Spatial and temporal variability in spectral-based surface energy evapotranspiration measured from Landsat 5TM across two mangrove ecotones

Lagomasino, David; Price, René M.; Whitman, Dean; Melesse, Assefa M.; Oberbauer, Steven F.

doi:10.1016/j.agrformet.2014.11.017

Cited by 23 publications

(6 citation statements)

References 67 publications

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“…Previous and planned mangrove forest inventories, particularly in Mozambique, Tanzania, and Gabon, will provide important advancements to incorporate cross-platform remote sensing as a decisive tool in the monitoring and verification of forest canopy height. In addition, the information on forest structure collected from similar mangrove studies can be incorporated into ecological function studies involving evapotranspiration [ 51 ], water quality [ 52 ], light-use-and water use-efficiency [ 53 ], carbon stock changes [ 54 ], and provide a new framework to refine regional carbon and water cycling.…”

Section: Discussionmentioning

confidence: 99%

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

et al. 2016

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Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

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Section: Discussionmentioning

confidence: 99%

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

et al. 2016

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“…Moreover, building a conceptual model prior to classification highlighted the data required to map mangrove degradation and thus any data gaps and limitations when no suitable data were available as input into the classification models. In the case studies here, no suitable data to represent evaporative stress were included in our classification models despite their potential importance in detecting mangrove degradation (Table 1) [46].…”

Section: Discussionmentioning

confidence: 99%

“…All three species occur near the mouth of Shark River, while the mangroves become progressively smaller and shorter upstream, with an increasing dominance of R. mangle, along with increasing presence of mangrove-associate Conocarpus erectus inland [45]. This ecosystem is considered relatively unaffected by direct anthropogenic impacts, but periodic disturbance by severe storms leads to extensive loss of foliage and structural damage [46,47]. We modelled the extent of degradation before (June 2016-May 2017) and after (November 2017-October 2018) a tropical cyclone (Hurricane Irma), which caused severe short-term degradation to the ecosystem [48,49].…”

Section: Study Regions and Ecosystem Descriptionmentioning

confidence: 99%

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

et al. 2021

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Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain biodiversity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km2) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global biodiversity targets.

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“…Freshwater flowing into coastal waters is used by mangroves and returned to that atmosphere through evapotranspiration (MacKenzie and Kryss, 2013), which in turn contributes to precipitation upwind and inland, providing water to landscapes, including forests and streams. While studies on evapotranspiration are generally lacking from mangrove forests, Lagomasino et al (2015) has suggested that mangrove evapotranspiration rates could produce an equivalent amount of water as annual rainfall in certain years, although this likely varies across forest structure, tidal regimes and salinities (Barr, DeLong and Fuentes, 2014;Krauss et al, 2015). Studies combining remote sensing and field measurements are needed to fully understand the spatial variability in mangrove evapotranspiration as well as their contributions to the regional water balance.…”

Section: Mangrove Research Needs and Knowledge Gapsmentioning

confidence: 99%

A guide to forest–water management

Boscolo¹,

Leonardi²,

Masiero³

et al. 2021

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The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) or the International Union of Forest Research Organizations (IUFRO) or U.S. Department of Agriculture (USDA) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO or IUFRO or USDA in preference to others of a similar nature that are not mentioned.The views expressed in this information product are those of the author(s) and do not necessarily reflect the views or policies of FAO or IUFRO or USDA.

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Spatial and temporal variability in spectral-based surface energy evapotranspiration measured from Landsat 5TM across two mangrove ecotones

Abstract: openAccessArticle: Falsecover date: 2015-11-01pii: S0168-1923(14)00296-2Harvest Date: 2016-01-06 13:08:19issueName:Page Range: 304-304href scidir: http://www.sciencedirect.com/science/article/pii/S0168192314002962pubType

Cited by 23 publications

References 67 publications

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

A guide to forest–water management

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