Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium最新文献_第9页

The use of remote sensing in addressing scaling issues for numerical models of atmospheric processes 利用遥感解决大气过程数值模式的标度问题

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322369

E. LeDrew, D. Barber, T. Papakyriakou

{"title":"The use of remote sensing in addressing scaling issues for numerical models of atmospheric processes","authors":"E. LeDrew, D. Barber, T. Papakyriakou","doi":"10.1109/IGARSS.1993.322369","DOIUrl":"https://doi.org/10.1109/IGARSS.1993.322369","url":null,"abstract":"The problems of thermal forcing during cyclogenesis in the Arctic Polar Basin and numerical modelling are discussed. For the past three years, the authors have been taking detailed surface radiation and energy balance measurements over the sea ice in the Canadian Arctic to more fully understand the process linkages and feedbacks between the atmosphere dynamics and surface processes. The link between the mesoscale models and micro-scale in situ observations is remote sensing. The authors have been exploring a variety of techniques to scale up from detailed micrometeorological measurements to the quasi-geostrophic models through aggregation of data based upon remote sensing information. In this paper the authors review the problems of scaling from observations to models through discussion of the results of the authors' modelling efforts at the synoptic scale and their high resolution observations at the ice surface as part of the SIMMS Programme (Seasonal Sea Ice Monitoring and Modelling Site) in Lancaster Sound. By use of an example, the authors illustrate how microwave scatter can be used to infer the climatological albedo, thereby demonstrating the role which remote sensing can play in bridging the scale gap. The authors outline their research plans over the next five years for addressing other terms of the surface interaction with the atmosphere.<<ETX>>","PeriodicalId":312260,"journal":{"name":"Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123722564","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: 1

Emissivity spectra derived from TIMS data acquired over a partially vegetated area 发射率光谱由在部分植被地区获得的TIMS数据得出

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322498

T. Matsunaga

引用次数: 4

A C-band backscatter model for lake ice in Alaska 阿拉斯加湖冰的c波段后向散射模型

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322103

H. Wakabayashi, W. Weeks, M. Jeffries

引用次数: 21

Preliminary observational study on microwave backscattering characteristics of snow using the PWRI microwave scatterometer PWRI微波散射仪对积雪微波后向散射特性的初步观测研究

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322106

K. Fukami, K. Masukura, T. Koike, I. Hasegawa

引用次数: 0

On-orbit calibration of the Japanese Earth Resources Satellite-1 Optical Sensor using the Airborne Visible-Infrared Imaging Spectrometer 利用机载可见红外成像光谱仪对日本地球资源卫星1号光学传感器进行在轨定标

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322090

R. Green, J. Conel, J. M. van den Bosch, M. Shimada, M. Nakai

引用次数: 5

GOMOS, Global Ozone Monitoring by Occultation of Stars 通过掩星监测全球臭氧

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322329

P. Mérat, J. Jouan, P. Hollier

引用次数: 6

Experiences of application of satellite remote sensing in Sri Lanka during the last decade 过去十年来斯里兰卡应用卫星遥感的经验

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322399

S. Jayatilaka

引用次数: 1

Robust adaptive detection of optical patterns in low resolution airborne radar images 低分辨率机载雷达图像中光学模式的鲁棒自适应检测

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322732

G. Vela, F.J. Jimenez Rodriguez, J.J. Martinez Madrid, J.R. Casar Corredera

引用次数: 0

Artificial oil pollution detection and wave observation in the sea adjacent to Japan by ERS-1 SAR images 基于ERS-1 SAR图像的日本邻近海域人工油污检测与波浪观测

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322173

T. Kobayashi, K. Okamoto, H. Masuko, K. Nakamura, H. Horie, H. Kumagai, M. Simada

引用次数: 5

Structured neural networks for the classification of multisensor remote-sensing images 多传感器遥感图像分类的结构化神经网络

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium Pub Date : 1993-08-18 DOI: 10.1109/IGARSS.1993.322191

S. Serpico, F. Roli, P. Pellegretti, G. Vernazza

{"title":"Structured neural networks for the classification of multisensor remote-sensing images","authors":"S. Serpico, F. Roli, P. Pellegretti, G. Vernazza","doi":"10.1109/IGARSS.1993.322191","DOIUrl":"https://doi.org/10.1109/IGARSS.1993.322191","url":null,"abstract":"Proposes the application of structured neural networks to the supervised classification of multisensor remote-sensing images. The purpose of the proposed approach is to exploit neural networks advantages while solving, in the context of the considered application, the problems of \"architecture definition\" and of \"opacity\". The architecture of the proposed neural networks reflects the provenance of data from different sensors. This allows one to easily define a network architecture by exploiting the characteristics of a given multisensor classification problem. In addition, the \"structuring\" of the architecture notably helps to understand the classification criteria implemented by the neural network classifier. To make possible such an interpretation, a transformation of the representation of original networks into a \"simplified representation\" has also been defined. The advantages provided by such networks are pointed out from the viewpoint of the remote-sensing application. Experimental results on multisensor data and comparisons with the Bayesian classifier are reported.<<ETX>>","PeriodicalId":312260,"journal":{"name":"Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129333348","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