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Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset

Natural wetlands are intrinsically heterogeneous and typically composed of a mosaic of ecosystem patches with different vegetation types. Hydrological and biogeochemical processes in wetlands vary strongly among these ecosystem patches. To date, most remote sensing classification approaches for wetl...

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Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-04, Vol.14 (9), p.2107
Main Authors: Ju, Yang, Bohrer, Gil
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description Natural wetlands are intrinsically heterogeneous and typically composed of a mosaic of ecosystem patches with different vegetation types. Hydrological and biogeochemical processes in wetlands vary strongly among these ecosystem patches. To date, most remote sensing classification approaches for wetland vegetation either rely on coarse images that cannot capture the spatial variability of wetland vegetation or rely on very-high-resolution multi-spectral images that are detailed but very sporadic in time (less than once per year). This study aimed to use NDVI time series, generated from NASA’s HLS dataset, to classify vegetation patches. We demonstrate our approach at a temperate, coastal lake, estuarine marsh. To classify vegetation patches, a standard time series library of the four land-cover patch types was built from referencing specific locations that were identified as “pure” pixels. These were identified using a single-time high-resolution image. We calculated the distance between the HLS-NDVI time series at each pixel and the “pure”-pixel standards for each land-cover type. The resulting true-positive classified rate was >73% for all patch types other than water lily. The classification accuracy was higher in pixels of a more uniform composition. A set of vegetation maps was created for the years 2016 to 2020 at our research site to identify the vegetation changes at the site as it is affected by rapid water elevation increases in Lake Erie. Our results reveal how changes in water elevation have changed the patch distribution in significant ways, leading to the local extinction of cattail by 2019 and a continuous increase in the area cover of water lily patches.
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subjects Aquatic plants
Carbon sequestration
Classification
Datasets
Estuaries
Floating plants
Flow velocity
Greenhouse gases
High resolution
HLS data
Hydrology
Image classification
Image resolution
Lake Erie
Lakes
Land cover
Landsat satellites
NDVI
Nitrogen
Nymphaea
Patches (structures)
Pixels
Remote sensing
Species extinction
Time series
Vegetation
Vegetation changes
vegetation classification
Vegetation mapping
Water quality
Watersheds
Wetlands
title Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset
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