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

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

GEOMORPHIC DETERMINANATS OF LANDUSE INTENSITY

GEOMORPHIC DETERMINANATS OF LANDUSE INTENSITY

引用

ISPRS Technical Commission VIII Symposium

作者： Chidi, Chhabi Lal Tribhuvan Univ Cent Dept Geog Kathmandu Nepal

Increasing population growth and lacking of further spatial expansion of various landuse have compelled to look intensity dimension of landuse. Grid cell based data extraction can give unique character of each locality of small land unit area which is very suitable technique for data extraction in the hill areas like Nepal. Landform plays an important role determining landuse intensity. Freely available 30m resolution Aster GDEM image has been used to extract geomorphic variables. Landuse data has been taken from aerial photo 1996. Quantitative weight has been given to landuse categories on the basis input, output and ecological importance for human life. One hectare square grid cells have been generated to extract geomorphic and landuse intensity information. The result shows that the average intensity of landuse is highly related to summarized categories of each geomorphic variable. Graphical presentation and quantitative analysis have been used to identify the effect of geomorphic variables on land use intensity. Simple and multiple correlation and regression analysis shows that there is higher control of altitude, slope gradient and slope aspect on landuse intensity. The average landuse intensity is highly determined by geomorphic variable then in local level. Multiple correlation coefficients is found to be 0.42 and the adjusted R-2 representing coefficient of determination is 0.178 which is significant at more than 99% of confidence level. So, it can be concluded that geomorphic factors have contributed 17.8% of the total variation determining landuse intensity in the study area.

关键词： Dummy variable Geomorphic variable Landuse intensity object based image analysis Grid cell base

来源：评论

学校读者我要写书评

暂无评论

STUDY ON THE INTELLIGENT EXTRACTION OF SEISMIC DAMAGE based ON THE MEAN-SHIFT SEGMENTATION

STUDY ON THE INTELLIGENT EXTRACTION OF SEISMIC DAMAGE BASED ...

引用

IEEE Joint International Geoscience and Remote Sensing Symposium (IGARSS) / 35th Canadian Symposium on Remote Sensing

作者： Zhang, Wei Wang, Xiaoqing Dou, Aixia China Earthquake Adm Inst Earthquake Sci Beijing Peoples R China

ISBN: (纸本)9781479957750

The limitations of parameter determination manually exist in the current object based image analysis (OBIA) of the commercial software, such as Definiens eCognition or ENVI FX, In this paper, an intelligent method based on Mean-Shift and support vector machines (SVM) algorithm of OBIA is proposed to extract the building damage caused by catastrophic earthquakes, which aims to improve the accuracy of classification and get the best bandwidth parameter of the Mean-Shift segmentation automatically by computing the Kappa index that has been used in a feedback loop. The improved method is applied to extract seismic damage information in a test area of the city of Dujiangyan after the 2008 Wenchuan earthquake by using post-earthquake aerial images acquired on May 18, 2008. The results of the experiments indicate that the improved OBIA is more effective and robust than traditional method of OBIA.

关键词： Mean-Shift SVM seismic damage extraction object based image analysis Kappa index

来源：评论

学校读者我要写书评

暂无评论

A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis

引用

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2008年第4期63卷 461-475页

作者： Liu, Yu Guo, Qinghua Kelly, Maggi Univ Calif Merced Sch Engn Merced CA 95344 USA Peking Univ Inst Remote Sensing & Geog Informat Syst Beijing 100871 Peoples R China Univ Calif Berkeley Geospatial Imaging and Infomat Facil Dept Environm Sci Policy & Management Berkeley CA 94720 USA

object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However. less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this "single-valued" space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent "line-like objects" and "point-like objects" are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasitopological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis. Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

关键词： region-based spatial relations single-valued space object based image analysis

来源：评论

学校读者我要写书评

暂无评论

Cascaded classification of high resolution remote sensing images using multiple contexts

引用

INFORMATION SCIENCES 2013年 221卷 84-97页

作者： Guo, Jun Zhou, Hui Zhu, Changren Natl Univ Def Technol Inst Elect Sci & Engn ATR Natl Lab Changsha Hunan Peoples R China Beijing Inst Tracking & Telecommun Technol Beijing Peoples R China

We present a novel cascaded classification approach by exploiting various contexts on different levels for high resolution remote sensing (HRRS) images. The contexts mentioned in our article are defined according to objects from a set of regions resulting from segmentation. The cascaded procedure comprises three stages: (1) initializing the classification using the object's inner context (i.e., the gray constraints of different pixels in an object), (2) correcting the classification using the object's neighbor context (i.e., the characteristic constraints of different objects adjacent to the concerned object), and (3) refining classification using the object's scene context (i.e., the distribution constraint of different objects' labels and their feature vectors in the whole scene). The proposed algorithm has the following distinctions. First, it uses an object's neighbor context to bridge the gap between its inner context and its scene context because the latter two types of contexts have inevitable drawbacks when being used for classification alone. Second, it carries on a cascaded classification procedure in which the previous stage provides a better initial classification for the following stage, and the result is gradually refined by integrating different contexts. The effectiveness and practicability of the proposed algorithm is demonstrated through a set of completely experimental results and substantiated using quantitative criteria. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Context-enabled classification object based image analysis Multiple contexts integration High resolution remote sensing images

来源：评论

学校读者我要写书评

暂无评论

Pocket parks in a compact city: how do birds respond to increasing residential density?

引用

LANDSCAPE ECOLOGY 2013年第1期28卷 45-56页

作者： Ikin, Karen Beaty, R. Matthew Lindenmayer, David B. Knight, Emma Fischer, Joern Manning, Adrian D. Australian Natl Univ Fenner Sch Environm & Soc Canberra ACT 0200 Australia CSIRO Ecosyst Sci Black Mt Labs Black Mt ACT 2601 Australia Australian Natl Univ Ctr Math & Its Applicat Canberra ACT 0200 Australia Univ Luneburg Dept Sustainabil Sci D-21335 Luneburg Germany

The desire to improve urban sustainability is motivating many city planners to adopt growth strategies that increase residential density, leading to substantial changes to urban landscapes. What effect this change will have on biodiversity remains unclear, but it is expected that the role of public greenspace in providing wildlife habitat will become critical. We explored the role of urban "pocket parks" as habitat for birds, and how this role changed with increasing residential density in the surrounding neighbourhood. We found that parks in neighbourhoods with high levels of public greenspace (corresponding to less residential land) supported more bird species and individuals overall, and more woodland-dependent species, insectivores and hollow-nesters. Total greenspace area was more important (included in the best ranked models for all bird responses) than the configuration (number, average size and connectivity) of greenspace patches. The majority of species were common suburban birds, indicating that species we assume are tolerant to urban areas will be negatively affected by increasing residential density. Parks form part of an interconnected network of urban open space. For parks to continue to support a diverse native bird community, the network must be viewed, managed, and maintained in its entirety. We suggest three key management actions to improve the bird diversity values of urban greenspaces in compact cities: (1) Increase urban greenspace cover in residential neighbourhoods. (2) Increase vegetation structure in greenspace. (3) Encourage homeowners to plant trees and shrubs.

关键词： Bird diversity object based image analysis Landscape composition Landscape configuration Planning and management Southeast Australia Spatial analysis Urban form Urban greenspace Urban sustainability

来源：评论

学校读者我要写书评

暂无评论

MONITORING LAND USE CHANGES ASSOCIATED WITH URBANIZATION IN THE UPPER BHIMA BASIN, MAHARASHTRA, INDIA

MONITORING LAND USE CHANGES ASSOCIATED WITH URBANIZATION IN ...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Samal, Dipak R. Gedam, Shirish S. ITT Bombay CSRE Bombay Maharashtra India

ISBN: (纸本)9781479911141

Urbanization is the most dramatic form of irreversible land transformation which occurs due to various anthropogenic activities. Multi-temporal Landsat images acquired from different sensors like MSS, TM and ETM+ between 1972-2009 as well as digital elevation dataset is used to study the influence of urbanization on its surrounding land use/cover pattern in the upper Bhima basin. An object based standard nearest neighbor (NN) classification technique is employed for precise classification of various land use classes in the basin. The study revealed that rapid built up area expansion driven by population growth, demand for water from city region leads to construction of new dams in high rainfall region and mass conversion of waste land to agricultural land are the major changes being noticed in the basin due to urbanization.

关键词： Urbanization Bhima basin object based image analysis GIS

来源：评论

学校读者我要写书评

暂无评论

MONITORING LAND USE CHANGES ASSOCIATED WITH URBANIZATION IN THE UPPER BHIMA BASIN, MAHARASHTRA, INDIA

MONITORING LAND USE CHANGES ASSOCIATED WITH URBANIZATION IN ...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Dipak R. Samal Shirish S. Gedam Centre of Studies in Resources Engineering (CSRE)

ISBN: (纸本)9781479911127

关键词： Urbanization Bhima basin object based image analysis GIS

来源：评论

学校读者我要写书评

暂无评论

A hybrid method combining SOM-based clustering and object-based analysis for identifying land in good agricultural condition

引用

COMPUTERS AND ELECTRONICS IN AGRICULTURE 2012年 83卷 92-101页

作者： Tasdemir, Kadim Milenov, Pavel Tapsall, Brooke Commiss European Communities Joint Res Ctr Monitoring Agr Resources Unit Inst Environm & Sustainabil I-21027 Ispra VA Italy

Remotely sensed imagery is currently used as an efficient tool for agricultural management and monitoring. In addition, the use of remotely sensed imagery in Europe has been extended towards determination of the areas potentially eligible for the farmer subsidies under the Common Agricultural Policy (CAP), through interactive or automatic land cover identification. For accurate quantification and fast identification of agricultural land cover areas from the imagery, a hybrid method, which combines automated clustering of self-organizing maps with object based image analysis, and called SOM + OBIA, is proposed. Performance analysis on three test zones (using multi-temporal Rapideye imagery) indicates that for the basic land cover categories (forest, water, vegetated areas, bare areas and sealed surfaces), unsupervised classification with the proposed SOM + OBIA method achieves an identification accuracy comparable to the accuracy of the traditional interactive object oriented analysis, with considerably less user interaction. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Land cover identification Unsupervised clustering Self-organizing maps CONN linkage object based image analysis Good agricultural condition

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：