نتایج جستجو برای: distribution mapping

تعداد نتایج: 793039  

2006
Rachel Sleeter

Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies...

2006
Jeremy Mennis

Geographically weighted regression (GWR) is a local spatial statistical technique for exploring spatial nonstationarity. Previous approaches to mapping the results of GWR have primarily employed an equal step classification and sequential no-hue colour scheme for choropleth mapping of parameter estimates. This cartographic approach may hinder the exploration of spatial nonstationarity by inadeq...

Journal: :Systematic biology 2002
Rasmus Nielsen

Mapping of mutations on a phylogeny has been a commonly used analytical tool in phylogenetics and molecular evolution. However, the common approaches for mapping mutations based on parsimony have lacked a solid statistical foundation. Here, I present a Bayesian method for mapping mutations on a phylogeny. I illustrate some of the common problems associated with using parsimony and suggest inste...

2004
Marcel Ji

Methods of nearest neighbors are essential in wide range of applications where it is necessary to estimate probability density (e.g. Bayes’s classifier, problems of searching in large databases). This paper contemplates on features of distribution of nearest neighbors’ distances in high-dimensional spaces. It shows that for uniform distribution of points in n-dimensional Euclidean space the dis...

2006
Chenn-Jung Huang Chih-Tai Guan Yi-Ta Chuang

Various methods, such as address-calculation sort, distribution counting sort, radix sort, and bucket sort, adopt the values being sorted to improve sorting efficiency, but require extra storage space. This work presents a specific key-address mapping sort implementation. The proposed algorithm has the advantages of linear average-time performance and no requirement for linked-list data structu...

      In this research, the capability of Rapid Eye satellite imagery for mapping the crown distribution of oak trees in Zagros forests was investigated in the Dashtebarm forest area of ​​Kazeroun, Fars province. In this study, data quality was investigated geometrically and radiometrically and geometric correction of the images was done using a linear method and using precision ground control ...

2005
Marko Grobelnik

EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D4.3.1 (WP4) This deliverable describes a library of ontology mapping patterns, as well as a mapping language based on these patterns. This language, together with the mapping patterns, allows the user to more easily identify mappings and to describe mappings in an intuitive way. The mappings are organized in a library in a hierarc...

Journal: :journal of tethys 0

expensive to provide these maps  with field measurements  therefore  it is better to use new methods. this study provides a lithological and alteration mapping units with dominant minerals based on hyperspectral images of eo1-hyperion satellite. to do so, two different zones  were  investigated:  the  cuprite-nevada  and  mozahem  volcano  in  iran  which  have suitable conditions for our study...

2002
Cameron Yates

A standard method for assessing the accuracy of fire mapping derived from NOAA-AVHRR imagery was applied to five Landsat scenes sampling different regions across northern Australia. The procedure involved the undertaking of: (1) detailed ground verification exercises (using ground and aerial transects) at the time of Landsat overpasses; (2) assessment of the accuracy of fire mapping derived fro...

Machine learning is an application of artificial intelligence that is able to automatically learn and improve from experience without being explicitly programmed. The primary assumption for most of the machine learning algorithms is that the training set (source domain) and the test set (target domain) follow from the same probability distribution. However, in most of the real-world application...

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