Super-resolution mapping of lakes from imagery with a coarse spatial and fine temporal resolution

Muad, Anuar Mikdad; Foody, Giles M.

doi:10.1016/j.jag.2011.06.002

Cited by 52 publications

(27 citation statements)

References 45 publications

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“…Super-resolution techniques have been proposed to improve mapping by increasing the spatial resolution of satellite images, while preserving their spectral properties, e.g. in representation of lakes using data time series, halftoning, and morphological filtering (Muad and Foody 2012). Approaches based on discrete wavelet transform for hyperspectral images (Patel and Joshi 2015) and structural self-similarity, identifying similar structures in RS images (Pan et al 2013), have been recently proposed.…”

Section: Aquatic Mappingmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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Recognizing the imperative need for biodiversity protection, the Convention on Biological Diversity (CBD) has recently established new targets towards 2020, the so-called Aichi targets, and updated proposed sets of indicators to quantitatively monitor the progress towards these targets. Remote sensing has been increasingly contributing to timely, accurate, and cost-effective assessment of biodiversity-related characteristics and functions during the last years. However, most relevant studies constitute individual research efforts, rarely related with the extraction of widely adopted CBD biodiversity indicators. Furthermore, systematic operational use of remote sensing data by managing authorities has still been limited. In this study, the Aichi targets and the related CBD indicators whose monitoring can be facilitated by remote sensing are identified. For each headline indicator a number of recent remote sensing approaches able for the extraction of related properties are reviewed. Methods cover a wide range of fields, including: habitat extent and condition monitoring; species distribution; pressures from unsustainable management, pollution and climate change; ecosystem service monitoring; and conservation status assessment of protected areas. The advantages and limitations of different remote sensing data and algorithms are discussed. Sorting of the methods based on their reported accuracies is attempted, when possible. The extensive literature survey aims at reviewing highly performing methods that can be used for large-area, effective, and timely biodiversity assessment, to encourage the more systematic use of remote sensing solutions in monitoring progress towards the Aichi targets, and to decrease the gaps between the remote sensing and management communities.

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Section: Aquatic Mappingmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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“…SRM may be incorporated into this emissivity estimation method to enhance the spatial resolution of a land cover and so ultimately an emissivity map. Using soft classification as an input (Foody, 1996), SRM exploits the class composition information of each pixel to map land cover at a fine (sub-pixel) resolution often through some form of iterative spatial analysis (Muad & Foody, 2012;Tatem, Lewis, Atkinson, & Nixon, 2001b). The final product is a fine spatial resolution land cover map which allows the characterisation of emissivity at this fine resolution.…”

Section: Enhancing the Spatial Resolution Of Emissivity Mapsmentioning

confidence: 99%

Enhancing the spatial resolution of satellite-derived land surface temperature mapping for urban areas

Feng

Foody

Aplin

et al. 2015

Sustainable Cities and Society

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(2015) Enhancing the spatial resolution of satellite-derived land surface temperature mapping for urban areas. Sustainable Cities and Society, 19 . pp. 341-348. ISSN 2210-6707 Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/31519/1/Published_text.pdf Copyright and reuse:The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions. This article is made available under the Creative Commons Attribution Non-commercial No Derivatives licence and may be reused according to the conditions of the licence. For more details see: http://creativecommons.org/licenses/by-nc-nd/2.5/ A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.

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“…Therefore, it is obvious that this kind of method is applicable for mapping lake shorelines at subpixel scale. Several studies have implemented different subpixel mapping methods to derive finer-resolution shorelines or lake areas [42][43][44][45][46][47].…”

Section: Introductionmentioning

confidence: 99%

Spatial Downscaling of Suomi NPP–VIIRS Image for Lake Mapping

Huang

Chen

Zhang

et al. 2017

Water

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Abstract:Capturing the dynamics of a lake-water area using remotely sensed images has always been an essential task. Most of the fine spatial resolution data are unsuitable for this purpose because of their low temporal resolution and limited scene coverage. A Visible Infrared Imaging Radiometer Suite on board the Suomi National Polar-orbiting Partnership (Suomi NPP-VIIRS) is a newly-available and appropriate sensor for monitoring large lakes due to its frequent revisits and wide swath (more than 3000 km). However, it provides visible and infrared images at relatively coarse spatial resolutions, which would sometimes hamper the accurate mapping of lake shorelines. This study, therefore, proposes a two-step downscaling method that combines spectral unmixing and subpixel mapping to produce a finer resolution lake map from NPP-VIIRS imagery, which is then applied to delineate the shorelines of five plateau lakes in Yunnan Province, as well as the shoreline dynamics of Poyang Lake at three separate times. A newly published global water dynamic dataset is employed in this study to improve the downscaling method. Results suggest that the proposed method can generate a finer resolution lake map that exhibits more details of the shoreline than hard classification. The downscaling results of the Suomi NPP-VIIRS generally achieve higher than 75% accuracy, while the downscaling results of a Landsat-simulated fraction map could have accuracy higher than 85%. This reveals that errors and uncertainties exist in both procedures, but mainly come from the spectral unmixing procedure which retrieves water fractions from NPP-VIIRS data.

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Super-resolution mapping of lakes from imagery with a coarse spatial and fine temporal resolution

Cited by 52 publications

References 45 publications

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Enhancing the spatial resolution of satellite-derived land surface temperature mapping for urban areas

Spatial Downscaling of Suomi NPP–VIIRS Image for Lake Mapping

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