Data for: Can we locate shrimp aquaculture ponds from space? – A case study for Thailand

Published: 5 October 2020| Version 1 | DOI: 10.17632/nc4cg9bdcd.1
Contributors:
Martin Dorber, Kenji Sudo, Masahiro NAKAOKA, Francesca Verones

Description

This shapefile (generated with ArcGis Desktop Version 10.8) contains the identified water areas in Thailand that have a high likelihood to be a shrimp pond and the identified land cover change. -9999 = NoData Pond 1= Shrimp water area 2= Non-Shrimp water area Farm_Unit = Identification number of the corresponding "farm unit" Water_Cat =Water category obtained from the global water surface explorer (Pekel, J.-F.; Cottam, A.; Gorelick, N.; Belward, A. S., High-resolution mapping of global surface water and its long-term changes. Nature 2016, 540, 418.) 1=Permanent 2=New permanent 4=Seasonal 5=New seasonal 7=Seasonal to permanent 8=Permanent to seasonal 9=Ephemeral permanent 10=Ephemeral seasonal Coastal = defines the location 1 = inland region 2 = costal region Area_km2 = Area of the related polygon in km2; measured by using the WGS 1984 World Mercator projection. Forest_km2 = “primary forested land” area in km2, that has potentially been converted by shrimp pond construction NFores_km2 = “primary non-forested” area in km2, that has potentially been converted by shrimp pond construction NPrima_km2 = “non-primary land” area in km2, that has potentially been converted by shrimp pond construction likelihood = Attributed shrimp pond water area likelihood class Class 1 has the comparably lowest likelihood to be a shrimp pond and class 3 has the comparably highest likelihood to be a shrimp pond.

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Remote Sensing, Land Use Change, Environmental Assessment, Environment Footprint

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