Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and...Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.展开更多
Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land ...Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.展开更多
Groundwater is the main source of water in the studied area;therefore, it is significantly requested in all the activities of the inhabitants. These natural resources are affected by some drivers especially Land Use/L...Groundwater is the main source of water in the studied area;therefore, it is significantly requested in all the activities of the inhabitants. These natural resources are affected by some drivers especially Land Use/Land Cover (LULC) and Climate Change. A Land Use/Land Cover (LULC) dynamics study is crucial for any global environmental change evaluation. For instance, for a given place, its change could affect considerably water cycle components. Therefore, the knowledge of the effects of LULC on groundwater recharge is then the key in water resources management system, in particular for the decision makers of the Koda Catchment where the scarcity of the water availability for agriculture is real. The spatiotemporal variation of the different units of LULC present in the catchment has been examined in this study. The Envi 4.5 Software coupled with ArcGIS using the Supervised Classification method, was applied to subset Landsat images from 1990 to 2016. Five (5) major LULC categories, cultivated land, bare land, herbaceous savannah, shrubby savannah and degraded savannah, were identified in the catchment. In a parallel direction, the groundwater recharge has been estimated through the conceptual Gardenia model for the same period 1990-2016. The results showed that the portion of cultivated land and bare land increased (14.9% and 23.5% respectively) while, the portion of savannah decreased: herbaceous savannah by 24.4%, degraded savannah by 10.32% and Shrubby Savannah by 3.6%. Savannah areas in Koda catchment is converted to agricultural land and urban area due to human activities. The decline of 8.4% in groundwater recharge might become so far obvious in the future if the current rate of deforestation continues in the Koda catchment. There is a need to closely monitor the changes in LULC for sustainable development. The results of this study could help to well understand the recharge pattern across Koda catchment under a changing LULC.展开更多
The Upper Chongwe River Catchment has recently been overexploited for water resources with increased complaints by various water users about the deteriorating quality of surface water within the sub-catchment. This st...The Upper Chongwe River Catchment has recently been overexploited for water resources with increased complaints by various water users about the deteriorating quality of surface water within the sub-catchment. This study was motivated by the need to investigate and understand the response of surface water quality to land use land cover (LULC) change due to urbanization. Water samples, collected at 9 sampling sites from 2006 to 2017, were analyzed for water quality using the weighted arithmetic water quality index and trend using the Mann-Kendall statistics. LULC change is detected and analyzed in ERDAS Imagine 2014 and ArcGIS 10.4 using 2006 Landsat 5 TM and 2017 Landsat 8 OLI imageries. The relationship between LULC change and water quality was performed with multiple regression analysis and Pearson correlation. The results reveal that Built-up area, Grassland and surface water increased by 5.48%, 13.34% and 0.03% respectively while Agricultural land and Forest Land decreased by <span style="white-space:nowrap;">−</span>13.41% and <span style="white-space:nowrap;">−</span>5.42% respectively. The water quality index ranged from 43.04 to 110.40 in 2006 and from 170 to 430 in 2017 indicating a deterioration in the quality of surface water from good to unsuitable for drinking at all the sampled sites. Built-up/bare lands exhibited a significant positive correlation with EC (<em>R<sup>2</sup></em> = 0.61, p ≤ 0.05), turbidity (<em>R<sup>2</sup></em><sup> </sup>= 0.69, p ≤ 0.05), TDS (<em>R<sup>2</sup></em> = 0.61, p ≤ 0.05), Cl (<em>R<sup>2</sup></em> = 0.62, p ≤ 0.05) and a significant negative correlation with NH<sub>4</sub> (<em>R<sup>2</sup></em> = <span style="white-space:nowrap;">−</span>0.729, p ≤ 0.05). Agriculture exhibited a significant positive correlation with turbidity (<em>R<sup>2</sup></em> = 0.71, p ≤ 0.01) and Fe (<em>R<sup>2</sup></em> = 0.75, p ≤ 0.01. Forest cover correlated negatively with most of the water quality parameters apart from Fe, DO, NO<sub>3</sub> but was not statistically significant. Grassland had a significant negative correlation with temperature (<em>R<sup>2</sup></em> = <span style="white-space:nowrap;">−</span>0.68, p ≤ 0.05). Clearly, urbanization has made a disproportionately strong contribution to the deterioration of surface water quality indicating that intensive anthropogenic activities exacerbate water quality degradation. These results provide essential information for land use planners and water managers towards sustainable and equitable management of limited water resources.展开更多
The climate change and Land Use/Land Cover(LULC)change both have an important impact on the rainfall-runoff processes.How to quantitatively distinguish and predict the impacts of the above two factors has been a hot s...The climate change and Land Use/Land Cover(LULC)change both have an important impact on the rainfall-runoff processes.How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources.In this research,the SWAT(Soil and Water Assessment Tool)model was established for the Jinsha River Basin,and the method of scenarios simulation was used to study the runoff response to climate change and LULC change.Furthermore,the climate variables exported from 7 typical General Circulation Models(GCMs)under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017-2050.Results showed that:(1)During the past 57 years,the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious.(2)Compared with the significant increase of temperature in the Jinsha River Basin,the LULC change was very small.(3)During the historical period,the LULC change had little effect on the hydrological processes in the basin,and climate change was one of the main factors affecting runoff.(4)In the context of global climate change,the precipitation,temperature and runoff in the Jinsha River Basin will rise in 2017-2050 compared with the historical period.This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.展开更多
基金partly funded by the National Key Research and Development Program of China(NK2023190801)the National Foreign Experts Program of China(G2023041024L)the Key Scientific Research Program of Shaanxi Provincial Education Department,China(21JT028)。
文摘Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.
基金the University Grants Commission,New Delhi,India,for providing financial support in the form of the Junior Research Fellowship。
文摘Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.
文摘Groundwater is the main source of water in the studied area;therefore, it is significantly requested in all the activities of the inhabitants. These natural resources are affected by some drivers especially Land Use/Land Cover (LULC) and Climate Change. A Land Use/Land Cover (LULC) dynamics study is crucial for any global environmental change evaluation. For instance, for a given place, its change could affect considerably water cycle components. Therefore, the knowledge of the effects of LULC on groundwater recharge is then the key in water resources management system, in particular for the decision makers of the Koda Catchment where the scarcity of the water availability for agriculture is real. The spatiotemporal variation of the different units of LULC present in the catchment has been examined in this study. The Envi 4.5 Software coupled with ArcGIS using the Supervised Classification method, was applied to subset Landsat images from 1990 to 2016. Five (5) major LULC categories, cultivated land, bare land, herbaceous savannah, shrubby savannah and degraded savannah, were identified in the catchment. In a parallel direction, the groundwater recharge has been estimated through the conceptual Gardenia model for the same period 1990-2016. The results showed that the portion of cultivated land and bare land increased (14.9% and 23.5% respectively) while, the portion of savannah decreased: herbaceous savannah by 24.4%, degraded savannah by 10.32% and Shrubby Savannah by 3.6%. Savannah areas in Koda catchment is converted to agricultural land and urban area due to human activities. The decline of 8.4% in groundwater recharge might become so far obvious in the future if the current rate of deforestation continues in the Koda catchment. There is a need to closely monitor the changes in LULC for sustainable development. The results of this study could help to well understand the recharge pattern across Koda catchment under a changing LULC.
文摘The Upper Chongwe River Catchment has recently been overexploited for water resources with increased complaints by various water users about the deteriorating quality of surface water within the sub-catchment. This study was motivated by the need to investigate and understand the response of surface water quality to land use land cover (LULC) change due to urbanization. Water samples, collected at 9 sampling sites from 2006 to 2017, were analyzed for water quality using the weighted arithmetic water quality index and trend using the Mann-Kendall statistics. LULC change is detected and analyzed in ERDAS Imagine 2014 and ArcGIS 10.4 using 2006 Landsat 5 TM and 2017 Landsat 8 OLI imageries. The relationship between LULC change and water quality was performed with multiple regression analysis and Pearson correlation. The results reveal that Built-up area, Grassland and surface water increased by 5.48%, 13.34% and 0.03% respectively while Agricultural land and Forest Land decreased by <span style="white-space:nowrap;">−</span>13.41% and <span style="white-space:nowrap;">−</span>5.42% respectively. The water quality index ranged from 43.04 to 110.40 in 2006 and from 170 to 430 in 2017 indicating a deterioration in the quality of surface water from good to unsuitable for drinking at all the sampled sites. Built-up/bare lands exhibited a significant positive correlation with EC (<em>R<sup>2</sup></em> = 0.61, p ≤ 0.05), turbidity (<em>R<sup>2</sup></em><sup> </sup>= 0.69, p ≤ 0.05), TDS (<em>R<sup>2</sup></em> = 0.61, p ≤ 0.05), Cl (<em>R<sup>2</sup></em> = 0.62, p ≤ 0.05) and a significant negative correlation with NH<sub>4</sub> (<em>R<sup>2</sup></em> = <span style="white-space:nowrap;">−</span>0.729, p ≤ 0.05). Agriculture exhibited a significant positive correlation with turbidity (<em>R<sup>2</sup></em> = 0.71, p ≤ 0.01) and Fe (<em>R<sup>2</sup></em> = 0.75, p ≤ 0.01. Forest cover correlated negatively with most of the water quality parameters apart from Fe, DO, NO<sub>3</sub> but was not statistically significant. Grassland had a significant negative correlation with temperature (<em>R<sup>2</sup></em> = <span style="white-space:nowrap;">−</span>0.68, p ≤ 0.05). Clearly, urbanization has made a disproportionately strong contribution to the deterioration of surface water quality indicating that intensive anthropogenic activities exacerbate water quality degradation. These results provide essential information for land use planners and water managers towards sustainable and equitable management of limited water resources.
基金National Key Research and Development Program of China,N.2017YFA0603702National Natural Science Foundation of China,No.51539009,No.51339004。
文摘The climate change and Land Use/Land Cover(LULC)change both have an important impact on the rainfall-runoff processes.How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources.In this research,the SWAT(Soil and Water Assessment Tool)model was established for the Jinsha River Basin,and the method of scenarios simulation was used to study the runoff response to climate change and LULC change.Furthermore,the climate variables exported from 7 typical General Circulation Models(GCMs)under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017-2050.Results showed that:(1)During the past 57 years,the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious.(2)Compared with the significant increase of temperature in the Jinsha River Basin,the LULC change was very small.(3)During the historical period,the LULC change had little effect on the hydrological processes in the basin,and climate change was one of the main factors affecting runoff.(4)In the context of global climate change,the precipitation,temperature and runoff in the Jinsha River Basin will rise in 2017-2050 compared with the historical period.This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.