Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data

Nguyen, Dung Van; Clauss, Kersten; Cao, Senmao; Naeimi, Vahid; Kuenzer, Claudia; Wagner, Wolfgang

doi:10.3390/rs71215808

Cited by 86 publications

(78 citation statements)

References 70 publications

(108 reference statements)

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“…The utility of C band SAR for wetlands monitoring is largely conditioned by the shorter (5.6 cm) wavelength, which does not allow for uniform detection of standing water in densely vegetated or forested wetlands. Nevertheless, ERS, Envisat, and RADARSAT data have been used to monitor lower vegetation in artificial wetlands, such as irrigated rice [Le Toan et al, 1997;Nguyen et al, 2009Nguyen et al, , 2015Kumar et al, 2016] and to map lake types in the Brazilian Pantanal [Costa and Telmer, 2006]. Also, C band altimeters have proven to be useful for measuring changes in water levels in lakes, (large) rivers, and wetlands [Birkett, 1998].…”

Section: Current Methods For Wetland Mappingmentioning

confidence: 99%

Wetland monitoring with Global Navigation Satellite System reflectometry

Nghiem

Zuffada

Shah

et al. 2017

Earth and Space Science

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Information about wetland dynamics remains a major missing gap in characterizing, understanding, and projecting changes in atmospheric methane and terrestrial water storage. A review of current satellite methods to delineate and monitor wetland change shows some recent advances, but much improved sensing technologies are still needed for wetland mapping, not only to provide more accurate global inventories but also to examine changes spanning multiple decades. Global Navigation Satellite Systems Reflectometry (GNSS‐R) signatures from aircraft over the Ebro River Delta in Spain and satellite measurements over the Mississippi River and adjacent watersheds demonstrate that inundated wetlands can be identified under different vegetation conditions including a dense rice canopy and a thick forest with tall trees, where optical sensors and monostatic radars provide limited capabilities. Advantages as well as constraints of GNSS‐R are presented, and the synergy with various satellite observations are considered to achieve a breakthrough capability for multidecadal wetland dynamics monitoring with frequent global coverage at multiple spatial and temporal scales.

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Section: Current Methods For Wetland Mappingmentioning

confidence: 99%

Wetland monitoring with Global Navigation Satellite System reflectometry

Nghiem

Zuffada

Shah

et al. 2017

Earth and Space Science

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“…Some researchers have successfully used SAR data for rice mapping using time series [12,13]. Their success relies on the detection of the changes in plant morphology that take place during the three growing phases of rice per harvest, as opposed to the less frequent changes in other crops and other non-agricultural wetlands and grasslands [12].…”

Section: Introductionmentioning

confidence: 99%

Short-Term Change Detection in Wetlands Using Sentinel-1 Time Series

et al. 2016

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Automated monitoring systems that can capture wetlands' high spatial and temporal variability are essential for their management. SAR-based change detection approaches offer a great opportunity to enhance our understanding of complex and dynamic ecosystems. We test a recently-developed time series change detection approach (S1-omnibus) using Sentinel-1 imagery of two wetlands with different ecological characteristics; a seasonal isolated wetland in southern Spain and a coastal wetland in the south of France. We test the S1-omnibus method against a commonly-used pairwise comparison of consecutive images to demonstrate its advantages. Additionally, we compare it with a pairwise change detection method using a subset of consecutive Landsat images for the same period of time. The results show how S1-omnibus is capable of capturing in space and time changes produced by water surface dynamics, as well as by agricultural practices, whether they are sudden changes, as well as gradual. S1-omnibus is capable of detecting a wider array of short-term changes than when using consecutive pairs of Sentinel-1 images. When compared to the Landsat-based change detection method, both show an overall good agreement, although certain landscape changes are detected only by either the Landsat-based or the S1-omnibus method. The S1-omnibus method shows a great potential for an automated monitoring of short time changes and accurate delineation of areas of high variability and of slow and gradual changes.

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“…Gumma et al, (2014 also used MODIS NDVI data to map the rice crop extent and area for the year 2010, finding slightly higher rice area estimates (3-6%) than sub-national statistics. Similar studies have been carried out in other rice dominated areas such as the Mekong delta (Nguyen et al, 2015;Son et al, 2014). Whilst the production of irrigated rice can be assessed with NDVI, the response to variation in rainfall may be different than that of nonirrigated rice due to the potentially different timings of water availability.…”

Section: Normalised Difference Vegetation Indexmentioning

confidence: 89%

Food and nutrition security trends and challenges in the Ganges Brahmaputra Meghna (GBM) delta

Soesbergen

Nilsen

Burgess

et al. 2017

Elementa: Science of the Anthropocene

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The population of the Ganges Brahmaputra Meghna (GBM) delta is highly vulnerable to food insecurity and malnutrition due to the specific environmental, climatic and human development factors affecting agricultural production and fisheries. To better understand the impacts of climate and environmental change on food security and nutrition in this delta, this study combines spatially explicit data from the 2007 and 2011 Bangladesh Demographic and Health Survey (BDHS) with a standard satellite remotely sensed vegetation greenness index (Normalised Difference Vegetation Index, NDVI), used as a proxy for rice production. The strength of association between NDVI and child nutrition in this tropical mega-delta were tested, showing correlations between two widely used indicators of child malnutrition; stunting and wasting, and deviations from a 10 year mean NDVI (anomalies) for rice crop growing seasons – regarded as critical to individual children’s early lives. For children surveyed in 2007 we found that the likelihood of being stunted decreased with increased NDVI as a measure of food production. Similarly, for children surveyed in 2011, the likelihood of being wasted reduced with increased NDVI. However, regression results for stunting in 2011 and wasting in 2007 were not statistically significant. Our findings suggest that NDVI can be regarded as indicative of climatic variability and periods of low food production but is only partly successful as an indicator of climate related impacts on child nutrition in the GBM delta. Furthermore, our study highlights some of the uncertainties and challenges with linking environmental indicators such as the NDVI with household survey data across spatial and temporal scales.

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Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data

Cited by 86 publications

References 70 publications

Wetland monitoring with Global Navigation Satellite System reflectometry

Wetland monitoring with Global Navigation Satellite System reflectometry

Short-Term Change Detection in Wetlands Using Sentinel-1 Time Series

Food and nutrition security trends and challenges in the Ganges Brahmaputra Meghna (GBM) delta

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