检索结果-内蒙古大学图书馆

Topic Modelling for object-based Unsupervised Classification of VHR Panchromatic Satellite images based on Multiscale image Segmentation

引用

REMOTE SENSING 2017年第8期9卷 840-840页

作者： Shen, Li Wu, Linmei Dai, Yanshuai Qiao, Wenfan Wang, Ying Southwest Jiaotong Univ State Prov Joint Engn Lab Spatial Informat Techno Chengdu 611756 Sichuan Peoples R China Southwest Jiaotong Univ Fac Geosci & Environm Engn Chengdu 611756 Sichuan Peoples R China

image segmentation is a key prerequisite for object-based classification. However, it is often difficult, or even impossible, to determine a unique optimal segmentation scale due to the fact that various geo-objects, and even an identical geo-object, present at multiple scales in very high resolution (VHR) satellite images. To address this problem, this paper presents a novel unsupervised object-based classification for VHR panchromatic satellite images using multiple segmentations via the latent Dirichlet allocation (LDA) model. Firstly, multiple segmentation maps of the original satellite image are produced by means of a common multiscale segmentation technique. Then, the LDA model is utilized to learn the grayscale histogram distribution for each geo-object and the mixture distribution of geo-objects within each segment. Thirdly, the histogram distribution of each segment is compared with that of each geo-object using the Kullback-Leibler (KL) divergence measure, which is weighted with a constraint specified by the mixture distribution of geo-objects. Each segment is allocated a geo-object category label with the minimum KL divergence. Finally, the final classification map is achieved by integrating the multiple classification results at different scales. Extensive experimental evaluations are designed to compare the performance of our method with those of some state-of-the-art methods for three different types of images. The experimental results over three different types of VHR panchromatic satellite images demonstrate the proposed method is able to achieve scale-adaptive classification results, and improve the ability to differentiate the geo-objects with spectral overlap, such as water and grass, and water and shadow, in terms of both spatial consistency and semantic consistency.

关键词： very high resolution (VHR) satellite image topic modelling object-based image analysis image segmentation unsupervised classification multiscale representation

来源：评论

学校读者我要写书评

暂无评论

Towards a multi-scale approach for an Earth observation-based assessment of natural resource exploitation in conflict regions

引用

GEOCARTO INTERNATIONAL 2017年第10期32卷 1139-1158页

作者： Schoepfer, Elisabeth Sproehnle, Kristin Kranz, Olaf Blaes, Xavier Kolomaznik, Jan Hilgert, Filip Bartalos, Tomas Kemper, Thomas German Remote Sensing Data Ctr DFD German Aerosp Ctr DLR Oberpfaffenhofen Germany European Commiss Joint Res Ctr Ispra Italy Gisat Sro Prague Czech Republic IPIS Antwerp Belgium

The exploitation of resources, if not properly managed, can lead to spoiling natural habitats as well as to threatening people's health, livelihoods and security. The paper discusses a multi-scale Earth observation-based approach to provide independent information related to exploitation activities of natural resources for countries which are experiencing armed conflict. The analyses are based on medium to very high spatial resolution optical satellite data. object-based image analysis is used for information extraction at these different scales. On a subnational level, conflict-related land cover changes as an indication of potential hot spots for exploitation activities are classified. The regional assessment provides information about potential activity areas of resource exploitation, whereas on a local scale, a site-specific assessment of exploitation areas is performed. The study demonstrates the potential of remote sensing for supporting the monitoring and documentation of natural resource exploitation in conflict regions.

关键词： Democratic Republic of the Congo land cover natural resources mining object-based image analysis

来源：评论

学校读者我要写书评

暂无评论

High-resolution riparian vegetation mapping to prioritize conservation and restoration in an impaired desert river

引用

RESTORATION ECOLOGY 2017年第3期25卷 333-341页

作者： Macfarlane, William W. McGinty, Christopher M. Laub, Brian G. Gifford, Suzanne J. Utah State Univ Dept Watershed Sci Logan UT 84322 USA Utah State Univ RS GIS Lab Logan UT 84322 USA Utah State Univ Ctr Ecol Logan UT 84322 USA

In highly impaired watersheds, it is critical to identify both areas with desirable habitat as conservation zones and impaired areas with the highest likelihood of improvement as restoration zones. We present how detailed riparian vegetation mapping can be used to prioritize conservation and restoration sites within a riparian and instream habitat restoration program targeting 3 native fish species on the San Rafael River, a desert river in southeastern Utah, United States. We classified vegetation using a combination of object-based image analysis (OBIA) on high-resolution (0.5m), multispectral, satellite imagery with oblique aerial photography and field-based data collection. The OBIA approach is objective, repeatable, and applicable to large areas. The overall accuracy of the classification was 80% (Cohen's =0.77). We used this high-resolution vegetation classification alongside existing data on habitat condition and aquatic species' distributions to identify reaches' conservation value and restoration potential to guide management actions. Specifically, cottonwood (Populus fremontii) and tamarisk (Tamarix ramosissima) density layers helped to establish broad restoration and conservation reach classes. The high-resolution vegetation mapping precisely identified individual cottonwood trees and tamarisk thickets, which were used to determine specific locations for restoration activities such as beaver dam analogue structures in cottonwood restoration areas, or strategic tamarisk removal in high-density tamarisk sites. The site prioritization method presented here is effective for planning large-scale river restoration and is transferable to other desert river systems elsewhere in the world.

关键词： GIS habitat assessment native fish object-based image analysis San Rafael River vegetation classification

来源：评论

学校读者我要写书评

暂无评论

image analysis of immune cell patterns in the human mammary gland during the menstrual cycle refines lymphocytic lobulitis

引用

BREAST CANCER RESEARCH AND TREATMENT 2017年第2期164卷 305-315页

作者： Schaadt, Nadine S. Alfonso, Juan Carlos Lopez Schoenmeyer, Ralf Grote, Anne Forestier, Germain Wemmert, Cedric Kroenke, Nicole Stoeckelhuber, Mechthild Kreipe, Hans H. Hatzikirou, Haralampos Feuerhake, Friedrich Hannover Med Sch Inst Pathol Neuropathol Carl Neuberg Str 1 D-30625 Hannover Germany Univ Strasbourg ICube 300 Bvd Sebastien Brant F-67412 Illkirch Graffenstaden France Helmholtz Ctr Infect Res Dept Syst Immunol Inhoffenstr 7 D-38124 Braunschweig Germany Helmholtz Ctr Infect Res Braunschweig Integrated Ctr Syst Biol Inhoffenstr 7 D-38124 Braunschweig Germany Definiens AG Bernhard Wicki Str 5 D-80636 Munich Germany Univ Haute Alsace MIPS 12 Rue Freres F-68093 Mulhouse France Tech Univ Munich Dept Oral & Maxillofacial Surg Ismaningerstr 22 D-81675 Munich Germany Univ Clin Freiburg Inst Neuropathol Breisacher Str 64 D-76106 Freiburg Germany

Purpose To improve microscopic evaluation of immune cells relevant in breast cancer oncoimmunology, we aim at distinguishing normal infiltration patterns from lymphocytic lobulitis by advanced image analysis. We consider potential immune cell variations due to the menstrual cycle and oral contraceptives in non-neoplastic mammary gland tissue. Methods Lymphocyte and macrophage distributions were analyzed in the anatomical context of the resting mammary gland in immunohistochemically stained digital whole slide images obtained from 53 reduction mammoplasty specimens. Our image analysis workflow included automated regions of interest detection, immune cell recognition, and co-registration of regions of interest. Results In normal lobular epithelium, seven CD8 lymphocytes per 100 epithelial cells were present on average and about 70% of this T-lymphocyte population was lined up along the basal cell layer in close proximity to the epithelium. The density of CD8 T-cell was 1.6 fold higher in the luteal than in the follicular phase in spontaneous menstrual cycles and 1.4 fold increased under the influence of oral contraceptives, and not co-localized with epithelial proliferation. CD4 T-cells were infrequent. Abundant CD163 macrophages were widely spread, including the interstitial compartment, with minor variation during the menstrual cycle. Conclusions Spatial patterns of different immune cell subtypes determine the range of normal, as opposed to inflammatory conditions of the breast tissue microenvironment. Advanced image analysis enables quantification of hormonal effects, refines lymphocytic lobulitis, and shows potential for comprehensive biopsy evaluation in oncoimmunology.

关键词： Lymphocytic lobulitis Digital pathology Oncoimmunology object-based image analysis Menstrual cycle Hormonal fluctuations

来源：评论

学校读者我要写书评

暂无评论

Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale

引用

REMOTE SENSING 2018年第8期10卷 1285-1285页

作者： Attarzadeh, Reza Amini, Jalal Notarnicola, Claudia Greifeneder, Felix Univ Tehran Coll Engn Sch Surveying & Geospatial Engn Tehran *** Iran Inst Earth Observat Eurac Res I-39100 Bolzano Italy

This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R-2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.

关键词： soil moisture mapping object-based image analysis support vector regression Sentinel 1&2 SAR plot scale the C-band feature selection

来源：评论

学校读者我要写书评

暂无评论

INTEGRATION OF SAR AND GEOBIA FOR THE analysis OF TIME-SERIES DATA

INTEGRATION OF SAR AND GEOBIA FOR THE ANALYSIS OF TIME-SERIE...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： D. Amitrano F. Cecinati G. Di Martino A. Iodice P. -P. Mathieu D. Riccio G. Ruello University of Napoli Federico II Napoli Italy University of Bath Bath UK European Space Agency ESA ESRIN Frascati Italy

In this work, we present a new architecture for the analysis multitemporal SAR data combining classic synthetic aperture radar processing and geographical object-based image analysis. The architecture exploits the characteristics of the recently introduced RGB products of the Level-1α and Level-1β families, employing self-organizing map clustering and object-based image analysis aiming at the definition of opportune layers measuring scattering and geometric properties of candidate objects to classify. The obtained results have been compared with those given by literature and turned out to provide high degree of accuracy and negligible false alarms. The discussion is supported by an example concerning small reservoir mapping in semi-arid environment.

关键词： Multitemporal synthetic aperture radar Classification Self-organizing map clustering object-based image analysis

来源：评论

学校读者我要写书评

暂无评论

object based BUILDING EXTRACTION AND BUILDING PERIOD ESTIMATION FROM UNMANNED AERIAL VEHICLE DATA

OBJECT BASED BUILDING EXTRACTION AND BUILDING PERIOD ESTIMAT...

引用

The ISPRS Technical Commission III Midterm Symposium on "Developments, Technologies and Applications in Remote Sensing"

作者： R.Comert O.Kaplan Department of Geomatics Engineering Faculty of Engineering and Natural SciencesGumushane University Earth and Space Sciences Institute Anadolu University

The aim of this study is to examine whether it is possible to estimate the building periods with respect to the building heights in the urban scale seismic performance assessment studies by using the building height retrieved from the unmanned aerial vehicle(UAV) data. For this purpose, a small area, which includes eight residential reinforced concrete buildings, was selected in Eskisehir(Turkey) city center. In this paper, the possibilities of obtaining the building heights that are used in the estimation of building periods from UAV based data, have been investigated. The investigations were carried out in 3 stages;(i) Building boundary extraction with object based image analysis(OBIA),(ii) height calculation for buildings of interest from n DSM and accuracy assessment with the terrestrial survey.(iii) Estimation of building period using height information. The average difference between the periods estimated according to the heights obtained from field measurements and from the UAV data is 2.86% and the maximum difference is 13.2%. Results of this study have shown that the building heights retrieved from the UAV data can be used in the building period estimation in the urban scale vulnerability assessments.

关键词： Building Period Building Height UAV object-based image analysis

来源：评论

学校读者我要写书评

暂无评论

object-based image analysis AND DATA MINING FOR MAPPING SUGARCANE WITH LANDSAT imageRY IN BRAZIL

OBJECT-BASED IMAGE ANALYSIS AND DATA MINING FOR MAPPING SUGA...

引用

Conference on Geographic object-based image analysis (GEOBIA)

作者： Formaggio, A. R. Vieira, M. A. Renno, C. D. Aguiar, D. A. Mello, M. P. INPE BR-12227010 Sao Jose Dos Campos SP Brazil

Mapping of sugarcane planted area is an important information for decision making, mainly when the search for alternatives to mitigate greenhouse gas emissions has indicated the use of biofuels as a viable option. Thus, the aim of this research was to develop a methodology in order to automate the sugarcane mapping task when remote sensing data are used. Thus the integration of two major approaches of Artificial Intelligence, object-based image analysis (OBIA) and Data Mining (DM), were tested in a study area located in Sao Paulo state, which is well representative of the agriculture of large regions of Brazil and other countries. OBIA was used to emulate the interpreter knowledge in the process of sugarcane mapping, and DM techniques were employed for automatic generation of knowledge model. A time series of four Landsat images was acquired in order to represent the wide variability of the patterns during sugarcane crop season. Definiens Developer (R) multiresolution segmentation algorithm produced the objects and properly trained decision tree applied to the Landsat data for the generation of the thematic map with sugarcane as the main class of interest. An overall accuracy of 94% (Kappa = 0,87) was obtained, showing that OBIA and DM are very efficient and promising in the direction of automating the sugarcane classification process with Landsat multitemporal time series.

关键词： Sugarcane mapping Artificial Intelligence object-based image analysis Data Mining Landsat images

来源：评论

学校读者我要写书评

暂无评论

POLSAR image CLASSIFICATION based ON POLARIMETRIC object-based MORPHOLOGICAL PROFILES 37

POLSAR IMAGE CLASSIFICATION BASED ON POLARIMETRIC OBJECT-BAS...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Xu, Xiaofang Zou, Bin Zhang, Lamei Harbin Inst Technol Dept Informat Engn Harbin 150001 Heilongjiang Peoples R China

ISBN: (纸本)9781509049516

Morphology profiles (MPs) have been applied to the processing of different types of imagery, which have highly improved the segmentation and classification results. MPs can both preserve spatial structures of objects and construct the multiscale description of images. Since the speckle noise inherent in the images, the classification of PolSAR images cannot obtain satisfied results. In this paper, the framework of polarimetric object-based morphological profiles (POMPs) is proposed in which the MPs features and polarimetric features are combined and object-based image analysis (OBIA) is introduced to Po1SAR image classification. based on statistical measures of central tendency, the POMPs are obtained by integrating the feature vector of images with the segments of meanshift segmentation. To evaluate the effectiveness of the proposed method, POMPs are introduced to support vector machine (SVM) classifier. Experiments on the EMISAR image using object-based polarimetric features, object-based MPs and POMPs features respectively are implemented and compared. The results show that the proposed method can effectively improve classification accuracy of high resolution PolSAR images.

关键词： High resolution PolSAR image classification morphological profiles (MPs) object-based image analysis

来源：评论

学校读者我要写书评

暂无评论

Redevelopment and the urban forest: A study of tree removal and retention during demolition activities

引用

APPLIED GEOGRAPHY 2017年 82卷 1-10页

作者： Morgenroth, Justin -Dunne, Jarlath O'Neil Apiolaza, Luis A. Univ Canterbury New Zealand Sch Forestry Christchurch New Zealand Univ Vermont Spatial Anal Lab Burlington VT 05405 USA

Though relationships between urbanization and tree cover are generally well studied, the effect of redevelopment on urban trees, at the scale of the individual property, is not well understood. Developing knowledge in this area is important in order to limit tree loss during redevelopment and thus, ensure sustained ecosystem services. Here, we explore the removal or retention of trees adjacent to building demolition in Christchurch, New Zealand. We mapped the presence or absence of individual trees on 123 properties prior to, and following, building demolition. Using a classification tree (CT) analysis, the presence or absence of 1209 trees was modelled as a function of: tree-related variables, property-related variables, and economic variables. The CT model estimated tree presence/absence with overall accuracy of 80.4%. Results show that 21.6% of all trees were removed as a consequence of building demolition, resulting in a tree canopy cover reduction of 19.7% across all 123 properties. The CT showed that tree crown area was the most important variable for predicting the presence/absence of trees, whereby trees with small crown areas (<7.9 m(2)) were most frequently removed, especially if they were within 0.7 m of a demolished building. Land value was also an important determinant of tree presence/absence, such that tree removal was more prevalent on properties with higher land value ($/m(2)). The results provide important new insights into some of the reasons for tree removal or retention during redevelopment at the scale of the individual property where most tree-related decisions are made. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Green infrastructure Greenspace Landscape ecology object-based image analysis Sustainable urban development Urban consolidation Urban planning Urbanization Teardowns

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：