Groundwater Potential Zoning in Thirumanimuttar Sub-Basin Tamilnadu, India—A GIS and Remote Sensing Approach

The main objective of the study is to identify groundwater potential zones in Thirumanimuttar basin with an integrated approach using Remote Sensing and geographical information system(GIS).FCC Image of Landsat TM 30 m resolution data and topographic maps has been used to generate thematic maps like geology,geomorphology,lineament and lineament density,drain-age,drainage density,and slope map of the study area.A number of geomorphic units such as Denudational hills,structural hills,Bajadas,Colluvial plain,Pediplain,Deep Pediment and Alluvial plains have been observed.A composite groundwater potential map has been generated as very high,high,medium,low and very low based on the groundwater availability area.The upper,mid-dle and downstream of the basins have been identified as potential zones for groundwater exploration.The regions of lineaments and intersecting lineaments proved for groundwater potential zones.The data generated was validated with field checks and ob-served to be in conformity with the same.     

Groundwater Prospect Zoning Using Remote Sensing and Geographical Information System: A Case Study in Dala-Renukoot Area, Sonbhadra District, Uttar Pradesh

In the present study, ground water prospect zones in Dala-Renukoot area, in Sonebhadra district. Uttar Pradesh, India have been delineated, through integration of various thematic maps using ARC/INFO GIS. Thematic maps in respect of geology, geomorphology. slope, drainage, land-use/land cover, lineament and lineament intersection frequency were prepared on 1:50,000 scale using remote sensing and conventional methods. These maps were scanned and registered with reference to a basemap and are input as separate layers using ARC/INFO GIS. Each theme was assigned a weightage depending on its influence on the movement and storage of groundwater and each unit in every theme map is assigned a knowledge based ranking from 1 to 5 depending on its significance to groundwater occurrence. All the themes are overlaid, two at a time and the resultant composite coverage is classified into five groundwater prospect categories. This output map is correlated with the groundwater data collected in the field.     

Assessment of groundwater potential zones using GIS technique

A case study was conducted to find out the groundwater potential zones in Kattakulathur block, Tamil Nadu, India with an aerial extent of 360.60 km². The thematic maps such as geology, geomorphology, soil hydrological group, land use / land cover and drainage map were prepared for the study area. The Digital Elevation Model (DEM) has been generated from the 10 m interval contour lines (which is derived from SOI, Toposheet 1:25000 scale) and obtained the slope (%) of the study area. The groundwater potential zones were obtained by overlaying all the thematic maps in terms of weighted overlay methods using the spatial analysis tool in ArcGIS 9.2. During weighted overlay analysis, the ranking has been given for each individual parameter of each thematic map and weights were assigned according to the influence such as soil −25%, geomorphology − 25%, land use/land cover −25%, slope − 15%, lineament − 5% and drainage / streams − 5% and find out the potential zones in terms of good, moderate and poor zones with the area of 49.70 km², 261.61 km² and 46.04 km² respectively. The potential zone wise study area was overlaid with village boundary map and the village wise groundwater potential zones with three categories such as good, moderate and poor zones were obtained. This GIS based output result was validated by conducting field survey by randomly selecting wells in different villages using GPS instruments. The coordinates of each well location were obtained by GPS and plotted in the GIS platform and it was clearly shown that the well coordinates were exactly seated with the classified zones.     

Ranchi mega lineament and its correlation with geological and geophysical data

Remotely-sensed satellite data of Landsat 5 (TM) and IRS-1A (LISS II) covering parts of central portion of Chotanagapur plateau have been analysed visually to delineate some prominent lineaments in Ranchi district and its adjoining area. One of the most prominent lineament “Ranchi mega lineament? has been analysed in this paper. This lineament is a potential site for base metal mineralisation at some places, and it acts as good groundwater conduit in the region. No earlier attempt to map this entire structural unit as a separate entity is known. Geophysical bouguer gravity anomaly map, lithological and structural maps have some remarkable correlation with this lineament. In the present paper authors have tried to analyse the lineament with respect to its tectonic, mineralisation and groundwater prospects. Resistivity survey carried in close proximity of this lineament at selected sites, indicate that rocks are well fractured at depth. Available lithological and structural map support this lineament as a shear near Purulia (W.B.) and also having base-metal mineralisation potential in this area. Authors opine that existing gravity anomaly map may be further augmented in the light of present study.     

Regional Groundwater Assessment of Krishna River Basin Using Integrated GIS Approach

The groundwater occurrence and movement within the flow systems are governed by many natural factors like topography, geology, geomorphology, lineament structures, soil, drainage network and land use land cover (LULC). Due to complex natural geological/hydro-geological regime a systematic planning is needed for groundwater exploitation. It is even more important to characterize the aquifer system and delineate groundwater potential zones in different geological terrain. The study employed integration of weighted index overlay analysis (WIOA) and geographical information system (GIS) techniques to assess the groundwater potential zones in Krishna river basin, India and the validation of the result with existing groundwater levels. Different thematic layers such as geology, geomorphology, soil, slope, LULC, drainage density, lineament density and annual rainfall distribution were integrated with WIOA using spatial analyst tools in Arc-GIS 10.1. These thematic layers were prepared using Geological survey of India maps, European Digital Archive of Soil Maps, Bhuvan (Indian-Geo platform of ISRO, NRSC) and 30 m global land cover data. Drainage, watershed delineation and slope were prepared from the Shuttle Radar Topography Mission digital elevation model of 30 m resolution data. WIOA is being carried out for deriving the normalized score for the suitability classification. Weight factor is assigned for every thematic layer and their individual feature classes considering their significant importance in groundwater occurrence. The final map of the study area is categorized into five classes very good, good, moderate, poor and very poor groundwater potential zones. The result describes the groundwater potential zones at regional scale which are in good agreement with observed ground water condition at field level. Thus, the results derived can be very much useful in planning and management of groundwater resources in a regional scale.     

制图学是一门工具科学——对地图应用问题的设想

地图的特性在于运用系统化的符号抽象概括地表现事物或现象的空间位置。以测量为基础的精确定位的地形图为军事和其它经济建设起过重要的作用，而且制图工作成为隶属于政府的一种专业。在当代专题地图的迅速发展时期里，使传统的制图人员不可能包揽各种各样的专题制图工作，因为他们不可能同时是许多不同科学领域里的专家，为此，必须把地图的理论与方法普及，使在研究和管理工作中经常需用相应专题地图的广大工作人员掌握制图技术。从这一观点出发，在现代，我们是否可以把制图学看作是一门工具科学。     

Fuzzy–frequency ratio model for avalanche susceptibility mapping

Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for heavy damage to the property. Avalanche susceptibility maps assist decision-makers and planners to execute suitable measures to reduce the avalanche risk. In the present study, a probabilistic data-driven geospatial fuzzy–frequency ratio (fuzzy–FR) model is proposed and developed for avalanche susceptibility mapping, especially for the large undocumented region. The fuzzy–FR model for avalanche susceptibility mapping is initially developed and applied for Lahaul-Spiti region. The fuzzy–FR model utilized the six avalanche occurrence factors (i.e. slope, aspect, curvature, elevation, terrain roughness and vegetation cover) and one referent avalanche inventory map to generate the avalanche susceptibility map. Amongst 292 documented avalanche locations from the avalanche inventory map, 233 (80%) were used for training the model and remaining 59 (20%) were used for validation of the map. The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve (ROC-AUC) technique. For validation of the results using ROC-AUC technique, the success rate and prediction rate were calculated. The values of success rate and prediction rate were 94.07% and 91.76%, respectively. The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping.     

Forest fire susceptibility modeling using hybrid approaches

Forest fires are considered one of the most highly damaging and devastating of natural disasters, causing considerable casualties and financial losses every year. Hence, it is important to produce susceptibility maps for the management of forest fires so as to reduce their harmful effects. The purpose of this study is to map the susceptibility to forest fires over Nowshahr County in Iran, using an integrated approach of index of entropy (IOE) with fuzzy membership value (FMV), frequency ratio (FR), and information value (IV) with a comparison of their precision. The spatial database incorporated the inventory of forest fire and conditioning factors. As a whole, 41 forest fire locations were identified. Out of these, 29 locations (≈70%) were randomly chosen for the forest fire susceptibility modeling (FFSM), and the remaining 12 locations (≈30%) were utilized for the validation of the models. Subsequently, utilizing FMV‐IOE, FR‐IOE, and IV‐IOE models, forest fire susceptibility maps were acquired. Finally, the modeling ability of the models for FFSM was assessed using an area under the receiver operating characteristic (AUROC) curve. The results manifested that the prediction accuracy of the FMV‐IOE model is slightly higher than that of the FR‐IOE and IV‐IOE models. The incorporation of IOE with FMV, FR, and IV models had AUROC values of 0.890, 0.887, and 0.878, respectively. The resulting FFSM can be effective in fire repression resource planning, sustainable development, and primary warning in regions with similar conditions.     

城市专题地图指标内容的分析和处理

专题地图指标内容的选择是专题地图设计和制作的前提。本文从分析城市专题统计数据的内容、特点出发,综合考虑专题地图表达的可行性和多样性,形成了一套完整的城市专题地图指标内容分析和处理方法。提出并使用了＂指标——空间——时间＂模型来描述专题地图指标内容,该方法的确立是选定专题地图主题和确立专题内容结构的基础。     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

Application of lineament density and hydrogeomorphology to delineate groundwater potential zones of Baghmundi block in Purulia District, West Bengal

Groundwater being a valuable resource in today’s world needs proper evaluation and management for overall development within the region for its judicious use. The Baghmundi Block of Purulia district, West Bengal is within the hard rock terrain of Ayodhya hills and Matha Protected forest. The groundwater in this region is confined within the fracture zones and weathered residuum. Hydrogeomorphologically, the entire area is classified into following categories such as - i) Very shallow weathered pediment, ii) Moderately weathered pediment, iii) Valley fills, iv) Erosional gullies, v) Lateritic Upland and vi) Accumulation gullies. The hydrogeomorphic map of the area prepared by Department of Science and Technology, Govt. of West Bengal has been digitized for the present study. The lineament map has been prepared from the satellite imagery. The lineament map has also been digitized for the present study. From this the lineament density contour map has been prepared. An integrated remote sensing and Geographic Information System (GIS) based methodology has been used for the delineating Groundwater potential zones in the study area. Here the Geomorphology and Lineament density maps are overlaid following the Weighted Index Overlay Method, which delineates groundwater potential zones.     

基于WebGIS的动态专题地图发布技术研究

互联网技术的发展,使得传统的地图发布技术发生了重大的变化。目前地图发布正在走向网络化、实时化,并趋向于与W ebG IS相结合。本文分析了专题地图编制发布现状,对基于W ebG IS技术的动态专题地图进行了深入研究,分析了动态发布专题地图的目前常用的三种技术手段,并给出了一个基于ArcIMS的Java Connector二次开发的基于W ebG IS的人口动态发布专题地图的实例。     

Check dam positioning by prioritization of micro-watersheds using SYI model and morphometric analysis — Remote sensing and GIS perspective

Sediment Yield Index (SYI) model and results of morphometric analysis have been used to prioritize watersheds and to locate sites for checkdam positioning in Tarafeni watershed in Midnapur district. West Bengal. Various thematic maps such as land use/land cover, slope, drainage, soil etc. were prepared from 1RS ID LISS III digital data, SOI toposheets of 1:50,000 scale and other reference maps. Morphometric parameters such as bifurcation ratio (R_b). drainage density (D_d), texture ratio (T), length of overland flow (L_o), stream frequency (F_u), compactness coefficient (C_c), circularity ratio (R_c), elongation ratio (E_r), shape factor (B_s) and form factor (R_f) were computed. Automated demarcation of prioritization of micro-watersheds was done by using GIS overlaying technique by assigning weight factors to all the identified features in each thematic map and ranks were assigned to the morphometric parameters. Five categories of priority viz., very high, high, medium, low and very low, were given to all the watersheds in both the methods. Sixty-two micro-watersheds using SYI method and twenty-three micro-watersheds using morphometric have been prioritized as very high priority. Final priority map was prepared by considering the commonly occurred very high-prioritized micro-watersheds in both SYI model and morphometric analysis. Twenty-four suitable sites were identified for check dam construction in 21 highly prioritized watersheds. It is proved that integrated study of SYI model and morphometric analysis yield good result in prioritization of watersheds.     

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.     

基于GIS的矿产资源专题图制作

结合编制矿产资源专题图,探讨了基于GIS的矿产专题地图的设计流程以及制作方法 ;针对ArcGIS自带符号库不能满足专业需要的现状,重点研究了矿产资源类型符号库的设计与实现方法,并通过绘制徐州市矿产资源分布图进行了验证。     

浅谈基于ArcMap的制图符号设计与应用

随着互联网信息技术的飞速发展,电子化地图得到了广泛应用,高德地图、百度地图等互联网地图广泛应用于我们日常生活中,地图的美观性和设计感就决定了人们对它的第一印象.专题图作为一种集设计理念、空间信息于一体的地图产品,在很多场合中发挥着越来越大的作用.在制作专题地图中常常使用到的软件工具有ArcMap、CorelDRAW、A...     

A Geographic Information System approach to evaluation of groundwater potentiality of Shamri micro-watershed in the Shimla Taluk, Himachal Pradesh

GIS. a potential tool for facilitating the generation and use of thematic information, has been applied to groundwater potentiality of the Shamri micro-watershed in Shimla Taluk. The role of various parameters, namely, drainage. lineament. lithology . slope and landuse have been emphasised for delineation of groundwater potential iones. IRS-I C IAN and LISS Ill FCC merged satellite images on 1:25000 scale and Topographic map no. 53L/4 SI together with field traverses have been used as the data source. A multi-criteria evaluation following probability weighted approach has been applied for overlay analysis that allows a linear combination of weights of each thematic map with the individual capability value. 1 he resultant map indicates a high groundwater potentiality in the flood plains, river terraces and river channels in the vicinity of the Shamri nala. Other sites of high potentiality include places showing break in slopes and criss-crossing of lineaments.     

基于SVG的专题地图与Google地图混搭研究

Google地图开放API后,将Google地图作为地理底图,由用户定制专题要素成为专题地图制作的一种新形式。文中研究如何在Google地图上制作精美生动的网络专题地图。SVG用于表达网络专题要素有其独特的优势,文中结合SVG的优点探讨以Google地图为地理底图的网络专题地图的表达、设计与实现方法,尝试解决网络地理底图与专题要素的一致性表达问题。     

Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province,Iran

Flood is one of the most devastating natural disasters with socio-economic and environmental consequences. Thus, comprehensive flood management is essential to reduce the flood effects on human lives and livelihoods. The main goal of this study was to investigate the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran. At first, a flood inventory map was prepared using Iranian Water Resources Department and extensive field surveys. In total, 144 flood locations were identified in the study area. Of these, 101 (70%) floods were randomly selected as training data and the remaining 43 (30%) cases were used for the validation purposes. In the next step, flood conditioning factors such as lithology, land-use, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index (TWI) and altitude were prepared from the spatial database. Subsequently, the receiver operating characteristic (ROC) curves were drawn for produced flood susceptibility maps and the area under the curves (AUCs) was computed. The final results indicated that the FR (AUC = 76.47%) and WofE (AUC = 74.74%) models have almost similar and reasonable results. Therefore, these flood susceptibility maps can be useful for researchers and planner in flood mitigation strategies.