共查询到20条相似文献，搜索用时 297 毫秒
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坡度指标通常基于DEM数据以固定算法直接提取。坡度误差主要来源于算法模型误差和数据误差等,很少顾及在建立DEM时空间参考系方向的变化引起的坡度差异。本文以数学高斯曲面为基准,通过改变参考系X、Y轴方向,对不同参考系下的DEM数据以三阶反距离平方权差分坡度算法提取坡度并分析其差异,结果表明:1.空间参考系方向变化对坡度差异的影响与地表剖面曲率有关,在山顶、谷底以及鞍部等坡度变化较为明显的地形区域,较为显著,两者成一定的正相关,而且与坡向变化率也存在相关关系。2.坡度、坡向差异随着空间参考系方向变化呈现周期性,周期为90°,近似按正弦(y=a·sin(1/2kπ+φ)φ∈[0,π/2])规律变化,在45°处达到峰值,而在0°与90°附近,6°范围内平均差异变化较为平缓,但与正弦曲线偏离较大,且随着空间分辨率的降低,参考系方向引起的坡度、坡向差异有增加的趋势。实验表明在研究区建立独立参考系时应顺应平均坡向原则,以减小参考系方向对坡度、坡向的影响。 相似文献
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以浙江省仙居县为实验样区,通过气温空间分布的地形调节统计模型,使用10个气象站(哨)气温资料和4种不同空间分辨率的DEM(5 m,源于1∶1万数字化地形图;30 m,来源于Aster GDEM v2;90 m,来源于SRTMv4.1;900 m,源于GTOPO30’)模拟不同空间尺度年均气温空间分布,比较其误差大小及随宏观地形(海拔高度)和微观地形(坡度和坡向)的分布差异。结果表明:基于4种不同空间分辨率DEM模拟气温呈较大空间分布差异性;随着DEM空间分辨率减小,误差逐渐增加,空间差异性降低。微观地形因子(坡度和坡向)随空间分辨率的变化产生显著变化,明显影响气温空间分布,不同坡度和坡向间年均气温差最高可达到10～12.5℃,最小仅为1.9～2.6℃。 相似文献
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以浙江省仙居县为实验区,通过气温空间分布的地形调节统计模型,并使用了10个气象站(哨)的气温资料和不同空间分辨率的DEM(均来源于1:1万的数字化地形图),模拟了不同空间尺度的年平均气温空间分布,比较了它们的误差大小以及随宏观地形(海拔)和微观地形(坡度和坡向)的分布差异.结果表明:基于不同空间分辨率DEM模拟的平均气温呈现较大的空间分布差异性;随着DEM空间分辨率的减小,误差逐渐增加(最大绝对误差为2.04℃,相对误差为15.10％),且空间差异性降低.而且微观地形因子(坡度和坡向)随着空间分辨率的变化产生显著变化,进而明显影响气温的空间分布,不同坡度之间的年平均气温差最大为9.5℃,最小为1.8℃.不同坡向之间的年平均气温差最大为12.2℃,最小为2.4℃. 相似文献
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DEM采样间隔对地形描述精度的影响研究 总被引：1，自引：0，他引：1
数字高程模型(DEM)的精度包括采样点数据精度和地形描述精度两方面,前人对DEM精度的研究多集中在DEM采样点精度,而忽视了地形描述精度。该文提出基于窗口曲面拟合计算拟合曲面系列参数与"实际地形"曲面参数的标准差来衡量地形描述精度的方法,研究发现DEM地形描述精度随采样间隔的增大呈降低趋势;并利用坡度频率曲线和坡度累计频率曲线研究对DEM精度敏感的坡度因子与DEM采样间隔的关系,认为随DEM采样间隔增大,坡度衰减(变缓)的速率加快。 相似文献
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DEM结构特征对坡度坡向的影响分析 总被引：12，自引：0，他引：12
数字高程模型已严格定义为按规则格网阵列记录的地形高程数据,其固有的结构特征(如格网分辨率、格网方向、高程数据准确度等)直接影响DEM对地形表达和坡度、坡向的计算精度。该文通过理论和数据独立的DEM实验分析方法,研究了DEM结构特征对坡度、坡向的影响,得出如下结论:1)高分辨率的DEM并不一定能给出高精度的坡度、坡向计算结果;2)可通过g=bm/ms×180/π×cos2S来选择合适的DEM分辨率;3)三阶不带权差分算法的坡度、坡向计算结果对DEM方向有较强的依赖性。 相似文献
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局部曲面拟合法是基于DEM的计算坡度的常用方法之一,采用不同的拟合曲面和局部移动窗口将得到不同精度的计算模型,探索不同的局部窗口类型可以丰富局部曲面拟合法在数字地形分析中的应用。本文考虑不同距离临近点的高程信息,基于3×3局部窗口提出了一种由两种不同倍率、与主轴(x轴、y轴)呈45°夹角的格网点构成的新窗口——对称13点局部窗口,推导了三阶曲面拟合该窗口的坡度计算公式,并利用典型数学曲面对该模型的计算精度进行了分析。研究分析认为,相对于现有的坡度计算模型,三阶曲面拟合对称13点窗口模型能显著地提高坡度计算精度,但对误差的平滑能力较差,适用于高精度DEM。本文的研究扩展了曲面拟合法在数字地形分析中的应用。 相似文献
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基于室内人工降雨试验条件下获取的黄土坡面侵蚀的九期DEM数据，计算出不同演化时期黄土坡面的坡度、坡向及沟道网络，利用等分坡度直方图、等分坡向玫瑰花图和沟道分级网络对坡面侵蚀变异特征进行研究，并初步分析了该变异特征与黄土坡面侵蚀和演化过程之间的关系。结果表明：在黄土坡面侵蚀过程中，该坡面的坡度离散程度在逐步增加后基本保持稳定；其主导坡向总体呈现逐步有序化的变化特征，由多个主导坡向逐步演化为与该坡面主干沟道总体走向基本一致的一个主导坡向；其沟道网络逐步发育成典型树状网络并基本保持稳定，且形成了完整和严密的沟道等级结构。上述侵蚀坡面变异特征在一定程度上反映出该坡面在发育初期侵蚀较为强烈但在后期强度有所减弱。本研究是对黄土侵蚀坡面变异特征的初步探索，对未来进一步揭示黄土坡面的侵蚀机理和演化规律具有重要理论意义。 相似文献
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本研究利用天山胜利达坂地区2014—2016年Landsat系列卫星的57景ETM+或OLI遥感影像,基于SNOMAP算法提取研究区积雪面积,并结合DEM数据研究了海拔高度、坡向和坡度对研究区积雪空间分布的影响。结果表明,随着海拔的增加,积雪覆盖率持续增加;阴坡积雪覆盖率约是阳坡的2~3倍。进一步的一般线性模型(GLM)分析表明:海拔、坡向和坡度均显著影响积雪的空间分布,但各地形因子的影响程度在不同季节有所差异。在冬季(12~2月),坡向是影响积雪覆盖率空间变异的主要地形因子,贡献了积雪覆盖率总变异的57%,约是海拔的2倍,坡度的4.5倍。对其他季节而言,海拔是主要影响因子,其次是坡向,坡度的影响最小。 相似文献
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《西部资源》2017,(4)
数字高程模型(Digital Elevation Model简称DEM)是通过一组有序数值阵列对地面海拔高度数字描述的实体地面模型,是数字地形模型(Digital Terrain Model,简称DTM)的一个子集。并可通过对DTM数字处理得到其他各种地形特征值。DTM是描述包括高程在内的各种地貌因子,如坡度、坡向、坡度变化率等因子在内的线性和非线性组合的空间分布,其中DEM是单一的数字地貌模型,通过对DEM数据处理可派生出坡度、坡向及坡度变化率等地貌特性。基于ARCGIS技术平台,对DEM数据进行处理建模,可以得到地形真实情景再现,为震后应急指挥人员、工作人员了解震区的地貌、地形提供直接的数据支撑。 相似文献
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基于数字高程模型(DEM)计算得到的坡度、坡向等地形属性是滑坡危险性评价模型的重要输入数据, DEM误差会导致地形属性计算结果不确定性, 进而影响滑坡危险性评价模型的结果。本文选择基于专家知识的滑坡危险性评价模型和逻辑斯第回归模型, 采用蒙特卡洛模拟方法, 研究DEM误差所导致的滑坡危险性评价模型结果不确定性。研究区位于长江中上游的重庆开县, 采用5 m分辨率的DEM, 以序贯高斯模拟方法模拟了不同大小(误差标准差为1 m、7.5 m、15 m)和空间自相关性(变程为0 m、30 m、60 m、120 m)的12 类DEM误差场参与滑坡危险性评价。每次模拟包括100 个实现, 通过对每次模拟分别计算滑坡危险性评价结果的标准差图层和分类一致性百分比图层, 用以评价结果不确定性。评价结果表明, 在不同的DEM精度下, 两个滑坡危险性评价模型所得结果的总体不确定性随空间自相关程度的变化趋势并不相同。当DEM空间自相关性程度不同时, 基于专家知识的滑坡危险性评价模型的评价结果总体不确定随着DEM误差增加而呈现不同的变化趋势, 而逻辑斯第回归模型的评价结果总体不确定性随着DEM误差大小增加而单调增加。从评价结果总体不确定性角度而言, 总体上逻辑斯第回归模型比基于专家知识的滑坡危险性评价模型更加依赖于DEM数据质量。 相似文献
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J. GAO 《International journal of geographical information science》2013,27(8):875-890
This paper explores the quantitative relation between the reliability of slope aspect, gradient, and form mapped from a gridded DEM and the sampling interval (SI) of elevations. Grid DEMs initially interpolated from digitised contours at 10 m were sampled to five other resolution levels. The topographic variables mapped at these SIs were compared with those at 10 m. It is found that the reliability of mapped slope aspect and form is not significantly affected by SI. By comparison, the reliability of slope gradient is more susceptible to SI, especially if it is derived from a gently rolling terrain. Around 90% of the variation in the mapped slope aspect and gradient are accounted for by the inaccuracy of DEMs. A lower percentage exists for slope form. The stability of the mapped topographic variables can be reliably predicted from SI and terrain complexity. 相似文献
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Cheng-Zhi Qin Li-Li Bao Rong-Xun Wang Xue-Mei Hu 《International journal of geographical information science》2013,27(7):1364-1380
Terrain attributes such as slope gradient and slope shape, computed from a gridded digital elevation model (DEM), are important input data for landslide susceptibility mapping. Errors in DEM can cause uncertainty in terrain attributes and thus influence landslide susceptibility mapping. Monte Carlo simulations have been used in this article to compare uncertainties due to DEM error in two representative landslide susceptibility mapping approaches: a recently developed expert knowledge and fuzzy logic-based approach to landslide susceptibility mapping (efLandslides), and a logistic regression approach that is representative of multivariate statistical approaches to landslide susceptibility mapping. The study area is located in the middle and upper reaches of the Yangtze River, China, and includes two adjacent areas with similar environmental conditions – one for efLandslides model development (approximately 250 km2) and the other for model extrapolation (approximately 4600 km2). Sequential Gaussian simulation was used to simulate DEM error fields at 25-m resolution with different magnitudes and spatial autocorrelation levels. Nine sets of simulations were generated. Each set included 100 realizations derived from a DEM error field specified by possible combinations of three standard deviation values (1, 7.5, and 15 m) for error magnitude and three range values (0, 60, and 120 m) for spatial autocorrelation. The overall uncertainties of both efLandslides and the logistic regression approach attributable to each model-simulated DEM error were evaluated based on a map of standard deviations of landslide susceptibility realizations. The uncertainty assessment showed that the overall uncertainty in efLandslides was less sensitive to DEM error than that in the logistic regression approach and that the overall uncertainties in both efLandslides and the logistic regression approach for the model-extrapolation area were generally lower than in the model-development area used in this study. Boxplots were produced by associating an independent validation set of 205 observed landslides in the model-extrapolation area with the resulting landslide susceptibility realizations. These boxplots showed that for all simulations, efLandslides produced more reasonable results than logistic regression. 相似文献
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S. R. Januchowski R. L. Pressey J. VanDerWal A. Edwards 《International journal of geographical information science》2013,27(9):1327-1347
Digital topographic models are the foundation of more advanced modeling applications and ultimately inform planning and decision making in many fields. Despite this, the error associated with these models and derived attributes is commonly overlooked. Little attention has been given in the scientific literature to the benefits gained from having less error in a model or to the corresponding cost associated with reducing model error by choosing one product over another. To address these gaps in knowledge we evaluated the error associated with five digital elevation models (DEMs) and derived attributes of slope and aspect relative to the same attributes derived from LiDAR data. We also estimated the acquisition and processing costs per square kilometer of the five test models and the LiDAR models. We used three measures to characterize model error: (1) root mean square error, (2) mean error (and standard deviation), and (3) area of significant elevation error. We applied these measures to DEM products that are used extensively across a range of applications for planning and managing natural resources. We depicted the relationship between model accuracy (the inverse of error) and cost in two ways. One was accuracy/cost ratio for each model. The other used separate data on accuracy and cost to better guide potential users in choosing between models or deciding on necessary expenditure on models. The main conclusion of our work was that accounting for error in DEMs can inform choice of models and the need for financial outlays. 相似文献
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TANGGuoan ZHAOMudan LITianwen LIUYongmei ZHANGTing 《地理学报(英文版)》2003,13(4):387-394
Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as(0.0015S2 0.031S-0.0325)X-0.0045S2-0.155S 0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation. 相似文献
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不同分辨率DEM提取地面坡度的不确定性模拟:以在黄土高原的试验为例 总被引：1，自引：0，他引：1
Slope is one of the crucial terrain variables in spatial analysis and land use planning,especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas,but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation. 相似文献
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Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation. 相似文献
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1 Introduction Automated extraction of drainage features from DEMs is an effective alternative to the tedious manual mapping from topographic maps. The derived hydrologic characteristics include stream-channel networks, delineation of catchment boundaries, catchment area, catchment length, stream-channel long profiles and stream order etc. Other important characteristics of river catchments, such as the stream-channel density, stream-channel bifurcation ratios, stream-channel order, number… 相似文献
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使用固定翼无人机航测丹霞山核心区长老峰游览区（航测区面积4.25 km2）获得高精度影像数据638张，用Photoscan软件拼接正射影像地图及DEM数据生产。在ArcGIS10.5软件中将正射影像图批量分割成470幅图（长和宽为100 m×100 m，比例尺为1︰1 000），在分割后的地图上目测识别并定位珍稀物种丹霞梧桐（Firmiana danxiaensis H. H. Hsue & H. S. Kiu），共获取航测区内1 515株丹霞梧桐及其位置数据，构建地理数据库。利用ArcGIS10.5的空间分析模块，将DEM数据转换成坡度和坡向数据，叠加1 515株丹霞梧桐点位置数据与DEM数据、坡度和坡向数据后进行可视化定量分析。结果显示：航测区内有71.2%的丹霞梧桐（1078株）分布在海拔210±90 m的范围内。有68.3%（1033株）的丹霞梧桐分布在坡度>15°的丹霞崖壁地带，与实地观察的事实相吻合。虽然，在航测区长老峰的各个坡向上都可以实地观察丹霞梧桐的分布，但定量统计表明，在南东（295株）、南（276株）、南西（244株）3个坡向上分布相对集中，占总数的53.8%（815株），这也与实地观察到的丹霞梧桐属于喜光照的向阳植物一致。小区域范围内珍稀物种的数据采集与空间分析，是珍稀物种保护的重要基础工作，还可以为较大区域范围内丹霞梧桐生态保护红线更准确的落地提供参考和依据。 相似文献