shipping_2008_bilinear_interpolation (Map Service)
View In:
ArcGIS JavaScript
ArcGIS.com
WMTS
Current Version: 10.81
Service Description: Data taken from the
NCEAS report
A Global Map of Human Impacts to Marine Ecosystems.
Cumulative human impact on the ocean results from the combination of each of nineteen individual stressors. Understanding the pattern and intensity of the individual stressors is therefore a key first step in the analyses. These results also provide important snapshots of the individual contribution of each stressor to the current condition of the ocean.
Commercial shipping activity can lead to ship strikes of large animals, noise pollution, and a risk of ship groundings or sinkings. Ships from many countries voluntarily participate in collecting meteorological data globally, and therefore also report the location of the ship.
We used data collected from 12 months beginning October 2004 (collected as part of the World Meteorological Organization Voluntary Observing Ships Scheme; http://www.vos.noaa.gov/vos_scheme.shtml) as this year had the most ships with vetted protocols and so provides the most representative estimate of global ship locations. The data include unique identifier codes for ships (mobile or a single datum) and stationary buoys and oil platforms (multiple data at a fixed location); we removed all stationary and single point ship data, leaving 1,189,127 mobile ship data points from a total of 3,374 commercial and research vessels, representing roughly 11% of the 30,851 merchant ships >1000 gross tonnage at sea in 2005 (S14). We then connected all mobile ship data to create ship tracks, under the assumption that ships travel in straight lines (a reasonable assumption since ships minimize travel distance in an effort to minimize fuel costs). Finally, we removed any tracks that crossed land (e.g. a single ship that records its location in the Atlantic and the Pacific would have a track connected across North America), buffered the remaining 799,853 line segments to be 1 km wide to account for the width of shipping lanes, summed all buffered line segments to account for overlapping ship tracks, and converted summed ship tracks to raster data. This produced 1 km2 raster cells with values ranging from 0 to 1,158, the maximum number of ship tracks recorded in a single 1 km2 cell.
Because the VOS program is voluntary, much commercial shipping traffic is not captured by these data. Therefore our estimates of the impact of shipping are biased (in an unknown way) to locations and types of ships engaged in the program. In particular, high traffic locations may be strongly underestimated, although the relative impact on these areas versus low-traffic areas appears to be well-captured by the available data (Fig. S2), and areas identified as without shipping may actually have low levels of ship traffic. Furthermore, because ships report their location with varying distance between signals, ship tracks are estimates of the actual shipping route taken.
Map Name: Map
Legend
All Layers and Tables
Layers:
Tables:
Description: Data taken from the
NCEAS report
A Global Map of Human Impacts to Marine Ecosystems.
Cumulative human impact on the ocean results from the combination of each of nineteen individual stressors. Understanding the pattern and intensity of the individual stressors is therefore a key first step in the analyses. These results also provide important snapshots of the individual contribution of each stressor to the current condition of the ocean.
Commercial shipping activity can lead to ship strikes of large animals, noise pollution, and a risk of ship groundings or sinkings. Ships from many countries voluntarily participate in collecting meteorological data globally, and therefore also report the location of the ship.
We used data collected from 12 months beginning October 2004 (collected as part of the World Meteorological Organization Voluntary Observing Ships Scheme; http://www.vos.noaa.gov/vos_scheme.shtml) as this year had the most ships with vetted protocols and so provides the most representative estimate of global ship locations. The data include unique identifier codes for ships (mobile or a single datum) and stationary buoys and oil platforms (multiple data at a fixed location); we removed all stationary and single point ship data, leaving 1,189,127 mobile ship data points from a total of 3,374 commercial and research vessels, representing roughly 11% of the 30,851 merchant ships >1000 gross tonnage at sea in 2005 (S14). We then connected all mobile ship data to create ship tracks, under the assumption that ships travel in straight lines (a reasonable assumption since ships minimize travel distance in an effort to minimize fuel costs). Finally, we removed any tracks that crossed land (e.g. a single ship that records its location in the Atlantic and the Pacific would have a track connected across North America), buffered the remaining 799,853 line segments to be 1 km wide to account for the width of shipping lanes, summed all buffered line segments to account for overlapping ship tracks, and converted summed ship tracks to raster data. This produced 1 km2 raster cells with values ranging from 0 to 1,158, the maximum number of ship tracks recorded in a single 1 km2 cell.
Because the VOS program is voluntary, much commercial shipping traffic is not captured by these data. Therefore our estimates of the impact of shipping are biased (in an unknown way) to locations and types of ships engaged in the program. In particular, high traffic locations may be strongly underestimated, although the relative impact on these areas versus low-traffic areas appears to be well-captured by the available data (Fig. S2), and areas identified as without shipping may actually have low levels of ship traffic. Furthermore, because ships report their location with varying distance between signals, ship tracks are estimates of the actual shipping route taken.
Copyright Text: Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS.
Spatial Reference:
102100
Single Fused Map Cache: true
Capabilities: Map,TilesOnly,Tilemap
Tile Info:
- Height: 256
- Width: 256
- DPI: 96
- Levels of Detail: (# Levels: 24)
- Level ID: 0 [Start Tile, End Tile]
Resolution: 156543.033928
Scale: 5.91657527591555E8
- Level ID: 1 [Start Tile, End Tile]
Resolution: 78271.5169639999
Scale: 2.95828763795777E8
- Level ID: 2 [Start Tile, End Tile]
Resolution: 39135.7584820001
Scale: 1.47914381897889E8
- Level ID: 3 [Start Tile, End Tile]
Resolution: 19567.8792409999
Scale: 7.3957190948944E7
- Level ID: 4 [Start Tile, End Tile]
Resolution: 9783.93962049996
Scale: 3.6978595474472E7
- Level ID: 5 [Start Tile, End Tile]
Resolution: 4891.96981024998
Scale: 1.8489297737236E7
- Level ID: 6 [Start Tile, End Tile]
Resolution: 2445.98490512499
Scale: 9244648.868618
- Level ID: 7 [Start Tile, End Tile]
Resolution: 1222.99245256249
Scale: 4622324.434309
- Level ID: 8 [Start Tile, End Tile]
Resolution: 611.49622628138
Scale: 2311162.217155
- Level ID: 9 [Start Tile, End Tile]
Resolution: 305.748113140558
Scale: 1155581.108577
- Level ID: 10 [Start Tile, End Tile]
Resolution: 152.874056570411
Scale: 577790.554289
- Level ID: 11 [Start Tile, End Tile]
Resolution: 76.4370282850732
Scale: 288895.277144
- Level ID: 12 [Start Tile, End Tile]
Resolution: 38.2185141425366
Scale: 144447.638572
- Level ID: 13 [Start Tile, End Tile]
Resolution: 19.1092570712683
Scale: 72223.819286
- Level ID: 14 [Start Tile, End Tile]
Resolution: 9.55462853563415
Scale: 36111.909643
- Level ID: 15 [Start Tile, End Tile]
Resolution: 4.77731426794937
Scale: 18055.954822
- Level ID: 16 [Start Tile, End Tile]
Resolution: 2.38865713397468
Scale: 9027.977411
- Level ID: 17 [Start Tile, End Tile]
Resolution: 1.19432856685505
Scale: 4513.988705
- Level ID: 18 [Start Tile, End Tile]
Resolution: 0.597164283559817
Scale: 2256.994353
- Level ID: 19 [Start Tile, End Tile]
Resolution: 0.298582141647617
Scale: 1128.497176
- Level ID: 20 [Start Tile, End Tile]
Resolution: 0.14929107082380833
Scale: 564.248588
- Level ID: 21 [Start Tile, End Tile]
Resolution: 0.07464553541190416
Scale: 282.124294
- Level ID: 22 [Start Tile, End Tile]
Resolution: 0.03732276770595208
Scale: 141.062147
- Level ID: 23 [Start Tile, End Tile]
Resolution: 0.01866138385297604
Scale: 70.5310735
- Format: Mixed
- Compression Quality: 75
- Origin:
X: -2.0037508342787E7
Y: 2.0037508342787E7
- Spatial Reference:
102100
Initial Extent:
XMin: -5380593.167547981
YMin: -4269398.647666949
XMax: 2553279.6391667994
YMax: 4052808.013894004
Spatial Reference:
102100
Full Extent:
XMin: -2.0037507842788246E7
YMin: -3.024097145838615E7
XMax: 2.0037507842788246E7
YMax: 3.024097145838615E7
Spatial Reference:
102100
Min Scale: 5.91657527591555E8
Max Scale: 6000000.0
Min LOD: 0
Max LOD: 7
Units: esriMeters
Supported Image Format Types: Mixed
Export Tiles Allowed: false
Max Export Tiles Count: 100000
Document Info:
- Title: Global Shipping Routes (2008)
- Author: StoryMaps
- Comments:
- Subject: Cumulative commercial shipping activity in the twelve months beginning October 2004
- Category:
- Keywords: anthropocene, shipping, networks, ArcGIS