sensing has revolutionized forest management and has been widely employed to model canopy gaps. In this study, a canopy height model (CHM) and an intensity raster (IR) derived from light detection and ranging (LiDAR) data were used to model canopy gaps within a four-year-old Eucalyptus grandis forest using an object-based image analysis (OBIA) approach. Model thematic accuracies using the CHM, intensity raster and combined data set (CHM and IR) were all above 90%, with KHAT values ranging from 0.88 to 0.96. Independent test thematic accuracies were also above 90%, with KHAT values ranging from 0.82 to 0.91. A comparative area-based assessment yielded accuracies ranging from 70 to 90%, with the highest accuracies achieved using the combined data set. The results of this study show that using a CHM and intensity raster, and an OBIA approach, provides a viable framework to accurately detect and delineate canopy gaps within a commercial forest environment.     

A genetic algorithm for locating optimal sites on raster suitability maps

Locating optimal sites on raster suitability maps is a complex problem when the size of the sites is larger than the cell size. There are a number of techniques for generating suitability maps, but these maps are not solutions to the site location problem. Feasible solutions are clusters of contiguous cells which meet spatial criteria concerning the size and shape of the clusters. Locaring optimal sites involves a trade-off between the intrinsic suitability of individual cells and the spatial configuration of cells. This paper describes a genetic algorithm which searches for optimal clusters and thereby locates optimal sites. The genetic algorithm uses a parameterized regiongrowing program to translate numeric strings into regions on a raster and employs raster GIS functions to evaluate utility scores. In a range of simulated problems, comparisons with an exhaustive search show that the genetic algorithm is efficient and robust. The results indicate that the genetic algorithm can find good solutions to real problems when exhaustive search methods are impractical.     

一种抗切割处理的栅格地理数据水印算法

本文提出了一种基于精度特征的栅格地理数据盲水印算法。首先,分析了栅格地理数据切割处理的特征及其对常规水印算法产生的影响,在此基础上,结合栅格地理数据精度特点,依据栅格地理数据的有效位平面生成水印信息位,而后,采用量化思想将水印信息嵌入对应的可变位平面。实验表明,所提出的水印算法在保证栅格地理数据精度的基础上,对于任意尺寸的数据都有较好的适用性,同时,对于任意强度的切割处理,该算法都体现了良好的鲁棒性。     

Algorithms for Tetrahedral Network(ten) generation

The Tetrahedral Network(TEN) is a powerful 3-D vector structure in GIS, which has a lot of advantages such as simple structure, fast topological relation processing and rapid visualization. The difficulty of TEN application is automatic creating data structure. Although a raster algorithm has been introduced by some authors, the problems in accuracy, memory requirement, speed and integrity are still existent. In this paper, the raster algorithm is completed and a vector algorithm is presented after a 3-D data model and structure of TEN have been introducted. Finally, experiment, conclusion and future work are discussed.     

A building extraction approach for Airborne Laser Scanner data utilizing the Object Based Image Analysis paradigm

In the past two decades Object-Based Image Analysis (OBIA) established itself as an efficient approach for the classification and extraction of information from remote sensing imagery and, increasingly, from non-image based sources such as Airborne Laser Scanner (ALS) point clouds. ALS data is represented in the form of a point cloud with recorded multiple returns and intensities. In our work, we combined OBIA with ALS point cloud data in order to identify and extract buildings as 2D polygons representing roof outlines in a top down mapping approach. We performed rasterization of the ALS data into a height raster for the purpose of the generation of a Digital Surface Model (DSM) and a derived Digital Elevation Model (DEM). Further objects were generated in conjunction with point statistics from the linked point cloud. With the use of class modelling methods, we generated the final target class of objects representing buildings. The approach was developed for a test area in Biberach an der Riß (Germany). In order to point out the possibilities of the adaptation-free transferability to another data set, the algorithm has been applied “as is” to the ISPRS Benchmarking data set of Toronto (Canada). The obtained results show high accuracies for the initial study area (thematic accuracies of around 98%, geometric accuracy of above 80%). The very high performance within the ISPRS Benchmark without any modification of the algorithm and without any adaptation of parameters is particularly noteworthy.     

Algorithms for Tetrahedral Network(ten) generation

1 IntroductionA fulI 3-D GIS is needed in rnany gerecience ap-plication fields, such as goology, mine, oil and en-virorunental engineering, etc. Not only medelingand visualization but also rnanipulation are requiredin these applications. But the traditional 2-D GIShas difficulty in satisfying these fequirements, es-pecially in the representation of vertical infOrma-tion. Although a number Of studies have been dOneby researchers in the world (Molenaar, 1992; RaPerand Kelk, 199l; Li Rong…     

Satellite-based investigation of flood-affected rice cultivation areas in Chao Phraya River Delta,Thailand

The occurrence of catastrophic floods in Thailand in 2011 caused significant damage to rice agriculture. This study investigated flood-affected rice cultivation areas in the Chao Phraya River Delta (CRD) rice bowl, Thailand using time-series moderate resolution imaging spectroradiometer (MODIS) data. The data were processed for 2008 (normal flood year) and 2011, comprising four main steps: (1) data pre-processing to construct time-series MODIS vegetation indices (VIs), to filter noise from the time-series VIs by the empirical mode decomposition (EMD), and to mask out non-agricultural areas in respect to water-related cropping areas; (2) flood-affected area classification using the unsupervised linear mixture model (ULMM); (3) rice crop classification using the support vector machines (SVM); and (4) accuracy assessment of flood and rice crop mapping results. The comparisons between the flood mapping results and the ground reference data indicated an overall accuracy of 97.9% and Kappa coefficient of 0.62 achieved for 2008, and 95.7% and 0.77 for 2011, respectively. These results were reaffirmed by close agreement (R² > 0.8) between comparisons of the two datasets at the provincial level. The crop mapping results compared with the ground reference data revealed that the overall accuracies and Kappa coefficients obtained for 2008 were 88.5% and 0.82, and for 2011 were 84.1% and 0.76, respectively. A strong correlation was also found between MODIS-derived rice area and rice area statistics at the provincial level (R² > 0.7). Rice crop maps overlaid on the flood-affected area maps showed that approximately 16.8% of the rice cultivation area was affected by floods in 2011 compared to 4.9% in 2008. A majority of the flood-expanded area was observed for the double-cropped rice (10.5%), probably due to flood-induced effects to the autumn–summer and rainy season crops. Information achieved from this study could be useful for agricultural planners to mitigate possible impacts of floods on rice production.     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

一种面向海量数字高程模型数据的洪水淹没区快速生成算法

常见种子点填充算法在实现DEM数据下的洪水淹没区生成时,具有难以处理大数据量以及过多的递归计算易导致算法效率较低等缺点。针对此问题,本文提出一种面向海量DEM数据的洪水淹没区生成算法分块压缩追踪法,该算法采用条带分块和实时栅格压缩存储技术,以解决海量地形数据下的淹没分析计算问题。最后,通过将本算法与常见种子点填充算法和分块种子点填充算法进行了对比测试,实验结果表明本算法不仅较好地解决了海量DEM数据下的洪水淹没区生成问题,与常规种子点填充算法和分块种子点填充算法相比亦具有较高的计算效率。     

洪水风险图管理与应用系统的设计与实现

洪水风险图是洪水管理的重要技术支撑,当洪水风险图的编制成果积累到一定程度时,面临着如何有效管理和共享应用的问题。文章在分析洪水风险图的数据特点以及在管理和应用上的功能与性能需求的基础上,采用面向服务思想的地理信息共享技术,设计了洪水风险图的管理与应用系统。该系统为洪水风险图空间数据和专题数据的有效管理和应用提供了信息交流和共享的平台,有利于洪水风险图编制和应用的推广。