Geocoded digital videography for validation of land cover mapping in the Amazon basin

Four Validation Overflights for Amazon Mosaics (VOAM) aerial video surveys have been carried out in the Brazilian Amazon to provide ground verification for mapping of wetland cover with the Global Rain Forest Mapping (GRFM) Project JERS-1 (Japanese Earth Remote Sensing Satellite) mosaics of the Amazon basin. Surveys in 1995 and 1996, acquired with handheld analog camcorders from small aircraft, were timed to imaging of the GRFM low- and high-water mosaics, and limited to within 600 km of Manaus. For the 1997 and 1999 flights, digital camcorder systems were installed in the Bandeirante survey plane operated by Brazil's National Institute for Space Research. The VOAM97 and VOAM99 surveys circumscribed the Brazilian Amazon, documenting ground conditions at resolutions on the order of 1 m (wide-angle format) and 10 cm (zoom format) for wetlands, forests, savannas, and human-impacted areas. Global Positioning System (GPS) information encoded on the video audio track was extracted by mosaicking software that automatically generates geocoded digital mosaics from video clips. On the 1999 survey, a laser altimeter recorded profiles of terrain and vegetation canopy heights. A validation dataset was compiled from the videography for a portion of the GRFM mosaics extending 6° by 4° in longitude and latitude, using randomly selected points along flight lines. Other applications of the VOAM videography include acquisition of ground control points for image geolocation, creation of a high-resolution geocoded mosaic of a forest study area, forest biomass estimation, and rapid assessment of fire damage. Geocoded digital videography provides a cost-effective means of compiling high-resolution validation datasets for land cover mapping in remote, cloud-covered regions.     

A procedure for modelling the differences between the gravimetric geoid model and GPS/levelling data with an example in the north part of Algeria

Local gravimetric geoid models from a combination of a global geopotential model and local gravity data generally contain errors of dm-level on the long wavelengths and sometimes they may be significantly higher in areas lacking accurate gravity information like Algeria where only few gravity data from Bureau Gravimétrique International (BGI) have been included in the development of the recent geopotential models. Consequently, these models do not have the required accuracy to transform the GPS ellipsoidal heights to orthometric heights. One of the main causes for this is the limited precision of the global and detailed DTM models. On the other hand, we can now measure by means of the space techniques, on land through a combination of GPS positioning and precise levelling and at sea through satellite altimetry, the geoid on some points on the earth's surface with very high absolute accuracy. These points can be used to correct the systematic effects, the medium and longer wavelength errors in the gravimetric geoid. The main goal of this study is to propose a procedure, for combination of available gravimetric geoid and external data from GPS and levelling in an optimal way and for estimating the gravimetric geoid accuracy using the collocation approach. So, the question is to find what is the adequate functional representation of the correction that should be applied to the gravimetric geoid? Several functions have been tested and the most suitable will be selected in test area from a statistical testing procedure. For this purpose, the improved Algerian gravimetric geoid computed by the Geodetic Laboratory of the National Center of Space Techniques from the gravity data supplied by the Geophysical Exploration Technology Ltd. (GETECH), and the precise GPS data collected from the international TYRhenian GEOdynamical NETwork (TYRGEONET), ALGerian GEOdynamical NETwork (ALGEONET) projects with baseline length ranging from about 1 to 1000 km have been used. The comparisons based on different GPS campaigns provide after fitting a RMS of the differences ±1.9 cm and prove that a good fit in experimental area between the gravimetric geoid and GPS/levelling data using the seven-parameter model transformation has been reached. Moreover, the analysis of statistics shows that the residuals in benchmarks are due principally to gravimetric geoid errors. The main outlines of the Algerian geoid computation, the available GPS/levelling data, the developed procedure and the obtained results will be presented.     

Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data

Tree species identification is important for a variety of natural resource management and monitoring activities including riparian buffer characterization, wildfire risk assessment, biodiversity monitoring, and wildlife habitat assessment. Intensity data recorded for each laser point in a LIDAR system is related to the spectral reflectance of the target material and thus may be useful for differentiating materials and ultimately tree species. The aim of this study is to test if LIDAR intensity data can be used to differentiate tree species. Leaf-off and leaf-on LIDAR data were obtained in the Washington Park Arboretum, Seattle, Washington, USA. Field work was conducted to measure tree locations, tree species and heights, crown base heights, and crown diameters of individual trees for eight broadleaved species and seven coniferous species. LIDAR points from individual trees were identified using the field-measured tree location. Points from adjacent trees within a crown were excluded using a procedure to separate crown overlap. Mean intensity values of laser returns within individual tree crowns were compared between species. We found that the intensity values for different species were related not only to reflective properties of the vegetation, but also to a presence or absence of foliage and the arrangement of foliage and branches within individual tree crowns. The classification results for broadleaved and coniferous species using linear discriminant function with a cross validation suggests that the classification rate was higher using leaf-off data (83.4%) than using leaf-on data (73.1%), with highest (90.6%) when combining these two LIDAR data sets. The result also indicates that different ranges of intensity values between two LIDAR datasets didn't affect the result of discriminant functions. Overall results indicate that some species and species groups can be differentiated using LIDAR intensity data and implies the potential of combining two LIDAR datasets for one study.     

激光雷达数据特点

作为一种获取地表信息、建立三维模型的有力工具，激光雷达技术引起人们的广泛关注并取得快速的发展。其直接获取量测点三维坐标的工作方式使其数据具有某些明显特征。本从数据内容、种类、分布形式等几方面对激光雷达数据特点进行了总结；结合数据获取方式探讨其形成机制；并对其优、劣势及几个相关问题加以阐述。     

Localizing Ground Penetrating RADAR: A Step Toward Robust Autonomous Ground Vehicle Localization

Autonomous ground vehicles navigating on road networks require robust and accurate localization over long‐term operation and in a wide range of adverse weather and environmental conditions. GPS/INS (inertial navigation system) solutions, which are insufficient alone to maintain a vehicle within a lane, can fail because of significant radio frequency noise or jamming, tall buildings, trees, and other blockage or multipath scenarios. LIDAR and camera map‐based vehicle localization can fail when optical features become obscured, such as with snow or dust, or with changes to gravel or dirt road surfaces. Localizing ground penetrating radar (LGPR) is a new mode of a priori map‐based vehicle localization designed to complement existing approaches with a low sensitivity to failure modes of LIDAR, camera, and GPS/INS sensors due to its low‐frequency RF energy, which couples deep into the ground. Most subsurface features detected are inherently stable over time. Significant research, discussed herein, remains to prove general utility. We have developed a novel low‐profile ultra‐low power LGPR system and demonstrated real‐time operation underneath a passenger vehicle. A correlation maximizing optimization technique was developed to allow real‐time localization at 126 Hz. Here we present the detailed design and results from highway testing, which uses a simple heuristic for fusing LGPR estimates with a GPS/INS system. Cross‐track localization accuracies of 4.3 cm RMS relative to a “truth” RTK GPS/INS unit at speeds up to 100 km/h (60 mph) are demonstrated. These results, if generalizable, introduce a widely scalable real‐time localization method with cross‐track accuracy as good as or better than current localization methods.     

Phytoplankton distribution in the Arabian Sea using IRS-P4 OCM satellite data

For rapid static mode global positioning system (GPS) satellite surveying, our data processing method uses linear combinations of dual-frequency carrier phase observables, which are double differencing wide lane signals between the satellites and the receivers. Wide lane ambiguily parameters estimated in a least squares sense lead to corresponding candidate integer ambiguities on LI carrier waves. This shortens the search time appreciably in order to resolve the integer ambiguities. A contrast statistic and an ambiguily function provide indices which are utilized together to guarantee the correctness of the relative position solutions. Coordinate repeatabilities obtained are qualified for the generation of local ground control points. With five vertical control points, geometric heights from GPS surveying are transformed into orthometric heights. They are then compared to heights independently derived from precise levelling. Accuracies in height ranging from ± 0·8 to 1·6 cm are realizable for an experiment area of about 4 km by 5 km.     

一种新的机载LIDAR数据条带平差模型

机载LIDAR数据在DEM提取以及三维建模等方面正逐步得到广泛的应用,但是,残余系统误差的存在影响了LIDAR数据的应用,需要进行条带平差以消除残余系统误差。由于目前用户通常得不到原始的观测值,因此,本文在对机载LIDAR系统误差分析的基础上,针对系统检校后的LIDAR数据中存在的GPS定位和INS测姿误差,提出了一种条带平差的数学模型,该模型从LIDAR严格传感器模型出发,并且不需要系统原始的观测值。试验结果表明,该模型能够有效地提高LIDAR数据的精度。     

Impact of training and validation sample selection on classification accuracy and accuracy assessment when using reference polygons in object-based classification

Reference polygons are homogenous areas that aim to provide the best available assessment of ground condition that the user can identify. Delineation of such polygons provides a convenient and efficient approach for researchers to identify training and validation data for supervised classification. However, the spatial dependence of training and validation data should be taken into account when the two data sets are obtained from a common set of reference polygons. We investigate the effect on classification accuracy and the accuracy estimates derived from the validation data when training and validation data are obtained from four selection schemes. The four schemes are composed of two sampling designs (simple random and systematic) and two methods for splitting sample points between training and validation (validation points in separate polygons from training points and validation points and training points split within the same polygons). A supervised object-based classification of the study region was repeated 30 times for each selection scheme. The selection scheme did not impact classification accuracy, but estimates of overall (OA), user's (UA), and producer's (PA) accuracies produced from the validation data overestimated accuracy for the study region by about 10%. The degree of overestimation was slightly greater when the validation sample points were allowed to be in the same polygons as the training data points. These results suggest that accuracy estimates derived from splitting training and validation within a limited set of reference polygons should be regarded with suspicion. To be fully confident in the validity of the accuracy estimates, additional validation sample points selected from the region outside the reference polygons may be needed to augment the validation sample selected from the reference polygons.     

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

We used a single-beam, first return profiling LIDAR (Light Detection and Ranging) measurements of canopy height, intensive biometric measurements in plots, and Forest Inventory and Analysis (FIA) data to quantify forest structure and ladder fuels (defined as vertical fuel continuity between the understory and canopy) in the New Jersey Pinelands. The LIDAR data were recorded at 400 Hz over three intensive areas of 1 km² where transects were spaced at 200 m, and along 64 transects spaced 1 km apart (total of ca. 2500 km²). LIDAR and field measurements of canopy height were similar in the three intensive study areas, with the 80th percentile of LIDAR returns explaining the greatest amount of variability (79%). Correlations between LIDAR data and aboveground tree biomass measured in the field were highly significant when all three 1 km² areas were analyzed collectively, with the 80th percentile again explaining the greatest amount of variability (74%). However, when intensive areas were analyzed separately, correlations were poor for Oak/Pine and Pine/Scrub Oak stands. Similar results were obtained using FIA data; at the landscape scale, mean canopy height was positively correlated with aboveground tree biomass, but when forest types were analyzed separately, correlations were significant only for some wetland forests (Pitch Pine lowlands and mixed hardwoods; r² = 0.74 and 0.59, respectively), and correlations were poor for upland forests (Oak/Pine, Pine/Oak and Pine/Scrub Oak, r² = 0.33, 0.11 and 0.21, respectively). When LIDAR data were binned into 1-m height classes, more LIDAR pulses were recorded from the lowest height classes in stands with greater shrub biomass, and significant differences were detected between stands where recent prescribed fire treatments had been conducted and unburned areas. Our research indicates that single-beam LIDAR can be used for regional-scale (forest biomass) estimates, but that relationships between height and biomass can be poorer at finer scales within individual forest types. Binned data are useful for estimating the presence of ladder fuels (vertical continuity of leaves and branches) and horizontal fuel continuity below the canopy.     

Generation of road maps from trajectories collected with smartphone – A method based on Genetic Algorithm

Smartphones and automotive GPS have considerably boosted the use of digital road maps. For this reason, they must be updated regularly with accurate new data. The methods currently used to generate maps — photogrammetry and collaborative editing — have low frequency of update because they depend on manual intervention. By using an automated method it should be possible to improve map update speeds while maintaining similar level of accuracy. The literature presents some approaches for automatic road map creation using moving objects, but none of them is prepared for continuous update. Therefore, this work aims to propose a new automated method that uses trajectories provided by GPS receivers integrated in smartphones. It is assumed that the points that represent the center of the roads can be found through approximations provided by Genetic Algorithm. After that, these points are combined to generate the road map. However, the use of trajectories collected with smartphones provides some challenges, such as: elimination of data with bad accuracy, identification of the means of transport used and reduction of the volume of data processed. Thus, the objective of this work is to propose a method that cleans, analyzes and enriches data from smartphones to generate accurate road maps that can be continuously updated, using Genetic Algorithm. Tests indicate that the proposed method can generate maps with quality similar to the reference maps with less than 2 m of difference in average. Additionally, a comparison between the Fuzzy C-Means algorithm and the Genetic Algorithm shows that the later is a little slower but generates more accurate results.     

Remote survey of large-scale braided,gravel-bed rivers using digital photogrammetry and image analysis

The use of conventional survey methods to monitor large, gravel river beds has traditionally led to a reliance on repeat measurements of cross-sections which, unless very closely spaced, may give unreliable information about three-dimensional channel morphology and morphological change. Provided certain technological limitations can be overcome, remote survey techniques, such as digital photogrammetry and airborne laser scanning, remove the spatial and temporal constraints typically associated with ground-based surveys, allowing high spatial resolution, distributed, elevation mapping of gravel river beds. This paper develops the use of digital photogrammetry for the survey of a 3.3 km reach of the braided Waimakariri River, New Zealand, which, when combined with image analysis of water colour to infer water depth, provides a Digital Elevation Model (DEM) of the entire river bed. Central to the successful application of this method is DEM post-processing. Errors take two forms: (i) individual point errors associated with incorrect stereo-matching during automated data collection; and (ii) spatially-variable systematic errors that are associated with uncertainties in sensor position and orientation as determined during the bundle adjustment. An automated post-processing procedure is developed to deal with individual point errors and this improves DEM surface quality in terms of accuracy, precision and internal reliability. Systematic errors in the final DEM surface were reduced by applying a simple correction based on surveyed photo-control point elevations.     

Airborne laser scanning for riverbank erosion assessment

Worldwide, rivers and streams are negatively impacted by sedimentation. However, there are few broad scale techniques for quantifying the sources of sediment, i.e. upland vs. river bank erosion. This research was designed to evaluate the use of airborne LIDAR for characterizing sediment and phosphorus contributions from river bank erosion. The evaluation was done on the main stem of the Blue Earth River in southern Minnesota. Detailed topographic data were collected on an annual basis in April 2001 and 2002 over a 56 km length of the river with a helicopter mounted Topeye laser system. The raw database included X, Y, Z coordinates of laser returns sampled from the river valley with a density of 1-3.3 elevations per m². Uniform 1 m bare earth digital elevation models were constructed by stripping vegetation laser returns and interpolation. The two models were differenced to determine volume change over time, which was then converted to mass wasting by multiplying volume change with bulk density. Mass wasting rates were further converted to sediment load based on percentage of transportable material in the bank strata. The average difference between LIDAR measured elevations and RTK GPS surveyed elevations on 5 highway bridge surfaces was 2.5 and 8.8 cm for the 2001 and 2002 scans, respectively. The elevation errors were quasi-normally distributed with standard deviation of 6.7 and 6.1 cm for 2001 and 2002, respectively. No elevation or planimetric corrections were made to the laser data before calculating mass wasting rates because it was not possible to determine the source of error or if it was uniform within and between scans. The mass wasting estimate from the LIDAR surveys varied from 23% to 56% of the sediment mass transported past the downstream gauging station depending on the range of textural material that was entrained once in the river. These estimates are in the range of values reported in the literature. Total P contribution due to bank erosion from the river reach was estimated to be 201 t/yr.     

关于GPS研究中几个问题的探讨

GPS卫星测量技术是测绘发展史上的一个里程碑,建立和发展局域差分全球性定位系统和广域差分全球定位系统是提高GPS实时定位精度的有效手段。利用设在地面参考点上和飞机上的GPS接收机进行载波相位差分测量及区域网平差,可以满足多种比例尺航测成图对空中三角测量的精度要求。目前,RS、GIS与GPS的集成技术是地球空间信息学研究的重要内容,三者综合利用,成为整体的实时的和动态的对地观测、分析和应用的运行系统。     

Improving bird population models using airborne remote sensing

This work was undertaken to devise a technique to measure the height of crops in farmland fields through remote sensing. Crop height is a useful spatial variable which, when measured by ground-based manual survey, has proven to be an important predictor of bird species population. An airborne scanning laser system capable of measuring topography to a height accuracy of better than 10 cm was used to acquire height data over a region of farmland near Oxford, UK. A scanning laser was pulsed from an aircraft at the ground, measuring the time between transmission and receipt of the last significant return signal. Differential Geographical Positioning System (GPS) and onboard attitude sensors were combined with these delay times to construct a set of spot heights through the region. Crop height was also measured from the ground. Pulses were returned from mainly within the crop, rather than predominantly the canopy or ground, so an algorithm to measure the variation of the returned height, after detrending the heights for topography, was developed. A simple relationship was found between the mean crop height and the standard deviation of detrended return heights within a field. This relationship could be used to derive crop height from Light Detection and Ranging (LiDAR) data with an accuracy better than 10cm.     

Integrating profiling LIDAR with Landsat data for regional boreal forest canopy attribute estimation and change characterization

Forest dynamics are characterized by both continuous (i.e., growth) and discontinuous (i.e., disturbance) changes. Change detection techniques that use optical remotely sensed data to capture disturbance related changes are established and commonly applied; however, approaches for the capture of continuous forest changes are less mature. Optical remotely sensed imagery is well suited for capturing horizontally distributed conditions, structures, and changes, while Light Detection And Ranging (LIDAR) data are more appropriate for capturing vertically distributed elements of forest structure and change. The integration of optical remotely sensed imagery and LIDAR data provides improved opportunities to fully characterize forest canopy attributes and dynamics.The study described in this paper captures forest conditions along a corridor approximately 600 km long through the boreal forest of Canada. Two coincident LIDAR transects, representing 1997 and 2002 forest conditions respectively, are compared using image segments generated from Landsat ETM+ imagery. The image segments are used to provide a spatial framework within which the attributes and temporal dynamics of the forest canopy are estimated and compared. Segmented and classified Landsat imagery provides a context for the comparison of sufficiently spatially related LIDAR profiles and for the provision of categories to aid in the application of empirical models requiring knowledge of land cover.Global and local approaches were employed for characterizing changes in forest attributes over time. The global approach, emphasized the overall trend in forest change along the length of the entire transect, and indicated that key canopy attributes were stable, and transect characteristics, including forest canopy height, did not change significantly over the five-year period of this study (two sample t-test, p = 0.08). The local approach analyzed segment-based changes in canopy attributes, providing spatially explicit indications of forest growth and depletion. The local approach identified that 84% of the Landsat segments intercepted by both LIDAR transects either have no change, or have a small average increase in canopy height (0.7 m), while the other 16% of segments have an average decrease in canopy height of 1.6 m. As expected, the difference in the magnitude of the changes was markedly greater for depletions than it was for growth, but was less spatially extensive. Growth tends to occur incrementally over broad areas; whereas, depletions are dramatic and spatially constrained. The approach presented holds potential for investigating the impacts of climate change across a latitudinal gradient of boreal forest.     

基于WorldView-2制备大野口流域高分辨率DEM及精度分析

在全野外GPS地面控制点基础上,对WorldView-2影像自带RPC文件进行校正,利用数字摄影测量软件系统在立体模型上通过影像自动匹配技术快速提取黑河流域上游大野口子流域1∶5 000比例尺数字高程模型(DEM)。由于区域地形复杂、交通不便,研究区南部无地面控制点覆盖。基于立体模型交互式操作,匹配60个均匀分布高精度影像连接点,提高了DEM自动提取精度。并在对阴坡森林覆盖区、大野口水库等重点区域进行DEM编辑基础上,辅助地形特征点和线数据提高了成果精度。由15个外业控制点、12个模型保密点组成的检查点进行定量DEM验证,结果表明:两组高程中误差最大为1.9 m,达到该比例尺山地一级精度2.5 m的要求。
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基于LIDAR数据的城市数字表面模型生成技术

激光雷达(LIDAR)数据是一种新型数据源,它产生的是高密度点云数据。为了更加方便地应用这些数据,首先要生成数字表面模型(DSM)。采用传统的方法生成城市DSM,对城市区域复杂性的考虑不足,也没有对数据存在的缺值情况进行相应处理,故无法生成高质量的城市DSM。该文阐述了一种新颖的生成高质量城市DSM的方法,兼顾城市的复杂性和LIDAR传感器本身的特点。试验证明,该方法生成的DSM与传统方法相比,具备更好的效果。     

Visual Analysis and Semantic Exploration of Urban LIDAR Change Detection

Many previous approaches to detecting urban change from LIDAR point clouds interpolate the points into rasters, perform pixel‐based image processing to detect changes, and produce 2D images as output. We present a method of LIDAR change detection that maintains accuracy by only using the raw, irregularly spaced LIDAR points, and extracts relevant changes as individual 3D models. We then utilize these models, alongside existing GIS data, within an interactive application that allows the chronological exploration of the changes to an urban environment. A three‐tiered level‐of‐detail system maintains a scale‐appropriate, legible visual representation across the entire range of view scales, from individual changes such as buildings and trees, to groups of changes such as new residential developments, deforestation, and construction sites, and finally to larger regions such as neighborhoods and districts of a city that are emerging or undergoing revitalization. Tools are provided to assist the visual analysis by urban planners and historians through semantic categorization and filtering of the changes presented.     

Life-space characterization from cellular telephone collected GPS data

Life-space is an emerging method for measuring older adults’ functional status. Although global positioning system (GPS)-enabled smartphones can collect life-space data passively and accurately, researchers lack an effective process to derive activity information from the raw GPS data. In addition, the influence of GPS retrieving frequency on life-space characterization is unknown. We describe a GPS data processing procedure to estimate life-space. A cellular telephone was used to collect GPS data by a subject during a 4-month period. The GPS data processing procedure was then implemented and evaluated in terms of classification accuracy, reliability, and sensitivity to observation frequency. The proposed scheme generated sufficient zone-based activity information to characterize an individual’s life-space. The speed-based sensitivity assessment suggests 75 s as an appropriate GPS observation interval for smartphone based life-space data collection.