BioVeL_ESW_DIFF___ENinput100 Input of the current layer. The difference will be computed as predictionLayer - currentLayer Expected as input files are raster images as a URL from openModeller created by an ENM workflow. A file upload is not possible! Supported formats are: - ERDASImagine (.img) files with a value range 0 - 100, noData value 101 - GeoTIFF (.tif) files with a value range 0 - 254, noData Value 255 Input files with a different extent will be intersected to a common extent and the current layer (inputfile 1) will be resampled to the prediction layer (inputfile 2) using the "nearest neighbour" sampling method 2014-05-21 14:51:08.184 UTC http://biovel.github.io/esw/sample_data/present.tif 2014-05-21 14:51:30.799 UTC input200 http://biovel.github.io/esw/sample_data/prediction.tif 2014-05-21 14:52:49.318 UTC Input of the prediction layer. The difference will be computed as predictionLayer - currentLayer Expected as input files are raster images as a URL from openModeller created by an ENM workflow. A file upload is not possible! Supported formats are: - ERDASImagine (.img) files with a value range 0 - 100, noData value 101 - GeoTIFF (.tif) files with a value range 0 - 254, noData Value 255 Input files with a different extent will be intersected to a common extent and the current layer (inputfile 1) will be resampled to the prediction layer (inputfile 2) using the "nearest neighbor" sampling method 2014-05-21 14:52:12.17 UTC label_species00 Enter your favorite name for the species used in the "changes" output table only 2014-05-21 14:53:14.398 UTC my_spezies_name 2012-12-13 15:29:34.651 UTC PNG_output_size00 Size of the output PNG's in pixels. 2014-05-21 14:53:37.584 UTC 800 2013-07-05 15:09:17.103 UTC occurrence_csv00 none 2014-01-17 12:56:05.157 UTC URL to the CSV File with occurrence points coming from ENM. If you don't want to display any points, type "none" at the begin, else paste a CSV URL or the content from a CSV or a CSV file as input Example CSV URL: http://biovel.github.io/esw/sample_data/dendrolimus_pini.csv 2014-05-21 14:50:16.651 UTC center_of_mass00 false 2014-01-17 12:56:19.383 UTC Enter false or true. If you want to display centers of mass on the layers type "true". 2014-05-21 14:49:41.102 UTC summary This file contains the summary for the current, prediction and the difference layer: - Number of cells (ncell), - Mean and median value (mean,median) - Coefficient of variation (cv) - Standard deviation (sd) - current minimal and maximal values (min,max) - Number of noData values in file (countNA) 2014-05-21 15:09:58.654 UTC XX,ncell,mean,median,cv,sd,min,max,countNA currentLayer,1064979,12.0542036613726,0,249.631587493174,30.0910999595447,0,223,509832 predictionLayer,1064979,15.013555322091,0,220.535786355749,33.1102622895288,0,219,547175 diffLayer,1064979,2.48103722644089,0,1217.13054589666,30.1974619380793,-197,208,547175 2014-05-21 15:10:29.311 UTC currentLayerPng PNG overview of the input current layer with a background country borders based on the TDWG level4 layer Used color ramp: ERDASImagine file: breakpoints = (0,1,25,50,75,100) GeoTIFF file breakpoints = c(0,2,63,127,190,254) colors = c(rgb(1.0,1.0,1.0),rgb(0.996,0.898,0.851),rgb(0.988,0.682,0.569),rgb(0.984,0.416,0.290),rgb(0.871,0.176,0.149),rgb(0.647,0.059,0.082)) 2014-05-21 15:06:18.50 UTC predictionLayerPng PNG overview of the input prediction layer with a background country borders based on the TDWG level4 layer Used color ramp: ERDASImagine file: breakpoints = c(0,1,25,50,75,100) GeoTIFF file breakpoints = c(0,2,63,127,190,254) colors = c(rgb(1.0,1.0,1.0),rgb(0.996,0.898,0.851),rgb(0.988,0.682,0.569),rgb(0.984,0.416,0.290),rgb(0.871,0.176,0.149),rgb(0.647,0.059,0.082)) 2014-05-21 15:08:38.540 UTC diffLayerPng PNG overview of the output difference layer with a background country borders based on the TDWG level4 layer Used color ramp: ERDASImagine file: breakpoints = c(-100,-70,-50,-25,-1,1,25,50,70,100) GeoTIFF file breakpoints = c(-254,-190,-127,-63,-2,2,63,127,190,254) colors = c(rgb(0.396,0.310,0.635),rgb(0.196,0.533,0.741),rgb(0.4,0.761,0.647),rgb(0.671,0.867,0.643),rgb(1.0,1.0,1.0),rgb(0.992,0.682,0.380),rgb(0.957,0.427,0.263),rgb(0.835,0.243,0.310),rgb(0.620,0.004,0.259)) 2014-05-21 15:12:20.820 UTC changes This file contains the changes computation in the submitted files: Overall coverage in the input raster files and their difference overall_coverage = ((ncell(x)-cellStats(x, 'countNA')-count(x,0))/(ncell(x)-cellStats(x, 'countNA')))*100 difference = coverage_prediction - coverage_current Overall intensity absolute and in percent and their difference overall_intensity = (cellStats(x, sum)/(ncell(x)-cellStats(x, 'countNA'))) difference = intensity_prediction - intensity_current 2014-05-21 15:05:37.811 UTC XX,Overall coverage,Overall coverage,Difference overall coverage,Overall intensity (absolute),Overall intensity (absolute),Difference overall intensity (absolute),Overall intensity (percentage),Overall intensity (percentage),Difference overall intensity (percentage),Mass centre longitude,Mass centre latitude,Mass centre longitude,Mass centre latitude,Shift distance species,current,prediction,prediction-current,current,prediction,prediction-current,current_%,prediction_%,prediction-current,prediction-current_%,current,current,prediction,prediction,km my_spezies_name,38.8307961675016,47.3236977698125,8.49290160231094,12.0542036613726,15.013555322091,2.95935166071841,4.74574947298133,5.91084855200432,1.16509907902299,15.7230264580409,51.0632712451619,21.0357128253069,55.4100745868783,599.25644 2014-05-21 15:05:43.523 UTC diffImg Image file of the difference layer, the format is the same as the input files: ERDASImagine or GeoTIFF 2014-05-21 15:07:15.966 UTC matrix_diff Matrix table of the output raster file for the difference layer. The file is in ArcGRID format 2014-05-21 15:06:38.55 UTC logfile computation start: 2013-07-05 16:11:22 File 1 input format: GeoTIFF (.tif) value range: 0 <> 254, noData 255, current values: min 0, max: 181 File 2 input format: GeoTIFF (.tif) value range: 0 <> 254, noData 255, current values: min 0, max: 89 input files cropped: NO input files normalized: NO output file format: GeoTIFF (.tif) 2014-05-21 15:08:03.108 UTC This file contains a overview about the used files and the computation 2014-05-21 15:07:58.537 UTC matrix_x Matrix table of the input raster file for the current layer. The file is in ArcGRID format 2014-05-21 15:11:36.175 UTC matrix_y Matrix table of the input raster file for the prediction layer. The file is in ArcGRID format 2014-05-21 15:11:49.598 UTC Rshellin10in20label0png_size0center_of_mass0csv_url0rastersummary00currentLayerPng00diffLayerPng00predictionLayerPng00changes00diffImg00diffascii00logfile00x_matrix00y_matrix00net.sf.taverna.t2.activitiesrshell-activity1.4net.sf.taverna.t2.activities.rshell.RshellActivity in1 0 false in2 0 false label 0 false png_size 0 false csv_url 0 false center_of_mass 0 false rastersummary 0 0 currentLayerPng 0 0 predictionLayerPng 0 0 diffLayerPng 0 0 changes 0 0 diffImg 0 0 diffascii 0 0 logfile 0 0 x_matrix 0 0 y_matrix 0 0 output_format 0 0 false localhost 6311 false false in1 STRING in2 STRING label STRING png_size STRING csv_url STRING center_of_mass STRING rastersummary STRING currentLayerPng PNG_FILE predictionLayerPng PNG_FILE diffLayerPng PNG_FILE changes STRING diffImg PNG_FILE diffascii PNG_FILE logfile STRING x_matrix PNG_FILE y_matrix PNG_FILE output_format STRING 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16e32a27-16dd-41ae-a159-b1877ed0979d 2012-11-20 20:30:46.201 UTC 2ae2c447-6ae8-4dad-92ff-eae7b1b32dab 2012-11-19 15:41:32.377 UTC 130777fd-2d0e-4cbe-b3b5-913a0e47494a 2013-07-04 12:26:37.482 UTC 143eab78-3137-488b-8440-c625df587718 2013-01-25 14:48:40.953 UTC 46742105-3e07-4f76-93a6-aa46ce366438 2012-11-06 13:46:16.535 UTC ab386568-1213-496f-a270-86d04f401eb8 2012-11-14 16:41:43.877 UTC fecf5e90-3350-47a0-b3e7-62fbc60fbd53 2013-06-27 11:41:06.327 UTC 426b900c-0a58-49bf-a99d-88e59c59cb3d 2012-11-15 16:49:48.889 UTC aeb5cb85-1409-4f0b-93c3-c78443a1fd15 2013-07-04 12:04:16.196 UTC 890b4e06-6cba-4b83-a2ac-23996b946fdc 2013-01-30 12:42:35.799 UTC 47895df1-3665-4fc0-a015-0ee5ad7d8b42 2013-06-17 12:19:59.137 UTC 6430f5ae-68cd-438d-a1bc-46635c7b80e8 2013-01-30 14:37:51.546 UTC 929e26a8-c470-4e0b-bbe6-3b6ef8dcbe16 2012-11-19 16:56:39.125 UTC 7245dfce-8c23-4b12-89fe-315fe86fbdde 2012-11-15 16:39:05.167 UTC e6bee6dd-7506-4155-8af6-987c8600af3a 2012-11-14 15:40:38.127 UTC 503030a6-6d55-47a6-aa22-d5dd96128708 2012-11-20 19:41:30.455 UTC 304ddbaa-2710-4161-a1ce-757e2976dd29 2012-11-06 14:03:16.946 UTC f8782fc4-0204-43de-91f8-545344ed818a 2013-11-10 22:35:06.349 UTC 6b521246-4c3b-4f31-8dbe-b5c4060e33fa 2012-11-14 14:24:30.676 UTC a90ba418-46f4-4027-938f-650a2893c824 2013-02-12 09:54:01.284 UTC 86b02a51-99ce-4779-ae11-91f256297870 2013-01-30 13:15:02.790 UTC 2c3005d0-5737-463e-9a2c-edc83ec2c796 2012-11-14 15:28:20.551 UTC c6da0d16-5360-4e77-b4bd-01cce99e773e 2012-11-14 14:51:50.60 UTC 150e0bf7-f439-4e3b-987c-975de0fc3919 2012-12-13 14:42:33.242 UTC 855ff19e-8738-4b39-8e61-e01f9017062d 2012-11-14 14:21:11.92 UTC 02742e75-a8d9-4794-a22d-e3ad6a24afa6 2014-01-29 18:17:45.419 UTC 5751ae89-bf26-4593-b936-287fa97cc6d5 2013-09-03 13:18:25.335 UTC e02b3b29-33a0-465c-b2c5-8c2e131cfc8f 2013-01-30 14:26:02.692 UTC ba8e84e6-0992-49d0-b378-926a6e69bb93 2013-01-30 12:24:37.360 UTC 20802cea-b41e-4ca2-a2ca-0a9a813b7b1a 2012-11-21 10:59:10.107 UTC fdba2215-3e5e-443d-8de1-e33b16dbb065 2013-06-18 06:04:22.957 UTC ac4621b4-aea5-4a7a-bf60-c4f22eda484b 2012-11-19 14:59:52.328 UTC fc1dfdc7-146e-44d6-9391-2cde9a7ac0be 2012-11-14 16:39:10.445 UTC e4c9d7f1-db65-4129-9c55-efa43b6f4c8c 2012-11-06 12:40:58.675 UTC 8da7947c-7501-4cb6-904a-6e335dcec672 2012-11-14 15:25:36.231 UTC 1415ed9c-34fd-4b6d-9bb1-499a310b137b 2012-11-14 16:32:41.724 UTC 5662548d-6ec9-400e-b862-a5b8454217b2 2012-11-19 17:09:45.937 UTC f4576b43-1866-44cb-8af6-00f1e941af49 2013-07-03 15:44:13.114 UTC 05d073ab-9752-4504-abf3-8a5af9c91a13 2013-09-18 12:00:39.581 UTC 71a7ef1c-c553-45e9-90ee-ffd22962dc10 2013-01-30 13:02:02.258 UTC The ENM Statistical Difference Workflow (ESW DIFF) allows the computation of the extent and intensity of change in species potential distribution through computation of the differences between two raster layers using the R statistical environment (R Core Team 2013). The difference file is computed from two input files (in this case present projection and 2050 projection) coming from the Ecological Niche Modelling (ENM) Workflow (http://www.myexperiment.org/workflows/3355). The difference between each corresponding raster cell value is computed and stored in the difference file, regardless of the input files’ geographical extent and origin. If the files have a different geographical extent and/or origin the raster-diff workflow automatically crops them to the same extent and resamples the values using the “nearest neighbour” method, resulting in a perfect cell match between the two rasters. The resulting value in the difference file ranges from the negative and positive maximum values of the input files to represent the maximum possible change in both directions. The diff result values are classified into six positive and negative classes. The predicted differences are presented for each species as a heat map, where cells with colors from green to red indicate an increase and from green to blue a decrease of predicted potential for a species. The workflow enables the computation of the raster centerpoints, overall coverage, overall intensity and the difference in intensity or coverage between two raster layers, as well as the distance between the centerpoints of the two input files (shift vector). The centerpoint is computed as the weighted average of raster cells inside the mask, overall coverage as the percentage of raster cells with values >0, overall intensity as the sum of all valued cells divided by the number of raster cells, and finally the shift vector as the distance between the centerpoints of the two input files using the Vincenty’s formulae. Summary statistics for the raster layers are also provided: number of raster cells, mean intensity, median, CV, SD, Min value, Max value and number of cells outside the mask. This workflow store the computed difference image to the BioVeL Geoserver and create PNG overwiews contains the input and output files and the distribution points. The difference result image could be shown in the BioSTIF web visualisation client The workflow contains the computation methods: - Computation of the difference layer: difference = inputfile_B - inputfile_A - Computation of the overall coverage and intensity overall_coverage = ((ncell(x)-cellStats(x, 'countNA')-count(x,0))/(ncell(x)-cellStats(x, 'countNA')))*100 overall_intensity = cellStats(x, sum)/(ncell(x)-cellStats(x, 'countNA')) - Used standard R functions: cellStats: https://r-forge.r-project.org/scm/viewvc.php/pkg/raster/R/cellStats.R?view=markup&root=raster The PNG overview will be created with these values (corresponding to the Geoserver style) ERDASImagine file: breakpoints = c(0,1,25,50,75,100) GeoTIFF file breakpoints = c(0,2,63,127,190,254) colors = c(rgb(1.0,1.0,1.0), rgb(0.996,0.898,0.851), rgb(0.988,0.682,0.569), rgb(0.984,0.416,0.290), rgb(0.871,0.176,0.149), rgb(0.647,0.059,0.082)) Expected as input files are those raster images as a URL reference e.g. output files from openModeller created by an ENM workflow. *A file upload into the workflow is not possible, only a reference to the input file as URL* Supported formats are: - ERDASImagine (.img) files with a value range 0 - 100, noData value 101 - GeoTIFF (.tif) files with a value range 0- 254, noData Value 255 Input files with a different extent will be intersected to a common extent and the current layer (inputfile 1) will be resampled to the prediction layer (inputfile 2) using the "nearest neighbor" sampling method. The difference layer will be computed as inputfile_2 - inputfile_1 For working with the ESW in a own localhost an R instance should by installed on a own machine (http://cran.r-project.org/). For the computation the followed extensions must be installed: rgdal, raster and rserve. Rserve must be started before the computation. -------------------- This workflow has been created by the Biodiversity Virtual e-Laboratory (BioVeL http://www.biovel.eu/) project. BioVeL is funded by the EU’s Seventh Framework Program, grant no. 283359. 2014-05-21 14:57:01.920 UTC e318a054-d98a-41d5-8e39-8206120a7e91 2012-11-20 18:08:18.11 UTC 583d1585-e2ac-4269-b676-8768beac9cfb 2013-07-05 14:07:14.489 UTC eb5e47e9-b4a0-422a-8152-42ea171e8dd9 2013-09-03 13:36:55.227 UTC 94b6b4ea-f8da-4ee4-a48a-445b2870fc5a 2013-07-03 15:38:37.832 UTC caddc975-8b8b-4234-bf88-df7b90c06ed4 2013-06-27 11:48:30.722 UTC 82eb68fe-d735-46f5-9384-33932af9500b 2012-11-19 15:52:47.228 UTC 66d1a819-7835-4b17-9a5a-a11a6d85fd76 2012-11-22 14:39:21.634 UTC 3931377f-531d-45c3-b1a3-3352fea2ffae 2014-06-02 14:03:01.149 UTC ee2df214-0fca-459d-8c6d-d93cd4584766 2012-11-19 14:52:45.966 UTC 56515018-dcd4-4822-8d99-511cc1dfe7fd 2012-11-14 14:31:36.988 UTC 2c10c399-60f8-4a53-aa06-ffabb33663f3 2013-01-28 17:37:53.358 UTC eb893a34-d99f-426a-83c1-3e15afa28f84 2012-11-21 09:59:48.922 UTC ad31a1ad-858d-4aaa-8ba1-9bd01a4fae01 2012-11-19 16:16:39.868 UTC 7720d10d-5d37-45b0-94a4-fd37efa58b47 2012-11-19 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