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1.
For areas of the world that do not have access to lidar, fine-scale digital elevation models (DEMs) can be photogrammetrically created using globally available high-spatial resolution stereo satellite imagery. The resultant DEM is best termed a digital surface model (DSM) because it includes heights of surface features. In densely vegetated conditions, this inclusion can limit its usefulness in applications requiring a bare-earth DEM. This study explores the use of techniques designed for filtering lidar point clouds to mitigate the elevation artifacts caused by above ground features, within the context of a case study of Prince William Forest Park, Virginia, USA. The influences of land cover and leaf-on vs. leaf-off conditions are investigated, and the accuracy of the raw photogrammetric DSM extracted from leaf-on imagery was between that of a lidar bare-earth DEM and the Shuttle Radar Topography Mission DEM. Although the filtered leaf-on photogrammetric DEM retains some artifacts of the vegetation canopy and may not be useful for some applications, filtering procedures significantly improved the accuracy of the modeled terrain. The accuracy of the DSM extracted in leaf-off conditions was comparable in most areas to the lidar bare-earth DEM and filtering procedures resulted in accuracy comparable of that to the lidar DEM.  相似文献   

2.
Digital surface models (DSMs) extracted from very high resolution (VHR) satellite stereo images are becoming more and more important in a wide range of geoscience applications. The number of software packages available for generating DSMs has been increasing rapidly. The main goal of this work is to explore the capabilities of VHR satellite stereo pairs for DSMs generation over different land-cover objects such as agricultural plastic greenhouses, bare soil and urban areas by using two software packages: (i) OrthoEngine (PCI), based on a hierarchical subpixel mean normalized cross correlation matching method, and (ii) RPC Stereo Processor (RSP), with a modified hierarchical semi-global matching method. Two VHR satellite stereo pairs from WorldView-2 (WV2) and WorldView-3 (WV3) were used to extract the DSMs. A quality assessment on these DSMs on both vertical accuracy and completeness was carried out by considering the following factors: (i) type of sensor (i.e., WV2 or WV3), (ii) software package (i.e., PCI or RSP) and (iii) type of land-cover objects (plastic greenhouses, bare soil and urban areas). A highly accurate light detection and ranging (LiDAR) derived DSM was used as the ground truth for validation. By comparing both software packages, we concluded that regarding DSM completeness, RSP produced significantly (p < 0.05) better scores than PCI for all the sensors and type of land-cover objects. The percentage improvement in completeness by using RSP instead of PCI was approximately 2%, 18% and 26% for bare soil, greenhouses and urban areas respectively. Concerning the vertical accuracy in root mean square error (RMSE), the only factor clearly significant (p < 0.05) was the land cover. Overall, WV3 DSM showed slightly better (not significant) vertical accuracy values than WV2. Finally, both software packages achieved similar vertical accuracy for the different land-cover objects and tested sensors.  相似文献   

3.
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4.
The reconstruction of digital surface models (DSMs) of urban areas from interferometric synthetic aperture radar (SAR) data is a challenging task. In particular the SAR inherent layover and shadowing effects need to be coped with by sophisticated processing strategies. In this paper, a maximum-likelihood estimation procedure for the reconstruction of DSMs from multi-aspect multi-baseline InSAR imagery is proposed. In this framework, redundant as well as contradicting observations are exploited in a statistically optimal way. The presented method, which is especially suited for single-pass SAR interferometers, is examined using test data consisting of experimental airborne millimeterwave SAR imagery. The achievable accuracy is evaluated by comparison to LiDAR-derived reference data. It is shown that the proposed estimation procedure performs better than a comparable non-statistical reconstruction method.  相似文献   

5.
The exploitation of different non-rigorous mathematical models as opposed to the satellite rigorous models is discussed for geometric corrections and topographic/thematic maps production of high-resolution satellite imagery (HRSI). Furthermore, this paper focuses on the effects of the number of GCPs and the terrain elevation difference within the area covered by the images on the obtained ground points accuracy. From the research, it is obviously found that non-rigorous orientation and triangulation models can be used successfully in most cases for 2D rectification and 3D ground points determination without a camera model or the satellite ephemeris data. In addition, the accuracy up to the sub-pixel level in plane and about one pixel in elevation can be achieved with a modest number of GCPs.  相似文献   

6.
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   

7.
杨幸彬  吕京国  江珊  张丹璐 《测绘学报》2018,47(10):1372-1384
提出一种基于改进半全局匹配算法的高分辨率遥感影像数字表面模型（digital surface model,DSM）生成方法。首先利用影像间连接点几何约束关系对有理函数模型进行系统误差补偿,在补偿模型的基础上对影像进行分块,利用投影轨迹法逐块得到核线影像对;在密集匹配阶段,对影像建立金字塔后逐层进行半全局匹配,匹配过程中引入顾及影像纹理信息的视差图膨胀腐蚀算法约束每一层视差搜索范围,增加了视差图边缘处的有效像素数,同时减少了算法所需的内存开销和计算时间;在视差图后处理阶段,利用加权中值滤波算法保护了视差图的边缘信息;最后基于前方交会获取DSM。选取WorldView 3和资源三号立体影像进行试验,结果表明,本文方法获取的DSM精度在高程方向上接近于1.5倍GSD,并且较好地保持了地物的边缘特性,在计算效率和内存开销方面也具有较好的平衡。  相似文献   

8.
Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.  相似文献   

9.
As a model for sensor orientation and 3D geopositioning for high-resolution satellite imagery (HRSI), the affine transformation from object to image space has obvious advantages. Chief among these is that it is a straightforward linear model, comprising only eight parameters, which has been shown to yield sub-pixel geopositioning accuracy when applied to Ikonos stereo imagery. This paper aims to provide further insight into the affine model in order to understand why it performs as well as it does. Initially, the model is compared to counterpart, ‘rigorous’ affine transformation formulations which account for the conversion from a central perspective to affine image. Examination of these rigorous models sheds light on issues such as the effects of terrain and size of area, as well as upon the choice of reference coordinate system and the impact of the adopted scanning mode of the sensor. The results of application of the affine sensor orientation model to four multi-image Ikonos test field configurations are then presented. These illustrate the very high geopositioning accuracy attainable with the affine model, and illustrate that the model is not affected by size of area, but can be influenced to a modest extent by mountainous terrain, the mode of scanning and the choice of object space coordinate system. Above all, the affine model is shown to be both a robust and practical sensor orientation/triangulation model with high metric potential.  相似文献   

10.
Automatic digital elevation model (DEM) generation has become an established technique within mapping agencies. This paper assesses the effectiveness of automatic DEM generation using area-based matching for glaciated terrain in Antarctica. DEM accuracy is assessed by comparison with check data acquired using analytical photogrammetry and independent field measurements.An optimum DEM collection strategy is identified. DEM success is linked to ground terrain type and it is found that areas of a DEM which can be collected successfully are relatively insensitive to changes in the collection strategy. A method of isolating unsuccessful areas of a DEM for manual editing is tested for Antarctic terrain. In this example, over 90% success is achieved in identifying erroneous DEM results measured against check data.  相似文献   

11.
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12.
ABSTRACT

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.  相似文献   

13.
Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic.In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment.The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation–orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available.To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV since only the HOV is implemented.The software comparison guaranteed about the overall correctness and good performances of the SISAR model, whereas the results showed the good features of the LOOCV method.  相似文献   

14.
森林垂直结构信息缺乏严重制约森林地上生物量估算精度的提高。立体雷达具备对森林垂直结构探测的能力,但早期雷达图像分辨率低。TerraSAR-X等高分辨率雷达数据的出现为利用立体雷达数据进行森林垂直结构探测提供了新的契机。本研究尝试采用立体雷达处理技术,利用TerraSAR-Xstripmap模式数据,以内蒙古根河大兴安岭林区和长白山自然保护区为研究区,重点探讨金字塔分层匹配策略中涉及的关键匹配参数对DSM提取精度的影响规律。结果发现:(1)影像匹配采用的金字塔层数对DSM提取精度影响明显,在大兴安岭研究区,采用5、6、7层金字塔匹配得到的DSM误差在±10m内的像元百分比分别为81.8%、77.7%和77.1%,5层金字塔能以较高的初始分辨率减少林区纹理信息的损失;在长白山研究区,采用7层金字塔得到的DSM能够抑制明显的误匹配点,提高地形提取精度;(2)影像匹配窗口对同名点识别的质量影响明显,采用25×25的匹配窗口,与9×9匹配窗口相比,大兴安岭和长白山研究区影像的平均相关性分别由0.43、0.40提高到0.49、0.45,林区纹理信息欠丰富,宜采用较大匹配窗口;(3)大兴安岭和长白山研究区提取的DSM与参考DSM线性回归的RMSE分别为6.682 m和10.384 m,DSM误差主要存在于坡度变化剧烈的地区,透视收缩和叠掩等几何畸变导致匹配结果不可靠。  相似文献   

15.
Terrain Moisture Classification Using GPS Surface-Reflected Signals   总被引：1，自引：0，他引：1  
In this letter, a novel method of land-surface classification using surface-reflected global positioning system (GPS) signals in combination with digital imagery is presented. Two GPS-derived classification features are merged with visible image data to create terrain moisture classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, the use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping  相似文献   

16.
Lidar and photogrammetry have both been evaluated for detecting shortterm coastal change using the Black Ven mudslide, Dorset as a case study. A lidar-generated digital elevation model (DEM) was obtained and initially compared with a DEM generated using available 1:7500 scale aerial photography and automated digital photogrammetry. The quality of these two data sets was assessed using a third DEM, derived using a total station and conventional ground survey methods. The vertical accuracies (rms error) of the lidar and photogrammetry were 0.26m and 0.43m respectively, although both data sets displayed a tendency to generate heights slightly lower than the elevation of the terrain surface. The quality of the two data sets was then assessed with respect to local slope angle. The accuracy of photogrammetrically derived elevations varied with slope and more so than in the case of lidar
From these basic tests, lidar has proved to be more accurate than photogrammetry for soft-cliff. monitoring. Further research is required to establish whether this trend is applicable to other data sets and specifically for photogrammetric data acquired using larger scale imagery  相似文献   

17.
A lot of studies have been done for correcting the systematic biases of high resolution satellite images (HRSI), which is a fundamental work in the geometric orientation and the geopositioning of HRSI. All the existing bias-corrected models eliminate the biases in the images by expressing the biases as a function of some deterministic parameters (i.e. shift, drift, or affine transformation models), which is indeed effective for most of the commercial high resolution satellite imagery (i.e. IKONOS, GeoEye-1, WorldView-1/2) except for QuickBird. Studies found that QuickBird is the only one that needs more than a simple shift model to absorb the strong residual systematic errors. To further improve the image geopositioning of QuickBird image, in this paper, we introduce space correlated errors (SCEs) and model them as signals in the bias-corrected rational function model (RFM) and estimate the SCEs at the ground control points (GCPs) together with the bias-corrected parameters using least squares collocation. With these estimated SCEs at GCPs, we then predict the SCEs at the unknown points according to their stochastic correlation with SCEs at the GCPs. Finally, we carry out geopositioning for these unknown points after compensating both the biases and the SCEs. The performance of our improved geopositioning model is demonstrated with a stereo pair of QuickBird cross-track images in the Shanghai urban area. The results show that the SCEs exist in HRSI and the presented geopositioning model exhibits a significant improvement, larger than 20% in both latitude and height directions and about 2.8% in longitude direction, in geopositioning accuracy compared to the common used affine transformation model (ATM), which is not taking SCEs into account. The statistical results also show that our improved geopositioning model is superior to the ATM and the second polynomial model (SPM) in both accuracy and reliability for the geopositioning of HRSI.  相似文献   

18.
Gaussian decomposition has been used to extract terrain elevation from waveforms of the satellite lidar GLAS (Geoscience Laser Altimeter System), on board ICESat (Ice, Cloud, and land Elevation Satellite). The common assumption is that one of the extracted Gaussian peaks, especially the lowest one, corresponds to the ground. However, Gaussian decomposition is usually complicated due to the broadened signals from both terrain and objects above over sloped areas. It is a critical and pressing research issue to quantify and understand the correspondence between Gaussian peaks and ground elevation. This study uses ～2000 km2 airborne lidar data to assess the lowest two GLAS Gaussian peaks for terrain elevation estimation over mountainous forest areas in North Carolina. Airborne lidar data were used to extract not only ground elevation, but also terrain and canopy features such as slope and canopy height. Based on the analysis of a total of ～500 GLAS shots, it was found that (1) the lowest peak tends to underestimate ground elevation; terrain steepness (slope) and canopy height have the highest correlation with the underestimation, (2) the second to the lowest peak is, on average, closer to the ground elevation over mountainous forest areas, and (3) the stronger peak among the lowest two is closest to the ground for both open terrain and mountainous forest areas. It is expected that this assessment will shed light on future algorithm improvements and/or better use of the GLAS products for terrain elevation estimation.  相似文献   

19.
The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition can vary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed the effect of lidar return density on the accuracy of lidar metrics and regression models for estimating aboveground biomass (AGB) and basal area (BA) in tropical peat swamp forests (PSF) in Kalimantan, Indonesia. A large dataset of ALS covering an area of 123,000 ha was used in this study. This study found that cumulative return proportion (CRP) variables represent a better accumulation of AGB over tree heights than height-related variables. The CRP variables in power models explained 80.9% and 90.9% of the BA and AGB variations, respectively. Further, it was found that low-density (and low-cost) lidar should be considered as a feasible option for assessing AGB and BA in vast areas of flat, lowland PSF. The performance of the models generated using reduced return densities as low as 1/9 returns per m2 also yielded strong agreement with the original high-density data. The use model-based statistical inferences enabled relatively precise estimates of the mean AGB at the landscape scale to be obtained with a fairly low-density of 1/4 returns per m2, with less than 10% standard error (SE). Further, even when very low-density lidar data was used (i.e., 1/49 returns per m2) the bias of the mean AGB estimates were still less than 10% with a SE of approximately 15%. This study also investigated the influence of different DTM resolutions for normalizing the elevation during the generation of forest-related lidar metrics using various return densities point cloud. We found that the high-resolution digital terrain model (DTM) had little effect on the accuracy of lidar metrics calculation in PSF. The accuracy of low-density lidar metrics in PSF was more influenced by the density of aboveground returns, rather than the last return. This is due to the flat topography of the study area. The results of this study will be valuable for future economical and feasible assessments of forest metrics over large areas of tropical peat swamp ecosystems.  相似文献   

20.
The accuracy of topographic correction of Landsat data based on a Digital Surface Model (DSM) depends on the quality, scale and spatial resolution of the DSM data used and the co-registration between the DSM and the satellite image. A physics-based bidirectional reflectance distribution function (BRDF) and atmospheric correction model in conjunction with a 1-second DSM was used to conduct the analysis in this paper. The results show that for the examples used from Australia, the 1-second DSM, can provide an effective product for this task. However, it was found that some remaining artefacts in the DSM data, originally due to radar shadow, can still cause significant local errors in the correction. Where they occur, false shadows and over-corrected surface reflectance factors can be observed. More generally, accurate co-registration between satellite images and DSM data was found to be critical for effective correction. Mis-registration by one or two pixels could lead to large errors of retrieved surface reflectance factors in gully and ridge areas. Using low-resolution DSM data in conjunction with high-resolution satellite images will also fail to correct significant terrain components where they occur at the finer scales of the satellite images. DSM resolution appropriate to the resolution of satellite image and the roughness of the terrain is needed for effective results, and the rougher the terrain, the more critical will be the accurate registration.  相似文献   

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