CAD在数字地质填图中的应用

针对区域地质调查的特点,结合1:50000区域地质矿产调查项目的实际情况,介绍了基于CAD的数字地质填图的方法、工作流程、具体步骤以及关键技术,论述了数据的采集和数据的融合。     

城市植被制图中SPOT5影像融合方法研究

不同的融合方法用于不同应用目的融合效果不同,本文采用主成分分析、HIS变换以及基于小波变换的主成分分析和HIS变换四种融合方法对SPOT5全色波段和多光谱波段进行融合,并针对城市植被制图特点对融合结果进行质量评价。结果表明,基于小波变换的PCA和HIS变换融合法光谱保持能力最好,但是空间结构特征较差,不适于城市植被零星分布的特点。主成分分析既有较好的空间结构特征,细小地物纹理清晰,同时又具有较好的光谱保持能力,最适合于城市植被制图研究。     

GDI+在遥感数据处理中的应用

本文利用GDI+在图像处理方面的新特点,举例说明了GDI+在遥感图像的基本操作、空间滤波增强、图像的灰度化及伪彩色处理和图像的编码解码和多格式转化等方面的优势,从而为GDI+在遥感图像处理系统中的应用提供了新思路。     

Generation of thermal inertia image over a part of Gujarat: A new tool for geological mapping

Thermal inertia is a volume property and can be used to detect the subsurface features in an alluvium-covered area. A thermal inertia image has been generated over a part of Gujarat using consecutive day and night NOAA-AVHRR data. Gujarat contains two important rift basins in the western margin of India, namely, Cambay and Kutch basins. Major land covers exist in this region are alluvium, continental sediments, various rocks of Mesozoic and Cenozoic origin followed by Deccan Volcanics, tertiary and quaternary deposits. Validation of thermal inertia parameters with existing values obtained from literature indicates the efficacy of the developed technique. The study indicates that thermal inertia image can be used as a new method for geologic mapping/basin delineation where exposure is less or contrast is negligible between litho-units using traditional photography/sensing techniques.     

Land cover mapping applications with MODIS: a literature review

Abstract

Land use/land cover monitoring and mapping is crucial to efficient management of the land and its resources. Since the late 1980s increased attention has been paid to the use of coarse resolution optical data. The Moderate Resolution Imaging Spectroradiometer (MODIS) has features, which make it particularly suitable to earth characterization purposes. MODIS has 10 products dedicated mainly to land cover characterization and provides three kinds of data: angular, spectral and temporal. MODIS data also includes information about the data quality through the ‘Quality Assessment’ product. In this paper, we review how MODIS data are used to map land cover including the preferred MODIS products, the preprocessing and classification approaches, the accuracy assessment, and the results obtained.     

Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities

ABSTRACT

Researchers are continually finding new applications of satellite images because of the growing number of high-resolution images with wide spatial coverage. However, the cost of these images is sometimes high, and their temporal resolution is relatively coarse. Crowdsourcing is an increasingly common source of data that takes advantage of local stakeholder knowledge and that provides a higher frequency of data. The complementarity of these two data sources suggests there is great potential for mutually beneficial integration. Unfortunately, there are still important gaps in crowdsourced satellite image analysis by means of crowdsourcing in areas such as land cover classification and emergency management. In this paper, we summarize recent efforts, and discuss the challenges and prospects of satellite image analysis for geospatial applications using crowdsourcing. Crowdsourcing can be used to improve satellite image analysis and satellite images can be used to organize crowdsourced efforts for collaborative mapping.     

European forest cover mapping with high resolution satellite data: The Carpathians case study

The aim of the study was to elaborate a methodology for forest mapping based on high resolution satellite data, relevant for reporting on forest cover and spatial pattern changes in Europe. The Carpathians were selected as a case study area and mapped using 24 Landsat scenes, processed independently with a supervised approach combining image segmentation, knowledge-based rules to extract a training set and the maximum likelihood decision rule. Validation was done with available very high resolution imagery. Overall accuracies per scene ranged from 93 to 96%. The labelling disagreement in overlapping areas of adjacent scenes was 6.8% on average.     

超像元尺度下的多光谱图像超分辨率洪水淹没制图

超分辨率制图SRM(Super-resolution Mapping)技术可以有效地处理遥感图像中的混合像元,获得准确的地物类别分布信息.目前,SRM技术已经成功地应用于多光谱图像洪水淹没定位中,称为超分辨率洪水淹没制图SRFIM(Super-resolution Flood Inundation Mapping).然...     

Rapid texture mapping from image sequences for building geometry model

An effective approach,mapping the texture for building model based on the digital photogrammetric theory, is proposed. The easily-ac-quired image sequences from digital video camera on helicopter are used as texture resource, and the correspon-dence between the space edge in build-ing geometry model and its line feature in image sequences is determined semi-automatically. The experimental re-sults in production of three-dimension-al data for car navigation show us an attractive future both in efficiency and effect.     

Rapid texture mapping from image sequences for building geometry model

An effective approach, mapping the texture for building model based on the digital photogrammetric theory, is proposed. The easily-acquired image sequences from digital video camera on helicopter are used as texture resource, and the correspondence between the space edge in building geometry model and its line feature in image sequences is determined semiautomatically. The experimental results in production of three-dimensional data for car navigation show us an attractive future both in efficiency and effect.     

Quantitative urban climate mapping based on a geographical database: A simulation approach using Hong Kong as a case study

The urban environment has been dramatically changed by artificial constructions. How the modified urban geometry affects the urban climate and therefore human thermal comfort has become a primary concern for urban planners. The present study takes a simulation approach to analyze the influence of urban geometry on the urban climate and maps this climatic understanding from a quantitative perspective. A geographical building database is used to characterize two widely discussed aspects: urban heat island effect (UHI) and wind dynamics. The parameters of the sky view factor (SVF) and the frontal area density (FAD) are simulated using ArcGIS-embedded computer programs to link urban geometry with the UHI and wind dynamic conditions. The simulated results are synergized and classified to evaluate different urban climatic conditions based on thermal comfort consideration. A climatic map is then generated implementing the classification. The climatic map shows reasonable agreement with thermal comfort understanding, as indicated by the biometeorological index of the physiological equivalent temperature (PET) obtained in an earlier study. The proposed climate mapping approach can provide both quantitative and visual evaluation of the urban environment for urban planners with climatic concerns. The map could be used as a decision support tool in planning and policy-making processes. An urban area in Hong Kong is used as a case study.     

Integrating data from remote sensing,geology and gravity for geological investigation in the Tarhunah area,Northwest Libya

Abstract

The present work deals with the integration of remote-sensing, surface-geology and gravity-survey data to improve the structural knowledge of the Tarhunah area, northwest Libya. Geological information and remote-sensing data provided information about the surface structure. A gravity survey was conducted to decipher the subsurface structure. The results revealed that a basin having a width of 39 to 48 km trends NE. A two-dimensional (2-D) schematic model shows that the basin gradually deepens toward the southwest. Faults determined from a horizontal gradient, tilt derivative, and Euler deconvolution show a depth range of 2.5 to 7.5 km. The integration and interpretation of the results indicate that volcanic activity was related to the tectonic activity of an anticlinal structure called the Jabal Uplift.     

Accounting for image uncertainty in SAR-based flood mapping

Operational flood mitigation and flood modeling activities benefit from a rapid and automated flood mapping procedure. A valuable information source for such a flood mapping procedure can be remote sensing synthetic aperture radar (SAR) data. In order to be reliable, an objective characterization of the uncertainty associated with the flood maps is required.This work focuses on speckle uncertainty associated with the SAR data and introduces the use of a non-parametric bootstrap method to take into account this uncertainty on the resulting flood maps. From several synthetic images, constructed through bootstrapping the original image, flood maps are delineated. The accuracy of these flood maps is also evaluated w.r.t. an independent validation data set, obtaining, in the two test cases analyzed in this paper, F-values (i.e. values of the Jaccard coefficient) comprised between 0.50 and 0.65. This method is further compared to an image segmentation method for speckle analysis, with which similar results are obtained. The uncertainty analysis of the ensemble of bootstrapped synthetic images was found to be representative of image speckle, with the advantage that no segmentation and speckle estimations are required.Furthermore, this work assesses to what extent the bootstrap ensemble size can be reduced while remaining representative of the original ensemble, as operational applications would clearly benefit from such reduced ensemble sizes.     

Evaluation of ICA and CEM algorithms with Landsat-8/ASTER data for geological mapping in inaccessible regions

Many regions remain poorly studied in terms of geological mapping and mineral exploration in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistic difficulties. Application of specialized image processing techniques is capable of revealing the hidden linear mixing spectra in multispectral and hyperspectral satellite images. In this study, the applications of Independent component analysis (ICA) and Constrained Energy Minimization (CEM) algorithms were evaluated for Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. The results of this investigation demonstrate the capability of the two algorithms in distinguishing pixel and subpixel targets in the multispectral satellite data. The application of the methods for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable implications for geological mapping and mineral exploration in inaccessible regions.     

Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes

Remote sensing has been proven promising in wetland mapping. However, conventional methods in a complex and heterogeneous urban landscape usually use mono temporal Landsat TM/ETM + images, which have great uncertainty due to the spectral similarity of different land covers, and pixel-based classifications may not meet the accuracy requirement. This paper proposes an approach that combines spatiotemporal fusion and object-based image analysis, using the spatial and temporal adaptive reflectance fusion model to generate a time series of Landsat 8 OLI images on critical dates of sedge swamp and paddy rice, and the time series of MODIS NDVI to calculate phenological parameters for identifying wetlands with an object-based method. The results of a case study indicate that different types of wetlands can be successfully identified, with 92.38%. The overall accuracy and 0.85 Kappa coefficient, and 85% and 90% for the user’s accuracies of sedge swamp and paddy respectively.     

利用高分辨率立体测绘影像进行中小比例尺地貌要素更新

利用高分辨率立体测绘卫星遥感影像进行地貌更新,因其覆盖面积大、更新周期短等优势,在中小比例尺地貌要素更新中具有极大的应用潜力。本文分别利用WorldView-2和资源三号卫星影像,探索基于高分辨率立体测绘卫星影像的中小比例尺地貌更新技术方案流程,并在不同的试验区开展试验验证。试验结果表明：本文方法能够满足1：50 000比例尺地形图地貌更新精度要求,更新效率提升了约25%。     

遥感影像流程化处理系统的设计与实现

在进行遥感影像处理过程中,因处理目的不同而采用不同的方法来处理遥感影像,同时遥感影像处理流程并非是一个简单的单步操作,而是多种操作综合的结果。遥感影像类型颇多,处理流程差异较大,因此,固定的流程化操作显然不妥。本文将建立一个高效集成的处理系统,它可以方便用户定制直观的处理流程,并且提供较优的扩展功能。本系统在实际遥感影像处理应用(如数据融合等)中已经取得了理想的效果。     

Geological mapping of Jharia Coalfield,India using GRACE EGM2008 gravity data: a vertical derivative approach

High-resolution satellite gravity data of gravity recovery and climate experiment (GRACE) generated by Earth Gravity Model-2008 (EGM2008) have been utilised for geological mapping of the Jharia coalfield. The generated GRACE EGM2008 classical gravity data have been processed for estimation of gravity anomaly map. The gravity anomaly map has been enhanced using the first and second Vertical Derivatives techniques. Geological and structural maps of the study area have been overlapped over different derivative maps to analyse the correlation with the subsurface geological structures of the study area. Major distinct geological signatures, on different derivative maps, are correlated well with the existing geological map. Moreover, vertical derivative maps of the gravity data generated from GRACE EGM2008 model provide better agreement and understanding for geological setting of the Jharia coalfield.     

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.