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1.
Digital elevation models (DEMs) are essential to various applications in topography, geomorphology, hydrology, and ecology. The Shuttle Radar Topographic Mission (SRTM) DEM data set is one of the most complete and most widely used DEM data sets; it provides accurate information on elevations over bare land areas. However, the accuracy of SRTM data over vegetated mountain areas is relatively low as a result of the high relief and the penetration limitation of the C-band used for obtaining global DEM products. The objective of this study is to assess the performance of SRTM DEMs and correct them over vegetated mountain areas with small-footprint airborne Light Detection and Ranging (Lidar) data, which can develop elevation products and vegetation products [e.g., vegetation height, Leaf Area Index (LAI)] of high accuracy. The assessing results show that SRTM elevations are systematically higher than those of the actual land surfaces over vegetated mountain areas. The mean difference between SRTM DEM and Lidar DEM increases with vegetation height, whereas the standard deviation of the difference increases with slope. To improve the accuracy of SRTM DEM over vegetated mountain areas, a regression model between the SRTM elevation bias and vegetation height, LAI, and slope was developed based on one control site. Without changing any coefficients, this model was proved to be applicable in all the nine study sites, which have various topography and vegetation conditions. The mean bias of the corrected SRTM DEM at the nine study sites using this model (absolute value) is 89% smaller than that of the original SRTM DEM, and the standard deviation of the corrected SRTM elevation bias is 11% smaller. 相似文献
2.
目前,针对利用无人机技术在山地起伏大、山体植被密集区域,难以获取地面点及DEM等问题,本文提出了一种结合布料模拟算法和改进的局部最大值算法,利用树顶点、树高等植被信息,提取地面点,进而生成整个区域的DEM的方法。以中国传统村落德夯村为例,利用植被系数和高程信息将点云分割为植被密集区和非植被密集区两个部分。在非植被密集区,通过布料模拟算法和改进的局部最大值算法分别提取地面点和树顶点,计算平均树高;在植被密集区,通过该区域的树顶点推算得到植被密集区的近似地面点,最终将两部分的地面点云进行TIN插值得到该地区的DEM。试验结果表明,利用此方法生成的DEM均方根误差,在非植被密集区达0.037 m,植被密集区可达1.606 m,整体平均误差达1.492 m,总体精度较好,基本可以满足村落尺度空间分析的需求。 相似文献
3.
Discriminating laser scanner data points belonging to ground from points above-ground (vegetation or buildings) is a key issue in research. Methods for filtering points into ground and non-ground classes have been widely studied mostly on datasets derived from airborne laser scanners, less so for terrestrial laser scanners. Recent developments in terrestrial laser sensors (longer ranges, faster acquisition and multiple return echoes) has aroused greater interest for surface modelling applications. The downside of TLS is that a typical dataset has high variability in point density, with evident side-effects on processing methods and CPU-time. In this work we use a scan dataset from a sensor which returns multiple target echoes, in this case providing more than 70 million points on our study site. The area presents low, medium and high vegetation, undergrowth with varying density, as well as bare ground with varying morphology (i.e. very steep slopes as well as flat areas). We test an integrated work-flow for defining a terrain and surface model (DTM and DSM) and successively for extracting information on vegetation density and height distribution on such a complex environment. Attention was given to efficiency and speed of processing. The method consists on a first step which subsets the original points to define ground candidates by taking into account the ordinal return number and the amplitude. A custom progressive morphological filter (opening operation) is applied next, on ground candidate points using a multidimensional grid to account for the fallout in point density as a function of distance from scanner. Vegetation density mapping over the area is then estimated using a weighted ratio of point counts in the tri-dimensional space over each cell. The overall result is a pipeline for processing TLS points clouds with minimal user interaction, producing a Digital Terrain Model (DTM), a Digital Surface Model (DSM), a vegetation density map and a derived Canopy Height Model (CHM). These products are of high importance for many applications ranging from forestry to hydrology and geomorphology. 相似文献
4.
The aim of this paper was to analyze the ground and low vegetation points of a Light Detection and Ranging (LiDAR) point cloud from the aspect of the generated digital terrain model (DTM). We determined the height difference between the surveyed surface and the DTM and the level of interspersion of ground and low vegetation points in a floodplain. Finally, we performed a supervised classification with topographic (elevation, slope and aspect) variables and an Normalized Difference Vegetation Index (NDVI) layer to identify swales and point bars as floodplain forms. Cross sections of field surveys provided reference data to express the magnitude of the bias on the DTM caused by the vegetation, and we proved that the bias can reach the 60% of the relative height and depth of the floodplain forms (mean error was 0.15 ± 0.12 m). A landscape metric, the Aggregation Index, provided an appropriate tool to analyze and quantify the interspersion of the ground and vegetation points: indicating a high level of interspersion of the classified points, i.e. proved that vegetation points where the last echoes reflected from the vegetation became ground points. Floodplain classification performed best with the common use of DTM, slope, aspect and NDVI coverages, with 71% overall accuracy. 相似文献
5.
《International Journal of Digital Earth》2013,6(3):198-211
Current researches based on areal or spaceborne stereo images with very high resolutions (<1 m) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is the state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 m) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that the accurate coregistration between ASTER GDEM and national elevation dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-second and further improved to 0.6 if only homogenous vegetated areas were considered. 相似文献
6.
我国茂密植被山区地质灾害具有高位、高隐蔽性的特点,传统地质灾害排查手段在有效解决隐患的早期识别方面存在一定困难。机载雷达技术不仅可获取地面反射的三维激光点云,同时能够提供高分辨率、高精度的地形地貌二维影像。机载雷达的多次回波技术可“穿透”地面植被,通过滤波算法能够有效去除地表植被的影响,获取真地面高程数据信息,从而可获取相关区域精细准确的地面特征和坡体变形迹象及灾害体形态特征。本文将机载LiDAR技术在广东佛山西樵山公园进行应用实践,研究成果表明,机载LiDAR技术可提高茂密植被山区地质灾害隐患的早期识别能力,对进一步提高综合防灾减灾能力作用显著。 相似文献
7.
《International Journal of Digital Earth》2013,6(6):34-49
An algorithm for retrieving global eight-day 5 km broadband emissivity (BBE) from advanced very high resolution radiometer (AVHRR) visible and near-infrared data from 1981 through 1999 was presented. Land surface was divided into three types according to its normalized difference vegetation index (NDVI) values: bare soil, vegetated area, and transition zone. For each type, BBE at 8–13.5 µm was formulated as a nonlinear function of AVHRR reflectance for Channels 1 and 2. Given difficulties in validating coarse emissivity products with ground measurements, the algorithm was cross-validated by comparing retrieved BBE with BBE derived through different methods. Retrieved BBE was initially compared with BBE derived from moderate-resolution imaging spectroradiometer (MODIS) albedos. Respective absolute bias and root-mean-square error were less than 0.003 and 0.014 for bare soil, less than 0.002 and 0.011 for transition zones, and ?0.002 and 0.005 for vegetated areas. Retrieved BBE was also compared with BBE obtained through the NDVI threshold method. The proposed algorithm was better than the NDVI threshold method, particularly for bare soil. Finally, retrieved BBE and BBE derived from MODIS data were consistent, as were the two BBE values. 相似文献
8.
Biological soil crusts (BSCs) modify numerous soil surface properties and affect many key ecosystem processes. As BSCs are considered one of the most important components of semiarid ecosystems, accurate characterisation of their spatial distribution is increasingly in demand. This paper describes a novel methodology for identifying the areas dominated by different types of BSCs and quantifying their relative cover at subpixel scale in a semiarid ecosystem of SE Spain. The approach consists of two consecutive steps: (i) First, Support Vector Machine (SVM) classification to identify the main ground units, dominated by homogenous surface cover (bare soil, cyanobacteria BSC, lichen BSC, green and dry vegetation), which are of strong ecological relevance. (ii) Spectral mixture analysis (SMA) of the ground units to quantify the proportion of each type of surface cover within each pixel, to correctly characterize the complex spatial heterogeneity inherent to semiarid ecosystems. SVM classification showed very good results with a Kappa coefficient of 0.93%, discriminating among areas dominated by bare soil, cyanobacteria BSC, lichen BSC, green and dry vegetation. Subpixel relative abundance images achieved relatively high accuracy for both types of BSCs (about 80%), whereas general overestimation of vegetation was observed. Our results open the possibility of introducing the effect of presence and of relative cover of BSCs in spatially distributed hydrological and ecological models, and assessment and monitoring aimed at reducing degradation in these areas. 相似文献
9.
针对传统沟蚀监测手段劳作强度大,且数据采集的完整性、代表性受切沟复杂地形制约等问题,提出了一种针对植被稀疏地区沟蚀变化的地面激光扫描（terrestrial laser scanning,TLS）监测方法,形成了一套数据处理与侵蚀量计算技术流程。以河北省官厅水库东岸某大型切沟为例,利用高精度TLS进行两年3期野外监测与点云数据分析。通过点云配准、滤波、重采样及曲面拟合等预处理,生成不同采样分辨率下3期切沟表面模型,并提取地形信息;采用杨赤中滤波推估法计算并比较不同点云重采样分辨率下的沟蚀量。结果表明:（1）当点云重采样分辨率与切沟表面凹凸微结构暨石块粒径（2~6cm）接近时,沟蚀量估算值趋于稳定、结果可靠;（2）经侵蚀作用,切沟外壁表面高程整体降低2~20 cm;（3）切沟内壁侵蚀量不均衡,坡度较大处侵蚀最为显著。 相似文献
10.
R. Suraj Reddy Chandra Shekhar Jha Krishnan Sundara Rajan 《Journal of the Indian Society of Remote Sensing》2018,46(6):937-943
Forest inventory parameters, primarily tree diameter and height, are required for several management and planning activities. Currently, Terrestrial Laser Scanning (TLS) is a promising technology in automated measurements of tree parameters using dense 3D point clouds. In comparison with conventional manual field inventory methods, TLS systems would supplement field data with detailed and relatively higher degree of accurate measurements and increased measurement frequency. Although, multiple scans from TLS captures more area, they are resource and time consuming to ensure proper co-registration between the scans. On the other hand, Single scans provide a fast and recording of the data but are often affected by occlusions between the trees. The current study evaluates potential of single scan TLS data to (1) develop an automatic method for tree stem identification and diameter estimation (diameter at breast height—DBH) using random sample consensus (RANSAC) based circle fitting algorithm, (2) validate using field based measurements to derive accuracy estimates and (3) assess the influence of distance to scanner on detection and measurement accuracies. Tree detection and diameter measurements were validated for 5 circular plots of 20 m radius using single scans in dry deciduous forests of Betul, Madhya Pradesh. An overall tree detection accuracy of 85 and 70% was observed in the scanner range of 15 and 20 m respectively. The tree detection accuracies decreased with increased distance to the scanner due to the decrease in visible area. Also, estimated stem diameter using TLS was found to be in agreement with the field measured diameter (R2 = 0.97). The RMSE of estimated DBH was found to be 3.5 cm (relative RMSE ~20%) over 202 trees detected over 5 plots. Results suggest that single scan approach suffices the cause of accuracy, reducing uncertainty and adds to increased sampling frequency in forest inventory and also implies that TLS has a seemingly high potential in forest management. 相似文献
11.
Yogesh Kant B. D. Bharath Javed Mallick Clement Atzberger Norman Kerle 《Journal of the Indian Society of Remote Sensing》2009,37(2):201-214
The knowledge of the surface temperature is important to a range of issues and themes in earth sciences central to urban climatology,
global environmental change and human-environment interactions. The study analyses land surface temperature (LST) estimation
using temporal ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) datasets (day time and night time) over
National Capital Territory Delhi using the surface emissivity information at pixel level. The spatial variations of LST over
different land use/land cover (LU/LC) at day time and night time were analysed and relationship between the spatial distribution
of LU/LC and vegetation density with LST was developed. Minimum noise fraction (MNF) was used for LU/LC classification which
gave better accuracy than classification with original bands. The satellite derived emissivity values were found to be in
good agreement with literature and field measured values. It was observed that fallow land, waste land/bare soil, commercial/industrial
and high dense built-up area have high surface temperature values during day time, compared to those over water bodies, agricultural
cropland, and dense vegetation. During night time high surface temperature values are found over high dense built-up, water
bodies, commercial/industrial and low dense built-up than over fallow land, dense vegetation and agricultural cropland. It
was found that there is a strong negative correlation between surface temperature and NDVI over dense vegetation, sparse vegetation
and low dense built-up area while with fraction vegetation cover, it indicates a moderate negative correlation. The results
suggest that the methodology is feasible to estimate NDVI, surface emissivity and surface temperature with reasonable accuracy
over heterogeneous urban area. The analysis also indicates that the relationship between the spatial distribution of LU/LC
and vegetation density is closely related to the development of urban heat islands (UHI). 相似文献
12.
Umut Gunes Sefercik Naci Yastikli Iulia Dana 《Journal of the Indian Society of Remote Sensing》2014,42(2):279-290
Three-dimensional (3D) spatial information is crucial for improving the quality of human life through urban planning and management, and it is widely utilized due to its rapid, periodic and inexpensive acquisition. In this context, extraction of digital surface and elevation models (DSM and DEM) is a significant research topic for space-borne optical and synthetic aperture radar (SAR) remote sensing. The DSMs include visible features on the earth’s surface such as vegetation, forest and elevated man-made objects, while DEMs contain only the bare ground. In this paper, using TerraSAR-X (TSX) high resolution Spotlight (HS) images, high-resolution interferometric DEM generation in a part of Istanbul urban area is aimed. This is not an easy task because of SAR imaging problems in complex geometry of urban settlements. The interferometric processing steps for DSM generation were discussed including critical parameters and thresholds to improve the quality of the final product and a 3 m gridded DSM was generated. The DSM-DEM conversion was performed by filtering and the quality of generated DEM was verified against a reference DEM from stereo photogrammetry with 3 m original grid spacing. The achieved root mean square error of height differences (RMSZ) varies from 7.09 to 8.11 m, depending on the terrain slope. The differential DEM, illustrates the height differences between generated DEM and the reference DEM, was generated to show the correlation between height differences and the coherence map. Finally, a perspective view of test area was created draping extracted DEM and a high-resolution IKONOS panchromatic image. 相似文献
13.
Since soil moisture and vegetation index are direct and important indicators for surface drought status, a new drought monitoring method (MPDI1) is developed in NIR-Red reflectance space. It is a combination of two satellite-derived variables—a soil moisture component using the Perpendicular Drought Index (PDI), and a vegetation component using the Perpendicular Vegetation Index (PVI). Enhanced Thematic Mapper Plus (ETM+) image and in-situ ground observation are introduced to validate the accuracy of the proposed method. Results indicate that MPDI1 is highly consistent to the in-situ ground observation with the coefficient of determination (R2?=?0.49) between MPDI1 and 5–20 cm mean soil moisture, which is slightly higher than the coefficient of determination (R2?=?0.42) between MPDI1 and 10 cm soil moisture. Compared with drought indices such as PDI and the Modified Perpendicular Drought Index (MPDI), MPDI1 provides quite similar trends for bare soil or lower vegetated surface, but it demonstrates a better performance in measuring densely vegetated surface. This paper concludes that MPDI1 provides correct and sufficient information on surface drought status in soil-plant continuum, which appears to have robust available and great potential for surface drought estimation in China and other countries. 相似文献
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随着信息化社会的到来,现代水利测绘已经由传统测绘向信息化测绘发展,无人机技术应用于测绘行业推进了信息化测绘进程。本文探讨了如何有效利用无人机技术解决测绘领域在山区遇到的问题。固定翼无人机能及时获取地面数字正射影像数据,捕获裸露地面的平面和高程,但是无法获取植被覆盖下的地表高程信息,因此,本文通过机载激光雷达获取植被覆盖下的LiDAR点云数据;将二者数据相结合,再通过EPS软件生成三维地表模型,可以快速获取任何测区地物和地形数据,不仅提高了工作效率,还降低了外业劳动强度。 相似文献
16.
地形特征信息是地学研究中的重要依据,用于描述地形变化的总体样貌,决定了基础地形地貌形态特征。本文对禄丰恐龙谷南缘环状微地貌的地形特征进行提取及分析。首先,采用无人机测量技术获取测区影像数据,通过影像数据处理构建测区0.5 m分辨率的DOM数据与点云数据,并基于TerraSolid软件平台搭建滤波规则对点云数据进行分类、抽稀压缩处理,提取测区地面点,以地面点数据为基础数据构建测区2 m分辨率的DEM;然后,通过叠加ArcGIS空间分析中最大值提取与正负地形提取,完成地形特征点的提取分析;并结合ArcGIS中水文分析、平面曲率与坡型组合的方法,完成地形特征线提取分析;最后,在eCognition 9.0中通过面向对象的方法,实现地形面状特征提取。试验结果表明：①提取鞍部点的最佳分析窗口为11×11。②通过鞍部点位及两种方法提取脊—谷线,其中水文分析提取脊线更为细致,整体连贯性更为突出且从山体两侧脊线分布密集,试验区山体崎岖处提取鞍部点,即说明恐龙谷南缘整体受亚热带低纬度高原季风气候影响,山体受一定程度风化侵蚀。③恐龙谷南缘地形面状特征中裸岩、裸地两者面积占比较大,两者相加后占测区总面积64.2%,结合实地干湿分明的气候特点和实际勘察植被相对低矮的特征,在一定程度上说明该区域表层土壤疏松,需注意水土流失引起的生态问题。 相似文献
17.
用基于知识的决策树方法分层提取矿区土地类型——以湖北大冶为例 总被引：6，自引：0，他引：6
以湖北大冶为研究区,采用多时相陆地卫星遥感图像,通过不同波段组合,以及ironoxide指数和归一化差异植被指数(NDVI)等,详细分析了各地表地物光谱特征和空间特征,建立了研究区分类知识库表,采用决策二叉树法进行分类,得到了高精度分类结果图。基于不同时相分类结果的变化检测,通过对研究区水体污染、矿区复垦、耕地变化等分析,认为从1986～2002年,研究区水质虽有一定改善,但矿区植被退化严重,耕地大量减少,停产矿区复垦仅为20%,为合理保护矿区生态环境和科学管理采矿企业提供了有用资料。 相似文献
18.
Reliable quantification of savanna vegetation structure is critical for accurate carbon accounting and biodiversity assessment under changing climate and land-use conditions. Inventories of fine-scale vegetation structural attributes are typically conducted from field-based plots or transects, while large-area monitoring relies on a combination of airborne and satellite remote sensing. Both of these approaches have their strengths and limitations, but terrestrial laser scanning (TLS) has emerged as the benchmark for vegetation structural parameterization – recording and quantifying 3D structural detail that is not possible from manual field-based or airborne/spaceborne methods. However, traditional TLS approaches suffer from similar spatial constraints as field-based inventories. Given their small areal coverage, standard TLS plots may fail to capture the heterogeneity of landscapes in which they are embedded. Here we test the potential of long-range (>2000 m) terrestrial laser scanning (LR-TLS) to provide rapid and robust assessment of savanna vegetation 3D structure at hillslope scales. We used LR-TLS to sample entire savanna hillslopes from topographic vantage points and collected coincident plot-scale (1 ha) TLS scans at increasing distances from the LR-TLS station. We merged multiple TLS scans at the plot scale to provide the reference structure, and evaluated how 3D metrics derived from LR-TLS deviated from this baseline with increasing distance. Our results show that despite diluted point density and increased beam divergence with distance, LR-TLS can reliably characterize tree height (RMSE = 0.25–1.45 m) and canopy cover (RMSE = 5.67–15.91%) at distances of up to 500 m in open savanna woodlands. When aggregated to the same sampling grain as leading spaceborne vegetation products (10–30 m), our findings show potential for LR-TLS to play a key role in constraining satellite-based structural estimates in savannas over larger areas than traditional TLS sampling can provide. 相似文献
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《地理信息系统科学与遥感》2013,50(5):664-686
Accurate high-resolution terrain data are essential for hydrological modeling in lowlands. This study integrates elevation survey data and vegetation data at the point and 50 m scales to develop a fine-resolution digital elevation model (DEM) for the northern Everglades of Florida. The terrain was divided into two vertical strata (lowland and highland) based on a 50 m scale vegetation map. The DEM in highlands was interpolated with all the survey points and later adjusted using an association between vegetation and hydroperiod (the number of days per year that land is flooded). The DEM in lowlands was interpolated with elevation surveys tagged as lowland types. The two DEMs were then combined, forming a new DEM with a 7.7 cm mean absolute validation error—a significant (2.3 cm) improvement over the previous DEM. 相似文献