The development of integrated terrestrial and marine pathways in the Argo-Saronic region,Greece

Least cost path applications can be a powerful tool for understanding connectivity across a landscape. A limitation to this method is its difficulty in integrating terrestrial, marine, and cultural factors – all of which would have been at play in the prehistoric Aegean. This study looks at a method of modeling pathways that integrates major factors (land, sea, and culture) that would be in play while considering medium- to long-distance travel in the Aegean. This test case explores the possible relationships between proposed routes for communication and identified coastal sites with parameters modeled in geographic information system that affect travel in cultural, marine, and terrestrial contexts. The methods presented have significance beyond the Late Bronze Age Aegean. The development of a methodology that incorporates marine, cultural, and terrestrial environments provides a mechanism by which specific hypotheses regarding complex communication routes may be addressed in regions of the world where there is an intensive interplay between terrestrial and marine geographies.     

海岸带地理环境遥感监测综述

海岸带作为连接海洋和陆地系统的特殊地理地带,与人类的生存与发展密切相关,但其自然和生态环境极其脆弱和敏感。气候变化和人类活动给海岸带环境带来了巨大压力,导致其生态环境不断恶化。随着技术的发展,近年来遥感技术已成为海岸带地理环境监测的重要手段之一,在海岸带规划、管理和保护中扮演着举足轻重的角色。本文对遥感技术在海岸带地理环境监测典型应用(土地利用/覆盖、土壤质量、植被、海岸线、水色、水深和水下地形及灾害)中的主要数据源、方法、结果和局限性进行归纳和总结,并对其未来发展提出展望。     

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.     

An automatic procedure for co-registration of terrestrial laser scanners and digital cameras

Driven by progress in sensor technology, algorithms and data processing capabilities, close range photogrammetry has found a wide range of new application fields over the past two decades. Particularly, the emergence of terrestrial laser scanner has contributed to the close range photogrammetry “popularization” through many promising new applications. Nevertheless, a central issue in many of these developments is the integration of sensor technology with reliable data processing schemes to generate highly automated photogrammetric measurements systems.This paper presents a flexible approach for the automatic co-registration of terrestrial laser scanners (TLS) and amateur digital cameras (DC) to be used effectively in practice. Particularly, the developed approach deals with two different images: a camera image acquired with a DC and a range image obtained with a TLS. To this end, an open-source tool “USAlign” has been developed for testing the different experiments.     

Spectral Filtering and Classification of Terrestrial Laser Scanner Point Clouds

A method is presented for filtering and classification of terrestrial laser scanner point clouds. The algorithm exploits the four-channel (blue, green, red and near infrared) multispectral imaging capability of some terrestrial scanners using supervised, parametric classification to assign thematic class labels to all scan cloud points. Its principal advantage is that it is a completely data-driven algorithm and is independent of spatial sampling resolution since the processing is performed in four-dimensional spectral feature space. Its application to two data-sets of different spatial extent and spatial and spectral complexity is reported, for which respective overall classification accuracies of 87·0% and 82·0% were achieved. Analysis of the input data with emphasis on the characteristics pertinent to the anticipated outcomes precedes detailed analysis of the classification results and error sources and their causes. Erroneously classified points are attributed to radiometric errors stemming from both detector hardware and physical effects.     

Land use/land cover changes near HAzira Region, Gujarat using remote sensing satellite data

Human activities have great influence on fragile coastal ecosystem. For sustainable use of coastal resources it is very important to understand land use/land cover changes and its implications on coastal systems. Remote sensing data because of its synoptic, multispectral and multi temporal nature can be a very good source for mapping, monitoring and understanding these changes. IRS LISS III sensor data were used to find out the rate of land use/land cover changes in Hazira area near Surat, Gujarat. Because of major industrial activities it has become a hot spot area which requires regular monitoring. In the present study, land cover information of the period 1970–1972 from the Survey of India topographical maps, and satellite data of the year 1989 and 1999–2002 have been used and visual analysis has been carried out to measure the land use/land cover changes. Erosion and deposition has been observed around the newly constructed jetty. Forest area and agriculture area is found to decreased, whereas built-up area has increased.     

基于球面投影的单站地面激光扫描点云构网方法

为正确判断点与点之间的邻接关系，结合单站地面激光扫描点云数据的特性，提出了利用球面投影对其构建三角网的方法；讨论了球面Delaunay构网方法的若干细节；采用球面有向搜索和球面LOP局部优化算法，提高了构网时间效率；实验表明本方法能快速、有效的对单站激光扫描点云构网。相似文献   

Derivation of maximum value composite images using multidate NOAA-AVHRR data

Multidate NOAA-AVHRR Data has been used for monitoring dynamic changes of the vegetation and coastal processes. However, the interpretation of the data is significantly affected by presence of the clouds. An attempt has been made in this paper to evaluate the technical aspects of a processing methodology to generate a cloud masked imagery using multidate NOAA-AVHRR data to minimize cloud cover in the scene. A Maximum Value Composite Image is generated after cloud minimisation. The utility of the technique has been tested in a case study to generate Normalised Difference Vegetation Index (NDVI) over the Indian Subcontinent. The process over two days produced spatially continuous cloud-masked imagery to study green vegetation dynamics. The technique minimizes cloud contamination, reduces off-nadir viewing effects and generates maximum value composite image.     

利用多探测任务数据建立新一代月球全球控制网的方案与关键技术

目前广泛应用的月球统一控制网2005（Unified Lunar Control Network 2005,ULCN2005）是由1994年的克莱门汀（Clementine）影像和之前的遥感数据联合平差构建的。提出利用21世纪获取的分辨率更高、精度更好的多探测任务数据,建立新一代月球控制网的方案与关键技术。该方案基于全球覆盖的月球遥感影像与激光高度计数据的联合平差,同时利用在月球轨道侦察器窄角相机影像上能高精度定位的绝对定位精度在厘米级的5个激光棱角反射标志点作为绝对控制。此外,还通过新的无线电测量方法对嫦娥三号着陆器进行高精度定位,将其定位结果也作为一个新的绝对控制数据。新一代控制网构建的重点有高精度的轨道器严密及通用成像几何模型的构建、多任务多模态数据间的多尺度特征提取与匹配、最优化多重覆盖影像的选择、全月球整体平差等。基于新的数据和技术,新一代月球控制网的精度和点的密度有望远超ULCN2005。     

Coastal landform mapping around the Gulf of Khambhat using Landsat TM data

Landsat TM data was utilised for coastal geomorphic mapping around the Gulf of Khambhat. Various landforms like shoreline, estuaries, mudflats, islands, mangroves, relict aluvium, cliffs, dunes, flood plains, paleochannel, paleomeanders, oxbow lake, etc. were delineated. The estuaries were divided into salt-wedge estuary, fully mixed estuary and partially mixed estuary based on amount of freshwater discharge and nature of tidal currents. The mudflats were classified into high tide flats, intertidal slopes and subtidal zones. These classes were further classified based on their composition. It was concluded that TM data has broughtout many new features and improved the classification of coastal landforms. The presence of coastal features like drowned river valleys, paleomudflats, relict alluvium, dunes, paleomeanders, oxbow lake and terraces clearly indicate the sea-level changes of the Quarternary period.     

EDINBURGH CASTLE ROCK:

Edinburgh Castle is an ancient monument situated on a basalt crag which has steep cliffs falling away on three of its sides. Periodically, remedial measures have to be carried out on these cliffs by engineering geologists in order to stabilise loosened parts of the surface and thus prevent rock falls occurring. The rock structure on the sheer north-facing cliff is currently being studied to determine the extent of work required to ensure its stability. Before such a study could proceed satisfactorily it was necessary to obtain a large scale, contoured survey of the face and this has been achieved by terrestrial photogrammetric methods. Stereoscopic photography was taken with a Wild RC5A wide angle camera pointing horizontally, being specially mounted on its side in the elevated bucket of a Simon hydraulic platform, positioned 17 metres above ground level at a distance of 100 metres from the rock face and at eight successive locations in West Princes Street Gardens. The elevation was plotted with a Zeiss Stereoplanigraph C8 at a scale of 1 : 50 with contours (with respect to a vertical datum) at horizontal intervals of 250 mm.     

GIS-based simulation as an exploratory analysis for space-time processes

The purpose of this paper is to argue for a novel use of geographical information system (GIS) as an exploratory device for understanding complex space-time processes. Conventionally, a GIS has been configured as a spatial database management system. Therefore, the capabilities of data input, storage, retrieval, manipulation and display have been well developed, whereas the analytical and dynamic processing and modelling capabilities are under-developed. The importance of integrating GIS with dynamic and analytical models has been widely recognised. Extending the use of GIS into spatial simulation represents a plausible research direction. On the other hand, the usefulness of conventional deductive model becomes limited when dealing with complex space-time processes. In essence, the inherent complexity calls for a simulation approach. The new nonlinear modelling paradigm, for example, cellular automata (CA), opened a way in which behaviourally-richer dynamics and more micro-spatial data could be incorporated into understanding space-time processes. It is argued therefore that GIS can be used as a platform – a controlled environment or laboratory – for exploring complex space-time processes. The discussion of GIS-based simulation in this paper is illustrated with a primitive simulation of the evolution of urban spatial structure. Received: 2 July 1997/Accepted: 19 November 1998     

无人机低空摄影测量在城市测绘保障中的应用前景

无人机低空摄影测量具有高清晰、大比例尺、小面积、高现势性的优点,是卫星遥感与普通航空摄影不可缺少的补充。可为大比例尺影像地图生产、重点地区正射影像制作、高精度DEM格网和DLG产品提供高分辨率清晰影像数据源,满足城市信息化建设对大比例尺基础地理空间数据的需求,为城市建设提供有效的测绘保障。通过高分辨率测绘产品支持、应急测绘保障、三维数字建模和重点区域动态监测等多个方面对无人机低空摄影测量在城市测绘保障中的应用前景进行论述展望。     

An improved ANUDEM method combining topographic correction and DEM interpolation

Void filling and anomaly replacement in conjunction with auxiliary sources of data have been widely used to improve the quality of existing problematic high-resolution digital elevation models. However, the traditional interpolation methods used for this purpose have always failed to eliminate the discrepancies between different data-sets. In this paper, an improved ANUDEM method is presented for DEM interpolation, which incorporates the idea of topographic correction using high correlation of topological structure between contour lines (CLs) from multi-scale digital elevation models (DEM). Firstly, the terrain topological structure is extracted from the CLs of a low-resolution DEM. The topographic surface correction is then undertaken based on the extracted structure, which recovers the topographic information of the sharp depressions and eminences to fit the high-resolution representation. Finally, the breaklines of the terrain surface are distilled and integrated into the denser DEM generation. The experiments undertaken confirmed the superiority of the proposed method over the other DEM interpolation methods. It is shown that the proposed method can provide results with a higher accuracy, as well as a better visual quality.     

A shoreline change analysis along the coast between Kanyakumari and Tuticorin,India, using digital shoreline analysis system

The shoreline is one of the rapidly changing landforms in coastal areas.They are the key element in coastal GIS and provide the most information on coastal land form dynamics.Therefore,accurate detection and frequent monitoring of shorelines is very essential to understand the coastal processes and dynamics of various coastal features.The present study is to investigate the shoreline changes along the coast between Kanyakumari and Tuticorin of south India(where hydrodynamic and morphologic changes occur continuously after the December 2004 tsunami)by using Digital Shoreline Analysis System(DSAS),an extension of ArcGIS.Multidate IRS and Landsat Satellite data(1999,2001,2003,2005,2007,and 2009)are used to extract the shorelines.The data is processed by using the ERDAS IMAGINE 9.1 software and analyzed by ArcGIS 9.2 workstation.The rates of shoreline changes are estimated by three statistical methods,namely,End Point Rate(EPR),Linear Regression Rate(LRR),and Least Me-dian of Squares(LMS)by using DSAS.The study reveals that most of the study area has undergoing erosion.Both natural and an-thropogenic processes along the coast modify the shoreline configuration and control the erosion and accretion of the coastal zones.The coastal zones along the estuary have experienced accretion due to the littoral processes.The zones with headlands have more eroded than other zones along the study area.The study also shows that the coastal zones where sand is mined have relatively more rate of erosion than that of the other zones.Improper and unsustainable sand mining may also lead to severe erosion problem along this area.The shoreline change rates are altered by various geological processes along the coast.Thus,the present study implies that proper beach filling and nourishment projects should be made in the study area to save from hazards.It also indicates the advantage and suitability of DSAS to assess the shoreline changes compared with the traditional manual shoreline change analysis and prom-ising its applications for coastal zone management in other regions.     

Integrating GIS‐Based Geo‐Atom Theory and Voxel Automata to Simulate the Dispersal of Airborne Pollutants

Environmental processes are usually conceptualized as complex systems whose dynamics are best understood by examining the relationships and interactions of their constituent parts. The cellular automata paradigm, as a bottom‐up modeling approach, has been widely used to study the macroscopic behavior of these complex natural processes. However, the cellular automata models are largely restricted to the two‐dimensional spatial perspective even though the process dynamics they represent evolve in the three spatial dimensions. The objective of this study is to develop a voxel‐based automata approach for modeling the propagation of airborne pollutants in three‐dimensional space over time. The GIS‐based geo‐atom theory was used to manage the data within the automaton. The simulation results indicate the model has the capability to generate effective four‐dimensional (4D) simulations from simple transition rules that describe the processes of particle advection and diffusion. The application of voxel‐based automata and the geo‐atom concepts allows for a detailed 4D analysis and tracking of the changes in the voxel space at every time‐step. The proposed modeling approach provides new means to examine the relationships between pattern and process in 4D.     

A novel method for discovering spatio-temporal clusters of different sizes,shapes, and densities in the presence of noise

The discovery of spatio-temporal clusters in complex spatio-temporal data-sets has been a challenging issue in the domain of spatio-temporal data mining and knowledge discovery. In this paper, a novel spatio-temporal clustering method based on spatio-temporal shared nearest neighbors (STSNN) is proposed to detect spatio-temporal clusters of different sizes, shapes, and densities in spatio-temporal databases with a large amount of noise. The concepts of windowed distance and shared nearest neighbor are utilized to define a novel spatio-temporal density for a spatio-temporal entity with definite mathematical meanings. Then, the density-based clustering strategy is employed to uncover spatio-temporal clusters. The spatio-temporal clustering algorithm developed in this paper is easily implemented and less sensitive to density variation among spatio-temporal entities. Experiments are undertaken on several simulated data-sets to demonstrate the effectiveness and advantage of the STSNN algorithm. Also, the real-world applications on two seismic databases show that the STSNN algorithm has the ability to uncover foreshocks and aftershocks effectively.     

Dynamics of coastal landform features along the southern Tamil Nadu of India by using remote sensing and Geographic Information System

This article reveals an application of multi-spectral satellite data for analysing the dynamics of different coastal landform features along the southern coastal Tamil Nadu of India. An integrated approach comprising visual image interpretation and maximum-likelihood supervised classification has been employed to classify the coastal landforms by using IRS data (during the period 1999–2006). The quality of image classification has been assessed by performing the accuracy assessments with the existing thematic maps and finally the coastal landforms have been mapped. The study reveals that the dynamics of coastal landforms such as sandy beaches, mud-flats, sand dunes and salt marshes along the study area are mostly influenced by the coastal processes, sediment transport, geomorphology and anthropogenic activities. Major anthropogenic sources for the perturbation of beach sediment budgets and a cause of beach erosion along the study area are excessive sand mining, removal of sand dunes, coastal urbanization, tourism and developmental activities.     

Ground-based hyperspectral imaging and terrestrial laser scanning for fracture characterization in the Mississippian Boone Formation

Petroleum geoscientists have been using cores and well logs to study source rocks and reservoirs, however, the inherent discontinuous nature of these data cannot account for horizontal heterogeneities. Modern exploitation requires better understanding of important source rocks and reservoirs at outcrop scale. Remote sensing of outcrops is becoming a first order tool for reservoir analog studies including horizontal heterogeneities. This work used ground-based hyperspectral imaging, terrestrial laser scanning (TLS), and high-resolution photography to study a roadcut of the Boone Formation at Bella Vista, northwest Arkansas, and developed an outcrop model for reservoir analog analyses.The petroliferous Boone Formation consists of fossiliferous limestones interbedded with chert of early Mississippian age. We used remote sensing techniques to identify rock types and to collect 3D geometrical data. Mixture tuned matched filtering classification of hyperspectral data show that the outcrop is mostly limestones with interbedded chert nodules. 1315 fractures were classified according to their strata-bounding relationships, among these, larger fractures are dominantly striking in ENE – WSW directions. Fracture extraction data show that chert holds more fractures than limestones, and both vertical and horizontal heterogeneities exist in chert nodule distribution.Utilizing ground-based remote sensing, we have assembled a virtual outcrop model to extract mineral composition as well as fracture data from the model. We inferred anisotropy in vertical fracture permeability based on the dominancy of fracture orientations, the preferential distribution of fractures and distribution of chert nodules. These data are beneficial in reservoir analogs to study rock mechanics and fluid flow, and to improve well performances.     

三维激光扫描数据获取高分辨率DTM试验研究

三维激光扫描技术能够提供实体表面点云数据,可用于获取高精度高分辨率数字地形模型。本文以重庆万州区付家岩滑坡体为例探讨了采用三维激光扫描监测技术获取数字地形模型的方法,着重讨论了相关点云数据处理流程和关键技术问题。通过结合差分GPS技术进行激光数据的相对定位和绝对定位、去噪、拼接等方法,获得了该区域地表高精度地形数据,并生成了相应的数字高程模型。试验结果初步说明该技术可用于获取小尺度高精度高分辨率数字地形模型,具有一定的应用前景。