%0 Journal Article %1 dlr127666 %A Ottinger, Marco %A Clauss, Kersten %A Leinenkugel, Patrick %A Kuenzer, Claudia %D 2019 %J ESA Living Planet Symposium 2019 %K DLR Kuenzer LSFE %T Copernicus Sentinel Data for Supporting the Estimation of Aquaculture Production in Coastal Regions %U https://elib.dlr.de/127666/ %X Aquaculture, the farming of aquatic organisms, such as fish, shrimp and molluscs, is one of the fastest growing food production sectors, supplies more than half of the fish consumed today and is a primary source of animal protein and essential fatty acids for millions of people. With an average annual growth rate of 7.2 \%, world aquaculture production increased from 13 million t in 1990 to more than 80 million t in 2016 and is currently valued at USD 231 billion. Rising demand for fish and seafood, stagnating capture fishery production and the development of new technologies and management practices fostered the rapid growth of aquaculture. Aquaculture makes an important contribution to the supply of protein-rich foods in human consumption of the growing world population, ensuring global food security. Land-based pond aquaculture is the predominant culture system in coastal regions and widely spread along coastal environments of East and South-East Asia, where new challenges emerge from global climate change, land use changes and environmental degradation. We present a novel approach for the estimation of aquaculture production utilizing earth observation data and statistical data. An object-based image processing chain was developed to detect and map rectangular shaped aquaculture pond in coastal regions utilizing high-resolution Copernicus Sentinel-1 SAR time series, image segmentation methods and pond object shape features. Production and yield statistics were collected and harmonized at national, regional and local level to link earth observation based findings with production estimations based on a regression model. The combined methodological approaches include a large-scale assessment of land-based pond systems, regression analysis, and pond production estimates. It enables a quantification of aquaculture area at large spatial scale and provides valuable information on productivity of the derived systems. Space-borne data can assist aquaculture producing countries by enabling improved estimation, particularly for non-reporting regions. With the world's growing population and rising demand for fish and seafood, this framework can be used as a basis to gain more knowledge with regard to the analyses of coastal land use dynamics and food security.

@article{dlr127666, abstract = {Aquaculture, the farming of aquatic organisms, such as fish, shrimp and molluscs, is one of the fastest growing food production sectors, supplies more than half of the fish consumed today and is a primary source of animal protein and essential fatty acids for millions of people. With an average annual growth rate of 7.2 \%, world aquaculture production increased from 13 million t in 1990 to more than 80 million t in 2016 and is currently valued at USD 231 billion. Rising demand for fish and seafood, stagnating capture fishery production and the development of new technologies and management practices fostered the rapid growth of aquaculture. Aquaculture makes an important contribution to the supply of protein-rich foods in human consumption of the growing world population, ensuring global food security. Land-based pond aquaculture is the predominant culture system in coastal regions and widely spread along coastal environments of East and South-East Asia, where new challenges emerge from global climate change, land use changes and environmental degradation. We present a novel approach for the estimation of aquaculture production utilizing earth observation data and statistical data. An object-based image processing chain was developed to detect and map rectangular shaped aquaculture pond in coastal regions utilizing high-resolution Copernicus Sentinel-1 SAR time series, image segmentation methods and pond object shape features. Production and yield statistics were collected and harmonized at national, regional and local level to link earth observation based findings with production estimations based on a regression model. The combined methodological approaches include a large-scale assessment of land-based pond systems, regression analysis, and pond production estimates. It enables a quantification of aquaculture area at large spatial scale and provides valuable information on productivity of the derived systems. Space-borne data can assist aquaculture producing countries by enabling improved estimation, particularly for non-reporting regions. With the world{'}s growing population and rising demand for fish and seafood, this framework can be used as a basis to gain more knowledge with regard to the analyses of coastal land use dynamics and food security.}, added-at = {2020-10-30T11:29:13.000+0100}, author = {Ottinger, Marco and Clauss, Kersten and Leinenkugel, Patrick and Kuenzer, Claudia}, biburl = {https://www.bibsonomy.org/bibtex/2f5f94bb25ef0c96f7cdc6b7e13322259/earthobs_uniwue}, interhash = {b6368a78c9020616cbfd0d92567fa4ac}, intrahash = {f5f94bb25ef0c96f7cdc6b7e13322259}, journal = {ESA Living Planet Symposium 2019}, keywords = {DLR Kuenzer LSFE}, timestamp = {2020-11-18T22:08:33.000+0100}, title = {Copernicus Sentinel Data for Supporting the Estimation of Aquaculture Production in Coastal Regions}, url = {https://elib.dlr.de/127666/}, year = 2019 }