Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China

Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Abd El-Hamid, Hazem T. [verfasserIn] Caiyong, Wei [verfasserIn] Hafiz, Mohammed A. [verfasserIn] Mustafa, Elhadi K. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Yellow River Dynamics LULC Vulnerability Remote sensing

Übergeordnetes Werk:	Enthalten in: Arabian journal of geosciences - Berlin : Springer, 2008, 13(2020), 20 vom: Okt.
Übergeordnetes Werk:	volume:13 ; year:2020 ; number:20 ; month:10

Links:	Volltext

DOI / URN:	10.1007/s12517-020-06047-6

Katalog-ID:	SPR041352300

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100	1		\|a Abd El-Hamid, Hazem T. \|e verfasserin \|4 aut
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520			\|a Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem.
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700	1		\|a Caiyong, Wei \|e verfasserin \|4 aut
700	1		\|a Hafiz, Mohammed A. \|e verfasserin \|4 aut
700	1		\|a Mustafa, Elhadi K. \|e verfasserin \|4 aut
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912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
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author_variant	e h h t a ehht ehhta w c wc m a h ma mah e k m ek ekm
matchkey_str	article:18667538:2020----::fetolnueadoeadlmtchnenheoyt
hierarchy_sort_str	2020
publishDate	2020
allfields	10.1007/s12517-020-06047-6 doi (DE-627)SPR041352300 (SPR)s12517-020-06047-6-e DE-627 ger DE-627 rakwb eng 550 ASE Abd El-Hamid, Hazem T. verfasserin aut Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem. Yellow River (dpeaa)DE-He213 Dynamics (dpeaa)DE-He213 LULC (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Caiyong, Wei verfasserin aut Hafiz, Mohammed A. verfasserin aut Mustafa, Elhadi K. verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 13(2020), 20 vom: Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:13 year:2020 number:20 month:10 https://dx.doi.org/10.1007/s12517-020-06047-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2020 20 10
spelling	10.1007/s12517-020-06047-6 doi (DE-627)SPR041352300 (SPR)s12517-020-06047-6-e DE-627 ger DE-627 rakwb eng 550 ASE Abd El-Hamid, Hazem T. verfasserin aut Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem. Yellow River (dpeaa)DE-He213 Dynamics (dpeaa)DE-He213 LULC (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Caiyong, Wei verfasserin aut Hafiz, Mohammed A. verfasserin aut Mustafa, Elhadi K. verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 13(2020), 20 vom: Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:13 year:2020 number:20 month:10 https://dx.doi.org/10.1007/s12517-020-06047-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2020 20 10
allfields_unstemmed	10.1007/s12517-020-06047-6 doi (DE-627)SPR041352300 (SPR)s12517-020-06047-6-e DE-627 ger DE-627 rakwb eng 550 ASE Abd El-Hamid, Hazem T. verfasserin aut Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem. Yellow River (dpeaa)DE-He213 Dynamics (dpeaa)DE-He213 LULC (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Caiyong, Wei verfasserin aut Hafiz, Mohammed A. verfasserin aut Mustafa, Elhadi K. verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 13(2020), 20 vom: Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:13 year:2020 number:20 month:10 https://dx.doi.org/10.1007/s12517-020-06047-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2020 20 10
allfieldsGer	10.1007/s12517-020-06047-6 doi (DE-627)SPR041352300 (SPR)s12517-020-06047-6-e DE-627 ger DE-627 rakwb eng 550 ASE Abd El-Hamid, Hazem T. verfasserin aut Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem. Yellow River (dpeaa)DE-He213 Dynamics (dpeaa)DE-He213 LULC (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Caiyong, Wei verfasserin aut Hafiz, Mohammed A. verfasserin aut Mustafa, Elhadi K. verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 13(2020), 20 vom: Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:13 year:2020 number:20 month:10 https://dx.doi.org/10.1007/s12517-020-06047-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2020 20 10
allfieldsSound	10.1007/s12517-020-06047-6 doi (DE-627)SPR041352300 (SPR)s12517-020-06047-6-e DE-627 ger DE-627 rakwb eng 550 ASE Abd El-Hamid, Hazem T. verfasserin aut Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem. Yellow River (dpeaa)DE-He213 Dynamics (dpeaa)DE-He213 LULC (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Caiyong, Wei verfasserin aut Hafiz, Mohammed A. verfasserin aut Mustafa, Elhadi K. verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 13(2020), 20 vom: Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:13 year:2020 number:20 month:10 https://dx.doi.org/10.1007/s12517-020-06047-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2020 20 10
language	English
source	Enthalten in Arabian journal of geosciences 13(2020), 20 vom: Okt. volume:13 year:2020 number:20 month:10
sourceStr	Enthalten in Arabian journal of geosciences 13(2020), 20 vom: Okt. volume:13 year:2020 number:20 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Yellow River Dynamics LULC Vulnerability Remote sensing
dewey-raw	550
isfreeaccess_bool	true
container_title	Arabian journal of geosciences
authorswithroles_txt_mv	Abd El-Hamid, Hazem T. @@aut@@ Caiyong, Wei @@aut@@ Hafiz, Mohammed A. @@aut@@ Mustafa, Elhadi K. @@aut@@
publishDateDaySort_date	2020-10-01T00:00:00Z
hierarchy_top_id	572421877
dewey-sort	3550
id	SPR041352300
language_de	englisch
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author	Abd El-Hamid, Hazem T.
spellingShingle	Abd El-Hamid, Hazem T. ddc 550 misc Yellow River misc Dynamics misc LULC misc Vulnerability misc Remote sensing Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China
authorStr	Abd El-Hamid, Hazem T.
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topic_title	550 ASE Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China Yellow River (dpeaa)DE-He213 Dynamics (dpeaa)DE-He213 LULC (dpeaa)DE-He213 Vulnerability (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213
topic	ddc 550 misc Yellow River misc Dynamics misc LULC misc Vulnerability misc Remote sensing
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title	Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China
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title_full	Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China
author_sort	Abd El-Hamid, Hazem T.
journal	Arabian journal of geosciences
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author_browse	Abd El-Hamid, Hazem T. Caiyong, Wei Hafiz, Mohammed A. Mustafa, Elhadi K.
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title_sort	effects of land use/land cover and climatic change on the ecosystem of north ningxia, china
title_auth	Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China
abstract	Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem.
abstractGer	Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem.
abstract_unstemmed	Abstract Land use/land cover change (LUCC) and climate changes are responsible for degradation of any ecosystem in arid and semi-arid regions. Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. Results of this study could help planners in formulating effective strategies for better management of ecosystem.
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title_short	Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China
url	https://dx.doi.org/10.1007/s12517-020-06047-6
remote_bool	true
author2	Caiyong, Wei Hafiz, Mohammed A. Mustafa, Elhadi K.
author2Str	Caiyong, Wei Hafiz, Mohammed A. Mustafa, Elhadi K.
ppnlink	572421877
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isOA_txt	true
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doi_str	10.1007/s12517-020-06047-6
up_date	2024-07-03T21:40:01.125Z
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Studying the ecological variations is particularly essential for any type of sustainable development, in which LUCC considers as one of the chief inputs. The main objective is to evaluate the impacts of LUCC and climatic changes on the Ecosystem Vulnerability ($ E_{S} $V) using remote sensing and some statistical models around the Yellow River, Ningxia, China. Eleven classes of LUCC were identified during 1995 and 2019: village land, bare land, grassland, industrial land, irrigated land, swamp land, tidal flat, transportation land, urban land, water bodies, and water channels. Grassland may be decreased annually with percentage − 5.873% due to some human activities and environmental changes in climate from one season to another. About 24.23 $ km^{2} $ and 24.86 $ km^{2} $ was converted from grassland to industrial lands and irrigated lands, respectively. $ E_{S} $V has been calculated using LULC, DEM, slope, soil, and geology. About 45% and 60% of 1995 and 2019, respectively, undergone moderate vulnerability. The annual rate of $ E_{S} $VI decreased in low and reasonable but it was increased in moderate, high, and extreme showing – 4.166% as a total percentage of annual vulnerability. High vulnerability area needs proper management. Majority of vegetation area is located in zone under the moderate vulnerability zone; in contrast, grasslands were subjected to high vulnerability. Areas around the Yellow River were subjected to drought and flooding due to climatic change affecting negatively on the production of crops. Also, the desert lands of the study area have been turned to agriculture according to statistical model. Population growth, industrial development, and governmental policies for ecosystem protection were responsible for major changes. This study is more beneficial for decision-making in eco-environmental protecting and planning. 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Effects of land use/land cover and climatic change on the ecosystem of North Ningxia, China

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