Three‐dimensional displays for natural hazards analysis,using classified Landsat thematic mapper digital data and large‐scale digital elevation models

Abstract

Professional aerial photography missions are generally outside the reach of most students and faculty involved with teaching and research. Oblique aerial photography using handheld cameras for image acquisition from a light high‐wing aircraft offers an excellent learning experience for students in a first course in remote sensing and offers a useful research tool for graduate students and faculty engaged in environmental investigations. This paper is essentially a guide, covering all aspects of hand‐held camera aerial imaging and the subsequent processing needed to produce low‐obliques, stereograms, anaglyphs, and flight line mosaics. Scales, ground coverage distances, and stereogram and mosaic timing intervals, are included along with a section on the calculations used to produce these numbers. A list of additional resources concludes the paper.     

Parallelizing maximum likelihood classification on computer cluster and graphics processing unit for supervised image classification

ABSTRACT

Supervised image classification has been widely utilized in a variety of remote sensing applications. When large volume of satellite imagery data and aerial photos are increasingly available, high-performance image processing solutions are required to handle large scale of data. This paper introduces how maximum likelihood classification approach is parallelized for implementation on a computer cluster and a graphics processing unit to achieve high performance when processing big imagery data. The solution is scalable and satisfies the need of change detection, object identification, and exploratory analysis on large-scale high-resolution imagery data in remote sensing applications.     

The applications of high resolution satellite data for coastal management and planning in a pacific coral Island

Abstract

Coastal Tropism is a worldwide phenomenon. It induces urgent needs for observation inventories and management of coastal environment, mainly in developing countries.

High resolution satellite data may solve some aspects of the problems. Three examples based upon the potential use of shrimp aquaculture sites in tropical salt marshes, the biotopes mapping in coral reef environments for biologic stock assessments and the characterization and quantification of evolutive stages of coral platforms, are developed. All three are relative to the same tropical Pacific Island with respect, for the first and second examples, to actual needs for the management of mangroves and coral reefs and for the third, to a scientific approach related to evolutive theory of reefs platforms in lagoons.

Methodology and results based upon digital image processing and computer assisted photointerpretation are exposed.

New trends in digital processing and associated digital cartography are listed.     

A rule-based system for forest land use planning

This paper reports the results of an exercise on the development and application of a rule-based software program,Combine for integration of thematic information in simplest possible way. The program was used for forest land use planning in a shifting cultivation area in north-east India. The program can integrate 28 thematic information layers with upto 256 classes in each layer using 8-bit data. Additionally the software can be used for many per pixel image processing operations like merging of digitally and visually classified images, merging of a large number of thematic classes into a few wanted ones, density slicing, image thresholding etc. conveniently.     

Study of spectral signatures for exploration of Bauxite ore deposits in Panchpatmali,India

Spectral analysis technique has been utilized to identify the Bauxite mineral occurrences in Panchpatmali, Orissa, India. Spectral processing of Landsat ETM+ data has been carried out by converting the digital data from quantized and calibrated values to reflectance values. Minimum noise fraction transformation is used to determine the inherent dimensionality of reflected Landsat ETM+ data, to segregate noise in the data, and to reduce the computational requirements for subsequent processing and interactively to locate pure pixels within the data-set, projecting n-dimensional scatterplots. Spectral processing results are displayed in the form of images corresponding to each group of pixels (endmembers). Mixed tune matched filtering method has been applied on Landsat ETM+ images which gave three score (abundance) images for three different classes (endmembers) such as Bauxite, vegetation and soil. Further, mineralized zones are identified using image fusion of ERS-2 SAR and Landsat ETM+ data using intensity-hue-saturation technique.     

FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

ABSTRACT

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.     

Developments in digital map production and data integration within the British Geological Survey

Abstract

Digital techniques for cartographic data capture and high quality map production have been developed and applied over some 18 years to the mapping of the geoscientific datasets of the British Geological Survey, in particular to the geochemical dataset. Over this period, technological advances and developments in both vector and raster data processing techniques have facilitated high quality map production and the integration and display of multiple datasets. This paper reviews the developments in high quality map production and interpretation of survey information, with particular regard to the Regional Geochemical Atlas Series, through the application of image processing techniques on the display and analysis of multiple datasets.     

Distribution of Errors in a Classified Map of Satellite Data

Abstract

The output from any spatial data processing method may contain some uncertainty. With the increasing use of satellite data products as a source of data for Geographical Information Systems (GIS), there have been some major concerns about the accuracy of the satellite‐based information. Due to the nature of spatial data and remotely sensed data acquisition technology, and conventional classification, any single classified image can contain a number of mis‐classified pixels. Conventional accuracy evaluation procedures can report only the number of pixels that are mis‐classified based on some sampling observation. This study investigates the spatial distribution and the amount of these pixels associated with each cover type in a product of satellite data. The study uses Thematic Mapper (TM) and SPOT multispectral data sets obtained for a study area selected in North East New South Wales, Australia. The Fuzzy c‐Means algorithm is used to identify the classified pixels that contained some uncertainty. The approach is based on evaluating the strength of class membership of pixels. This study is important as it can give an indication of the amount of error resulting from the mis‐classification of pixels of specific cover types as well as the spatial distribution of such pixels. The results show that the spatial distribution of erroneously classified pixels are not random and varies depending on the nature of cover types. The proportions of such pixels are higher in spectrally less clearly defined cover types such as grasslands.     

Multi-threaded compression of Earth observation time-series data

ABSTRACT

Earth observation data are typically compressed using general-purpose single-threaded compression algorithms that operate at a fraction of the bandwidth of modern storage and processing systems. We present evidence that recently developed multi-threaded compression codecs offer substantial benefits over widely used single-threaded codecs in terms of compression efficiency when applied to a selection of moderate resolution imaging spectroradiometer (MODIS) datasets stored in the HDF5 format. Compression codecs from the LZ77 and Rice families are shown to vary in efficacy when applied to different MODIS data products, highlighting the need for compression strategies to be tailored to different classes of data. We also introduce LPC-Rice, a new multi-threaded codec, that performs particularly well when applied to time-series data.     

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.     

Generating and mapping population density surfaces within a geographical information system

Abstract

The spatially discontinuous choropleth map is a poor representation of the underlying continuous distribution of population density. A possible alternative is to derive dasymetric maps at a fine spatial resolution by making use of satellite imagery in a geographical information system. However, there are cartographic problems when these maps are displayed and further processing is needed in order to obtain approximations to a continuous density surface. Isarithmic maps of these density surfaces retain a high degree of spatial accuracy while providing pleasing and highly adaptable presentations.

The methods used to generate dasymetric and isarithmic maps are readily implemented in most raster based geographical information systems. For example, the classification of remotely sensed imagery, the subsequent processing and integration of data, and most of the cartographic display, were all undertaken in this work using the low cost IDRISI GIS that operates on standard IBM PC compatible hardware.     

A high-level architecture for a Geomatics Informatization Technology System: the Chinese case

Abstract

China will, as a component of ‘Digital Earth,’ establish a Geomatics Informatization Technology System (GITS) which is characterized by real-time acquisition, automatic processing, networking service, and socialized application with fundamental geographical information. The basic composition of GITS is proposed. GITS covers four layers and six platforms. The four layers are data acquisition, processing, management, and application and services. The six platforms are informatic geodetic datum, high-precision geo-spatial data acquisition, automatic geo-spatial data processing, grid-based geo-spatial information management, comprehensive geo-spatial information sharing and service, and geo-spatial information integration and application. The informatic geodetic datum platform provides a carrier for all the four layers and a base for the other five platforms. The high-precision geo-spatial data acquisition platform belongs to the acquisition layer. The automatic geo-spatial data processing platform belongs to the processing layer. The grid-based geo-spatial information management platform belongs to the management layer and is a bridge connecting geo-spatial data acquisition and spatial information sharing service and integrated applications. The comprehensive geo-spatial information sharing and service platform belongs to the application and service layer. Finally, this paper presents thoughts for constructing GITS.     

An approach to extracting information of residential areas from Beijing-1 image based on Gabor texture segmentation

Abstract

According to the features of high-resolution panchromatic imagery of Beijing-1 small satellite, an approach to extracting information of residential areas is proposed in this paper based on Gabor texture segmentation. The algorithm extracts the features in different directions and different scales by building the Gabor filter, uses cluster analysis of multiple features to segment the image, and performs the fusion processing based on morphological scale space. It solves the problems in image processing resulting from low contrast between remote sensing objects and background, the blurring of image edges and high noise. It has the benefits of direction selection and frequency selection with strong self-adaptive ability. Our experiments prove the effectiveness of the approach for extracting information of residential areas from Beijing-1 high-resolution imagery.     

GEOID: GRID Services for Earth Observation Image Data Processing

Abstract

Recent developments in space technology and exponential increase in demand of earth observation data from space have generated a requirement of a data processing environment, where users can discover the data and process, based on their requirements. Grid Services for Earth Observation Image Data Processing (GEOID) is proposed with a motivation to cater to future earth observation applications requirements of digital earth. This paper discusses the overview of the GEOID architecture, its deployment scenario, use-cases and simulation results. Core technologies used for implementation include Grid computing and Service Oriented Architecture. GEOID provides capability to address requirements of applications such as real-time monitoring, time series data processing and processing with user required quality to meet the requirements of end user applications. GEOID allows users to access the archive products or the raw satellite data stream and process their area of interest. Simulations show that applications such as time series analysis show considerable improvement in processing time by using GEOID.     

Overview and preliminary idea for building Digital Earth with Grid computing technology

Abstract

Digital Earth is an important field of information technology and a research frontier of geosciences in the 21st century. So far, the Grid computing technique is one of the best solutions for Digital Earth infrastructure. Digital Earth can only be realised through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organisationally dispersed. Earth observation (EO) includes information acquisition, processing and applications. Information acquisition provides a vast amount of spatial data for building the fabric resource infrastructure. Information processing means that spatial information processing middleware is used with large amounts of secure Grid computing resources for real-time processing of all kinds of spatial data. We are currently working on the development of core-middleware for EO data processing and applications for the Digital Earth Prototype System, which is available in the Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS) The further results will be available soon.     

Research on SAR data integrated processing methodology oriented on earth environment factor inversions

ABSTRACT

As an important advanced technique in the field of Earth observations, Synthetic Aperture Radar (SAR) plays a key role in the study of global environmental change, resources exploration, disaster mitigation, urban environments, and even lunar exploration. However, studies on imaging, image processing, and Earth factor inversions have often been conducted independently for a long time, which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing. Focusing on this SAR application issue, this paper proposes and describes a new SAR data processing methodology – SAR data integrated processing (DIP) oriented on Earth environment factor inversions. The simple definition, typical integrated modes and overall implementation ideas are introduced. Finally, focusing on building information extraction (man-made targets) and sea ice classification (natural targets) applications, three SAR DIP methods and experiments are conducted. Improved results are obtained under the guidance of the SAR DIP framework. Therefore, the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies.     

A new kernel method for hyperspectral image feature extraction

Abstract

Hyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground covers. However, the increasing spectral dimensions, as well as the information redundancy, make the analysis and interpretation of hyperspectral images a challenge. Feature extraction is a very important step for hyperspectral image processing. Feature extraction methods aim at reducing the dimension of data, while preserving as much information as possible. Particularly, nonlinear feature extraction methods (e.g. kernel minimum noise fraction (KMNF) transformation) have been reported to benefit many applications of hyperspectral remote sensing, due to their good preservation of high-order structures of the original data. However, conventional KMNF or its extensions have some limitations on noise fraction estimation during the feature extraction, and this leads to poor performances for post-applications. This paper proposes a novel nonlinear feature extraction method for hyperspectral images. Instead of estimating noise fraction by the nearest neighborhood information (within a sliding window), the proposed method explores the use of image segmentation. The approach benefits both noise fraction estimation and information preservation, and enables a significant improvement for classification. Experimental results on two real hyperspectral images demonstrate the efficiency of the proposed method. Compared to conventional KMNF, the improvements of the method on two hyperspectral image classification are 8 and 11%. This nonlinear feature extraction method can be also applied to other disciplines where high-dimensional data analysis is required.     

The circular dataimage,a graph for high-resolution circular-spatial data

Abstract

Vectors and periodic phenomena, e.g. traffic versus time, have direction on a circular scale of 360°. An overview of existing methods for the display of circular-spatial and vectorial-spatial data, such as arrow plots, is given. We introduce the circular dataimage, a new type of graphic for the display of circular-spatial data. It is defined by encoding direction in a spatial display by using colors from a color wheel constructed by connecting three or more two-color gradients with color continuity at the connections. Therefore, image discontinuity from using a single-color gradient, e.g. blue–red, does not occur. High-resolution global views of ocean wind direction are used as a running example throughout the paper. Advantages and disadvantages of circular dataimages compared to arrow plots were obtained from a usability study. Circular dataimages provide for simultaneous recognition of fine structure on a small-scale and large-scale structure on a global scale.     

Use of Very High Spatial Resolution Remotely Sensed Imagery for Assessing Land‐Cover Changes in Shrub Habitat Preserves of Southern California

Abstract

The goal of this research was to explore the utility of very high spatial resolution, digital remotely sensed imagery for monitoring land‐cover changes in habitat preserves within southern California coastal shrublands. Changes were assessed for Los Penasquitos Canyon Preserve, a large open space in San Diego County, over the 1996 to 1999 period for which imagery was available.

Multispectral, digital camera imagery from two summer dates, three years apart, was acquired using the Airborne Data Acquisition and Registration (ADAR) digital‐camera system. These very high resolution (VHR) image data (1m), composed of three visible and one near‐infrared wavebands (V/NIR), were the primary image input for assessing land cover change. Image‐derived datasets generated from georeferenced and registered ADAR imagery included multitemporal overlays and multitemporal band differencing with threshold selection. Two different multitemporal image classifications were generated from these datasets and compared. Single‐date imagery was analyzed interactively with image‐derived datasets and with information from field observations in an effort to discern change types. A ground sampling survey conducted soon after the 1999 image acquisition provided concurrent ground reference data.

Most changes occurring within the three‐year interval were associated with transitional phenological states and differential precipitation effects on herbaceous cover. Variations in air temperatures and timing of rainfall contributed to differences that the seven‐week image acquisition offset may have caused. Disturbance factors of mechanical clearing, erosion, potentially invasive plants, and fire were evident and their influence on the presence, absence, and type of vegetation cover were likely sources of change signals.

The multitemporal VHR, V/NIR image data enabled relatively fine‐scale land cover changes to be detected and identified. Band differencing followed by multitemporal classification provided an effective means for detecting vegetation increase or decrease. Detailed information on short‐term disturbance effects and long‐term vegetation type conversions can be extracted if image acquisitions are carefully planned and geometric and radiometric processing steps are implemented.     

Population Enumeration on a Grid Square Basis: The Census of Scotland,a Test Case

Abstract

After examination of the existing Census organisation, the problems of making full use of the data are investigated, in particular the disparity of units on the ground, changes over time, and variations in the nature of the published information. Proposals are made and explained for the adoption of a grid square enumeration system, which in this case is tested by application to an urban and a rural area. The problem of conflict between grid square and local authority boundary is examined. The more general usefulness of a grid square enumeration system is demonstrated in relation to comparability of data, mechanisation of processing and graphic output, and the data bank concept. Further testing by means of a sample census is being currently undertaken.