2022 Vol. 32, No. 6
Display Method:
2022, 32(6): 933-945.
doi: 10.1007/s11769-022-1313-1
Abstract:
Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development. Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite (NPP-VIIRS) Nighttime Light (NTL) data, this paper investigated the characteristics of urban landscape in West Africa. Using the harmonized NTL data, spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018. We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas. In addition, we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa. The accuracy of urban area extraction based on NTL data were R2 = 0.8314 in 2000, R2 = 0.8809 in 2006, R2 = 0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R2 = 0.8426 in 2018, by using Google Earth images as validation. The results indicated that there was a high rate and acceleration of urban landscapes in West Africa, with rates of 0.016 0, 0.017 3, 0.018 9, and 0.068 6, and accelerations of 0.31, 0.42, 0.54, and 0.90 for the periods of 1998–2003, 2003–2008, 2008–2013, and 2013–2018, respectively. The expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to inland. However, cities located in the Sahel Region of Africa and in the middle zone expanded from north to south. Finally, the results showed that the urban landscape of West Africa was mainly in a scattered and disordered ‘diffusion’ process, whereas only a few cities located in coastal areas experiencing the process of ‘coalescence’ according to urban growth phase theory. This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.
Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development. Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite (NPP-VIIRS) Nighttime Light (NTL) data, this paper investigated the characteristics of urban landscape in West Africa. Using the harmonized NTL data, spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018. We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas. In addition, we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa. The accuracy of urban area extraction based on NTL data were R2 = 0.8314 in 2000, R2 = 0.8809 in 2006, R2 = 0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R2 = 0.8426 in 2018, by using Google Earth images as validation. The results indicated that there was a high rate and acceleration of urban landscapes in West Africa, with rates of 0.016 0, 0.017 3, 0.018 9, and 0.068 6, and accelerations of 0.31, 0.42, 0.54, and 0.90 for the periods of 1998–2003, 2003–2008, 2008–2013, and 2013–2018, respectively. The expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to inland. However, cities located in the Sahel Region of Africa and in the middle zone expanded from north to south. Finally, the results showed that the urban landscape of West Africa was mainly in a scattered and disordered ‘diffusion’ process, whereas only a few cities located in coastal areas experiencing the process of ‘coalescence’ according to urban growth phase theory. This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.
2022, 32(6): 946-962.
doi: 10.1007/s11769-022-1309-x
Abstract:
Under the background of collaborative innovation, innovation spillovers at urban agglomeration (UA) level is an important issue but rarely discussed. Using balanced panel data of innovation activities in China’s five UAs from 2003 to 2016, this paper shows spatio-temporal evolution process of their technological innovation capacity with discussing polarization-diffusion patterns, and simultaneously examines driving factors of that evolution processes. We report three main findings: 1) there is a high degree of concentration in technological innovation capacity distribution within all China’s five UAs, linked by economic and innovation collaboration. 2) Innovation capacity increase of China’s five UAs is driven by government’s investment in science and technology (S&T) to a large extent, followed by influences of infrastructure facilities construction, human capital for S&T, as well as transformation of industrial structure, with great disparities emerged between UAs in our sample period. 3) While the intra-region innovation gaps are reducing in Yangtze River Delta Urban Agglomeration (YRD) with obvious innovation diffusion, urban agglomeration in middle reaches of the Yangtze River (MYR) is still dominated by innovation polarized growth. Differences in polarization-diffusion patterns between these two UAs may be explained by opposite returns of industrial structure and internet infrastructure. Our findings contribute to more effective policy making in promoting innovation development when reducing regional inequality through innovation diffusion.
Under the background of collaborative innovation, innovation spillovers at urban agglomeration (UA) level is an important issue but rarely discussed. Using balanced panel data of innovation activities in China’s five UAs from 2003 to 2016, this paper shows spatio-temporal evolution process of their technological innovation capacity with discussing polarization-diffusion patterns, and simultaneously examines driving factors of that evolution processes. We report three main findings: 1) there is a high degree of concentration in technological innovation capacity distribution within all China’s five UAs, linked by economic and innovation collaboration. 2) Innovation capacity increase of China’s five UAs is driven by government’s investment in science and technology (S&T) to a large extent, followed by influences of infrastructure facilities construction, human capital for S&T, as well as transformation of industrial structure, with great disparities emerged between UAs in our sample period. 3) While the intra-region innovation gaps are reducing in Yangtze River Delta Urban Agglomeration (YRD) with obvious innovation diffusion, urban agglomeration in middle reaches of the Yangtze River (MYR) is still dominated by innovation polarized growth. Differences in polarization-diffusion patterns between these two UAs may be explained by opposite returns of industrial structure and internet infrastructure. Our findings contribute to more effective policy making in promoting innovation development when reducing regional inequality through innovation diffusion.
2022, 32(6): 963-978.
doi: 10.1007/s11769-022-1314-0
Abstract:
Against the background of global warming, research on the spatial distribution of high-temperature risk is of great significance to effectively prevent the adverse effects of high temperatures. By using air temperature data from 1951 to 2018 measured by meteorological stations located in the Yangtze River Delta urban agglomeration, the daily maximum air temperature distribution is interpolated at a resolution of 1 km based on the local thin disk smooth spline function; the high-temperature threshold for return periods of 5, 10, 20 and 30 yr are then calculated by using the generalized extreme value method. The yearly average high-temperature intensity and high-temperature days are finally calculated as high-temperature danger factors. Socioeconomic statistical data and remotely sensed image data in 2018 are used as the background data to calculate the spatial distribution of high-temperature vulnerability factors and prevention capacity factors, which are then used to compute the high-temperature risk index during different recurrence periods in the Yangtze River Delta urban agglomerations. The results show that the spatial distribution features of high-temperature risk in different return periods are similar. The high-temperature risk index gradually increases from northeast to southwest and from east coast to inland, which has obvious latitude variation characteristics and a relationship with the comprehensive influence of the underlying surface and urban scale. In terms of time variation, the high-temperature risk index and its spatial distribution difference gradually decreases with increasing return period. In different cities, the high-temperature risk in the central area of the city is generally higher than that in the surrounding suburban areas. Jinhua, Hangzhou of Zhejiang Province and Xuancheng of Anhui Province are the top three cities with high-temperature risk in the study area.
Against the background of global warming, research on the spatial distribution of high-temperature risk is of great significance to effectively prevent the adverse effects of high temperatures. By using air temperature data from 1951 to 2018 measured by meteorological stations located in the Yangtze River Delta urban agglomeration, the daily maximum air temperature distribution is interpolated at a resolution of 1 km based on the local thin disk smooth spline function; the high-temperature threshold for return periods of 5, 10, 20 and 30 yr are then calculated by using the generalized extreme value method. The yearly average high-temperature intensity and high-temperature days are finally calculated as high-temperature danger factors. Socioeconomic statistical data and remotely sensed image data in 2018 are used as the background data to calculate the spatial distribution of high-temperature vulnerability factors and prevention capacity factors, which are then used to compute the high-temperature risk index during different recurrence periods in the Yangtze River Delta urban agglomerations. The results show that the spatial distribution features of high-temperature risk in different return periods are similar. The high-temperature risk index gradually increases from northeast to southwest and from east coast to inland, which has obvious latitude variation characteristics and a relationship with the comprehensive influence of the underlying surface and urban scale. In terms of time variation, the high-temperature risk index and its spatial distribution difference gradually decreases with increasing return period. In different cities, the high-temperature risk in the central area of the city is generally higher than that in the surrounding suburban areas. Jinhua, Hangzhou of Zhejiang Province and Xuancheng of Anhui Province are the top three cities with high-temperature risk in the study area.
2022, 32(6): 979-994.
doi: 10.1007/s11769-022-1315-z
Abstract:
The accurate and reliable interpretation of regional land cover data is very important for natural resource monitoring and environmental assessment. At present, refined land cover data are mainly obtained by manual visual interpretation, which has the problems of heavy workload and inconsistent interpretation scales. Deep learning has greatly improved the automatic processing and analysis of remote sensing data. However, the accurate interpretation of feature information from massive datasets remains a difficult problem in wide regional land cover classification. To improve the efficiency of deep learning-based remote sensing image interpretation, we selected multisource remote sensing data, assessed the interpretability of the U-Net model based on surface spatial scenes with different levels of complexity, and proposed a new method of stereoscopic accuracy verification (SAV) to evaluate the reliability of the classification result. The results show that classification accuracy is more highly correlated with terrain and landscape than with other factors related to image data, such as platform and spatial resolution. As the complexity of surface spatial scenes increases, the accuracy of the classification results mainly shows a fluctuating declining trend. We also find the distribution characteristics from the SAV evaluation results of different land cover types in each surface spatial scene. Based on the results observed in this study, we consider the distinction of interpretability and reliability in diverse ground object types and design targeted classification strategies for different surface scenes, which can greatly improve the classification efficiency. The key achievement of this study is to provide the theoretical basis for remote sensing information analysis and an accuracy evaluation method for regional land cover classification, and the proposed method can help improve the likelihood that intelligent interpretation can replace manual acquisition.
The accurate and reliable interpretation of regional land cover data is very important for natural resource monitoring and environmental assessment. At present, refined land cover data are mainly obtained by manual visual interpretation, which has the problems of heavy workload and inconsistent interpretation scales. Deep learning has greatly improved the automatic processing and analysis of remote sensing data. However, the accurate interpretation of feature information from massive datasets remains a difficult problem in wide regional land cover classification. To improve the efficiency of deep learning-based remote sensing image interpretation, we selected multisource remote sensing data, assessed the interpretability of the U-Net model based on surface spatial scenes with different levels of complexity, and proposed a new method of stereoscopic accuracy verification (SAV) to evaluate the reliability of the classification result. The results show that classification accuracy is more highly correlated with terrain and landscape than with other factors related to image data, such as platform and spatial resolution. As the complexity of surface spatial scenes increases, the accuracy of the classification results mainly shows a fluctuating declining trend. We also find the distribution characteristics from the SAV evaluation results of different land cover types in each surface spatial scene. Based on the results observed in this study, we consider the distinction of interpretability and reliability in diverse ground object types and design targeted classification strategies for different surface scenes, which can greatly improve the classification efficiency. The key achievement of this study is to provide the theoretical basis for remote sensing information analysis and an accuracy evaluation method for regional land cover classification, and the proposed method can help improve the likelihood that intelligent interpretation can replace manual acquisition.
2022, 32(6): 995-1012.
doi: 10.1007/s11769-022-1316-y
Abstract:
Exploring the spatial and temporal evolution characteristics of the border land use multifunctionality (LUMF) provides insights for taking advantage of border land use and optimizing border land use policies. Based on the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) mode, this study identifies and evaluates the LUMFs in the China-Vietnam border area between 2000 and 2018 from the perspectives of agricultural production, social security, ecological service, landscape recreation, and national security. The results show that: 1) The comprehensive land use functions in most counties and cities continued to be improved. 2) The comprehensive land use function exhibits remarkable spatial divergence and aggregation characteristics. The high-value area of the agricultural production function and social security function evolves from the east to the west. In addition, the spatial evolution of ecological service function is complicated, without an obvious spatial divergence and aggregation pattern. The landscape recreation function shows different spatial differentiation characteristics in the early and middle stage, and forms a large cluster in the later stage. Finally, the spatial evolution pattern of the national security function is significant. 3) Designing differentiated border land policies, improving border land use security, and establishing a long-term mechanism for ecological protection and ecological compensation can aid in optimizing the LUMF level in the border area.
Exploring the spatial and temporal evolution characteristics of the border land use multifunctionality (LUMF) provides insights for taking advantage of border land use and optimizing border land use policies. Based on the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) mode, this study identifies and evaluates the LUMFs in the China-Vietnam border area between 2000 and 2018 from the perspectives of agricultural production, social security, ecological service, landscape recreation, and national security. The results show that: 1) The comprehensive land use functions in most counties and cities continued to be improved. 2) The comprehensive land use function exhibits remarkable spatial divergence and aggregation characteristics. The high-value area of the agricultural production function and social security function evolves from the east to the west. In addition, the spatial evolution of ecological service function is complicated, without an obvious spatial divergence and aggregation pattern. The landscape recreation function shows different spatial differentiation characteristics in the early and middle stage, and forms a large cluster in the later stage. Finally, the spatial evolution pattern of the national security function is significant. 3) Designing differentiated border land policies, improving border land use security, and establishing a long-term mechanism for ecological protection and ecological compensation can aid in optimizing the LUMF level in the border area.
2022, 32(6): 1013-1034.
doi: 10.1007/s11769-022-1317-x
Abstract:
China is vigorously implementing a rural revitalization strategy with the prosperity of rural industries as the primary goal. The characteristic economy of ‘One Village One Product’ (OVOP) is particularly significant in promoting rural revitalization and increasing farmers’ income. Accurately identifying the spatial distribution characteristics and influencing factors of agricultural specialized villages (ASVs) under OVOP provides a preliminary research basis for constructing the theoretical framework of specialization and clustering of rural industrial development. This study takes Guangdong Province, China as an example, using kernel density estimation, Ripley’s K function, geometric fractals, principal component regression and other methods to identify the spatial distribution characteristics and influencing factors of ASVs. It was found that the ASVs in Guangdong Province are dominated by the planting industry, with an uneven number in space and a multi patch distribution. Specifically, ASVs are mainly distributed in the Chaoshan Plain in the eastern Guangdong, the northern mountainous area of Guangzhou, and the eastern part of Maoming City. Its spatial distribution mode obeys the aggregation distribution pattern at the scale of province, region and municipality (prefecture-level city). In addition, the formation and development of ASVs are affected by multiple internal and external factors. The influence of basic factors such as natural environmental conditions is gradually weakening, while the influence of social and economic factors such as market demand is gradually increasing. This study can enrich the research results of ASVs and provide guidance and reference for the long-term and high-quality development of rural industry revitalization.
China is vigorously implementing a rural revitalization strategy with the prosperity of rural industries as the primary goal. The characteristic economy of ‘One Village One Product’ (OVOP) is particularly significant in promoting rural revitalization and increasing farmers’ income. Accurately identifying the spatial distribution characteristics and influencing factors of agricultural specialized villages (ASVs) under OVOP provides a preliminary research basis for constructing the theoretical framework of specialization and clustering of rural industrial development. This study takes Guangdong Province, China as an example, using kernel density estimation, Ripley’s K function, geometric fractals, principal component regression and other methods to identify the spatial distribution characteristics and influencing factors of ASVs. It was found that the ASVs in Guangdong Province are dominated by the planting industry, with an uneven number in space and a multi patch distribution. Specifically, ASVs are mainly distributed in the Chaoshan Plain in the eastern Guangdong, the northern mountainous area of Guangzhou, and the eastern part of Maoming City. Its spatial distribution mode obeys the aggregation distribution pattern at the scale of province, region and municipality (prefecture-level city). In addition, the formation and development of ASVs are affected by multiple internal and external factors. The influence of basic factors such as natural environmental conditions is gradually weakening, while the influence of social and economic factors such as market demand is gradually increasing. This study can enrich the research results of ASVs and provide guidance and reference for the long-term and high-quality development of rural industry revitalization.
2022, 32(6): 1035-1051.
doi: 10.1007/s11769-022-1312-2
Abstract:
In order to investigate the evolutionary characteristics of rural functions and their interaction, 37 districts and counties in Chongqing, China are used as research objects to measure the level of rural functions and analyze the interaction between rural functions using entropy value method and spatial autocorrelation method. The results show that from 2009 to 2019, the three main functions of production, living and ecology in Chongqing’s villages have been greatly enhanced, especially the production function. On the whole, the production and living functions are stronger in the western part, while the ecological functions are significant in the eastern and southern parts of Chongqing, with some differences in local spatial characteristics. This finding is consistent with the regional economic and social development of Chongqing. In addition, the interaction between rural functions is also evident. In general, production and living functions are mainly expressed in synergistic relationships. Ecological and production functions, including ecological and subsistence functions, mainly present a trade-off relationship. The interactions between rural functions also show clear spatial and temporal differences. In addition, different regions have different comparative advantage functions, and in this study, the counties of Chongqing are classified into four types. Policy makers are advised to adopt different measures according to the different types to promote sustainable rural development by coordinating the ‘production-living-ecological’ functions of rural areas. This study reveals the spatio-temporal evolution of rural functions and the interaction between rural functions, which can provide theoretical support and practical reference for rural revitalisation and sustainable development.
In order to investigate the evolutionary characteristics of rural functions and their interaction, 37 districts and counties in Chongqing, China are used as research objects to measure the level of rural functions and analyze the interaction between rural functions using entropy value method and spatial autocorrelation method. The results show that from 2009 to 2019, the three main functions of production, living and ecology in Chongqing’s villages have been greatly enhanced, especially the production function. On the whole, the production and living functions are stronger in the western part, while the ecological functions are significant in the eastern and southern parts of Chongqing, with some differences in local spatial characteristics. This finding is consistent with the regional economic and social development of Chongqing. In addition, the interaction between rural functions is also evident. In general, production and living functions are mainly expressed in synergistic relationships. Ecological and production functions, including ecological and subsistence functions, mainly present a trade-off relationship. The interactions between rural functions also show clear spatial and temporal differences. In addition, different regions have different comparative advantage functions, and in this study, the counties of Chongqing are classified into four types. Policy makers are advised to adopt different measures according to the different types to promote sustainable rural development by coordinating the ‘production-living-ecological’ functions of rural areas. This study reveals the spatio-temporal evolution of rural functions and the interaction between rural functions, which can provide theoretical support and practical reference for rural revitalisation and sustainable development.
2022, 32(6): 1052-1068.
doi: 10.1007/s11769-022-1283-3
Abstract:
The construction of a livable environment for the elderly is an important measure to address the challenges of aging and improve their livelihood and well-being. Based on China’s national conditions and combined with the actual development needs of the cities, it is of great significance to explore the coupling and coordination characteristics and influencing factors within the livable environment system for the elderly for the coordination and stable development. This article was based on the three subsystems of ‘living service environment, socioeconomic environment and ecological livable environment’, following the research framework of ‘process-pattern-trend-impact’, constructs an evaluation index system for the livable environment for the elderly. Entropy weight-TOPSIS evaluation model, coupling coordination degree model, center of gravity and standard deviation ellipse model and the geographic detector model were used starting from the evolution of coupling coordination types to study the spatial and temporal pattern and dynamic trend characteristics and influencing factors of internal coupling coordination types in the livable environment system for the elderly from 2010 to 2019. The results showed that: 1) The coordinated development of life service environment system and ecological livable environment system (LE) and socioeconomic environment system and ecological livable environment system (SE) in the livable environment for the elderly decreased from the intermediate coordination level coordination areas to the low-level quality improvement and optimization areas: coordinated transition type. The overall development level of life service environment system and socioeconomic environment system (LS) was low, and it was always at a low level. 2) The coupling degree of livable environment system for the elderly was high, the coupling coordination type shown a gradually decreasing layer structure with Zhejiang, Beijing and Guangdong high-level leading demonstration areas as the axis belt. 3) The coupling coordination center of the elderly livable environment system was located in Henan, and the standard deviation ellipse was distributed in the northeast-southwest direction. The development center and the ellipse of the high-level leading demonstration areas and the intermediate coordination level areas were concentrated in the central and eastern regions, while the low-level coordination areas for improving quality and efficiency are mainly located in the western region. 4) Urban development, green facilities, infrastructure, government macroscopic regulation and control, economic stimulus, and housing construction were all important factors affecting the coordinated development of the livable environment system for the elderly, exerting a varying degree of effect on the level of coordinated development of various types of systems.
The construction of a livable environment for the elderly is an important measure to address the challenges of aging and improve their livelihood and well-being. Based on China’s national conditions and combined with the actual development needs of the cities, it is of great significance to explore the coupling and coordination characteristics and influencing factors within the livable environment system for the elderly for the coordination and stable development. This article was based on the three subsystems of ‘living service environment, socioeconomic environment and ecological livable environment’, following the research framework of ‘process-pattern-trend-impact’, constructs an evaluation index system for the livable environment for the elderly. Entropy weight-TOPSIS evaluation model, coupling coordination degree model, center of gravity and standard deviation ellipse model and the geographic detector model were used starting from the evolution of coupling coordination types to study the spatial and temporal pattern and dynamic trend characteristics and influencing factors of internal coupling coordination types in the livable environment system for the elderly from 2010 to 2019. The results showed that: 1) The coordinated development of life service environment system and ecological livable environment system (LE) and socioeconomic environment system and ecological livable environment system (SE) in the livable environment for the elderly decreased from the intermediate coordination level coordination areas to the low-level quality improvement and optimization areas: coordinated transition type. The overall development level of life service environment system and socioeconomic environment system (LS) was low, and it was always at a low level. 2) The coupling degree of livable environment system for the elderly was high, the coupling coordination type shown a gradually decreasing layer structure with Zhejiang, Beijing and Guangdong high-level leading demonstration areas as the axis belt. 3) The coupling coordination center of the elderly livable environment system was located in Henan, and the standard deviation ellipse was distributed in the northeast-southwest direction. The development center and the ellipse of the high-level leading demonstration areas and the intermediate coordination level areas were concentrated in the central and eastern regions, while the low-level coordination areas for improving quality and efficiency are mainly located in the western region. 4) Urban development, green facilities, infrastructure, government macroscopic regulation and control, economic stimulus, and housing construction were all important factors affecting the coordinated development of the livable environment system for the elderly, exerting a varying degree of effect on the level of coordinated development of various types of systems.
2022, 32(6): 1069-1082.
doi: 10.1007/s11769-022-1311-3
Abstract:
It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity (NPP) inorder to understand the driving mechanism of NPP and prevent desertification. This study investigated the spatial and temporal differentiation features of actual net primary productivity (ANPP) in the Ili River Basin, a transboundary river between China and Kazakhstan, as well as the proportional contributions of climate and human causes to ANPP variation. Additionally, we analyzed the pixel-scale relationship between ANPP and significant climatic parameters. ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest; furthermore, it was distributed in a ring around the Tianshan Mountains. In the vegetation improvement zone, human activities were the dominant driving force, whereas in the degraded zone, climate change was the primary major driving force. The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098, respectively. In most areas, there was a positive relationship between vegetation change, temperature and precipitation. During 2001 to 2020, the basin’s climatic change trend was warm and humid, which promoted vegetation growth. One of the driving factors in the vegetation improvement area was moderate grazing by livestock.
It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity (NPP) inorder to understand the driving mechanism of NPP and prevent desertification. This study investigated the spatial and temporal differentiation features of actual net primary productivity (ANPP) in the Ili River Basin, a transboundary river between China and Kazakhstan, as well as the proportional contributions of climate and human causes to ANPP variation. Additionally, we analyzed the pixel-scale relationship between ANPP and significant climatic parameters. ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest; furthermore, it was distributed in a ring around the Tianshan Mountains. In the vegetation improvement zone, human activities were the dominant driving force, whereas in the degraded zone, climate change was the primary major driving force. The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098, respectively. In most areas, there was a positive relationship between vegetation change, temperature and precipitation. During 2001 to 2020, the basin’s climatic change trend was warm and humid, which promoted vegetation growth. One of the driving factors in the vegetation improvement area was moderate grazing by livestock.
2022, 32(6): 1083-1098.
doi: 10.1007/s11769-022-1318-9
Abstract:
Evapotranspiration (ET) is the key to the water cycle process and an important factor for studying near-surface water and heat balance. Accurately estimating ET is significant for hydrology, meteorology, ecology, agriculture, etc.. This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009−2018 based on the Soil and Water Assessment Tool (SWAT) model, which was calibrated and validated using the MODIS (Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid (MOD16A2) dataset and measured ET. Two calibration strategies (lumped calibration (LC) and spatially distributed calibration (SDC)) were used. The basin was divided into 34 sub-basins, and the coefficient of determination (R2) and Nash-Sutcliffe efficiency coefficient (NSE) of each sub-basin were greater than 0.6 in both the calibration and validation periods. The R2 and NSE were higher in the validation period than those in the calibration period. Compared with the measured ET, the accuracy of the model on the daily scale is: R2= 0.704 and NSE = 0.759 (SDC results). The model simulation accuracy of LC and SDC for the sub-basin scale was R2 = 0.857, R2 = 0.862 (monthly) and R2 = 0.227, R2 = 0.404 (annually), respectively; for the whole basin scale was R2 = 0.902, R2 = 0.900 (monthly) and R2 = 0.507 and R2 = 0.519 (annually), respectively. The model performed acceptably, and SDC performed the best, indicating that remote sensing data can be used for SWAT model calibration. During 2009−2018, ET generally increased in the Madu River Basin (SDC results, 7.21 mm/yr), with a multiyear average value of 734.37 mm/yr. The annual ET change rate for the sub-basin was relatively low upstream and downstream. The linear correlation analysis between ET and meteorological factors shows that on the monthly scale, precipitation, solar radiation and daily maximum and minimum temperature were significantly correlated with ET; annually, solar radiation and wind speed had a moderate correlation with ET. The correlation between maximum temperature and ET is best on the monthly scale (Pearson correlation coefficient R = 0.945), which may means that the increasing ET originating from increasing temperature (global warming). However, the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate, which means that ET decreases in these sub-basins, indicating that the ‘Evaporation Paradox’ exists in these sub-basins. This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.
Evapotranspiration (ET) is the key to the water cycle process and an important factor for studying near-surface water and heat balance. Accurately estimating ET is significant for hydrology, meteorology, ecology, agriculture, etc.. This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009−2018 based on the Soil and Water Assessment Tool (SWAT) model, which was calibrated and validated using the MODIS (Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid (MOD16A2) dataset and measured ET. Two calibration strategies (lumped calibration (LC) and spatially distributed calibration (SDC)) were used. The basin was divided into 34 sub-basins, and the coefficient of determination (R2) and Nash-Sutcliffe efficiency coefficient (NSE) of each sub-basin were greater than 0.6 in both the calibration and validation periods. The R2 and NSE were higher in the validation period than those in the calibration period. Compared with the measured ET, the accuracy of the model on the daily scale is: R2= 0.704 and NSE = 0.759 (SDC results). The model simulation accuracy of LC and SDC for the sub-basin scale was R2 = 0.857, R2 = 0.862 (monthly) and R2 = 0.227, R2 = 0.404 (annually), respectively; for the whole basin scale was R2 = 0.902, R2 = 0.900 (monthly) and R2 = 0.507 and R2 = 0.519 (annually), respectively. The model performed acceptably, and SDC performed the best, indicating that remote sensing data can be used for SWAT model calibration. During 2009−2018, ET generally increased in the Madu River Basin (SDC results, 7.21 mm/yr), with a multiyear average value of 734.37 mm/yr. The annual ET change rate for the sub-basin was relatively low upstream and downstream. The linear correlation analysis between ET and meteorological factors shows that on the monthly scale, precipitation, solar radiation and daily maximum and minimum temperature were significantly correlated with ET; annually, solar radiation and wind speed had a moderate correlation with ET. The correlation between maximum temperature and ET is best on the monthly scale (Pearson correlation coefficient R = 0.945), which may means that the increasing ET originating from increasing temperature (global warming). However, the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate, which means that ET decreases in these sub-basins, indicating that the ‘Evaporation Paradox’ exists in these sub-basins. This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.
2022, 32(6): 1099-1109.
doi: 10.1007/s11769-022-1310-4
Abstract:
For centuries, reclamation of sodic soils has been an essential part of cropping practices in several parts of the world. Parallel to increasing population, the need for new cropland constantly re-evaluates land suitability concepts. Therefore, the importance of sodic soils as potential croplands is increasing worldwide. Although theoretically farmers can choose from a wide variety of reclamation options, according to profitability, business plans, and human and financial resources, in practice, few reclamation methods are applied at large scale. This article touches on the early history, 20th Century intensive research, and current trends of sodic soil reclamation. New approaches such as leaching, chemical amendments, addition of organic material, and biological and microbial improvements are discussed, and also brand-new approaches are reviewed. The early history is reviewed using historical books, the achievements of the last hundred years using basic technical literature, mostly books, and the current approaches of our time with fresh publications, mostly papers and two very recent conferences published in English.
For centuries, reclamation of sodic soils has been an essential part of cropping practices in several parts of the world. Parallel to increasing population, the need for new cropland constantly re-evaluates land suitability concepts. Therefore, the importance of sodic soils as potential croplands is increasing worldwide. Although theoretically farmers can choose from a wide variety of reclamation options, according to profitability, business plans, and human and financial resources, in practice, few reclamation methods are applied at large scale. This article touches on the early history, 20th Century intensive research, and current trends of sodic soil reclamation. New approaches such as leaching, chemical amendments, addition of organic material, and biological and microbial improvements are discussed, and also brand-new approaches are reviewed. The early history is reviewed using historical books, the achievements of the last hundred years using basic technical literature, mostly books, and the current approaches of our time with fresh publications, mostly papers and two very recent conferences published in English.
2022, 32(6): 1110-1118.
doi: 10.1007/s11769-022-1285-1
Abstract:
The evolution of Holocene climate was investigated using grain size and magnetic susceptibility of the Holocene paleosols from Baicaoyuan (BCY), Xifeng (XF) and Linyou (LY) sections in the northwest, central and southern Chinese Loess Plateau (CLP). The results show that the Holocene in the BCY, XF and LY paleosol sections could be divided into three phases: during the early Holocene (11.8–10.5 kyr B. P.), increased magnetic susceptibility (χ) and frequency-dependent magnetic susceptibility (χfd) and decreased median grain size (Md) indicate that the East Asian Summer Monsoon (EASM) has become more intense and the climate has changed from cold to warm. During the middle Holocene (10.5–5.0 kyr B. P.), the values of χ, χfd and 2–5 µm grain-size fraction (GT2/5) are higher and Md and 30–63 µm grain-size fraction (GT30/63) are the lowest, which reflect a warm and humid regional climate. At ~ 8.0 kyr B. P., there was a transient dry-cold climatic spike corresponding to a Heinrich Event, the cold event was likely due to the collapse of the Laurentide ice sheet. During the late Holocene (5.0–0 kyr B. P.), χ and χfd values are the lowest, while Md and GT30/63 are high, as proxies of a weakened EASM, when the dry-cold climate prevailed in the region. Decreased irradiance since 5.0 kyr B.P. may have caused climatic cooling and drying. Spatially, the increased main peak values and skewness from BCY, XF to LY sections show that the grain size became fine, the East Asian Winter Monsoon (EAWM) reduced, and climate was warmer and wetter from northwest to southeast. In addition, Md can be used as alternative proxy for EAWM, while χfd is positive with the intensity of EASM under semiarid climate conditions in CLP.
The evolution of Holocene climate was investigated using grain size and magnetic susceptibility of the Holocene paleosols from Baicaoyuan (BCY), Xifeng (XF) and Linyou (LY) sections in the northwest, central and southern Chinese Loess Plateau (CLP). The results show that the Holocene in the BCY, XF and LY paleosol sections could be divided into three phases: during the early Holocene (11.8–10.5 kyr B. P.), increased magnetic susceptibility (χ) and frequency-dependent magnetic susceptibility (χfd) and decreased median grain size (Md) indicate that the East Asian Summer Monsoon (EASM) has become more intense and the climate has changed from cold to warm. During the middle Holocene (10.5–5.0 kyr B. P.), the values of χ, χfd and 2–5 µm grain-size fraction (GT2/5) are higher and Md and 30–63 µm grain-size fraction (GT30/63) are the lowest, which reflect a warm and humid regional climate. At ~ 8.0 kyr B. P., there was a transient dry-cold climatic spike corresponding to a Heinrich Event, the cold event was likely due to the collapse of the Laurentide ice sheet. During the late Holocene (5.0–0 kyr B. P.), χ and χfd values are the lowest, while Md and GT30/63 are high, as proxies of a weakened EASM, when the dry-cold climate prevailed in the region. Decreased irradiance since 5.0 kyr B.P. may have caused climatic cooling and drying. Spatially, the increased main peak values and skewness from BCY, XF to LY sections show that the grain size became fine, the East Asian Winter Monsoon (EAWM) reduced, and climate was warmer and wetter from northwest to southeast. In addition, Md can be used as alternative proxy for EAWM, while χfd is positive with the intensity of EASM under semiarid climate conditions in CLP.
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