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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

1
Faculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810, Japan
2
United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS), Tokyo 150-8925, Japan
3
Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
4
Faculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810, Japan
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(5), 211; https://doi.org/10.3390/ijgi8050211
Received: 17 March 2019 / Revised: 24 April 2019 / Accepted: 4 May 2019 / Published: 7 May 2019
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Abstract

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. View Full-Text
Keywords: rice phenology; water infrastructure; rice cropping pattern mapping; SAR backscattering rice phenology; water infrastructure; rice cropping pattern mapping; SAR backscattering
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Minh, H.V.T.; Avtar, R.; Mohan, G.; Misra, P.; Kurasaki, M. 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. ISPRS Int. J. Geo-Inf. 2019, 8, 211.

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