Historical cropland datasets are fundamental for quantifying the effects of human land use activities on climatic change and the carbon cycle. Two representative global land-use datasets, the Global Land Use Database ...Historical cropland datasets are fundamental for quantifying the effects of human land use activities on climatic change and the carbon cycle. Two representative global land-use datasets, the Global Land Use Database (termed SAGE dataset) and the Historical Database of the Global Environment (termed HYDE dataset) have been established and used widely. Despite improvement of data quality and methodologies for extracting historical land use information, certain dataset limitations exist that need to be quantified and communicated to users so that they can make informed decisions on whether and how these land-use products should be used. The Cropland data of Northeast China (CNEC) is based on calibrated historical data and a multi-sourced data conversion model, and reconstructs cropland cover change in Northeast China over the last 300 years. Us- ing the CNEC as a reference, we evaluated the accuracy of cropland cover for SAGE and HYDE in Northeast China at spatial scales ranging from the entire Northeast China to provinces and even individual raster grid cells. Neither SAGE nor HYDE reflects real historical land reclamation. Cropland areas in SAGE are overestimated by 20.98 times in 1700 to 1.6 times in 1990. Although HYDE is better, there are significant disagreements in cropland area and distribution between HYDE and CNEC, especially in the 18th and 19th centuries. The proportion of total grid cells whose relative error was greater than 100% was 63.55% in 1700 and 53.27% in 1780. Global cropland dataset errors over Northeast China originate mainly from both the reverse calculation method for historical cropland data based on modern spatial patterns, and modern land-use outputs from satellite data.展开更多
Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, seve...Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.展开更多
Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this stud...Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.展开更多
Non-alcoholic fatty liver disease(NAFLD)is among the most frequent etiologies of cirrhosis worldwide,and it is associated with features of metabolic syndrome;the key factor influencing its prognosis is the progression...Non-alcoholic fatty liver disease(NAFLD)is among the most frequent etiologies of cirrhosis worldwide,and it is associated with features of metabolic syndrome;the key factor influencing its prognosis is the progression of liver fibrosis.This review aimed to propose a practical and stepwise approach to the evaluation and management of liver fibrosis in patients with NAFLD,analyzing the currently available literature.In the assessment of NAFLD patients,it is important to identify clinical,genetic,and environmental determinants of fibrosis development and its progression.To properly detect fibrosis,it is important to take into account the available methods and their supporting scientific evidence to guide the approach and the sequential selection of the best available biochemical scores,followed by a complementary imaging study(transient elastography,magnetic resonance elastography or acoustic radiation force impulse)and finally a liver biopsy,when needed.To help with the selection of the most appropriate method a Fagan′s nomogram analysis is provided in this review,describing the diagnostic yield of each method and their post-test probability of detecting liver fibrosis.Finally,treatment should always include diet and exercise,as well as controlling the components of the metabolic syndrome,+/-vitamin E,considering the presence of sleep apnea,and when available,allocate those patients with advanced fibrosis or high risk of progression into clinical trials.The final end of this approach should be to establish an opportune diagnosis and treatment of liver fibrosis in patients with NAFLD,aiming to decrease/stop its progression and improve their prognosis.展开更多
Spatially explicit modeling plays a vital role in land use/cover change and urbanization research as well as resources management;however,current models lack proper validation and fail to incorporate uncertainty into ...Spatially explicit modeling plays a vital role in land use/cover change and urbanization research as well as resources management;however,current models lack proper validation and fail to incorporate uncertainty into the formulation of model predictions.Consequently,policy makers and the general public may develop opinions based on potentially misleading research,which fails to allow for truly informed decisions.Here we use an uncertainty strategy of spatially explicit modeling combined with the series statistic of Kappa index for location and quantity to estimate the uncertainty of future predications and to determine model accuracy.We take the Beijing metropolitan area as an example to demonstrate the uncertainty in extrapolations of predictive land use change and urban sprawl with spatially explicit modeling at multiple resolutions.The sensitivity of scale effects is also discussed.The results show that an improvement in specification of location is more helpful in increasing accuracy as compared to an improvement in the specification of quantity at fine spatial resolutions.However,the spatial scale has great effects on modeling accuracy and correct due to chance tends to increase as resolution becomes coarser.The results allow us to understand the uncertainty when using spatially explicit models for land-use change or urbanization estimates.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos.40571165,40901099)Beijing Normal University Independent Research Fund (Grant No.2009SAP-2)National Key Technology R & D Program (Grant No.2007BAC03A11)
文摘Historical cropland datasets are fundamental for quantifying the effects of human land use activities on climatic change and the carbon cycle. Two representative global land-use datasets, the Global Land Use Database (termed SAGE dataset) and the Historical Database of the Global Environment (termed HYDE dataset) have been established and used widely. Despite improvement of data quality and methodologies for extracting historical land use information, certain dataset limitations exist that need to be quantified and communicated to users so that they can make informed decisions on whether and how these land-use products should be used. The Cropland data of Northeast China (CNEC) is based on calibrated historical data and a multi-sourced data conversion model, and reconstructs cropland cover change in Northeast China over the last 300 years. Us- ing the CNEC as a reference, we evaluated the accuracy of cropland cover for SAGE and HYDE in Northeast China at spatial scales ranging from the entire Northeast China to provinces and even individual raster grid cells. Neither SAGE nor HYDE reflects real historical land reclamation. Cropland areas in SAGE are overestimated by 20.98 times in 1700 to 1.6 times in 1990. Although HYDE is better, there are significant disagreements in cropland area and distribution between HYDE and CNEC, especially in the 18th and 19th centuries. The proportion of total grid cells whose relative error was greater than 100% was 63.55% in 1700 and 53.27% in 1780. Global cropland dataset errors over Northeast China originate mainly from both the reverse calculation method for historical cropland data based on modern spatial patterns, and modern land-use outputs from satellite data.
文摘Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.
文摘Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.
文摘Non-alcoholic fatty liver disease(NAFLD)is among the most frequent etiologies of cirrhosis worldwide,and it is associated with features of metabolic syndrome;the key factor influencing its prognosis is the progression of liver fibrosis.This review aimed to propose a practical and stepwise approach to the evaluation and management of liver fibrosis in patients with NAFLD,analyzing the currently available literature.In the assessment of NAFLD patients,it is important to identify clinical,genetic,and environmental determinants of fibrosis development and its progression.To properly detect fibrosis,it is important to take into account the available methods and their supporting scientific evidence to guide the approach and the sequential selection of the best available biochemical scores,followed by a complementary imaging study(transient elastography,magnetic resonance elastography or acoustic radiation force impulse)and finally a liver biopsy,when needed.To help with the selection of the most appropriate method a Fagan′s nomogram analysis is provided in this review,describing the diagnostic yield of each method and their post-test probability of detecting liver fibrosis.Finally,treatment should always include diet and exercise,as well as controlling the components of the metabolic syndrome,+/-vitamin E,considering the presence of sleep apnea,and when available,allocate those patients with advanced fibrosis or high risk of progression into clinical trials.The final end of this approach should be to establish an opportune diagnosis and treatment of liver fibrosis in patients with NAFLD,aiming to decrease/stop its progression and improve their prognosis.
基金supported by China Postdoctoral Science Foundation (Grant No.20070420630)National Basic Research Program of China (Grant Nos.2002CB412507,G19990435)
文摘Spatially explicit modeling plays a vital role in land use/cover change and urbanization research as well as resources management;however,current models lack proper validation and fail to incorporate uncertainty into the formulation of model predictions.Consequently,policy makers and the general public may develop opinions based on potentially misleading research,which fails to allow for truly informed decisions.Here we use an uncertainty strategy of spatially explicit modeling combined with the series statistic of Kappa index for location and quantity to estimate the uncertainty of future predications and to determine model accuracy.We take the Beijing metropolitan area as an example to demonstrate the uncertainty in extrapolations of predictive land use change and urban sprawl with spatially explicit modeling at multiple resolutions.The sensitivity of scale effects is also discussed.The results show that an improvement in specification of location is more helpful in increasing accuracy as compared to an improvement in the specification of quantity at fine spatial resolutions.However,the spatial scale has great effects on modeling accuracy and correct due to chance tends to increase as resolution becomes coarser.The results allow us to understand the uncertainty when using spatially explicit models for land-use change or urbanization estimates.
