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IEEE International Geoscience and Remote Sensing Symposium

作者： Dipak R. Samal Shirish S. Gedam Indian Institute of Technology Bombay

ISBN: (纸本)9781467311601

The process of urbanization and industrialization always have an impact on the hydrological regime and alternate land use pattern of the area. The present study is being carried out for the upper Bhima basin in western India. The basin has undergone various land use changes during last decade and before due to various anthropogenic activities. An object based image analysis approach along with rainfall and resulting stream flow records for last two decades (1985-2004) were analyzed to study the impact of land use on steam flow in the basin. The study revealed that rainfall pattern was nearly constant during study period, whereas a significant reduction in stream flow has been observed. Conversion of wasteland to agricultural land, construction of new dams/reservoirs in the high rainfall region, increase in domestic and industrial water demand are the major factors responsible for stream flow reduction in the basin.

关键词： Bhima basin Land use Stream flow object based image analysis Land use streamflow basins Basins image analysis approach steam flow Water requirements Case studies Hydrological regime rain Rainfall waste land Industrialization Urbanization

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SATELLITE image SEGMENTATION: A NOVEL ADAPTIVE MEAN-SHIFT CLUSTERING based APPROACH

SATELLITE IMAGE SEGMENTATION: A NOVEL ADAPTIVE MEAN-SHIFT CL...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Biplab Banerjee Surender Varma, G. Krishna Mohan Buddhiraju Satellite Image Analysis Lab Centre of Studies in Resources Engineering Indian Institute of Technology Bombay

ISBN: (纸本)9781467311601

Segmentation of satellite images using a novel adaptive non parametric mean-shift clustering algorithm is proposed in this paper. image segmentation refers to the process of splitting up an image into its constituent objects. It is also an important step in bridging the semantic gap between low level image interpretation and high level visual analysis. Mean-shift technique is based on the concept of kernel density estimation. It has been applied successfully in diverse vision related tasks including segmentation. The performance of the mean shift algorithm is greatly affected by the size of the parzen window and the terminating criteria. These two issues have been taken care of here in a purely statistical framework. The efficiency of this newly developed adaptive clustering has been judged for segmentation of any initially oversegmented satellite image. The notion of object based image analysis is preserved by initially over segmenting the image by watershed technique. Extensive experiments on several multispectral satellite images have confirmed the effectivity of this proposed approach in comparison to some widely used state of the art segmentation methods.

关键词： Segmentation Clustering Unsupervised learning Mean-Shift object based image analysis

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Solid modeling of fossil small mammal teeth

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COMPUTERS & GEOSCIENCES 2011年第9期37卷 1364-1371页

作者： Marschallinger, Robert Hofmann, Peter Daxner-Hoeck, Gudrun Ketcham, Richard A. Austrian Acad Sci GISci Inst Salzburg Austria Nat Hist Museum Vienna Austria Univ Texas Austin Jackson Sch geosci High Resolut Xray CT Facil Austin TX 78712 USA

This paper presents an approach to create solid models of fossil small mammal teeth using a combination of microcomputed tomography, object based image analysis and voxel modeling. Small mammal teeth, because of their durability, are widely found in Cenozioc sediments the world over and play a key role in stratigraphy as well as in researching the rapid evolution and the paleogeographic spreading of small mammals. Recent advances in microcomputed tomography make this non-destructive analysis method an ideal data source for high-resolution 3D models of fossil small animal teeth. To derive internally consistent solid models of such fossils from micro-CT imagery, we propose a combination of 3D object based image analysis and solid modeling. Incorporating paleontological expert knowledge in the image processing cycle, object based image analysis yields topologically consistent image stacks classified by the main tooth components-enamel, dentine and pulp. Forwarding these data to a voxel modeling system, they can be quantitatively analyzed in an unprecedented manner: going beyond the possibilities of the state-of-art surface models, solid models are capable of unambiguously portraying the entire object volume-teeth can be peeled by material properties, subvolumes can be extracted and automatically analyzed by Boolean operations. The proposed method, which can be flexibly extended to handle a range of paleontological and geological micro-objects, is demonstrated with two typical fossil small mammal teeth. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Microcomputed tomography object based image analysis Voxel modeling

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Mapping Green Spaces in Bishkek-How Reliable can Spatial analysis Be?

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REMOTE SENSING 2011年第6期3卷 1088-1103页

作者： Hofmann, Peter Strobl, Josef Nazarkulova, Ainura Austrian Acad Sci Dept GISci A-5020 Salzburg Austria Salzburg Univ Ctr Geoinformat A-5020 Salzburg Austria Austria Cent Asia Ctr GISci Bischkek 720020 Kyrgyzstan

Within urban areas, green spaces play a critically important role in the quality of life. They have remarkable impact on the local microclimate and the regional climate of the city. Quantifying the 'greenness' of urban areas allows comparing urban areas at several levels, as well as monitoring the evolution of green spaces in urban areas, thus serving as a tool for urban and developmental planning. Different categories of vegetation have different impacts on recreation potential and microclimate, as well as on the individual perception of green spaces. However, when quantifying the 'greenness' of urban areas the reliability of the underlying information is important in order to qualify analysis results. The reliability of geo-information derived from remote sensing data is usually assessed by ground truth validation or by comparison with other reference data. When applying methods of object based image analysis (OBIA) and fuzzy classification, the degrees of fuzzy membership per object in general describe to what degree an object fits (prototypical) class descriptions. Thus, analyzing the fuzzy membership degrees can contribute to the estimation of reliability and stability of classification results, even when no reference data are available. This paper presents an object based method using fuzzy class assignments to outline and classify three different classes of vegetation from GeoEye imagery. The classification result, its reliability and stability are evaluated using the reference-free parameters Best Classification Result and Classification Stability as introduced by Benz et al. in 2004 and implemented in the software package eCognition (***). To demonstrate the application potentials of results a scenario for quantifying urban 'greenness' is presented.

关键词： object based image analysis GeoEye urban green fuzzy classification classification reliability

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Automatic counting of fission tracks using object-based image analysis for dating applications

Automatic counting of fission tracks using object-based imag...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Lippold, J. Marpu, P. R. Gloaguen, R. Jonckheere, R. Tech Univ Bergakad Freiberg D-09596 Freiberg Germany

ISBN: (纸本)9781424412112

Geochronological dating with the fission-track method is based on time-consuming counts of the spontaneous and induced tracks. Automatic extraction and identification of tracks would not only improve the speed of track counting but also eliminate variation due to the observer. Pixel values alone are not enough to distinguish between tracks and background. Traditional pixel-based approaches are therefore inefficient for fission track counting. image analysis based on objects, which include shape, texture and context information is a more promising method.

关键词： object based image analysis fission-track-dating

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Forest Habitat Change Dynamics in a Riparian Wetland

Forest Habitat Change Dynamics in a Riparian Wetland

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1st International Conference on Spatial Statistics - Mapping Global Change

作者： Kollar, Szilvia Vekerdy, Zoltan Markus, Bela Univ W Hungary Fac Geoinformat H-8000 Szekesfehervar Hungary ITC Dept Water Resources NL-7500 AE Enschede Netherlands

Our study aims at monitoring ecosystem dynamics in the Szigetkoz Danube floodplain (Hungary), where the wetland communities have been seriously affected by the abrupt hydrological changes after the Danube-diversion in 1992. Wetland habitats were mapped in the last years for a chosen area, based on a comparable use of archived analogue and digital aerial images and available silvicultural and botanical inventories. During the object-based image analysis the classification was mainly based on texture measures. The resulting map time series show habitat borders for each year and present the changes separately for each class. The method is suitable for the characterization of spatial and temporal structure of wetland land cover in a realistic way. (C) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

关键词： remote sensing object based image analysis wetland change detection aerial imagery texture based classification.

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Mapping Carbon Stock using High Resolution satellite images In Sub-tropical Forest Of Nepal

Mapping Carbon Stock using High Resolution satellite Images ...

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作者： Srijana Baral University of Twente

学位级别：硕士

Estimation of above ground carbon stock is essential for understanding the global carbon cycle. All countries committed to UNFCCC and Kyoto Protocol and participating in REDD should update the inventories of emissions of greenhouse gases and estimate the amount of carbon stock. But accurate carbon stock mapping from satellite imagery is still a challenge. Thus, this study aims to develop a method to estimate amount of above ground carbon stock in the natural sub-tropical forest of Chitwan, Nepal using high resolution satellite images. Geo-Eye and Worldview, very high resolution images were used for the study. Both the images have same spatial resolution but have difference in spectral resolution. Total above ground biomass (AGB) is estimated using allometric equation from the DBH measured in the field, which was then converted to carbon stock using a conversion factor. The relationship between crown projection area (CPA) and Carbon was established using carbon stock of 78 trees recognized in the field and CPA derived from image. object based image analysis was carried out in both the images to obtain CPA. A non- linear regression model was developed between the calculated carbon and CPA derived from image to the estimate image carbon stock in the study area. The estimated carbon stock was validated using validation data set collected in field. The segmentation and classification results were better in case of Geo-Eye compared to Worldview. Classification was done in two classes with Shorea robusta and other species. So, CPA derived from Geo- Eye was used to develop a non-linear regression model to produce a carbon map. The regression model developed was significant and yield high coefficient of determination in both the classes. The model was applied to obtain carbon map with carbon stock approximately 70 MgCha- 1. Non-linear model explained 61% of the predicted carbon. Shadow content, use of general allometric equation and time lag in data collection and image acqu

关键词： object based image analysis Segmentation Classification Carbon Stock Allometric equation Regression

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Forest Habitat Change Dynamics in a Riparian Wetland

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Procedia Environmental Sciences 2011年 7卷 371-376页

作者： Szilvia Kollár Zoltán Vekerdy Béla Márkus Faculty of Geoinformatics University of West Hungary Székesfehérvár 8000 Hungary Department of Water Resources ITC Enschede 7500 AE The Netherlands

Our study aims at monitoring ecosystem dynamics in the Szigetköz Danube floodplain (Hungary), where the wetland communities have been seriously affected by the abrupt hydrological changes after the Danube-diversion in 1992. Wetland habitats were mapped in the last years for a chosen area, based on a comparable use of archived analogue and digital aerial images and available silvicultural and botanical inventories. During the object-based image analysis the classification was mainly based on texture measures. The resulting map time series show habitat borders for each year and present the changes separately for each class. The method is suitable for the characterization of spatial and temporal structure of wetland land cover in a realistic way.

关键词： remote sensing object based image analysis wetland change detection aerial imagery texture based classification

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Integration of LiDAR and QuickBird imagery for mapping riparian biophysical parameters and land cover types in Australian tropical savannas

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FOREST ECOLOGY AND MANAGEMENT 2010年第3期259卷 598-606页

作者： Arroyo, Lara A. Johansen, Kasper Armston, John Phinn, Stuart Univ Queensland Ctr Remote Sensing & Spatial Informat Sci Sch Geog Planning Environm Management Brisbane Qld 4072 Australia Ctr Remote Sensing Queensland Dept Environm & Resource Management Indooroopilly Qld 4068 Australia

Riparian zones are exposed to increasing pressures because of disturbance from agricultural and urban expansion and overgrazing. Accurate and cost-effective mapping of riparian environments is important for baseline inventories and monitoring and managing their functions associated with water quality, biodiversity, and wildlife habitats. In this study, we integrate remotely sensed light detection and ranging (LiDAR) data and high spatial resolution satellite imagery (QuickBird-2) to estimate riparian biophysical parameters and land cover types in the Fitzroy catchment in Queensland, Australia. An object based image analysis (OBIA) was adopted for the study. A digital terrain model (DTM), a tree canopy model (TCM) and a plant projective cover (PPC) map were first derived from the LiDAR data. A map of the streambed was then produced using the DTM information. Finally, all the LiDAR-derived biophysical map products and the QuickBird image bands were combined in an OBIA to (1) map the following land cover types: riparian vegetation, streambed, bare ground, woodlands and rangelands: (2) determine the distribution of overhang vegetation within the streambed;and (3) measure the width of both the riparian zone and the streambed. The combined use of both datasets allowed accurate land cover mapping, with an overall accuracy of 85.6%. The estimated widths of the riparian zone and the streambed showed strong correlation with the actual field measurements (r = 0.82 and 0.98 respectively). Our results show that the combined use of LiDAR and high spatial resolution imagery can potentially be used for the assessment of the riparian condition in a tropical savanna woodland riparian environment. This work also shows the capacity of OBIA to assist in the assessment of the composition of the riparian environment from multiple image datasets. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Riparian zone Riparian zone and streambed widths Riparian land cover object based image analysis LiDAR QuickBird Tropical savanna Australia

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Assessment of SPOT 5 and QuickBird remotely sensed imagery for mapping tree cover in savannas

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INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 2010年第4期12卷 217-224页

作者： Boggs, G. S. Charles Darwin Univ Sch Environm & Life Sci Darwin NT 0909 Australia

The relative abundance and distribution of trees in savannas has important implications for ecosystem function. High spatial resolution satellite sensors, including QuickBird and IKONOS, have been successfully used to map tree cover patterns in savannas. SPOT 5, with a 2.5 m panchromatic band and 10 m multispectral bands, represents a relatively coarse resolution sensor within this context, but has the advantage of being relatively inexpensive and more widely available. This study evaluates the performance of NDVI threshold and object based image analysis techniques for mapping tree canopies from QuickBird and SPOT 5 imagery in two savanna systems in southern Africa. High thematic mapping accuracies were obtained with the QuickBird imagery, independent of mapping technique. Geometric properties of the mapping indicated that the NDVI threshold produced smaller patch sizes, but that overall patch size distributions were similar. Tree canopy mapping using SPOT 5 imagery and an NDVI threshold approach performed poorly, however acceptable thematic accuracies were obtained from the object based image analysis. Although patch sizes were generally larger than those mapped from the QuickBird image data, patch size distributions mapped with object based image analysis of SPOT 5 have a similar form to the QuickBird mapping. This indicates that SPOT 5 imagery is suitable for regional studies of tree canopy cover patterns. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Tree cluster Canopy cover SPOT 5 QuickBird object based image analysis NDVI threshold Savanna Southern Africa

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