Oysters are nutritious food organisms,rich in protein,minerals and vitamins.Production from Pacific oyster(Crassostrea gigas)aquaculture is increasing and supports the livelihoods of coastal communities.To ensure both...Oysters are nutritious food organisms,rich in protein,minerals and vitamins.Production from Pacific oyster(Crassostrea gigas)aquaculture is increasing and supports the livelihoods of coastal communities.To ensure both success and long-term sustainability of oyster production,the determination of suitable sites is an important step in any aquaculture operation.This study applied GIS(Geographic Information System)based MCE(Multi-Criteria Evaluation)for locating suitable sites for Pacific oyster(Crassostrea gigas)farms in coastal regions in Central Vietnam.Remote sensing data were obtained viaMODIS(Moderate Resolution Imaging Spectroradiometer)and high resolution imagery from the Google Earth Engine,while oceanic data were obtained from HYCOM-NCODA(Hybrid Coordinate Ocean Model-Navy Coupled Ocean Data Assimilation)coupled with local hydrodynamic FEM(Finite Element Model)Hydrographic charts and GPS(Global Positioning System)data were used to extract required information layers for GIS based MCE for the suitable site selection of oyster farms.Six thematic layers of biophysical parameters were used to analysis MCE non-constraints including the depth,temperature,salinity,Chl-a(Chlorophyll-a)content,suspended matter concentration and velocity of sea current.Then,an MCE analysis with constraint was used to exclude the areas from suitability maps where oyster aquaculture could not be developed.They were conducted in two subgroups,biophysical subgroup(including un-suitable depth,un-suitable substratum and shore line types,potential regions prone to strong impact of natural disasters and environmental risks,sensitive habitats in MPAs(Marine Protection Areas),and social-infrastructural subgroups(including human settlement in urban area,wastewater system,industrial zones,piers,harbors etc.).A series of GIS models was developed to identify the most suitable areas for oyster culture using MCE with the estimating of factor score(Xi)based on expert knowledge as well as calculating of Weighting(Wi)based on Saaty’s matrix relevant展开更多
文摘Oysters are nutritious food organisms,rich in protein,minerals and vitamins.Production from Pacific oyster(Crassostrea gigas)aquaculture is increasing and supports the livelihoods of coastal communities.To ensure both success and long-term sustainability of oyster production,the determination of suitable sites is an important step in any aquaculture operation.This study applied GIS(Geographic Information System)based MCE(Multi-Criteria Evaluation)for locating suitable sites for Pacific oyster(Crassostrea gigas)farms in coastal regions in Central Vietnam.Remote sensing data were obtained viaMODIS(Moderate Resolution Imaging Spectroradiometer)and high resolution imagery from the Google Earth Engine,while oceanic data were obtained from HYCOM-NCODA(Hybrid Coordinate Ocean Model-Navy Coupled Ocean Data Assimilation)coupled with local hydrodynamic FEM(Finite Element Model)Hydrographic charts and GPS(Global Positioning System)data were used to extract required information layers for GIS based MCE for the suitable site selection of oyster farms.Six thematic layers of biophysical parameters were used to analysis MCE non-constraints including the depth,temperature,salinity,Chl-a(Chlorophyll-a)content,suspended matter concentration and velocity of sea current.Then,an MCE analysis with constraint was used to exclude the areas from suitability maps where oyster aquaculture could not be developed.They were conducted in two subgroups,biophysical subgroup(including un-suitable depth,un-suitable substratum and shore line types,potential regions prone to strong impact of natural disasters and environmental risks,sensitive habitats in MPAs(Marine Protection Areas),and social-infrastructural subgroups(including human settlement in urban area,wastewater system,industrial zones,piers,harbors etc.).A series of GIS models was developed to identify the most suitable areas for oyster culture using MCE with the estimating of factor score(Xi)based on expert knowledge as well as calculating of Weighting(Wi)based on Saaty’s matrix relevant
