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Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series

2015· article· en· 61 citations· W1537604559 on OpenAlex· 10.3390/rs70708516

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

About CanadaIts subject is Canada, wherever its authors sit.

No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.

The three-model screen

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All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Remote sensing of river delta inundation using MODIS time series; the object is hydrological monitoring.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

The study uses remote sensing to characterize river-delta inundation, not to study research itself.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Remote sensing of river delta inundation; earth observation domain application.

Abstract

River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta’s general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas—namely the Yellow River Delta (China), the Mekong Delta (Vietnam), the Irrawaddy Delta (Myanmar), and the Ganges-Brahmaputra (Bangladesh, India)—as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013). A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid-latitude, subtropical, and polar deltas are illustrated, and the advantages and limitations of the approach for inundation derivation are discussed.

Stored with the screening record, where it is evidence for the labels above.

The record

Venue
Remote Sensing
Topic
Flood Risk Assessment and Management
Field
Environmental Science
Canadian institutions
Funders
Keywords
DeltaRiver deltaWetlandUrbanizationEnvironmental scienceWater resourcesFluvialRemote sensingAlluvial plainClimate changeFlood mythHydrology (agriculture)Physical geographyGeologyGeographyStructural basinCartographyOceanographyGeomorphology
Has abstract in OpenAlex
yes