Sampling and testing are conducted on groundwater depth and vegetation coverage in the 670 km2 of the Sangong River Basin and semi-variance function analysis is made afterwards on the data obtained by the application ...Sampling and testing are conducted on groundwater depth and vegetation coverage in the 670 km2 of the Sangong River Basin and semi-variance function analysis is made afterwards on the data obtained by the application of geo-statistics. Results showed that the variance curve of the groundwater depth and vegetation coverage displays an exponential model. Analysis of sampling data in 2003 indicates that the groundwater depth and vegetation coverage change similarly in space in this area. The Sangong River Basin is composed of upper oasis, middle ecotone and lower sand dune. In oasis and ecotone, influenced by irrigation of the adjoining oasis, groundwater level has been raised and soil water content also increased compared with sand dune nearby, vegetation developed well. But in the lower reaches of the Sangong River Basin, because of descending of groundwater level, soil water content decreased and vegetation degenerated. From oasis to abandoned land and desert grassland, vegetation coverage and groundwater level changed greatly with significant difference respectively in spatial variation. Distinct but similar spatial variability exists among the groundwater depth and vegetation coverage in the study area, namely, the vegetation coverage decreasing (increasing) as the groundwater depth increases (decreases). This illustrates the great dependence of vegetation coverage on groundwater depth in arid regions and further implies that among the great number of factors affecting vegetation coverage in arid regions, groundwater depth turns out to be the most determinant one.展开更多
Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derive...Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Dif- ferent classification schemes are a key obstacle to the comparison of products and are considered the main fac- tor behind the disagreement among the different products. Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer （MODIS）, Global Land Cover 2000 （GLC2000）, and the National Land Cover/Use Data- sets （NLCD） products, and the author assessed the prod- ucts by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones, while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation. The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agree- ment or accuracy varied significantly. The high-agreement classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru- bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agree- ment could be partly explained by the complex landscapes, mixed vegetation, low separability of spectro-temporal- texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.展开更多
The Arctic sea ice minimum records appeared in the Septembers of 2007 and 2012, followed by high snow cover areas in the Northern Hemisphere winters. The snow cover distributions show different spatial patterns in the...The Arctic sea ice minimum records appeared in the Septembers of 2007 and 2012, followed by high snow cover areas in the Northern Hemisphere winters. The snow cover distributions show different spatial patterns in these two years: increased snow cover in Central Asia and Central North America in 2007, while increased snow cover in East Asia and northwestern Europe in 2012. The high snow cover anomaly shifted to higher latitudes in winter of 2012 compared to 2007. It is noticed that the snow cover had positive anomaly in 2007 and 2012 with the following conditions: the negative geopotential height and the related cyclonic wind anomaly were favorable for upwelling, and, with the above conditions, the low troposphere and surface air temperature anomaly and water vapor anomaly were favorable for the formation and maintenance of snowfalls. The negative geopotential height, cyclonic wind and low air temperature conditions were satisfied in different locations in 2007 and 2012, resulting in different spatial snow cover patterns. The cross section of lower air temperature move to higher latitudes in winter of 2012 compared to 2007.展开更多
A detailed investigation on 3D spatial distribution rules of Banded Iron-bearing Formation(BIF) with methods of gravity-magnetic inversion and 3D modeling of iron mine is presented based on the former analysis in the ...A detailed investigation on 3D spatial distribution rules of Banded Iron-bearing Formation(BIF) with methods of gravity-magnetic inversion and 3D modeling of iron mine is presented based on the former analysis in the Anshan-Benxi area.Three dimension spatial distribution types of BIF are concluded as hook-like,tabularlike and "W"-like.BIF was mainly developed in three types of space including(1) the syncline cores,(2)cover coverage area,and(3) the deeper buried area where the range of tectonic uplift is small.The influences of tectonism,magmatic intrusion and uplift-erosion on the spatial distribution shapes of BIF are clarified.展开更多
There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling ...There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.展开更多
基金National 973 Program for Basic Research No.G1999043506
文摘Sampling and testing are conducted on groundwater depth and vegetation coverage in the 670 km2 of the Sangong River Basin and semi-variance function analysis is made afterwards on the data obtained by the application of geo-statistics. Results showed that the variance curve of the groundwater depth and vegetation coverage displays an exponential model. Analysis of sampling data in 2003 indicates that the groundwater depth and vegetation coverage change similarly in space in this area. The Sangong River Basin is composed of upper oasis, middle ecotone and lower sand dune. In oasis and ecotone, influenced by irrigation of the adjoining oasis, groundwater level has been raised and soil water content also increased compared with sand dune nearby, vegetation developed well. But in the lower reaches of the Sangong River Basin, because of descending of groundwater level, soil water content decreased and vegetation degenerated. From oasis to abandoned land and desert grassland, vegetation coverage and groundwater level changed greatly with significant difference respectively in spatial variation. Distinct but similar spatial variability exists among the groundwater depth and vegetation coverage in the study area, namely, the vegetation coverage decreasing (increasing) as the groundwater depth increases (decreases). This illustrates the great dependence of vegetation coverage on groundwater depth in arid regions and further implies that among the great number of factors affecting vegetation coverage in arid regions, groundwater depth turns out to be the most determinant one.
基金supported by the National Basic Research Program of China (Grant No. 2009CB723904)the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA05090201)the National Natural Science Foundation of China (Grant No. 40810059003)
文摘Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Dif- ferent classification schemes are a key obstacle to the comparison of products and are considered the main fac- tor behind the disagreement among the different products. Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer （MODIS）, Global Land Cover 2000 （GLC2000）, and the National Land Cover/Use Data- sets （NLCD） products, and the author assessed the prod- ucts by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones, while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation. The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agree- ment or accuracy varied significantly. The high-agreement classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru- bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agree- ment could be partly explained by the complex landscapes, mixed vegetation, low separability of spectro-temporal- texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.
基金supported by the Project of Comprehensive Evaluation of Polar Areas on Global and Regional Climate Changes (CHINARE2015-04-04)the National Natural Science Foundation of China (Grant No. 41406027)+1 种基金the NSFC-Shandong Joint Fund for Marine Science Research Centers (Grant No. U1406404)the international cooperation project of Indo-Pacific ocean environment variation and air-sea interaction (Grant No. GASI-03-IPOVAI-05)
文摘The Arctic sea ice minimum records appeared in the Septembers of 2007 and 2012, followed by high snow cover areas in the Northern Hemisphere winters. The snow cover distributions show different spatial patterns in these two years: increased snow cover in Central Asia and Central North America in 2007, while increased snow cover in East Asia and northwestern Europe in 2012. The high snow cover anomaly shifted to higher latitudes in winter of 2012 compared to 2007. It is noticed that the snow cover had positive anomaly in 2007 and 2012 with the following conditions: the negative geopotential height and the related cyclonic wind anomaly were favorable for upwelling, and, with the above conditions, the low troposphere and surface air temperature anomaly and water vapor anomaly were favorable for the formation and maintenance of snowfalls. The negative geopotential height, cyclonic wind and low air temperature conditions were satisfied in different locations in 2007 and 2012, resulting in different spatial snow cover patterns. The cross section of lower air temperature move to higher latitudes in winter of 2012 compared to 2007.
文摘A detailed investigation on 3D spatial distribution rules of Banded Iron-bearing Formation(BIF) with methods of gravity-magnetic inversion and 3D modeling of iron mine is presented based on the former analysis in the Anshan-Benxi area.Three dimension spatial distribution types of BIF are concluded as hook-like,tabularlike and "W"-like.BIF was mainly developed in three types of space including(1) the syncline cores,(2)cover coverage area,and(3) the deeper buried area where the range of tectonic uplift is small.The influences of tectonism,magmatic intrusion and uplift-erosion on the spatial distribution shapes of BIF are clarified.
基金supported by the National Natural Science Foundation of China(Grant Nos.41272359&11001019)the Specialized Research Fund for the Doctoral Program of Higher Education(SRFDP)the Fundamental Research Funds for the Central Universities
文摘There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.
