An optical reflectance model-based method for fractional snow cover mapping applicable to continental scale

Metsämäki, Sari; Mattila, Olli-Pekka; Pulliainen, Jouni; Niemi, Kirsikka; Luojus, Kari; Böttcher, Kristin

doi:10.1016/j.rse.2012.04.010

Cited by 77 publications

(52 citation statements)

References 24 publications

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“…The accuracy exceeded 80% with R 2 values of 0.85 (year 2000) and 0.95 (year 2001). Such a validation technique has the drawback of underestimating at low FSC and overestimating at higher FSC [208].…”

Section: Snow Cover Fractionmentioning

confidence: 99%

“…The accuracy (MAE) of the SCAmod method ranges from 5% to 12% [212]. For a larger scale, Metsämäki et al [208] presented the application of SCAmod over northern and eastern Europe using MODIS-Terra and ENVISAT-AATSR data. Together with the MOD10_L2 fraction snow product, the authors further validated the SCAmod results against in-situ data.…”

Section: Snow Cover Fractionmentioning

confidence: 99%

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The Potential of Earth Observation for the Analysis of Cold Region Land Surface Dynamics in Europe—A Review

Kuenzer

Dietz

et al. 2017

Remote Sensing

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Abstract:Cold regions affect global, regional and local climate; oftentimes they are relevant for water supply, host valuable ecosystems, and support human livelihood. They are thus eminently important for human society. In the context of ongoing climate change, monitoring and understanding cold region land surface dynamics is essential for environmental scientists, stakeholders and decision makers. However, the definition of cold regions remains inexplicit, and no up-to-date cold region maps or overarching spatial analyses exist. For example, Europe has densely populated cold regions, but hardly an article exists that provides a solid overview of Earth Observation (EO) based applications assessing cold region land surface dynamics in Europe. With this review article we aim at closing this gap by providing an overview of EO-based techniques for cold region observation in Europe, focusing on the dynamics of glaciers and snow. We present a novel spatial delineation of cold regions for Europe before analyzing the benefits and limitations of different EO sensor types and data processing methods for EO based cold region research. Furthermore, we identify research gaps and discuss challenges for future studies.

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Section: Snow Cover Fractionmentioning

confidence: 99%

Section: Snow Cover Fractionmentioning

confidence: 99%

The Potential of Earth Observation for the Analysis of Cold Region Land Surface Dynamics in Europe—A Review

Kuenzer

Dietz

et al. 2017

Remote Sensing

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“…For the detection of ENF_SOS sat , we calculated the FSC based on the SCAmod algorithm by Metsämäki et al [65,66] at the same spatial resolution as the NDWI. Clouds in daily FSC and NDWI products were masked based on an automatic cloud masking algorithm developed at the Finnish Environment Institute.…”

Section: Remote Sensing Datamentioning

confidence: 99%

Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations

et al. 2016

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Abstract:The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle-and deciduous broad-leaf, was obtained for the period 2003-2011 from regional JSBACH (Jena Scheme for Biosphere-Atmosphere Hamburg) runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS) time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP) determined from CO 2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.

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“…Recently, a long-term data set of snow extent (SE) for the years 1995-2012 has been developed within the ESA GlobSnow project, which relies on a method by Metsämäki et al (2012). The ESA GlobProjects form a series of precursor projects for ESA CCI.…”

Section: Snow Covermentioning

confidence: 99%

Satellite-based climate information within the WMO RA VI Regional Climate Centre on Climate Monitoring

Obregón¹,

Nitsche

Körber

et al. 2014

Adv. Sci. Res.

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Abstract. The World Meteorological Organization (WMO) established Regional Climate Centres (RCCs) around the world to create science-based climate information on a regional scale within the Global Framework for Climate Services (GFCS). The paper introduces the satellite component of the WMO Regional Climate Centre on Climate Monitoring (RCC-CM) for Europe and the Middle East. The RCC-CM product portfolio is based on essential climate variables (ECVs) as defined by the Global Climate Observing System (GCOS), spanning the atmospheric (radiation, clouds, water vapour) and terrestrial domains (snow cover, soil moisture). In the first part, the input data sets are briefly described, which are provided by the EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) Satellite Application Facilities (SAF), in particular CM SAF, and by the ESA (European Space Agency) Climate Change Initiative (CCI). In the second part, the derived RCC-CM products are presented, which are divided into two groups: (i) operational monitoring products (e.g. monthly means and anomalies) based on near-real-time environmental data records (EDRs) and (ii) climate information records (e.g. climatologies, time series, trend maps) based on long-term thematic climate data records (TCDRs) with adequate stability, accuracy and homogeneity. The products are provided as maps, statistical plots and gridded data, which are made available through the RCC-CM website (www.dwd.de/rcc-cm).

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An optical reflectance model-based method for fractional snow cover mapping applicable to continental scale

Cited by 77 publications

References 24 publications

The Potential of Earth Observation for the Analysis of Cold Region Land Surface Dynamics in Europe—A Review

The Potential of Earth Observation for the Analysis of Cold Region Land Surface Dynamics in Europe—A Review

Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations

Satellite-based climate information within the WMO RA VI Regional Climate Centre on Climate Monitoring

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