Global cloud cover for assessment of optical satellite observation opportunities: A HyspIRI case study

Mercury, Michael; Green, R.; Hook, Simon J.; Oaida, Bogdan; Wu, Wenbin; Gunderson, Adam; Chodas, M.

doi:10.1016/j.rse.2012.08.007

Cited by 53 publications

(33 citation statements)

References 10 publications

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“…As expected, it decreases around the equator because of large occurrence of clouds, as well as for the higher latitudes for GEOV1 and MGVIo due to short day length and poor illumination conditions in addition to the cloud occurrence. This is not observed for MODIS because of the exploitation of the replication of views for the higher latitudes that are fully exploited, in agreement with the results reported by [65]. , during the periods defined in Table 2, and for the original temporal sampling.…”

Section: Continuity Assessmentsupporting

confidence: 89%

On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

et al. 2014

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The OLIVE (On Line Interactive Validation Exercise) platform is dedicated to the validation of global biophysical products such as LAI (Leaf Area Index) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation). It was developed under the framework of the CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. OLIVE has three main objectives: (i) to provide a consistent and centralized information on the definition of the biophysical variables, as well as a description of the main available products and their performances (ii) to provide transparency and traceability by an online validation procedure compliant with the CEOS LPV and QA4EO (Quality Assurance for Earth Observation) recommendations (iii) and finally, to provide a tool to benchmark new products, update product validation results and host new ground measurement sites for accuracy assessment. The functionalities and algorithms of OLIVE are described to provide full transparency of its procedures to the community. The validation process and typical results are illustrated for three FAPAR products: GEOV1 (VEGETATION sensor), MGVIo (MERIS sensor) and MODIS collection 5 FPAR. OLIVE is available on the European Space Agency CAL/VAL portal), including full documentation, validation exercise results, and product extracts.

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Section: Continuity Assessmentsupporting

confidence: 89%

On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

et al. 2014

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“…High temporal resolution also increases the chance of observing targets often obscured by clouds (Mercury et al. ).…”

Section: Requirements For Observing Coastal Biodiversity and Ecosystementioning

confidence: 99%

“…While the biodiversity of some structured communities like coral reefs, sea grass meadows, or mangrove forests may be expected to change more slowly, disturbance due to pollution events, severe storms, or cold or warm temperature extremes can lead to rapid changes in organism distribution, traits (e.g., bleaching), or habitat structure. High temporal resolution also increases the chance of observing targets often obscured by clouds (Mercury et al 2012).…”

Section: High Temporal Resolutionmentioning

confidence: 99%

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

Muller‐Karger

Hestir

Ade

et al. 2018

Ecological Applications

124

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The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

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“…We assessed the potential of HyspIRI to provide cloud-free coverage of global giant kelp habitat by using a Terra MODIS 5 km daytime cloud mask dataset to determine the percent of MODIS views that were cloud free between 2001 and 2010 (data provided by Mercury et al, 2012). Giant kelp habitat was identified using the global distribution map provided in Fig.…”

Section: Expected Cloud-free Hyspiri Coverage Of Global Giant Kelp Hamentioning

confidence: 99%

“…Assuming a 19-day revisit time for the HyspIRI VSWIR sensor, the total number of views during a season will be 4.789 (91 days in a season divided by the 19 day revisit time). The actual revisit time for a given location varies by latitude and will impact the true probability of cloud-free coverage (Mercury et al, 2012). To evaluate the potential of Landsat 8 (or a sensor with similar orbital characteristics) to complement HyspIRI's kelp monitoring, we also calculated the expected number of cloud-free views each season from Landsat 8 (16-day revisit time).…”

Section: Expected Cloud-free Hyspiri Coverage Of Global Giant Kelp Hamentioning

confidence: 99%

Remote monitoring of giant kelp biomass and physiological condition: An evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) mission

Bell

Cavanaugh

Siegel

2015

Remote Sensing of Environment

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Global cloud cover for assessment of optical satellite observation opportunities: A HyspIRI case study

Cited by 53 publications

References 10 publications

On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

Remote monitoring of giant kelp biomass and physiological condition: An evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) mission

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