Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China

The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Qin Ju [verfasserIn] Rongrong Zhang [verfasserIn] Guoqing Wang [verfasserIn] Wenlong Hao [verfasserIn] Qin Wang [verfasserIn] Yanli Liu [verfasserIn] Wei Wang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions

Übergeordnetes Werk:	In: Frontiers in Environmental Science - Frontiers Media S.A., 2014, 10(2022)
Übergeordnetes Werk:	volume:10 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fenvs.2022.996701

Katalog-ID:	DOAJ023532955

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ023532955
003	DE-627
005	20230307064943.0
007	cr uuu---uuuuu
008	230226s2022 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.3389/fenvs.2022.996701 \|2 doi
035			\|a (DE-627)DOAJ023532955
035			\|a (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a GE1-350
100	0		\|a Qin Ju \|e verfasserin \|4 aut
245	1	0	\|a Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China
264		1	\|c 2022
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes.
650		4	\|a frozen soil
650		4	\|a soil freezing-thawing processes
650		4	\|a soil temperature
650		4	\|a active soil depth
650		4	\|a cold regions
653		0	\|a Environmental sciences
700	0		\|a Rongrong Zhang \|e verfasserin \|4 aut
700	0		\|a Guoqing Wang \|e verfasserin \|4 aut
700	0		\|a Wenlong Hao \|e verfasserin \|4 aut
700	0		\|a Wenlong Hao \|e verfasserin \|4 aut
700	0		\|a Qin Wang \|e verfasserin \|4 aut
700	0		\|a Yanli Liu \|e verfasserin \|4 aut
700	0		\|a Wei Wang \|e verfasserin \|4 aut
773	0	8	\|i In \|t Frontiers in Environmental Science \|d Frontiers Media S.A., 2014 \|g 10(2022) \|w (DE-627)771401604 \|w (DE-600)2741535-1 \|x 2296665X \|7 nnns
773	1	8	\|g volume:10 \|g year:2022
856	4	0	\|u https://doi.org/10.3389/fenvs.2022.996701 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 \|z kostenfrei
856	4	0	\|u https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2296-665X \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_11
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_95
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 10 \|j 2022

Indexfelder

author_variant	q j qj r z rz g w gw w h wh w h wh q w qw y l yl w w ww
matchkey_str	article:2296665X:2022----::iuaighfezntaigrcsebsdnoidtitehe
hierarchy_sort_str	2022
callnumber-subject-code	GE
publishDate	2022
allfields	10.3389/fenvs.2022.996701 doi (DE-627)DOAJ023532955 (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56 DE-627 ger DE-627 rakwb eng GE1-350 Qin Ju verfasserin aut Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes. frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions Environmental sciences Rongrong Zhang verfasserin aut Guoqing Wang verfasserin aut Wenlong Hao verfasserin aut Wenlong Hao verfasserin aut Qin Wang verfasserin aut Yanli Liu verfasserin aut Wei Wang verfasserin aut In Frontiers in Environmental Science Frontiers Media S.A., 2014 10(2022) (DE-627)771401604 (DE-600)2741535-1 2296665X nnns volume:10 year:2022 https://doi.org/10.3389/fenvs.2022.996701 kostenfrei https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 kostenfrei https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full kostenfrei https://doaj.org/toc/2296-665X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
spelling	10.3389/fenvs.2022.996701 doi (DE-627)DOAJ023532955 (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56 DE-627 ger DE-627 rakwb eng GE1-350 Qin Ju verfasserin aut Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes. frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions Environmental sciences Rongrong Zhang verfasserin aut Guoqing Wang verfasserin aut Wenlong Hao verfasserin aut Wenlong Hao verfasserin aut Qin Wang verfasserin aut Yanli Liu verfasserin aut Wei Wang verfasserin aut In Frontiers in Environmental Science Frontiers Media S.A., 2014 10(2022) (DE-627)771401604 (DE-600)2741535-1 2296665X nnns volume:10 year:2022 https://doi.org/10.3389/fenvs.2022.996701 kostenfrei https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 kostenfrei https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full kostenfrei https://doaj.org/toc/2296-665X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
allfields_unstemmed	10.3389/fenvs.2022.996701 doi (DE-627)DOAJ023532955 (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56 DE-627 ger DE-627 rakwb eng GE1-350 Qin Ju verfasserin aut Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes. frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions Environmental sciences Rongrong Zhang verfasserin aut Guoqing Wang verfasserin aut Wenlong Hao verfasserin aut Wenlong Hao verfasserin aut Qin Wang verfasserin aut Yanli Liu verfasserin aut Wei Wang verfasserin aut In Frontiers in Environmental Science Frontiers Media S.A., 2014 10(2022) (DE-627)771401604 (DE-600)2741535-1 2296665X nnns volume:10 year:2022 https://doi.org/10.3389/fenvs.2022.996701 kostenfrei https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 kostenfrei https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full kostenfrei https://doaj.org/toc/2296-665X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
allfieldsGer	10.3389/fenvs.2022.996701 doi (DE-627)DOAJ023532955 (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56 DE-627 ger DE-627 rakwb eng GE1-350 Qin Ju verfasserin aut Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes. frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions Environmental sciences Rongrong Zhang verfasserin aut Guoqing Wang verfasserin aut Wenlong Hao verfasserin aut Wenlong Hao verfasserin aut Qin Wang verfasserin aut Yanli Liu verfasserin aut Wei Wang verfasserin aut In Frontiers in Environmental Science Frontiers Media S.A., 2014 10(2022) (DE-627)771401604 (DE-600)2741535-1 2296665X nnns volume:10 year:2022 https://doi.org/10.3389/fenvs.2022.996701 kostenfrei https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 kostenfrei https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full kostenfrei https://doaj.org/toc/2296-665X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
allfieldsSound	10.3389/fenvs.2022.996701 doi (DE-627)DOAJ023532955 (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56 DE-627 ger DE-627 rakwb eng GE1-350 Qin Ju verfasserin aut Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes. frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions Environmental sciences Rongrong Zhang verfasserin aut Guoqing Wang verfasserin aut Wenlong Hao verfasserin aut Wenlong Hao verfasserin aut Qin Wang verfasserin aut Yanli Liu verfasserin aut Wei Wang verfasserin aut In Frontiers in Environmental Science Frontiers Media S.A., 2014 10(2022) (DE-627)771401604 (DE-600)2741535-1 2296665X nnns volume:10 year:2022 https://doi.org/10.3389/fenvs.2022.996701 kostenfrei https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 kostenfrei https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full kostenfrei https://doaj.org/toc/2296-665X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
language	English
source	In Frontiers in Environmental Science 10(2022) volume:10 year:2022
sourceStr	In Frontiers in Environmental Science 10(2022) volume:10 year:2022
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions Environmental sciences
isfreeaccess_bool	true
container_title	Frontiers in Environmental Science
authorswithroles_txt_mv	Qin Ju @@aut@@ Rongrong Zhang @@aut@@ Guoqing Wang @@aut@@ Wenlong Hao @@aut@@ Qin Wang @@aut@@ Yanli Liu @@aut@@ Wei Wang @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	771401604
id	DOAJ023532955
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ023532955</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230307064943.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3389/fenvs.2022.996701</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ023532955</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">GE1-350</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Qin Ju</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">frozen soil</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">soil freezing-thawing processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">soil temperature</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">active soil depth</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">cold regions</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Environmental sciences</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rongrong Zhang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Guoqing Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wenlong Hao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wenlong Hao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qin Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yanli Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wei Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Frontiers in Environmental Science</subfield><subfield code="d">Frontiers Media S.A., 2014</subfield><subfield code="g">10(2022)</subfield><subfield code="w">(DE-627)771401604</subfield><subfield code="w">(DE-600)2741535-1</subfield><subfield code="x">2296665X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:10</subfield><subfield code="g">year:2022</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3389/fenvs.2022.996701</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2296-665X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">10</subfield><subfield code="j">2022</subfield></datafield></record></collection>
callnumber-first	G - Geography, Anthropology, Recreation
author	Qin Ju
spellingShingle	Qin Ju misc GE1-350 misc frozen soil misc soil freezing-thawing processes misc soil temperature misc active soil depth misc cold regions misc Environmental sciences Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China
authorStr	Qin Ju
ppnlink_with_tag_str_mv	@@773@@(DE-627)771401604
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	GE1-350
illustrated	Not Illustrated
issn	2296665X
topic_title	GE1-350 Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China frozen soil soil freezing-thawing processes soil temperature active soil depth cold regions
topic	misc GE1-350 misc frozen soil misc soil freezing-thawing processes misc soil temperature misc active soil depth misc cold regions misc Environmental sciences
topic_unstemmed	misc GE1-350 misc frozen soil misc soil freezing-thawing processes misc soil temperature misc active soil depth misc cold regions misc Environmental sciences
topic_browse	misc GE1-350 misc frozen soil misc soil freezing-thawing processes misc soil temperature misc active soil depth misc cold regions misc Environmental sciences
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Frontiers in Environmental Science
hierarchy_parent_id	771401604
hierarchy_top_title	Frontiers in Environmental Science
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)771401604 (DE-600)2741535-1
title	Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China
ctrlnum	(DE-627)DOAJ023532955 (DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56
title_full	Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China
author_sort	Qin Ju
journal	Frontiers in Environmental Science
journalStr	Frontiers in Environmental Science
callnumber-first-code	G
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2022
contenttype_str_mv	txt
author_browse	Qin Ju Rongrong Zhang Guoqing Wang Wenlong Hao Qin Wang Yanli Liu Wei Wang
container_volume	10
class	GE1-350
format_se	Elektronische Aufsätze
author-letter	Qin Ju
doi_str_mv	10.3389/fenvs.2022.996701
author2-role	verfasserin
title_sort	simulating the freezing-thawing processes based on modis data in the three-river souce region, china
callnumber	GE1-350
title_auth	Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China
abstract	The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes.
abstractGer	The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes.
abstract_unstemmed	The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700
title_short	Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China
url	https://doi.org/10.3389/fenvs.2022.996701 https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56 https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full https://doaj.org/toc/2296-665X
remote_bool	true
author2	Rongrong Zhang Guoqing Wang Wenlong Hao Qin Wang Yanli Liu Wei Wang
author2Str	Rongrong Zhang Guoqing Wang Wenlong Hao Qin Wang Yanli Liu Wei Wang
ppnlink	771401604
callnumber-subject	GE - Environmental Sciences
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.3389/fenvs.2022.996701
callnumber-a	GE1-350
up_date	2024-07-03T18:07:03.542Z
_version_	1803582201972916224
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ023532955</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230307064943.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3389/fenvs.2022.996701</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ023532955</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ02b0ec1e71384b1a95cb4e06161cdd56</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">GE1-350</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Qin Ju</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The processes of soil freezing-thawing lead to soil water and heat movement in cold regions, which significantly influences the hydrological and energy cycles in the soil-plant-atmosphere system. This study presents a soil water content coupled with heat transfer model based on physical processes of water and heat movement in frozen soil. The model was calibrated and validated using the measured data of soil temperature and frost and thaw depth at 19 stations in and around the Three-River Source Region of China. The results show that the frozen soil model could capture the processes of soil freezing-thawing processes well at this region. The relationship between model parameters and climate and vegetation factors was analyzed using the observation data and remote sensing data obtained from MODIS, and results showed that the parameter c which represents the soil properties has a good correlation with longitude and vegetation coverage. A multi-regression model was established to estimate the model parameters in regions without observation data and its determination coefficient R2 was 0.82. The mean relative error between calibration and inversion parameters of 19 stations is 6.29%. Thus, the proposed method can be applied to cold regions without observation data to obtain the parameters and simulated the soil freezing-thawing processes.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">frozen soil</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">soil freezing-thawing processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">soil temperature</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">active soil depth</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">cold regions</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Environmental sciences</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Rongrong Zhang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Guoqing Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wenlong Hao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wenlong Hao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qin Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yanli Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wei Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Frontiers in Environmental Science</subfield><subfield code="d">Frontiers Media S.A., 2014</subfield><subfield code="g">10(2022)</subfield><subfield code="w">(DE-627)771401604</subfield><subfield code="w">(DE-600)2741535-1</subfield><subfield code="x">2296665X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:10</subfield><subfield code="g">year:2022</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3389/fenvs.2022.996701</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/02b0ec1e71384b1a95cb4e06161cdd56</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.frontiersin.org/articles/10.3389/fenvs.2022.996701/full</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2296-665X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">10</subfield><subfield code="j">2022</subfield></datafield></record></collection>
score	7.401374

Nicht das Richtige dabei?

Schreiben Sie uns!

Simulating the freezing-thawing processes based on MODIS data in the Three-River Souce Region, China

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?