Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information syst...Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.展开更多
We describe how the Unit-Feature Spatial Classification Method(UFSCM) can be used operationally to classify cloud types in satellite imagery efficiently and conveniently.By using a combination of Interactive Data Lang...We describe how the Unit-Feature Spatial Classification Method(UFSCM) can be used operationally to classify cloud types in satellite imagery efficiently and conveniently.By using a combination of Interactive Data Language(IDL) and Visual C++(VC) code in combination to extend the technique in three dimensions(3-D),this paper provides an efficient method to implement interactive computer visualization of the 3-D discrimination matrix modification,so as to deal with the bi-spectral limitations of traditional two dimensional(2-D) UFSCM.The case study of cloud-type classification based on FY-2C satellite data (0600 UTC 18 and 0000 UTC 10 September 2007) is conducted by comparison with ground station data, and indicates that 3-D UFSCM makes more use of the pattern recognition information in multi-spectral imagery,resulting in more reasonable results and an improvement over the 2-D method.展开更多
This paper puts forward a new conceptual idea on constructing an international central city in the Tumen River Economy Development Zone (TREDZ) on the basis of analysis of the superiorities and problems in developing...This paper puts forward a new conceptual idea on constructing an international central city in the Tumen River Economy Development Zone (TREDZ) on the basis of analysis of the superiorities and problems in developing city, and from the view point of present social, economic and natural conditions in this area and the background of Northeast Asia. The united international central city is the best distribution model not only in its polycentric spatial structure but also in organizing form. Its feasibility and practicability are thoroughly proved from various aspects including urban planning principles, comparison of port cities, special characteristics of cooperation in TREDZ, and natural, social, cultural factors etc.展开更多
This article analyzes The Kite Runner with the help of spactial narrative. The novel will be analyzed from three angles—the function of spatial narrative, the basic unit of spatial narrative, the periphery of spatial...This article analyzes The Kite Runner with the help of spactial narrative. The novel will be analyzed from three angles—the function of spatial narrative, the basic unit of spatial narrative, the periphery of spatial narrative and the overall effect presented in the novel by using these narrative techniques.展开更多
Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispen...Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their dif- ferences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area （SSCA）. SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km^2 to 35.1 km^2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force （Td） and slope of slope （SOS）, were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force （Td） and SOS and a loga- rithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can represent the development degree of local landforms. The critical stable regions of the Loess Plateau represent the degree of development of loess landforms. Its chief significance is that the per- ception of stable areas can be used to determine the minimal geographical unit.展开更多
The Northeast United States spring is indicative of major meteorological and biological change though the seasonal boundaries are difficult to define and may even be changing with global climate warming. This research...The Northeast United States spring is indicative of major meteorological and biological change though the seasonal boundaries are difficult to define and may even be changing with global climate warming. This research aims to obtain a synoptic meteorological definition of the spring season through an assessment of air mass frequency over the past 60 years. The validity of recent speculations that the onset and termination of spring have changed in recent decades with global change is also examined. The Spatial Synoptic Classification is utilized to define daily air masses over the region. Annual and seasonal baseline frequencies are identified and their differences are acquired to characterize the season. Seasonal frequency departures of the early and late segments of the period of record are calculated and examined for practical and statistical significance. The daily boundaries of early and late spring are also isolated and assessed across the period of record to identify important changes in the season’s initiation and termination through time. Results indicate that the Northeast spring season is dominated by dry air masses, mainly the Dry Moderate and Dry Polar types. Prior to 1975, more polar air masses are detected while after 1975 more moderate and tropical types are identified. Late spring is characterized by increased variability in all moist air mass frequencies. These findings indicate that, from a synoptic perspective, the season is dry through time but modern springs are also warmer than those of past decades and the initiation of the season is likely arriving earlier. The end of the season represents more variable day-to-day air mass conditions in modern times than detected in past decades.展开更多
基金financially supported by the National Natural Science Foundation of China (41471365,41531179)
文摘Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.
基金supported by the National Natural Science Foundation of China(Grant No.40875012)the National Basic Research Program of China(Grant No.2009CB421502)the Meteorology Open Fund of Huaihe River Basin(HRM200704).
文摘We describe how the Unit-Feature Spatial Classification Method(UFSCM) can be used operationally to classify cloud types in satellite imagery efficiently and conveniently.By using a combination of Interactive Data Language(IDL) and Visual C++(VC) code in combination to extend the technique in three dimensions(3-D),this paper provides an efficient method to implement interactive computer visualization of the 3-D discrimination matrix modification,so as to deal with the bi-spectral limitations of traditional two dimensional(2-D) UFSCM.The case study of cloud-type classification based on FY-2C satellite data (0600 UTC 18 and 0000 UTC 10 September 2007) is conducted by comparison with ground station data, and indicates that 3-D UFSCM makes more use of the pattern recognition information in multi-spectral imagery,resulting in more reasonable results and an improvement over the 2-D method.
文摘This paper puts forward a new conceptual idea on constructing an international central city in the Tumen River Economy Development Zone (TREDZ) on the basis of analysis of the superiorities and problems in developing city, and from the view point of present social, economic and natural conditions in this area and the background of Northeast Asia. The united international central city is the best distribution model not only in its polycentric spatial structure but also in organizing form. Its feasibility and practicability are thoroughly proved from various aspects including urban planning principles, comparison of port cities, special characteristics of cooperation in TREDZ, and natural, social, cultural factors etc.
文摘This article analyzes The Kite Runner with the help of spactial narrative. The novel will be analyzed from three angles—the function of spatial narrative, the basic unit of spatial narrative, the periphery of spatial narrative and the overall effect presented in the novel by using these narrative techniques.
基金Foundation： National Natural Science Foundation of China, No.41171299, No.41171320, No.41401237
文摘Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their dif- ferences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area （SSCA）. SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km^2 to 35.1 km^2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force （Td） and slope of slope （SOS）, were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force （Td） and SOS and a loga- rithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can represent the development degree of local landforms. The critical stable regions of the Loess Plateau represent the degree of development of loess landforms. Its chief significance is that the per- ception of stable areas can be used to determine the minimal geographical unit.
文摘The Northeast United States spring is indicative of major meteorological and biological change though the seasonal boundaries are difficult to define and may even be changing with global climate warming. This research aims to obtain a synoptic meteorological definition of the spring season through an assessment of air mass frequency over the past 60 years. The validity of recent speculations that the onset and termination of spring have changed in recent decades with global change is also examined. The Spatial Synoptic Classification is utilized to define daily air masses over the region. Annual and seasonal baseline frequencies are identified and their differences are acquired to characterize the season. Seasonal frequency departures of the early and late segments of the period of record are calculated and examined for practical and statistical significance. The daily boundaries of early and late spring are also isolated and assessed across the period of record to identify important changes in the season’s initiation and termination through time. Results indicate that the Northeast spring season is dominated by dry air masses, mainly the Dry Moderate and Dry Polar types. Prior to 1975, more polar air masses are detected while after 1975 more moderate and tropical types are identified. Late spring is characterized by increased variability in all moist air mass frequencies. These findings indicate that, from a synoptic perspective, the season is dry through time but modern springs are also warmer than those of past decades and the initiation of the season is likely arriving earlier. The end of the season represents more variable day-to-day air mass conditions in modern times than detected in past decades.
