MONIMET Webcam Network, Database and Toolbox for Monitoring Phenology and Snow Cover

MONIMET Webcam Network creates scenarios of the impacts of climate change on land ecosystems, such as the snow cover stages on the boreal forests and peatlands.

The MONIMET Camera Network which consists of 28 cameras (26 operating) producing 30 image series from 14 different locations in Finland was established during EU Life MONIMET project during 2013-2017. The images collected were used to create scenarios of the impacts of climate change on land ecosystems, such as the snow cover stages on the boreal forests and peatlands.

The live images can be seen from http://monimet.fmi.fi/index.php?page=Camera_Network&style=warm

The project advocates open science and shares phenology camera images with other researchers in EU science data portal @ZENODO_ORG: https://www.zenodo.org/communities/phenology_camera/

Finnish Meteorological Institute image PROcessing Toolbox (http://monimet.fmi.fi?page=FMIPROT) is developed with following algorithms:

•        Green color fraction (Green chromatic coordinate)

•        Red color fraction (Red chromatic coordinate)

•        Blue color fraction (Blue chromatic coordinate)

•        Green-Red Vegetation Index

•        Green Excess Index

•        Fractional Snow Cover

Fractional snow cover (FSC) is an important parameter to estimate snow water equivalent (SWE) and surface albedo important to climatic and hydrological applications. The presence of forest creates challenges to retrieve FSC accurately from satellite data, as forest canopy can block the sensor's view of snow cover. In addition to the challenge related to presence of forest, in situ data of FSC—necessary for algorithm development and validation—are very limited.

FSC is calculated here using an algorithm based on defining a threshold value according to the histogram of an image, to classify a pixel as snow-covered or snow-free. Images from the MONIMET camera network, producing a continuous image series in Finland, are used in the analysis of FSC. The results obtained from automated image analysis of snow cover are compared with reference data estimated by visual inspection of same images. The results show the applicability and usefulness of digital imagery in the estimation of fractional snow cover in forested areas, with a Root Mean Squared Error (RMSE) in the range of 0.1–0.3 (with the full range of 0–1).

The MONIMET project was coordinated by the Finnish Meteorological Institute in collaboration with SYKE, LUKE and UHEL.

More information:

Senior Scientist, Dr. Ali Nadir Arslan, tel. +358 50 320 3386, ali.nadir.arslan@fmi.fi

Mikko Peltoniemi, Mika Aurela, Kristin Böttcher, Pasi Kolari, John Loehr, Tatu Hokkanen, Jouni Karhu, Maiju Linkosalmi, Cemal Melih Tanis, Sari Metsämäki, Juha-Pekka Tuovinen, Timo Vesala, Ali Nadir Arslan, Networked web-cameras monitor congruent seasonal development of birches with phenological field observations, Agricultural and Forest Meteorology, Available online 27 November 2017, ISSN 0168-1923, https://doi.org/10.1016/j.agrformet.2017.10.008. https://www.sciencedirect.com/science/article/pii/S0168192317303283

Arslan, A.N.; Tanis, C.M.; Metsämäki, S.; Aurela, M.; Böttcher, K.; Linkosalmi, M.; Peltoniemi, M. Automated Webcam Monitoring of Fractional Snow Cover in Northern Boreal Conditions. Geosciences 2017, 7, 55. http://www.mdpi.com/2076-3263/7/3/55

Peltoniemi, M., Aurela, M., Böttcher, K., Kolari, P., Loehr, J., Karhu, J., Linkosalmi, M., Tanis, C. M., Tuovinen, J.-P., and Arslan, A. N.: Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014–2016, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2017-62, in review, 2017. https://www.earth-syst-sci-data-discuss.net/essd-2017-62/