Elimination of hidden a priori information from remotely sensed profile data

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Elimination of hidden a priori information from remotely sensed profile data

Profiles of atmospheric state variables retrieved from remote measurements often contain a priori information which causes complication in the statistical use of data and in the comparison with other measured or modeled data. For such applications it often is desirable to remove the a priori information from the data product. If the retrieval involves an ill-posed inversion problem, formal remo...

متن کامل

Selection of Remotely Sensed Data

An increasing number of sensors are available for forest ecologists and managers seeking to map attributes of forest canopy cover, forest structure and composition, and their dynamics. This Chapter seeks to put these advances within the context of the needs of forest managers and scientists. To do so, we review the basic physics behind a variety of imagery types, discuss fundamental limitations...

متن کامل

CCSSM: A Toolkit for Information Extraction from Remotely Sensed Imagery

This paper presents a method named CCSSM (Classification of Combining Spectral information and Spatial information upon Multiple-point statistics) which is the derivation of two probability fields from the supervised classification for the spectral extraction and multiple-point simulation (MPS) for the spatial information, which then are fused. The performance of CCSSM for two-class classificat...

متن کامل

248 Remotely Sensed Data Characterization

EMPs Extended morphological profiles EMPs Extended morphological profiles LDA Linear discriminant analysis LogDA Logarithmic discriminant analysis MLR Multinomial logistic regression MLRsubMRF Subspace-based multinomial logistic regression followed by Markov random fields MPs Morphological profiles MRFs Markov random fields PCA Principal component analysis QDA Quadratic discriminant analysis RH...

متن کامل

Commercial Remotely Sensed (CRS) Data

Natural disasters can severely impact transportation networks. In the hours and days following a major flooding event, knowing the location and extent of the damage is crucial for incident managers for a number of reasons: it allows for emergency vehicle access to affected areas; it facilitates the efficient rerouting of traffic; it raises the quality and reduces the cost of repairs; and it all...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Atmospheric Chemistry and Physics

سال: 2007

ISSN: 1680-7324

DOI: 10.5194/acp-7-397-2007