Based on geomorphologic and digital elevation model(DEM) data, the topographic characteristics of the northwestern edge of the Qinghai-Tibet Plateau are analyzed. Five representative peaks are first determined accordi...Based on geomorphologic and digital elevation model(DEM) data, the topographic characteristics of the northwestern edge of the Qinghai-Tibet Plateau are analyzed. Five representative peaks are first determined according to the topographic profile maps for the ridge and piedmont lines, and then the topographic gradient characteristics are analyzed according to the representative topographic profile acquisition method.Based on the geomorphologic database data, the regions between the ridge and the piedmont lines are divided into four geomorphologic zones; and the topographic characteristics are finally analyzed for the different geomorphologic zones regions using the DEM data. The research results show that from the piedmont to the ridge, there exist four geomorphologic zones: arid, fluvial, periglacial and glacial. The arid has the lowest elevation, topographic gradient, relief and slope characteristics. The fluvial has lower elevation and the highest topographic gradient, but with lower relief and slope characteristics. With higher elevation, the periglcial has lower topographic gradient, but the highest relief and slope characteristics. The glacial has the highest elevation with higher topographic gradient, relief and slope characteristics.展开更多
A practical method to extract drainage network from DEM (digital elevation model) is introduced. DEM pretreatment includes depression and flat areas treatment. The flow direction of each grid cell in DEM is calculated...A practical method to extract drainage network from DEM (digital elevation model) is introduced. DEM pretreatment includes depression and flat areas treatment. The flow direction of each grid cell in DEM is calculated according to the 8-direction pour point model, and then the flow accumulation grid from the flow direction grid. With the flow accumulation grid, streams are defined according to the given threshold value of flow accumulation. Taking Gufo River watershed as an example, the extraction of drainage network was done from DEM. The results are basically consistent with the digitized drainage network from the relief maps.展开更多
The key aspect in planning and management of water resources is to analyze the runoff potential and erosion status of the river basin.For the detailed investigation of hydrological response freely available Cartosat-1...The key aspect in planning and management of water resources is to analyze the runoff potential and erosion status of the river basin.For the detailed investigation of hydrological response freely available Cartosat-1(IRS-P5) data was used for the preparation of digital elevation model(DEM).The runoff potential and type of erosive process of 22 river basins originating in the global biodiversity hotspot of Western Ghats,was inferred through hypsometric analysis.Several parameters like Hypsometric integral(HI),maximum concavity(Eh),coordinates of slope inflection point(I) given by a* and h* and normalized height of hypsometric curve(h) were extracted from the hypsometric curves and used for understanding the hydrological responses.From the hypsometric curves,the landform evolution processes were inferred.Contribution of diffusive and fluvial processes in slope degradation of the river basins was understood.Basins with lesser area(<100 km^2) were found to have a positive correlation between hypsometric integral and basin area,whereas for large basins no such correlation exists.Based on the study,river basins can be prioritized for the appropriate conservation measures.展开更多
Detailed soil surveys involve costly and time-consuming work and require expert knowledge. Since soil surveys provide information to meet a wide range of needs, new methods are necessary to map soils quickly and accur...Detailed soil surveys involve costly and time-consuming work and require expert knowledge. Since soil surveys provide information to meet a wide range of needs, new methods are necessary to map soils quickly and accurately. In this study, multilayer perceptron artificial neural networks(ANNs) were developed to map soil units using digital elevation model(DEM) attributes. Several optimal ANNs were produced based on a number of input data and hidden units. The approach used test and validation areas to calculate the accuracy of interpolated and extrapolated data. The results showed that the system and level of soil classification employed had a direct effect on the accuracy of the results. At the lowest level, smaller errors were observed with the World Reference Base(WRB)classification criteria than the Soil Taxonomy(ST) system, but more soil classes could be predicted when using ST(7 soils in the case of ST vs. 5 with WRB). Training errors were below 11% for all the ANN models applied, while the test error(interpolation error) and validation error(extrapolation error) were as high as 50% and 70%, respectively. As expected, soil prediction using a higher level of classification presented a better overall level of accuracy. To obtain better predictions, in addition to DEM attributes, data related to landforms and/or lithology as soil-forming factors, should be used as ANN input data.展开更多
Based on the estimating rule of the normal vector angles between two adjacent terrain units, we use the concept of terrain complexity factor to quantify the terrain complexity of DEM, and then the formula of terrain c...Based on the estimating rule of the normal vector angles between two adjacent terrain units, we use the concept of terrain complexity factor to quantify the terrain complexity of DEM, and then the formula of terrain complexity factor in Raster DEM and TIN DEM is deduced theoretically. In order to make clear how the terrain complexity factor ECF and the average elevation h affect the accuracy of DEM terrain representation RMSEEt, the formula of Gauss synthetical surface is applied to simulate several real terrain surfaces, each of which has different terrain complexity. Through the statistical analysis of linear regression in simula- tion data, the linear equation between accuracy of DEM terrain representation RMSEEt, terrain complexity factor ECF and the average elevation h is achieved. A new method is provided to estimate the accuracy of DEM terrain representation RMSEEt with a certain terrain complexity and it gives convincing theoretical evidence for DEM production and the corresponding error research in the future.展开更多
基金supported by the strategic plan project of science and technology of Institute of Geographic Sciences and Natural Resources Research (Grant No. 2012ZD009)the National Science Technology Support Plan Project (Grant No. 2012BAH28B01-03)+1 种基金the National Natural Science Foundation of China (Grant No. 41171332)the National Science Technology Basic Special Project (Grant No.2011FY110400-2)
文摘Based on geomorphologic and digital elevation model(DEM) data, the topographic characteristics of the northwestern edge of the Qinghai-Tibet Plateau are analyzed. Five representative peaks are first determined according to the topographic profile maps for the ridge and piedmont lines, and then the topographic gradient characteristics are analyzed according to the representative topographic profile acquisition method.Based on the geomorphologic database data, the regions between the ridge and the piedmont lines are divided into four geomorphologic zones; and the topographic characteristics are finally analyzed for the different geomorphologic zones regions using the DEM data. The research results show that from the piedmont to the ridge, there exist four geomorphologic zones: arid, fluvial, periglacial and glacial. The arid has the lowest elevation, topographic gradient, relief and slope characteristics. The fluvial has lower elevation and the highest topographic gradient, but with lower relief and slope characteristics. With higher elevation, the periglcial has lower topographic gradient, but the highest relief and slope characteristics. The glacial has the highest elevation with higher topographic gradient, relief and slope characteristics.
文摘A practical method to extract drainage network from DEM (digital elevation model) is introduced. DEM pretreatment includes depression and flat areas treatment. The flow direction of each grid cell in DEM is calculated according to the 8-direction pour point model, and then the flow accumulation grid from the flow direction grid. With the flow accumulation grid, streams are defined according to the given threshold value of flow accumulation. Taking Gufo River watershed as an example, the extraction of drainage network was done from DEM. The results are basically consistent with the digitized drainage network from the relief maps.
文摘The key aspect in planning and management of water resources is to analyze the runoff potential and erosion status of the river basin.For the detailed investigation of hydrological response freely available Cartosat-1(IRS-P5) data was used for the preparation of digital elevation model(DEM).The runoff potential and type of erosive process of 22 river basins originating in the global biodiversity hotspot of Western Ghats,was inferred through hypsometric analysis.Several parameters like Hypsometric integral(HI),maximum concavity(Eh),coordinates of slope inflection point(I) given by a* and h* and normalized height of hypsometric curve(h) were extracted from the hypsometric curves and used for understanding the hydrological responses.From the hypsometric curves,the landform evolution processes were inferred.Contribution of diffusive and fluvial processes in slope degradation of the river basins was understood.Basins with lesser area(<100 km^2) were found to have a positive correlation between hypsometric integral and basin area,whereas for large basins no such correlation exists.Based on the study,river basins can be prioritized for the appropriate conservation measures.
文摘Detailed soil surveys involve costly and time-consuming work and require expert knowledge. Since soil surveys provide information to meet a wide range of needs, new methods are necessary to map soils quickly and accurately. In this study, multilayer perceptron artificial neural networks(ANNs) were developed to map soil units using digital elevation model(DEM) attributes. Several optimal ANNs were produced based on a number of input data and hidden units. The approach used test and validation areas to calculate the accuracy of interpolated and extrapolated data. The results showed that the system and level of soil classification employed had a direct effect on the accuracy of the results. At the lowest level, smaller errors were observed with the World Reference Base(WRB)classification criteria than the Soil Taxonomy(ST) system, but more soil classes could be predicted when using ST(7 soils in the case of ST vs. 5 with WRB). Training errors were below 11% for all the ANN models applied, while the test error(interpolation error) and validation error(extrapolation error) were as high as 50% and 70%, respectively. As expected, soil prediction using a higher level of classification presented a better overall level of accuracy. To obtain better predictions, in addition to DEM attributes, data related to landforms and/or lithology as soil-forming factors, should be used as ANN input data.
基金Supported by Innovation Program of Shanghai Municipal Education Commission (No.10ZZ25)the Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping (No.200914)
文摘Based on the estimating rule of the normal vector angles between two adjacent terrain units, we use the concept of terrain complexity factor to quantify the terrain complexity of DEM, and then the formula of terrain complexity factor in Raster DEM and TIN DEM is deduced theoretically. In order to make clear how the terrain complexity factor ECF and the average elevation h affect the accuracy of DEM terrain representation RMSEEt, the formula of Gauss synthetical surface is applied to simulate several real terrain surfaces, each of which has different terrain complexity. Through the statistical analysis of linear regression in simula- tion data, the linear equation between accuracy of DEM terrain representation RMSEEt, terrain complexity factor ECF and the average elevation h is achieved. A new method is provided to estimate the accuracy of DEM terrain representation RMSEEt with a certain terrain complexity and it gives convincing theoretical evidence for DEM production and the corresponding error research in the future.
