SPATIAL RESOLUTION ASSESSMENT OF THE TELOPS AIRBORNE TIR IMAGERY

Having a high spatial resolution of Thermal InfraRed (TIR) Sensors is a challenge in remote sensing applications. Airborne high spatial resolution TIR is a novel source of data that became available lately. Recent developments in spatial resolution of the TIR sensors have been an interesting topic for scientists. TIR sensors are very sensitive to the energies emitted from objects. Past researches have been shown that increasing the spatial resolution of an airborne image will decrease the spectral content of the data and will reduce the Signal to Noise Ratio (SNR). Therefore, in this paper a comprehensive assessment is adapted to estimate an appropriate spatial resolution of the TIR data (TELOPS TIR data), in consideration of the SNR. So, firstly, a low-pass filter is applied on TIR data and the achieved products fed to a classification method for analysing of the accuracy improvement. The obtained results show that, there is no significant change in classification accuracy by applying low-pass filter. Furthermore, estimation of the appropriate spatial resolution of the TIR data is evaluated for obtaining higher spectral content and SNR. For this purpose, different resolutions of the TIR data are created and fed to the maximum likelihood classification method separately. The results illustrated in the case of using images with ground pixel size four times greater than the original image, the classification accuracy is not reduced. Also, SNR and spectral contents are improved. But the corners sharpening is declined

Mismatch distributions and Bayesian skyline plot of 5<i>i</i> sequences.

<p>The mismatch distribution is based on the complete <i>G</i> gene sequence and is calculated separately for the following: 152 <i>5i</i> sequences from Denmark, Germany, and the United Kingdom, collected between 2000 and 2011; and 137 Danish <i>5i</i> sequences from 2000 to 2009. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164475#pone.0164475.t001" target="_blank">Table 1</a> lists the respective values of the raggedness index (r), nucleotide diversity (PI), Tajima’s D, and Fu’s Fs of each dataset. The Bayesian skyline plot shows changes of the 5<i>i</i> population size between 2000 and 2009. The plot was generated using 137 Danish 5<i>i</i> sequences (complete <i>G</i> gene sequence). X axis: time in years, Y axis: population size. The middle solid line is the median estimate, and the area between the blue lines shows the 95% highest probability density (HPD).</p

Median-joining network based on the complete <i>G</i> gene sequence from 734 VHSV isolates (transition/transversion bias = 5).

<p>The country or region of origin is indicated using a color code. The North Sea (labeled by an asterisk) includes also the Barents Sea, English Channel, Kattegat, Norwegian Sea, Rogaland, and Skagerrak. The years represent the range of collection dates for isolates of every European subgenogroup <i>I</i> (<i>I(unclassified)</i>, and <i>Ia–e</i>) and <i>Ia</i> clades (clade <i>1–9</i>). The clades <i>5</i>, <i>8</i>, and <i>9</i> are additionally subdivided into the subsets <i>5i–iii</i>, <i>8i–iii</i>, and <i>9i–iii</i>. The black circles with the number 1 and 3 represent clear polytomy nodes (node 1 and 3), whereas the black circle with the number 2 represents a intermediate stage between a polytomy and bifurcating node (node 2). The node labeled by the gray circle Y may represents the bifurcating node between the <i>Ia</i> clades, or it may represent the more or less direct ancestor of the polytomy node 3.</p

Parameters of the analysis of a rapid population growth based on the complete <i>G</i> gene sequence data.

<p>Parameters of the analysis of a rapid population growth based on the complete <i>G</i> gene sequence data.</p

Maximum Likelihood trees and NeighborNet networks of the <i>Ia</i> subgenogroup.

<p>In diagrams a) and b) the phylogenetic relationship between the <i>Ia</i> clades (clades <i>1</i>–<i>9</i>), based on the complete <i>G</i> gene sequence, is illustrated as a bifurcating maximum likelihood tree, whereas in diagrams c) and d) it is shown as a NeighborNet network. Diagram a) is based on 650 <i>Ia</i> isolates (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164475#pone.0164475.s002" target="_blank">S1 Table</a>), diagram b) on 651 <i>Ia</i> isolates (the same isolates as in a) plus the isolate U288000, designated as X). Diagrams c) is based on isolates with the GenBank accession-number AY546571 (9<i>i</i>), LN877188 (9<i>ii</i>), EU708732 (9<i>iii</i>), EU708755 (8<i>iii</i>), EU708748 (8<i>ii</i>), LN877010 (8<i>i</i>), LN876935 (7), AJ233396 (6), LN876803 (5), EU708742 (4), FRG2192 (3), LN876782 (2), and AY546617 (1), diagram d) is based on the same isolates as in c) plus the isolate X. These isolates each represent the <i>Ia</i> clade isolate with the oldest collection date. Isolate AY546576 (VHSV genogroup II) is the outgroup in each diagram. The phylogenetic trees are pictured as cladograms. Numbers above branches represent the bootstrap support values obtained from 250 replicates. In case of the networks, the formation of parallelograms indicates possible alternative split events, and the small gray numbers are bootstrap values for each branch (shown only for values>50%). Black circles marked “1–3” represent nodes that correspond in the networks with a polytomy. Gray squares marked “BC1–3” represent nodes that occur only in the trees due to a bifurcation conflict. In the tree diagrams, the bootstrap support value of node Y was increased from 40% to 96% when isolate X was excluded. Small white circles marked “1–3” on a branch indicate the respective connection of this branch to the node 1–3 in the networks.</p

Mismatch distributions and Bayesian skyline plot of 9<i>i</i> sequences.

<p>The mismatch distribution is based on the complete <i>G</i> gene sequence and is calculated separately for the following: 213 <i>9i</i> sequences from Austria, France, Germany, Italy, Poland, Switzerland, and Slovenia, collected between 1999 and 2015; 145 German <i>9i</i> sequences from 2002 to 2015; 27 Swiss <i>9i</i> sequences from 1999 to 2012; 13 Italian <i>9i</i> sequences from 2002 to 2011; and 18 Polish <i>9i</i> sequences from 2006 to 2009. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164475#pone.0164475.t001" target="_blank">Table 1</a> lists the respective value of the raggedness index (r), nucleotide diversity (PI), Tajima’s D, and Fu’s Fs of each dataset. The Bayesian skyline plot shows changes of the 9<i>i</i> population size between 1999 and 2015. The plot was generated using all 213 9<i>i</i> sequences (complete <i>G</i> gene sequence). X axis: time in years, Y axis: population size. The middle solid line is the median estimate, and the area between the blue lines shows the 95% highest probability density (HPD).</p