Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data

Ottinger, Marco; Clauss, Kersten; Kuenzer, Claudia

doi:10.3390/rs10071076

Cited by 63 publications

(39 citation statements)

References 63 publications

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“…Clauss et al [54] conducted a study to estimate rice production and rice area in Vietnam. Ottinger et al [55] observed aquaculture ponds using more than 500 Sentinel-1 scenes and an object-based analysis method and revealed that Sentinel-1 SAR with high spatial resolution can be used for monitoring aquaculture ponds in Vietnam and China. The author showed this approach has great potential for global production projections.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Mapping of Rice Cropping Pattern in Flooding Area in the Vietnamese Mekong Delta Using Sentinel-1A Data: A Case of An Giang Province

Minh

Avtar

Mohan

et al. 2019

IJGI

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Cropping intensity is one of the most important decisions made independently by farmers in Vietnam. It is a crucial variable of various economic and process-based models. Rice is grown under irrigated triple- and double-rice cropping systems and a rainfed single-rice cropping system in the Vietnamese Mekong Delta (VMD). These rice cropping systems are adopted according to the geographical location and water infrastructure. However, little work has been done to map triple-cropping of rice using Sentinel-1 along with the effects of water infrastructure on the rice cropping intensity decision. This study is focused on monitoring rice cropping patterns in the An Giang province of the VMD from March 2017 to March 2018. The fieldwork was carried out on the dates close to the Sentinel-1A acquisition. The results of dual-polarized (VV and VH) Sentinel-1A data show a strong correlation with the spatial patterns of various rice growth stages and their association with the water infrastructure. The VH backscatter (σ°) is strongly correlated with the three rice growth stages, especially the reproductive stage when the backscatter is less affected by soil moisture and water in the rice fields. In all three cropping patterns, σ°VV and σ°VH show the highest value in the maturity stage, often appearing 10 to 12 days before the harvesting of the rice. A rice cropping pattern map was generated using the Support Vector Machine (SVM) classification of Sentinel-1A data. The overall accuracy of the classification was 80.7% with a 0.78 Kappa coefficient. Therefore, Sentinel-1A can be used to understand rice phenological changes as well as rice cropping systems using radar backscattering.

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Section: Introductionmentioning

confidence: 99%

Monitoring and Mapping of Rice Cropping Pattern in Flooding Area in the Vietnamese Mekong Delta Using Sentinel-1A Data: A Case of An Giang Province

Minh

Avtar

Mohan

et al. 2019

IJGI

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“…Using some of the world's most significant aquaculture production regions as case studies, i.e., the Mekong, Red, Pearl and Yellow Rivers, the method achieved an overall classification accuracy of 0.83. Extending this dataset, Ottinger et al [172] integrated the remotely-sensed pond maps with pond yield statistics from the literature to estimate aquaculture production in each mega delta, highlighting the great potential of EO for monitoring and management of aquaculture in these regions.…”

Section: The Earth Observation Potential For the Analysis Of Flood Anmentioning

confidence: 99%

“…This first continental-scale, multi-decadal assessment of annual mangrove distribution showed that mangrove forest extent in Australia peaked in 2010 and has since declined by about 240 km 2 [139]. Several recent studies have used Sentinel-1 SAR time series data to map the distribution of rice paddies and aquaculture ponds in river deltas, taking advantage of the unique seasonal inundation dynamics and microwave backscattering characteristics of these features [171,172,[188][189][190]. Advances in SAR-based mapping of aquaculture ponds are already covered in the previous chapter, and therefore, are not repeated here.…”

Section: Earth Observation Potential For Land Cover and Land Use Infomentioning

confidence: 99%

Remote Sensing for the Quantification of Land Surface Dynamics in Large River Delta Regions—A Review

Kuenzer

Heimhuber

Huth³

et al. 2019

Remote Sensing

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River deltas and estuaries belong to the most significant coastal landforms on our planet and are usually very densely populated. Nearly 600 million people live in river deltas, benefiting from the large variety of locational advantages and rich resources. Deltas are highly dynamic and vulnerable environments that are exposed to a wide range of natural and manmade threats. Sustainable management of river deltas therefore requires a holistic assessment of historic and recent ongoing changes and the dynamics in settlement sprawl, land cover and land use change, ecosystem development, as well as river and coastline geomorphology, all of which is difficult to achieve solely with traditional land-based surveying techniques. This review paper presents the potential of Earth Observation for analyses and quantification of land surface dynamics in the large river deltas globally, emphasizing the different geo-information products that can be derived from medium resolution, high resolution and highest resolution optical, multispectral, thermal and SAR data. Over 200 journal papers on remote sensing related studies for large river deltas and estuaries have been analyzed and categorized into thematic fields such as river course morphology, coastline changes, erosion and accretion processes, flood and inundation dynamics, regional land cover and land use dynamics, as well as the monitoring of compliance with respect to anthropogenic activity such as industry expansion-related habitat destruction. Additionally, our own exemplary analyses are interwoven into the review to visualize related delta work.

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“…Several studies pointed out that aquaculture has the potential to reduce poverty across the world [2][3][4]. Due to population growth, aquaculture as a controlled system of protein production is powerful in contributing to food security and covering future nutrition demands, which positively influences human well-being [5,6].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Patterns of Coastal Aquaculture Derived from Sentinel-1 Time Series Data and the Full Landsat Archive

2019

Self Cite

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Asia is the major contributor to global aquaculture production in quantity, accounting for almost 90%. These practices lead to extensive land-use and land-cover changes in coastal areas, and thus harm valuable and sensitive coastal ecosystems. Remote sensing and GIS technologies contribute to the mapping and monitoring of changes in aquaculture, providing essential information for coastal management applications. This study aims to investigate aquaculture expansion and spatio-temporal dynamics in two Chinese river deltas over three decades: the Yellow River Delta (YRD) and the Pearl River Delta (PRD). Long-term patterns of aquaculture change are extracted based on combining a reference layer on existing aquaculture ponds for 2015 derived from Sentinel-1 data with annual information on water bodies extracted from the long-term Landsat archive. Furthermore, the suitability of the proposed approach to be applied on a global scale is tested based on exploiting the Global Surface Water (GSW) dataset. We found enormous increases in aquaculture area for the investigated target deltas: an 18.6-fold increase for the YRD (1984–2016), and a 4.1-fold increase for the PRD (1990–2016). Furthermore, we detect hotspots of aquaculture expansion based on linear regression analyses for the deltas, indicating that hotspots are located in coastal regions for the YRD and along the Pearl River in the PRD. A comparison with high-resolution Google Earth data demonstrates that the proposed approach can detect spatio-temporal changes of aquaculture at an overall accuracy of 89%. The presented approach has the potential to be applied to larger spatial scales covering a time period of more than three decades. This is crucial to define appropriate management strategies to reduce the environmental impacts of aquaculture expansion, which are expected to increase in the future.

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Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data

Cited by 63 publications

References 63 publications

Monitoring and Mapping of Rice Cropping Pattern in Flooding Area in the Vietnamese Mekong Delta Using Sentinel-1A Data: A Case of An Giang Province

Monitoring and Mapping of Rice Cropping Pattern in Flooding Area in the Vietnamese Mekong Delta Using Sentinel-1A Data: A Case of An Giang Province

Remote Sensing for the Quantification of Land Surface Dynamics in Large River Delta Regions—A Review

Spatio-Temporal Patterns of Coastal Aquaculture Derived from Sentinel-1 Time Series Data and the Full Landsat Archive

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