检索结果-内蒙古大学图书馆

Conference on Remote Sensing of the Marine Environment II

作者： Pham Tien Dat Yoshino, Kunihiko HUA CARES Hanoi Vietnam Univ Tsukuba Grad Sch Life & Environm Sci Tsukuba Ibaraki 3058577 Japan Univ Tsukuba Fac Engn Informat & Syst Tsukuba Ibaraki 3058573 Japan

ISBN: (纸本)9780819492647

Mangroves that appear in the inter-tidal zones along the coast in most tropical and semi-tropical countries play a vital role in coastal zones and can defend against the impacts of tsunamis. Nevertheless, these forests are under severe threat because of high population growth, weak governance, poor planning, as well as uncoordinated economic development. Hai Phong city is located on the Northern coast of Vietnam where the mangroves are distributed between zone I and zone II among the four mangrove zones in Vietnam. This city is vulnerable to rising sea levels and tropical cyclones, which are forecasted to become more severe in coming next decades. The objectives of this research were to analyze the current status of mangroves using different ALOS sensors in Hai Phong, Vietnam in 2010 and compare the accuracy of the post satellite image processing of ALOS imagery in mapping mangroves. A combination of object-based and supervised classification was used to generate the land cover maps. The results of this research indicate that the total area of mangrove was approximately 2,549 hectares and mangrove is present in the five coastal districts in Hai Phong. The findings of this research showed that ALOS AVIR-2 provides better accuracy than ALOS PALSAR. This research indicates the potential of utilizing image segmentation associated with supervised method for both optical and SAR images to map mangrove forests in coastal zones

关键词： Mangrove analysis object-based classification supervised classification ALOS imagery Hai Phong

来源：评论

学校读者我要写书评

暂无评论

Detection and Mapping of Phragmites australis using High Resolution Multispectral and Hyperspectral Satellite Imagery

Detection and Mapping of Phragmites australis using High Res...

引用

作者： Nicholas J. Lantz University of Western Ontario

学位级别：硕士

Mapping invasive plant species is important to establish an invasion baseline, monitor plant propagation, and to implement an effective plan to deal with the invasion. In this thesis, methods are proposed to map invasive Phragmites australis in a Great Lakes coastal wetland. Chapter 2 presents an object-based Phragmites extraction method using Worldview-2 high-spatial-resolution satellite imagery. For the 4024 ha study area at Walpole Island, Ontario, 94% overall accuracy was achieved. Chapter 3 uses CHRIS PROBA hyperspectral satellite imagery for mapping the pixel abundance of Phragmites using a spectral mixture analysis method. An evaluation method was developed to assess the accuracy of the spectral mixture analysis fractions using the classification from Chapter 2. The overall accuracy for a Phragmites, native vegetation and water classification based on the dominant fraction in each pixel was 82.8%. A Phragmites invasion classification identifying pixels where Phragmites was non-dominant, potentially dominant, and dominant was 85.2% accurate.

关键词： Phragmites australis Invasive Species Non-Native Species Great Lakes Coastal Wetland Worldview-2 CHRIS PROBA object-based classification Spectral Mixture Analysis Walpole Island First Nation

来源：评论

学校读者我要写书评

暂无评论

object-based classification for mangrove with VHR remotely sensed image

Object-based classification for mangrove with VHR remotely s...

引用

15th International Conference on Geoinformatics

作者： Liu, Zhigang Li, Jing Lim, Boonleong Seng, Chungyueh Inbaraj, Suppiah State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China Beijing Normal Univ Sch Geog & Remote Sensing Sci Beijing 100875 Peoples R China Beijing Normal Univ Coll Resource Sci & Technol Beijing Peoples R China Cilix Corp Sdn Bhd Kuala Lumpur 57000 Malaysia

ISBN: (纸本)9780819469120

In remotely sensed imagery with high spatial resolution, more detail spatial information of mangrove forest can be shown. It is important to find a method to effectively use the spatial information so as to improve the accuracy of mangrove forest classification. In the study, different classification schemes (including pixel-based classification and object-based classification), different classifiers, and different texture features have been conducted. The classification results of SPOT-5 image of Matang Mangrove Forest Reserve in Malaysia show that the performances of object-based classifications are better than that of pixel-based classifications. However, the classifier type is important for object-based classification. The accuracies of nearest neighborhood classifiers, which are widely used in object-based classifications, were obviously lower that that of maximum likelihood classifiers and support vector Machines. It is also shown that the involvement of second-order texture features can't effectively improve the classification accuracy of neither object-based classifications nor pixel-based classifications.

关键词： mangrove SPOT-5 object-based classification

来源：评论

学校读者我要写书评

暂无评论

Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification

引用

REMOTE SENSING OF ENVIRONMENT 2010年第6期114卷 1141-1154页

作者： Ke, Yinghai Quackenbush, Lindi J. Im, Jungho SUNY Syracuse Coll Environm Sci & Forestry Dept Environm Resources & Forest Engn Syracuse NY 13210 USA

This study evaluated the synergistic use of high spatial resolution multispectral imagery (i.e., QuickBird, 2.4 m) and low-posting-density LIDAR data (3 m) for forest species classification using an object-based approach. The integration of QuickBird multispectral imagery and LIDAR data was considered during image segmentation and the subsequent object-based classification. Three segmentation schemes were examined: (1) segmentation based solely on the spectral image layers;(2) segmentation based solely on MAR-derived layers;and (3) segmentation based on both the spectral and LIDAR-derived layers. For each segmentation scheme, objects were generated at twelve different scales in order to determine optimal scale parameters. Six categories of classification metrics were generated for each object based on spectral data alone, LIDAR data alone and the combination of both data sources. Machine learning decision trees were used to build classification rule sets. Quantitative segmentation quality assessment and classification accuracy results showed the integration of spectral and LIDAR data, in both image segmentation and object-based classification, improved the forest classification compared to using either data source independently. Better segmentation quality led to higher classification accuracy. The highest classification accuracy (Kappa 91.6%) was acquired when using both spectral- and LIDAR-derived metrics based on objects segmented from both spectral and LIDAR layers at scale parameter 250, where best segmentation quality was achieved. Optimal scales were analyzed for each segmentation-classification scheme. Statistical analysis of classification accuracies at different scales revealed that there was a range of optimal scales that provided statistically similar accuracy. (C) 2010 Elsevier Inc. All rights reserved.

关键词： High spatial resolution multispectral imagery LIDAR object-based classification Decision tree Forest classification

来源：评论

学校读者我要写书评

暂无评论

Monitoring of the urban sprawl using geoprocessing tools in the Shenzhen Municipality, China

引用

ENVIRONMENTAL EARTH SCIENCES 2011年第6期62卷 1131-1141页

作者： Lv, Zhi-qiang Wu, Zhi-feng Wei, Jian-bing Sun, Cheng Zhou, Qi-gang Zhang, Jing-hua Guangdong Inst Ecoenvironm & Soil Sci Guangzhou 510650 Guangdong Peoples R China Chinese Acad Sci Guangzhou Inst Geochem Guangzhou 510630 Guangdong Peoples R China Chongqing Technol & Business Univ Tourism & Land Coll Chongqing 400067 Peoples R China Chinese Acad Sci China Grad Sch Beijing 100039 Peoples R China

Shenzhen, located in South China has experienced rapid urbanization over the past three decades. This paper focuses on the urban sprawl integrating remote sensing and geographic information systems (GIS). The overlay of the urban area maps for two adjacent study years was used to generate the sprawl categories map. The three main sprawl categories of infilling sprawl, edge-expansion sprawl and outlying sprawl were calculated and analyzed in regard to their distribution and change throughout different counties during the study years. The result showed that the urban area in the study region had increased dramatically from 19.55 km(2) in 1979 to 894.31 km(2) in 2005. The urban area centroids over the six study years transferred from southwest to northeast from 1979 to 2005. Among the study counties, the patterns of sprawl categories were markedly distinctive over different study periods. From 1979 to 2005, Shenzhen's chief spread was outlying sprawl. Bao'an experienced the maximum sprawl within the three study counties. The findings show that studying urban sprawl can provide a method of monitoring urban area change, which, in turn, gives us a clearer perspective of urban sprawl patterns over a longer period of time. This would prove invaluable to those researchers such as land and urban planners.

关键词： Monitoring Urban sprawl Sprawl category object-based classification Geoprocessing

来源：评论

学校读者我要写书评

暂无评论

Estimates of bark beetle infestation expansion factors with adaptive cluster sampling

引用

INTERNATIONAL JOURNAL OF PEST MANAGEMENT 2011年第1期57卷 11-21页

作者： Coggins, Sam B. Coops, Nicholas C. Wulder, Michael A. Univ British Columbia Dept Forest Resources Management Vancouver BC V5Z 1M9 Canada Nat Resources Canada Canadian Forest Serv Pacific Forestry Ctr Victoria BC Canada

Insects have infested over 37 million hectares of forested land, the most aggressive forest insect pest in North America is the mountain pine beetle that has attacked 14 million hectares. To determine infestation extent and spread rates, we examined mountain pine beetle damage at two sites over two consecutive years (2007-2008). High spatial resolution (20cm) airborne digital imagery was acquired over a range of infestation intensities (High: site A;Low: site B). An adaptive cluster sampling approach assessed the extent and severity of damage from the imagery. In 2007, site A contained 5.22 infested trees per hectare (variance: 10.65) increasing in 2008 to 11.02 trees per hectare (variance: 24.83). In contrast, site B had 0.25 infested trees per hectare in 2007 (variance: 0.02), which increased in 2008 to 0.47 trees per hectare, with a variance of 0.08 trees per hectare. At both sites, infestations approximately doubled over a 1-year period. Adaptive cluster sampling applied to high spatial resolution airborne imagery can provide estimates of the severity of attack on the landscape.

关键词： object-based classification high spatial resolution satellite digital aerial imagery bark beetles forest inventory adaptive cluster sampling

来源：评论

学校读者我要写书评

暂无评论

Utility of landsat Image in the Study of Land Cover and Land Surface Temperature Change

Utility of landsat Image in the Study of Land Cover and Land...

引用

3rd International Conference on Environmental Science and Information Application Technology (ESIAT)

作者： Lv, Zhi-qiang Zhou, Qi-gang Chongqing Technol & Business Univ Tourism & Land Dept Chongqing Peoples R China

Scientists have aimed at exploring land use and land cover (LULC) and their environmental influence in order to improve our understanding of the causes and consequences of these phenomena. This study addresses and use and land cover change (LUCC) in the upper reaches of Pearl River Delta, China, from 1990 to 2008. based on remotely sensed images of Landsat. LUCC and land surface temperature were assessed. Results showed that land surface temperature was highly influenced by the LUCC from 1990 to 2008. An examination of the relationship between the LULC and LST maps was finally conducted to comprehension their interactions. Results indicated that Landsat image was effective for quantifying the heat environment and providing reliable measurements of land use change. LST was found to be positively correlated with impervious surface but negatively correlated with vegetated land. Each temperature zone was associated with a dominant LULC category. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Conference ESIAT2011 Organization Committee.

关键词： Land use land surface temperature object-based classification TM/ETM Fast developing region

来源：评论

学校读者我要写书评

暂无评论

Plastic covered vineyard extraction from airborne sensor data with an object-oriented approach

Plastic covered vineyard extraction from airborne sensor dat...

引用

Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII/18th International Symposium on Remote Sensing

作者： Tarantino, E. Aiello, A. Politecn Bari I-70125 Bari Italy

ISBN: (纸本)9780819488015

In recent years, the wide-spreading of vineyard cultivation in the Apulia Region (Italy) has showed negative consequences on the hydrogeological balance of soils as well as on the visual quality of rural landscape which has been significantly altered by the heavy diffusion of artificial plastic coverings. In order to monitor and manage this phenomenon, a detailed site mapping has become essential. With the increase of spatial resolution, pixel based approaches no longer capture the characteristics of classification targets. Consequently, classification accuracy is poor. object-based image classification techniques overcome this issue by first segmenting the image into meaningful multipixel objects of various sizes and then assigning segments to classes using fuzzy methods and hierarchical decision keys. In this study an object-based classification procedure from Very High Spatial Resolution (VHSR) true color aerial data was developed on a test area located between the Apulian municipalities of Ginosa and Palagiano in order to support the update of the existing land use database aimed at plastic covered vineyard monitoring.

关键词： plastic covered vineyard object-based classification true color aerial data

来源：评论

学校读者我要写书评

暂无评论

Man-made Ground Collapse Detection Using High Resolution Aerial Image and object-based classification:Example of Pearl River Delta

Man-made Ground Collapse Detection Using High Resolution Aer...

引用

The Second International ISCRAM Workshop on Information Systems for Crisis Response and Management

作者： Jiinping Qian Guangzhou Institute of Geography,China Sun Yat-sen University,Guangzhou,China Xiaozhan Zheng Guangzhou Institute of Geological Survey, China Shuisen Chen Guangzhou Institute of Geography,China Ruihua Liu Guangzhou Institute of Geography,China Jie Dou Guangzhou Institute of Geography,China

In this paper,object-based image analysis method was used to detect the ground collapse sites using remote sensing ***,multi-scale image segmentation was performed on the 0.3-meter aerial image of study area and over tens of spatial,spectral,shape and texture features were extracted based on the segmented image *** 4 optimized features for ground collapse classification was selected using generic algorithm(GA),which get the best fitness value in ground collapse classification..After that,some on the spot land collapse sites were selected as cases sites and cased-based-reasoning(CBR) classification was applied on all the segmented image objects,from large scale to small *** the end,classification accuracy was evaluated over the whole study *** average error of object-based CBR classification of ground collapse area is about 20.7%.

关键词： Ground collapse urban geology high resolution image object-based classification CBR(Case-based Reasoning)

来源：评论

学校读者我要写书评

暂无评论

Agricultural Land Cover classification using RapidEye Satellite Imagery in South Korea - First Result

Agricultural Land Cover Classification using RapidEye Satell...

引用

Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII/18th International Symposium on Remote Sensing

作者： Kim, Hyun Ok Yeom, Jong Min Kim, Youn Soo Korea Aerosp Res Inst Taejon South Korea

ISBN: (纸本)9780819488015

Global climate changes as well as abnormal climate phenomena have affected the agricultural environment on a great scale. Thus, there is a strong need for countermeasures by making full use of agriculture related information. As agricultural lands in South Korea are mostly operated by private farmers on a small parcel level, it is difficult to gather information for an overview on changing crop condition and to construct database necessary for disease management, production estimation and compensation measures on a regional or governmental level. The objective of this study is to evaluate the multispectral reflectance characteristics of RapidEye image data to classify agricultural land cover as well as crop condition in South Korea. As the RapidEye sensor offers the spectral information in red edge range as a first multispectral satellite system, we focus on the usefulness of red edge reflectance for identifying crop species and for interpreting crop growth or stress condition.

关键词： RapidEye red edge spectral vegetation index object-based classification agriculture crop 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：