Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data
Abstract
:1. Introduction
1.1. Relevance of Aquaculture for Global Food Security
1.2. Sustainability and Challenges in the Context of Global Change
1.3. Characteristics of Aquaculture Pond Systems
1.4. Yields and Statistical Data
1.5. Potential of Earth Observation
2. Study Area
3. Earth Observation-Based Derivation of Pond Aquaculture
3.1. Earth Observation Data
3.2. Aquaculture Assessment Framework
4. The Potential of Earth Observation Data for Aquaculture Production Estimation
4.1. Available Datasets
4.1.1. Global Aquaculture Production Database
4.1.2. National Aquaculture Production Statistics
China
Vietnam
4.1.3. Literature
4.2. Regression Analysis
- -
- Pond size
- -
- Pond depth
- -
- Cultured species
- -
- Stocking density
- -
- External inputs (degree of intensification)
4.3. Best “Guesstimate” Approximation
5. Discussion
- -
- Set up of a production estimation framework for future predictions on food security
- -
- Create new maps, and update existing databases with new results and information
- -
- Aquaculture pond characterization based on high-resolution optical and thermal data (algae bloom, sediment content, water temperature)
- -
- Assessment of ecosystem service losses due to aquaculture expansion
- -
- Harvest loss estimation in case of disease outbreaks
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
- Python 2.7.11
- Scipy 0.17.0
- GDAL 1.11.2
- pandas 0.17.0
- seaborn 0.7.0
- Turf.js 2.0.0
- Orfeo Toolbox 5.4.0
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Total (All Species) | Fish | Crustaceans | Mollusks | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Tons | % WT | Tons | % NT | % WT | Tons | % NT | % WT | Tons | % NT | % WT | |
Vietnam | 3,438,378 | 4.5 | 2,606,272 | 75.8 | 5.0 | 612,038 | 17.8 | 3.7 | 21,562 | 0.6 | 0.3 |
China ** | 47,615,734 | 62.1 | 28,791,920 | 55.5 | 55.5 | 13,848,424 | 29.1 | 18.1 | 4,125,538 | 8.7 | 56.1 |
Global | 76,641,026 | 100.0 | 51,907,471 | 100.0 | 16,473,112 | 100.0 | 7,351,349 | 100.0 |
Region | Environment | Species | Yield * | Source |
---|---|---|---|---|
Global | general | general | 0.2–20 t/ha/yr | [35] |
Global | fertilized polyculture ponds | carp | 3.6–14.6 t/ha/yr | [35,67] |
Global | fertilized ponds | herbivorous or omnivorous fish | 3–10 t/ha/crop | [35,67] |
Tropics | fertilized ponds | nile tilapia | 3.6–7.3 t/ha/yr | [35] |
China | pond culture | - | 6.8 t/ha/yr | [68] |
Honduras | semi-intensive | shrimps | 0.4–2 t/ha/yr | [69] |
Thailand | - | shrimps | 7–8 t/ha/yr | [69,70] |
Vietnam | - | pangasius catfish | 370 t/ha/crop | [71] |
Mekong Delta | intensive culture | black tiger shrimps | 7 t/ha/crop | [15] |
Mekong Delta | brackish water polyculture | mud crab | 0.044 t/ha/yr | [72] |
Mekong Delta | brackish water polyculture | fish | 0.096 t/ha/yr | [72] |
Mekong Delta | rice–shrimp farms | fish | 0.116 t/ha/yr | [72] |
Mekong Delta | intensive | pangasius catfish | 300–400 t/ha/crop | [73] |
Mekong Delta | extensive farming | penaeus shrimp | 0.077–0.24 t/ha/yr | [72] |
Mekong Delta | semi-intensive or intensive systems | penaeus shrimp | 1.3–6.2 t/ha/yr | [72] |
Mekong Delta | inland pond | pangasius catfish | 370 t/ha | [74] |
Mekong Delta | intensively, in deep ponds | catfish | 450 t/ha/crop | [75] |
Study Area (in km²) | Earth Observation-Derived Ponds–Characteristics | ||||
---|---|---|---|---|---|
Number of Ponds * | Pond Area * (in ha) | Share of Pond Area to Study Area * (in %) | Average Pond Size * (in ha) | ||
Mekong Delta | 39,385 | 299,820 | 265,943 | 6.7 | 0.52 |
Red River Delta | 15,541 | 62,289 | 29,940 | 1.9 | 0.56 |
Pearl River Delta | 42,378 | 264,863 | 105,070 | 2.5 | 0.41 |
Yellow River Delta | 7435 | 20,671 | 86,371 | 11.6 | 3.55 |
Study Area (in km²) | Official Aquaculture Production * (in t) | Derived Yield (in t */ha **) | |
---|---|---|---|
Mekong Delta | 39,385 | 2,471,327 | 9.3 |
Red River Delta | 15,541 | 580,915 | 19.4 |
Pearl River Delta | 42,378 | 2,836,970 | 27.0 |
Yellow River Delta | 7435 | 419,516 | 4.9 |
Pond Area * (in ha) | Potential Pond Production Range (in t) | |||||
---|---|---|---|---|---|---|
Yield Values (t/ha) | ||||||
Min ** | 25th Perc | Mean | 75th Perc | Max ** | ||
0.2 t | 5.2 t | 10.1 t | 15.1 t | 20.0 t | ||
Mekong Delta | 265,943 | 53,189 | 1,369,606 | 2,686,024 | 4,002,442 | 5,318,860 |
Red River Delta | 29,940 | 5988 | 154,191 | 302,394 | 450,597 | 598,800 |
Pearl River Delta | 105,070 | 21,014 | 541,111 | 1,061,207 | 1,581,304 | 2,101,400 |
Yellow River Delta | 86,371 | 17,274 | 444,811 | 872,347 | 1,299,884 | 1,727,420 |
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Ottinger, M.; Clauss, K.; Kuenzer, C. Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data. Remote Sens. 2018, 10, 1076. https://doi.org/10.3390/rs10071076
Ottinger M, Clauss K, Kuenzer C. Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data. Remote Sensing. 2018; 10(7):1076. https://doi.org/10.3390/rs10071076
Chicago/Turabian StyleOttinger, Marco, Kersten Clauss, and Claudia Kuenzer. 2018. "Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data" Remote Sensing 10, no. 7: 1076. https://doi.org/10.3390/rs10071076
APA StyleOttinger, M., Clauss, K., & Kuenzer, C. (2018). Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data. Remote Sensing, 10(7), 1076. https://doi.org/10.3390/rs10071076