检索结果-内蒙古大学图书馆

Comparison of remotely-sensed surveys vs. in situ plot-based assessments of sea grass condition in Barnegat Bay-Little Egg Harbor, New Jersey USA

引用

JOURNAL OF COASTAL CONSERVATION 2014年第3期18卷 299-308页

作者： Lathrop, Richard G., Jr. Haag, Scott M. Merchant, Daniel Kennish, Michael J. Fertig, Benjamin Rutgers State Univ Ctr Remote Sensing & Spatial Anal New Brunswick NJ 08903 USA Rutgers State Univ Inst Marine & Coastal Sci New Brunswick NJ 08903 USA

With the increasing appreciation that sea grass habitats are in global decline, there is a great need to be able to efficiently and effectively assess and characterize the status and trends of sea grass in our coastal ecosystems. This paper examines the utility of remotely sensed vs. in situ plot-based monitoring using the Barnegat Bay-Little Egg Harbor (BB-LEH), New Jersey, USA estuarine system as a case study. Eelgrass (Zostera marina) is the dominant species, while widgeon grass (Ruppia maritima) is also common in lower salinity regions of the BB-LEH. Aerial imagery collected during the months of July and August 2009 was interpreted and mapped using object based image analysis techniques, similar to techniques used in the 2003 mapping survey of this system. Boat-based in situ monitoring data were collected concurrently with the aerial photography to assist the image interpretation and for an independent accuracy assessment. We compared the remotely-sensed mapping of sea grass cover change (in 2003 vs. 2009) vs. in situ plot-based monitoring conducted from 2004 through 2009. Comparison of the remotely-sensed vs. the in situ plot-change analysis suggests that the two methodologies had broadly similarly results, with the percent area showing declines in sea grass cover greater than those that exhibited increases. In conclusion, the two studies provide corroborating evidence that sea grass has declined in percent cover in the BB-LEH system during the decade of the 2000's. While remotely-sensed surveys provide synoptic information for a "big picture" view on sea grass distribution, site specific in situ sampling is required to determine other aspects of sea grass status, e.g. above vs. below-ground biomass, blade length, shoot density, epiphytic loading, etc. Either method alone gives an incomplete picture. As demonstrated in this study, to fully characterize the spatial extent, health, and density of sea grass meadows across the entire estuary, combining remote sensi

关键词： Sea grass status and trends Eutrophication Estuaries object based image analysis

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

A comparison of automated object extraction methods for mound and shell-ring identification in coastal South Carolina

引用

JOURNAL OF ARCHAEOLOGICAL SCIENCE-REPORTS 2019年 23卷 166-177页

作者： Davis, Dylan S. Lipo, Carl P. Sanger, Matthew C. Penn State Univ Dept Anthropol 403 Carpenter Bldg University Pk PA 16802 USA Binghamton Univ Dept Anthropol 4400 Vestal Pkwy Binghamton NY 13902 USA

One persistent archaeological challenge is the generation of systematic documentation for the extant archaeological record at the scale of landscapes. Often our information for landscapes is the result of haphazard and patchy surveys that stem from opportunistic and historic efforts. Consequently, overall knowledge of some regions is the product of ad hoc survey area delineation, degree of accessibility, effective ground visibility, and the fraction of areas that have survived destruction from development. These factors subsequently contribute unknown biases to our understanding of chronology, settlements patterns, interaction, and exchange. Aerial remote sensing offers one potential solution for improving our knowledge of landscapes. With sensors that include LiDAR, remote sensing can identify archaeological features that are otherwise obscured by vegetation. object-based image analyses (OBIA) of remote sensing data hold particular promise to facilitate regional analyses thorough the automation of archaeological feature recognition. Here, we explore four OBIA algorithms for artificial mound feature detection using LiDAR from Beaufort County, South Carolina: multiresolution segmentation, inverse depression analysis, template matching, and a newly designed algorithm that combines elements of segmentation and template matching. While no single algorithm proved to be consistently superior to the others, a combination of methods is shown to be the most effective for detecting archaeological features.

关键词： object based image analysis template matching automatic feature identification remote sensing shell rings LiDAR American Southeast

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Integrated with Multiscale Pixel and object Features for Hyperspectral image Classification 10

Deep Learning Integrated with Multiscale Pixel and Object Fe...

引用

10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)

作者： Zhang, Meng Hong, Liang Yunnan Normal Univ Sch Tourism & Geog Sci Kunming Yunnan Peoples R China Engn Res Ctr GIS Technol Western China Kunming Yunnan Peoples R China

ISBN: (纸本)9781538684795

The spectral resolution and spatial resolution of hyperspectral images are continuously improving, providing rich information for interpreting remote sensing image. How to improve the image classification accuracy has become the focus of many studies. Recently, Deep learning is capable to extract discriminating high-level abstract features for image classification task, and some interesting results have been acquired in image processing. However, when deep learning is applied to the classification of hyperspectral remote sensing images, the spectral-based classification method is short of spatial and scale information;the image patch-based classification method ignores the rich spectral information provided by hyperspectral images. In this study, a multi-scale feature fusion hyperspectral image classification method based on deep learning was proposed. Firstly, multiscale features were obtained by multi-scale segmentation. Then multiscale features were input into the convolution neural network to extract high-level features. Finally, the high-level features were used for classification. Experimental results show that the classification results of the fusion multi-scale features are better than the single-scale features and regional feature classification results.

关键词： Deep learning CNN multiscale feature fusion object based image analysis

来源：评论

学校读者我要写书评

暂无评论

Multiview Feature Selection for Very High Resolution Remote Sensing images 4

Multiview Feature Selection for Very High Resolution Remote ...

引用

4th International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Chen, Xi Li, Hongbo Gu, Yanfeng HIT SEIE Dept Informat Engn Harbin 150001 Heilongjiang Peoples R China

ISBN: (纸本)9781479965755

object based image analysis on very high resolution (VHR) remote sensing imagery often ignores the heterogeneous constitution of feature spaces. In this paper, a supervised multiview feature selection (SMFS) method is proposed. In this method, features are decomposed into multiple disjoint and meaningful feature subsets by employing affinity propagation, where each feature subset represents a view, and each view describes a data characteristic. Features are evaluated and selected within each view. The experimental results on two VHR satellite images, including Quickbird-2 and Worldview-2 images attest to the effectiveness and practicability of the method in compared with traditional single-view algorithms. The results also demonstrate the utility of multiview information in processing VHR datasets.

关键词： supervised multiview feature selection lasso affinity propagation object based image analysis

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Banerjee, Biplab Varma, Surender G. Buddhiraju, Krishna Mohan Indian Inst Technol Ctr Studies Resources Engn Satellite Image Anal Lab Bombay 400076 Maharashtra India

ISBN: (纸本)9781467311595

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

来源：评论

学校读者我要写书评

暂无评论

A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery 2

A local segmentation parameter optimization approach for map...

引用

Conference on Remote Sensing Technologies and Applications in Urban Environments II

作者： Grippa, Tais Georganos, Stefanos Lennert, Moritz Vanhuysse, Sabine Wolff, Eleonore Univ Libre Bruxelles Inst Environm Management & Land Use Planning Dept Geosci Environm & Soc IGEAT Brussels Belgium

ISBN: (数字)9781510613270

ISBN: (纸本)9781510613270;9781510613263

Mapping large heterogeneous urban areas using object-based image analysis (OBIA) remains challenging, especially with respect to the segmentation process. This could be explained both by the complex arrangement of heterogeneous land-cover classes and by the high diversity of urban patterns which can be encountered throughout the scene. In this context, using a single segmentation parameter to obtain satisfying segmentation results for the whole scene can be impossible. Nonetheless, it is possible to subdivide the whole city into smaller local zones, rather homogeneous according to their urban pattern. These zones can then be used to optimize the segmentation parameter locally, instead of using the whole image or a single representative spatial subset. This paper assesses the contribution of a local approach for the optimization of segmentation parameter compared to a global approach. Ouagadougou, located in sub-Saharan Africa, is used as case studies. First, the whole scene is segmented using a single globally optimized segmentation parameter. Second, the city is subdivided into 283 local zones, homogeneous in terms of building size and building density. Each local zone is then segmented using a locally optimized segmentation parameter. Unsupervised segmentation parameter optimization (USPO), relying on an optimization function which tends to maximize both intra-object homogeneity and inter-object heterogeneity, is used to select the segmentation parameter automatically for both approaches. Finally, a land-use/land-cover classification is performed using the Random Forest (RF) classifier. The results reveal that the local approach outperforms the global one, especially by limiting confusions between buildings and their bare-soil neighbors.

关键词： object based image analysis Unsupervised Segmentation Parameters Optimization Local Approach Urban Area Land Cover Mapping

来源：评论

学校读者我要写书评

暂无评论

objectS GROUPING FOR SEGMENTATION OF ROADS NETWORK IN HIGH RESOLUTION imageS OF URBAN AREAS 23

OBJECTS GROUPING FOR SEGMENTATION OF ROADS NETWORK IN HIGH R...

引用

23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

作者： Maboudi, M. Amini, J. Hahn, M. Univ Tehran Coll Engn Sch Surveying & Geospatial Engn Tehran 14174 Iran Univ Appl Sci Dept Geomat Engn Stuttgart Germany

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "object-based image analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refmement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

关键词： Road extraction Segmentation objects grouping object based image analysis Maximal similarity region merging

来源：评论

学校读者我要写书评

暂无评论

QUALITY ASSESSMENT AND CONTROL OF OUTPUTS OF A NATIONWIDE AGRICULTURAL LAND COVER MAPPING PROGRAM USING LIDAR: PHIL-LIDAR 2 PARMAP EXPERIENCE 37

QUALITY ASSESSMENT AND CONTROL OF OUTPUTS OF A NATIONWIDE AG...

引用

37th International Symposium on Remote Sensing of Environment

作者： Pagkalinawan, H. M. Gatdula, N. B. Jose, R. P. Rollan, T. M. Tanada, E. M. Magtalas, S. Y. Dela Torre, D. G. Dela Cruz, P. A. Aves, J. L. Tan, G. D. Apura, R. A. Dimalanta, C. P. Blanco, A. C. Univ Philippines Diliman Natl Engn Ctr Training Ctr Appl Geodesy & Photogrammetry Phil LiDAR 2 Project 1 Agr Resources Extract LIDA Quezon City Philippines Univ Philippines Diliman Coll Engn Dept Geodet Engn Quezon City Philippines

The Agricultural Resources Extraction from LiDAR Surveys (PARMAP) project component of the Nationwide Detailed Resources Assessment using LiDAR (Phil-LiDAR 2) Program aims to produce detailed agricultural maps using LiDAR. Agricultural land cover at crop level was classified through object based image analysis using Support Vector Machine as classifier and LiDAR derivatives from point cloud (2 points per sq.m.) and orthophoto (0.5-meter resolution) as inputs. An accuracy of at least 90%, assessed using validation points from the field and through image interpretation, was required before proceeding to post-processing and map lay-out. Knowledge sharing and capacity development facilitated by the University of the Philippines Diliman (UPD) enabled partner universities across the Philippines to produce outputs for their assigned region. Considering output layers were generated by multiple teams working on different landscape complexities with some degree of data quality variability, quality checking is crucial to ensure accuracy standards were met. UPD PARMap devised a centralized and end-to-end scheme divided into four steps-land classification, GIS post-processing, schema application, and map lay-out. At each step, a block is reviewed and, subsequently, either approved or returned with documentation on required revisions. Turnaround time of review is at least one block (area ranging from 10 to 580 ***.) per day. For coastal municipalities, an additional integration process to incorporate mapped coastal features was applied. Common problems observed during quality checking include misclassifications, gaps between features, incomplete attributes and missing map elements. Some issues are particular to specific blocks such as problematic LiDAR derivatives. UPD addressed these problems through discussion and mentoring visits to partner universities. As of March 2017, a total of 336 municipal agricultural maps have been turned-over to various stakeholders. For the remain

关键词： Agricultural Land Cover Nationwide Mapping Quality Assessment and Control LiDAR object based image analysis

来源：评论

学校读者我要写书评

暂无评论

Observing morphological changes in natural land form through archived satellite images

Observing morphological changes in natural land form through...

引用

International Conference on Technologies for Sustainable Development (ICTSD 2015)

作者： Mendiratta, Priya Gedam, Shirish Indian Inst Technol Ctr Studies Resources Engn Bombay Maharashtra India

ISBN: (纸本)9781479981878

The Mumbai Metropolitan Region (MMR), located to the east of the Arabian Sea, experiences tropical climate with annual rainfall of over 250 cms. Geographically, the Thane Creek separates the island city from the mainland comprising low-lying marshy lands, and is lined by north-south trending hills on either side. The Creek has historically served as the natural course for rainwater discharge from the adjoining hilly terrain. Owing to its peculiar topography, the city has a distinct linear morphology wherein the habitable area along the Creek lies between the water front and these hills. This has necessitated that creation of new firm land on both its shores would either require cutting of foothills and/ or filling of erstwhile low lying marshy lands, both having fragile ecology of their own. This study highlights the significance of satellite image classification and change detection to observe the effect of rapid development and expansion of urban areas over time in the MMR on the morphology of the Creek and its adjoining wetlands. Change-detection analysis performed on classified time-series Landsat images, using object based image analysis (OBIA), reveal gradual change in the profile of the Thane Creek over the years. It is observed that the Creek width has reduced on the western shore, due to the siltation caused by anthropogenic intervention, thereby affecting the adjoining wetland ecosystems. The observations provide useful inputs for the stakeholders, to foster a comprehensive action plan to ensure sustainable futures for both mankind and biodiversity.

关键词： Landsat images object based image analysis Change Detection Thane Creek profile

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：