2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)最新文献_第6页

An approach to conifer species classification based on crown structure modeling in high density airborne LiDAR data 基于高密度机载激光雷达数据树冠结构建模的针叶树种分类方法

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7729378

A. Harikumar, F. Bovolo, L. Bruzzone

{"title":"An approach to conifer species classification based on crown structure modeling in high density airborne LiDAR data","authors":"A. Harikumar, F. Bovolo, L. Bruzzone","doi":"10.1109/IGARSS.2016.7729378","DOIUrl":"https://doi.org/10.1109/IGARSS.2016.7729378","url":null,"abstract":"The knowledge about the species of trees is essential for precision forest management practices. Modern high density airborne Light Detection and Ranging (LiDAR) systems have the ability to acquire large number of LiDAR points, allowing a very detailed characterization of the forest at the individual tree level. In this context, it is possible to use LiDAR data for accurate classification of the tree species. In this paper, we consider the specific problem of species classification of trees belonging to the conifer class. This is particularly challenging when only the external geometric information is considered. To address the problem we propose a novel approach that model the internal crown structure of the conifers. The internal structure is identified by using 3D region growing and Principal Component Analysis (PCA) and is used for defining a set of novel Internal Crown Geometric features (IGFs). Some state-of-the-art External Crown Geometric Features (EGFs) were also used to improve the classification accuracy. Sparse Support Vector Machines (SSVM) was used for classification and to quantify the feature relevances.","PeriodicalId":179622,"journal":{"name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122713848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Equipping undergraduate STEM majors with Geoscience and remote sensing tools: A pathway to replenishing the Geoscience workforce 为本科STEM专业学生配备地球科学和遥感工具:补充地球科学劳动力的途径

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7730432

R. Blake, J. Liou-Mark, H. Norouzi

{"title":"Equipping undergraduate STEM majors with Geoscience and remote sensing tools: A pathway to replenishing the Geoscience workforce","authors":"R. Blake, J. Liou-Mark, H. Norouzi","doi":"10.1109/IGARSS.2016.7730432","DOIUrl":"https://doi.org/10.1109/IGARSS.2016.7730432","url":null,"abstract":"Reversing the dramatic decrease in geoscience interest, awareness, participation, and preparation among students at all levels in the United States has become a paramount priority, particularly since recent studies ([1], [2], and [3]) project that this critical regression is expected to continue well into this young century. Investments by the U.S. National Science Foundation's Opportunities for Enhancing Diversity in the Geosciences program ([4], [5], [6], [7], [8], [9]) have yielded innovative insights, practical strategies, and replicable models that are designed to broaden student access, participation, and success at various stages of the geoscience pipeline. However, despite these transformative initiatives, more needs to be done to ensure that evidence-based practices are utilized to attract students and to increase their persistence and achievement in the geosciences. At the New York City College of Technology (City Tech) of the City University of New York, a new, pioneering, piloted pathway model in which undergraduates majoring in STEM disciplines are being equipped with vital geoscience and remote sensing skills for the geoscience workforce is successfully on-going. Components of this work are presented in this manuscript.","PeriodicalId":179622,"journal":{"name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122748970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bernoulli filter for joint detection and tracking of target with low signal to clutter ratio 伯努利滤波用于低信杂比目标的联合检测与跟踪

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7729357

Xinglin Shen, Zhi-yong Song, Q. Fu

引用次数: 0

Eddies in the Western Mediterranean Seen by spaceborne radar 由星载雷达观测到的西地中海漩涡

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7730039

S. Karimova, M. Gade

引用次数: 6

Comparison of neutrospheric temperature and pressure between MSISE-90 model and ECMWF reanalysis data msse -90模式与ECMWF再分析资料对中性大气温度和压力的比较

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7729567

Danyang Zhao, Yueqiang Sun, W. Bai, X. Meng, Congliang Liu, Junming Xia, Q. Du, Xianyi Wang, Dongwei Wang, Yuerong Cai, Chunjun Wu, Di Wu, Wei Li, Cheng Liu

引用次数: 0

Comparison between Photosynthetically Available Radiation (PAR) estimated from MODIS and GOES over the Gulf of Mexico MODIS估算的光合有效辐射(PAR)与墨西哥湾GOES的比较

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7730527

Lin Qi, Z. Lee

引用次数: 0

Retrieval of paddy rice variables during the growth season with a modified water cloud model on polarimetric radar images 利用改进的水云模式在极化雷达图像上反演水稻生长季节变量

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7730955

Zhi Yang, Kun Li, Y. Shao, B. Brisco, Long Liu

{"title":"Retrieval of paddy rice variables during the growth season with a modified water cloud model on polarimetric radar images","authors":"Zhi Yang, Kun Li, Y. Shao, B. Brisco, Long Liu","doi":"10.1109/IGARSS.2016.7730955","DOIUrl":"https://doi.org/10.1109/IGARSS.2016.7730955","url":null,"abstract":"This paper proposed a modified Water Cloud Model (MWCM) for rice variable estimation during the whole growth season with eight RADARSAT-2 quad-pol SAR images. The improvements achieved with the MWCM include considering the heterogeneity of water content of the rice canopy in different directions and different phenologies, and applying the scattering components from an improved polarimetric decomposition in the model instead of the backscattering coefficients. With the MWCM, four rice variables were estimated through the genetic algorithm, including leaf area index (LAI), rice height (h), volumetric water content of total canopy (mv) and ear biomass (De). The validation was conducted using the field data with the average R2 of each variable above 0.8. The median relative error (MRE) of the rice variables ranged from 9% to 15% in most phenological stages. The results demonstrated that the MWCM works well for the estimation of rice biophysical parameters with polarimetric SAR data, and it is significant to consider the heterogeneity of water content of the rice canopy in the horizontal direction for estimation of rice variables during the whole rice growth season.","PeriodicalId":179622,"journal":{"name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114381844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Multiple band selection for anomaly detection in hyperspectral imagery 基于多波段选择的高光谱图像异常检测

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7730831

L. Wang, Chein-I. Chang

引用次数: 4

Detection of building radar footprints from single VHR SAR images 从单幅VHR SAR图像中检测建筑物雷达足迹

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7730911

Jinxing Chen, Fan Wu, Chao Wang, Wanming Lei

引用次数: 0

Automatic generation of frequently updated land cover products at national level using COSMO-SkyMed SAR imagery 使用COSMO-SkyMed SAR图像自动生成国家级频繁更新的土地覆盖产品

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI: 10.1109/IGARSS.2016.7729880

F. Carbone, A. Coletta, G. F. D. Luca, F. Frate, L. Fasano, G. Schiavon

引用次数: 2