Special Issue on Remote Sensing of Snow and Its Applications
Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water, and carbon cycles. Remote sensing provides a good understanding of snow cover an...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-06-01
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| Series: | Geosciences |
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| Online Access: | https://www.mdpi.com/2076-3263/9/6/277 |
| _version_ | 1818541303573512192 |
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| author | Ali Nadir Arslan Zuhal Akyürek |
| author_facet | Ali Nadir Arslan Zuhal Akyürek |
| author_sort | Ali Nadir Arslan |
| collection | DOAJ |
| description | Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water, and carbon cycles. Remote sensing provides a good understanding of snow cover and enable snow cover information to be assimilated into hydrological, land surface, meteorological, and climate models for predicting snowmelt runoff, snow water resources, and to warn about snow-related natural hazards. The main objectives of this Special Issue, “Remote Sensing of Snow and Its Applications” in Geosciences are to present a wide range of topics such as (1) remote sensing techniques and methods for snow, (2) modeling, retrieval algorithms, and in-situ measurements of snow parameters, (3) multi-source and multi-sensor remote sensing of snow, (4) remote sensing and model integrated approaches of snow, and (5) applications where remotely sensed snow information is used for weather forecasting, flooding, avalanche, water management, traffic, health and sport, agriculture and forestry, climate scenarios, etc. It is very important to understand (a) differences and similarities, (b) representativeness and applicability, (c) accuracy and sources of error in measuring of snow both in-situ and remote sensing and assimilating snow into hydrological, land surface, meteorological, and climate models. This Special Issue contains nine articles and covers some of the topics we listed above. |
| first_indexed | 2024-12-11T22:07:31Z |
| format | Article |
| id | doaj.art-62c0be1e1f36477e8e310154789e7f9d |
| institution | Directory Open Access Journal |
| issn | 2076-3263 |
| language | English |
| last_indexed | 2024-12-11T22:07:31Z |
| publishDate | 2019-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Geosciences |
| spelling | doaj.art-62c0be1e1f36477e8e310154789e7f9d2022-12-22T00:48:54ZengMDPI AGGeosciences2076-32632019-06-019627710.3390/geosciences9060277geosciences9060277Special Issue on Remote Sensing of Snow and Its ApplicationsAli Nadir Arslan0Zuhal Akyürek1Finnish Meteorological Institute (FMI), Erik Palménin aukio 1, FI-00560 Helsinki, FinlandDepartment of Civil Engineering, Middle East Technical University, 06800 Ankara, TurkeySnow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water, and carbon cycles. Remote sensing provides a good understanding of snow cover and enable snow cover information to be assimilated into hydrological, land surface, meteorological, and climate models for predicting snowmelt runoff, snow water resources, and to warn about snow-related natural hazards. The main objectives of this Special Issue, “Remote Sensing of Snow and Its Applications” in Geosciences are to present a wide range of topics such as (1) remote sensing techniques and methods for snow, (2) modeling, retrieval algorithms, and in-situ measurements of snow parameters, (3) multi-source and multi-sensor remote sensing of snow, (4) remote sensing and model integrated approaches of snow, and (5) applications where remotely sensed snow information is used for weather forecasting, flooding, avalanche, water management, traffic, health and sport, agriculture and forestry, climate scenarios, etc. It is very important to understand (a) differences and similarities, (b) representativeness and applicability, (c) accuracy and sources of error in measuring of snow both in-situ and remote sensing and assimilating snow into hydrological, land surface, meteorological, and climate models. This Special Issue contains nine articles and covers some of the topics we listed above.https://www.mdpi.com/2076-3263/9/6/277remote sensingsnow parametersspatial and temporal variability of snowsnow hydrologyintegration of remote sensing with models (hydrologicalland surfacemeteorological and climate) |
| spellingShingle | Ali Nadir Arslan Zuhal Akyürek Special Issue on Remote Sensing of Snow and Its Applications Geosciences remote sensing snow parameters spatial and temporal variability of snow snow hydrology integration of remote sensing with models (hydrological land surface meteorological and climate) |
| title | Special Issue on Remote Sensing of Snow and Its Applications |
| title_full | Special Issue on Remote Sensing of Snow and Its Applications |
| title_fullStr | Special Issue on Remote Sensing of Snow and Its Applications |
| title_full_unstemmed | Special Issue on Remote Sensing of Snow and Its Applications |
| title_short | Special Issue on Remote Sensing of Snow and Its Applications |
| title_sort | special issue on remote sensing of snow and its applications |
| topic | remote sensing snow parameters spatial and temporal variability of snow snow hydrology integration of remote sensing with models (hydrological land surface meteorological and climate) |
| url | https://www.mdpi.com/2076-3263/9/6/277 |
| work_keys_str_mv | AT alinadirarslan specialissueonremotesensingofsnowanditsapplications AT zuhalakyurek specialissueonremotesensingofsnowanditsapplications |