Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China

Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ruihao Cui [verfasserIn] Jiazheng Han [verfasserIn] Zhenqi Hu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector

Übergeordnetes Werk:	In: Land - MDPI AG, 2013, 11(2022), 6, p 944
Übergeordnetes Werk:	volume:11 ; year:2022 ; number:6, p 944

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/land11060944

Katalog-ID:	DOAJ044211465

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ044211465
003	DE-627
005	20240414201943.0
007	cr uuu---uuuuu
008	230227s2022 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.3390/land11060944 \|2 doi
035			\|a (DE-627)DOAJ044211465
035			\|a (DE-599)DOAJ4fe0a7beff034d0890970047727375e9
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
100	0		\|a Ruihao Cui \|e verfasserin \|4 aut
245	1	0	\|a Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, 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 Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City.
650		4	\|a Google Earth Engine
650		4	\|a remote sensing ecological index (RSEI)
650		4	\|a barycenter migration analysis
650		4	\|a landcover
650		4	\|a GeoDetector
653		0	\|a Agriculture
653		0	\|a S
700	0		\|a Jiazheng Han \|e verfasserin \|4 aut
700	0		\|a Zhenqi Hu \|e verfasserin \|4 aut
773	0	8	\|i In \|t Land \|d MDPI AG, 2013 \|g 11(2022), 6, p 944 \|w (DE-627)72649500X \|w (DE-600)2682955-1 \|x 2073445X \|7 nnns
773	1	8	\|g volume:11 \|g year:2022 \|g number:6, p 944
856	4	0	\|u https://doi.org/10.3390/land11060944 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/4fe0a7beff034d0890970047727375e9 \|z kostenfrei
856	4	0	\|u https://www.mdpi.com/2073-445X/11/6/944 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2073-445X \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
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_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_602
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_4307
912			\|a GBV_ILN_4313
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 11 \|j 2022 \|e 6, p 944

Indexfelder

author_variant	r c rc j h jh z h zh
matchkey_str	article:2073445X:2022----::sesetfptatmoacagsfclgclniomnqaiycs
hierarchy_sort_str	2022
publishDate	2022
allfields	10.3390/land11060944 doi (DE-627)DOAJ044211465 (DE-599)DOAJ4fe0a7beff034d0890970047727375e9 DE-627 ger DE-627 rakwb eng Ruihao Cui verfasserin aut Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City. Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector Agriculture S Jiazheng Han verfasserin aut Zhenqi Hu verfasserin aut In Land MDPI AG, 2013 11(2022), 6, p 944 (DE-627)72649500X (DE-600)2682955-1 2073445X nnns volume:11 year:2022 number:6, p 944 https://doi.org/10.3390/land11060944 kostenfrei https://doaj.org/article/4fe0a7beff034d0890970047727375e9 kostenfrei https://www.mdpi.com/2073-445X/11/6/944 kostenfrei https://doaj.org/toc/2073-445X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 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_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 6, p 944
spelling	10.3390/land11060944 doi (DE-627)DOAJ044211465 (DE-599)DOAJ4fe0a7beff034d0890970047727375e9 DE-627 ger DE-627 rakwb eng Ruihao Cui verfasserin aut Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City. Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector Agriculture S Jiazheng Han verfasserin aut Zhenqi Hu verfasserin aut In Land MDPI AG, 2013 11(2022), 6, p 944 (DE-627)72649500X (DE-600)2682955-1 2073445X nnns volume:11 year:2022 number:6, p 944 https://doi.org/10.3390/land11060944 kostenfrei https://doaj.org/article/4fe0a7beff034d0890970047727375e9 kostenfrei https://www.mdpi.com/2073-445X/11/6/944 kostenfrei https://doaj.org/toc/2073-445X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 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_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 6, p 944
allfields_unstemmed	10.3390/land11060944 doi (DE-627)DOAJ044211465 (DE-599)DOAJ4fe0a7beff034d0890970047727375e9 DE-627 ger DE-627 rakwb eng Ruihao Cui verfasserin aut Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City. Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector Agriculture S Jiazheng Han verfasserin aut Zhenqi Hu verfasserin aut In Land MDPI AG, 2013 11(2022), 6, p 944 (DE-627)72649500X (DE-600)2682955-1 2073445X nnns volume:11 year:2022 number:6, p 944 https://doi.org/10.3390/land11060944 kostenfrei https://doaj.org/article/4fe0a7beff034d0890970047727375e9 kostenfrei https://www.mdpi.com/2073-445X/11/6/944 kostenfrei https://doaj.org/toc/2073-445X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 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_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 6, p 944
allfieldsGer	10.3390/land11060944 doi (DE-627)DOAJ044211465 (DE-599)DOAJ4fe0a7beff034d0890970047727375e9 DE-627 ger DE-627 rakwb eng Ruihao Cui verfasserin aut Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City. Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector Agriculture S Jiazheng Han verfasserin aut Zhenqi Hu verfasserin aut In Land MDPI AG, 2013 11(2022), 6, p 944 (DE-627)72649500X (DE-600)2682955-1 2073445X nnns volume:11 year:2022 number:6, p 944 https://doi.org/10.3390/land11060944 kostenfrei https://doaj.org/article/4fe0a7beff034d0890970047727375e9 kostenfrei https://www.mdpi.com/2073-445X/11/6/944 kostenfrei https://doaj.org/toc/2073-445X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 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_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 6, p 944
allfieldsSound	10.3390/land11060944 doi (DE-627)DOAJ044211465 (DE-599)DOAJ4fe0a7beff034d0890970047727375e9 DE-627 ger DE-627 rakwb eng Ruihao Cui verfasserin aut Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City. Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector Agriculture S Jiazheng Han verfasserin aut Zhenqi Hu verfasserin aut In Land MDPI AG, 2013 11(2022), 6, p 944 (DE-627)72649500X (DE-600)2682955-1 2073445X nnns volume:11 year:2022 number:6, p 944 https://doi.org/10.3390/land11060944 kostenfrei https://doaj.org/article/4fe0a7beff034d0890970047727375e9 kostenfrei https://www.mdpi.com/2073-445X/11/6/944 kostenfrei https://doaj.org/toc/2073-445X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 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_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 6, p 944
language	English
source	In Land 11(2022), 6, p 944 volume:11 year:2022 number:6, p 944
sourceStr	In Land 11(2022), 6, p 944 volume:11 year:2022 number:6, p 944
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector Agriculture S
isfreeaccess_bool	true
container_title	Land
authorswithroles_txt_mv	Ruihao Cui @@aut@@ Jiazheng Han @@aut@@ Zhenqi Hu @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	72649500X
id	DOAJ044211465
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">DOAJ044211465</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414201943.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/land11060944</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ044211465</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ4fe0a7beff034d0890970047727375e9</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="100" ind1="0" ind2=" "><subfield code="a">Ruihao Cui</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, 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">Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Google Earth Engine</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">remote sensing ecological index (RSEI)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">barycenter migration analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">landcover</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">GeoDetector</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Agriculture</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">S</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jiazheng Han</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Zhenqi Hu</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">Land</subfield><subfield code="d">MDPI AG, 2013</subfield><subfield code="g">11(2022), 6, p 944</subfield><subfield code="w">(DE-627)72649500X</subfield><subfield code="w">(DE-600)2682955-1</subfield><subfield code="x">2073445X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:6, p 944</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/land11060944</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/4fe0a7beff034d0890970047727375e9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2073-445X/11/6/944</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2073-445X</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_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_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_105</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_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_602</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_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</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">11</subfield><subfield code="j">2022</subfield><subfield code="e">6, p 944</subfield></datafield></record></collection>
author	Ruihao Cui
spellingShingle	Ruihao Cui misc Google Earth Engine misc remote sensing ecological index (RSEI) misc barycenter migration analysis misc landcover misc GeoDetector misc Agriculture misc S Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China
authorStr	Ruihao Cui
ppnlink_with_tag_str_mv	@@773@@(DE-627)72649500X
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut
collection	DOAJ
remote_str	true
illustrated	Not Illustrated
issn	2073445X
topic_title	Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China Google Earth Engine remote sensing ecological index (RSEI) barycenter migration analysis landcover GeoDetector
topic	misc Google Earth Engine misc remote sensing ecological index (RSEI) misc barycenter migration analysis misc landcover misc GeoDetector misc Agriculture misc S
topic_unstemmed	misc Google Earth Engine misc remote sensing ecological index (RSEI) misc barycenter migration analysis misc landcover misc GeoDetector misc Agriculture misc S
topic_browse	misc Google Earth Engine misc remote sensing ecological index (RSEI) misc barycenter migration analysis misc landcover misc GeoDetector misc Agriculture misc S
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Land
hierarchy_parent_id	72649500X
hierarchy_top_title	Land
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)72649500X (DE-600)2682955-1
title	Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China
ctrlnum	(DE-627)DOAJ044211465 (DE-599)DOAJ4fe0a7beff034d0890970047727375e9
title_full	Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China
author_sort	Ruihao Cui
journal	Land
journalStr	Land
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2022
contenttype_str_mv	txt
author_browse	Ruihao Cui Jiazheng Han Zhenqi Hu
container_volume	11
format_se	Elektronische Aufsätze
author-letter	Ruihao Cui
doi_str_mv	10.3390/land11060944
author2-role	verfasserin
title_sort	assessment of spatial temporal changes of ecological environment quality: a case study in huaibei city, china
title_auth	Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China
abstract	Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City.
abstractGer	Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City.
abstract_unstemmed	Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 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_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700
container_issue	6, p 944
title_short	Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China
url	https://doi.org/10.3390/land11060944 https://doaj.org/article/4fe0a7beff034d0890970047727375e9 https://www.mdpi.com/2073-445X/11/6/944 https://doaj.org/toc/2073-445X
remote_bool	true
author2	Jiazheng Han Zhenqi Hu
author2Str	Jiazheng Han Zhenqi Hu
ppnlink	72649500X
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.3390/land11060944
up_date	2024-07-03T21:49:34.470Z
_version_	1803596201434546176
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">DOAJ044211465</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414201943.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/land11060944</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ044211465</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ4fe0a7beff034d0890970047727375e9</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="100" ind1="0" ind2=" "><subfield code="a">Ruihao Cui</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, 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">Under the short-term economic development goal, the excessive exploitation of natural resources and the destruction of the ecological environment make the ecological environment of Huaibei cities increasingly fragile. This study constructed the Remote Sensing Ecological Index (RSEI) to evaluate the ecological environment change trend and its driving factors in Huaibei City from 2000 to 2020. The barycenter migration model was used to determine the RSEI spatial change trend, and the geographic detector was used to analyze the influencing factors of the RSEI value change. The results showed that: (1) the average RSEI value of Huaibei City generally fluctuates within the range of good and excellent grades. (2) The migration direction of the barycenter of RSEI is similar when the level of RSEI improves or decreases from 2000 to 2020, and the barycenter migration is most severe from 2005 to 2015. (3) The driving factors of RSEI change were population density (0.47) < land use (0.24) < slope (0.14) < precipitation (0.08) < temperature (0.04) < altitude (0.03). All the factors had interaction effects on the RSEI, mainly with nonlinear enhancement. (4) From 2000 to 2010, urban construction encroached on all kinds of land, which was the direct reason for the decline in ecological environment quality. From 2010 to 2020, the surge of water and meadow areas improved the ecological environment quality of Huaibei city. Therefore, reducing the expansion of artificial land, returning farmland to forests and meadows, wetland park construction, and other ecological protection measures are the keys to ensuring the sustainable development of regional social and economic development. This study can provide a reference and scientific basis for sustainable development strategy and ecological protection planning to improve the ecological environment quality of Huaibei City.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Google Earth Engine</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">remote sensing ecological index (RSEI)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">barycenter migration analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">landcover</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">GeoDetector</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Agriculture</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">S</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jiazheng Han</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Zhenqi Hu</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">Land</subfield><subfield code="d">MDPI AG, 2013</subfield><subfield code="g">11(2022), 6, p 944</subfield><subfield code="w">(DE-627)72649500X</subfield><subfield code="w">(DE-600)2682955-1</subfield><subfield code="x">2073445X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:6, p 944</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/land11060944</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/4fe0a7beff034d0890970047727375e9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2073-445X/11/6/944</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2073-445X</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_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_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_105</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_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_602</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_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</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">11</subfield><subfield code="j">2022</subfield><subfield code="e">6, p 944</subfield></datafield></record></collection>
score	7.4004498

Nicht das Richtige dabei?

Schreiben Sie uns!

Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?