Digital Height Model Research Articles

Deciphering the effects of 2D/3D urban morphology on diurnal cooling efficiency of urban green space

Urban green spaces (UGS) have emerged as a main nature-based solution proven to effectively cool urban areas, and cooling efficiency (CE) serves as a prominent indicator for assessing the performance of UGS. Yet few studies have explored the diurnal dynamics of CE and the comprehensive effects of both 2D and 3D urban morphology on CE over a 24-h period. In this study, we employed diurnal land surface temperature (LST) data from Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to delve into the diurnal CE of UGS within the urban core area of megacity Paris, France. Meanwhile, using high-resolution land cover data, digital height model, and explainable machine learning models, we elucidated the intricate relationship between various 2D and 3D urban morphology metrics and CE during a 24-h cycle. In summary, city-scale continuous monitoring revealed diurnal CE variations, with values ranging from 0.008 °C to 0.13 °C and a standard deviation of 0.04 °C. On an average of a day, the relative importance of the 2D and 3D urban form indicators was 77.25 % and 22.75 %, respectively. Enhancing the dispersion of trees or improving the integrity of non-tree vegetation patches proves to be an effective strategy for augmenting CE. The results can be further used in urban planning to improve urban thermal resilience and adaptability.

Evaluating Statewide NAIP Photogrammetric Point Clouds for Operational Improvement of National Forest Inventory Estimates in Mixed Hardwood Forests of the Southeastern U.S.

The U.S. Forest Service, Forest Inventory and Analysis (FIA) program is tasked with making and reporting estimates of various forest attributes using a design-based network of permanent sampling plots. To make its estimates more precise, FIA uses a technique known as post-stratification to group plots into more homogenous classes, which helps lower variance when deriving population means. Currently FIA uses a nationally available map of tree canopy cover for post-stratification, which tends to work well for forest area estimates but less so for structural attributes like volume. Here we explore the use of new statewide digital aerial photogrammetric (DAP) point clouds developed from stereo imagery collected by the National Agricultural Imagery Program (NAIP) to improve these estimates in the southeastern mixed hardwood forests of Tennessee and Virginia, United States (U.S.). Our objectives are to 1. evaluate the relative quality of NAIP DAP point clouds using airborne LiDAR and FIA tree height measurements, and 2. assess the ability of NAIP digital height models (DHMs) to improve operational forest inventory estimates above the gains already achieved from FIA’s current post-stratification approach. Our results show the NAIP point clouds were moderately to strongly correlated with FIA field measured maximum tree heights (average Pearson’s r = 0.74) with a slight negative bias (−1.56 m) and an RMSE error of ~4.0 m. The NAIP point cloud heights were also more accurate for softwoods (R2s = 0.60–0.79) than hardwoods (R2s = 0.33–0.50) with an error structure that was consistent across multiple years of FIA measurements. Several factors served to degrade the relationship between the NAIP point clouds and FIA data, including a lack of 3D points in areas of advanced hardwood senescence, spurious height values in deep shadows and imprecision of FIA plot locations (which were estimated to be off the true locations by +/− 8 m). Using NAIP strata maps for post-stratification yielded forest volume estimates that were 31% more precise on average than estimates stratified with tree canopy cover data. Combining NAIP DHMs with forest type information from national map products helped improve stratification performance, especially for softwoods. The monetary value of using NAIP height maps to post-stratify FIA survey unit total volume estimates was USD 1.8 million vs. the costs of installing more field plots to achieve similar precision gains. Overall, our results show the benefit and growing feasibility of using NAIP point clouds to improve FIA’s operational forest inventory estimates.

Use Radial Basin Function &Empirical Bayesian kriging To derive and improve the digital height model from the topographic map (Case study on Lake Talker)

The study of lakes and how they are represented spatially is important and has a key role in the construction and development of any country and this depends on the main location of the lake and the possibility of investing its water in agriculture, tourism, electricity generation and others after water scarcity and low level of placements, which led us to study Lake Talker through the use of the model of digital height and topographic maps to reach the possibility of improving this model to reach an academic study that can be used in other scientific fields Lake Al-Tharthar is located 120 km northwest of Baghdad between the Tigris and Euphrates rivers, with an area of 2,710 km2. The highest storage level is 65 meters above sea level and the volume of water storage at this level is 85.89 billion m3. The lake is one of the largest natural depressions in Iraq, where it was established in 1956 to store excess water from the Tigris River, so that adequate amounts of irrigation water can be returned to the two rivers whenever needed.1 Lakes and dams have been established and developed mainly to avoid floods that feed Iraq's rivers from time to time. Two methods of completion were thus used: the Radail Basin Function method and the Empirical Bayesian Kriging and we were able to note that the Payson Road is the best in spatial fulfilment to reach the representation of the 3D shape of the lake. Based on the above, the research has reached a number of results, namely, the possibility of developing improved digital altitude models for different regions of Iraq with local specifications that form the basis of similar studies and research.

Creating a Basic Level Digital Height Model with Unmanned Aerial Vehicle in Ore Fields, Harput Example

İHA (İnsansız Hava Aracı), ilerleyen teknolojiyle beraber özellikle inşaat, maden ve haritacılık sektöründe de yerini almıştır. Zaman, iş gücü ve maliyet gibi parametrelerin külfetini en aza indirgenmesine yol açmıştır. İHA görüntülerinden ilgili alanının konum koordinatları ile beraber Z adı verilen yüksekliklerin farkından dengeleme sayesinde üzerinde uçuş yapılan bölgenin üç boyutlu modellemesi, eğim ve kübaj (hacim) hesaplarına erişmek son derece kolay olmaktadır. Açık maden ocak sahalarında olası hacim hesapları da İHA fotogrametrisi ile mümkündür. Çalışmamız, Elazığ İli Harput Mahallesi Alayaprak denilen mevki de seramik işlerinde kullanılmak üzere çıkarılan kırmızı toprak cevherinin sayısal yükseklik modeli oluşturulmaya çalışıldı. Basit düzeyde SYM(Sayısal Yükseklik Modeli) oluşumu hakkında irdeleme yapıldı. Toplam, 20 yer kontrol noktasından öncelikle RTK (Gerçek Zamanlı Kinematik ) yersel ölçümle noktalarının koordinatları belirlendi. Sonra 45 metre yükseklikten irtifa alınarak RTK sız bir İHA ile kolonlar taranarak karesel ortalama sapmaları değerlendirildi. Ortalama dengeleme ile 17443.839 nokta elde edilerek nokta bulutu oluşturularak DEM (Digital Yükseklik Modeli) verisi elde edildi. Yer önlem aralığı 4,78 cm/piksel alınarak ne kadar metreküp cevher olabilirliği araştırıldı.

Experimental Analysis of Geo-spatial Data to Evaluate Urban Greenspace: A Case Study in Dortmund, Germany

Urban greenspace is of high importance for the general public from different points of view. Among others, it is beneficial for recreational activities as well as for cooling effects during summer in urban climate. Many studies investigate urban greenspace from perspectives related to environmental justice or health geography that are usually based on environmental and sociodemographic data of diverse scales or spatial levels of detail and often suffer from high degrees of generalization. To demonstrate the benefit of a higher degree of spatial detail, a representative part of the city of Dortmund (Germany) is selected as study area. A time series of freely available Sentinel-2 images and a freely available digital object height model (DOHM) are used to analyze and describe the spatio-temporal distribution of urban vegetation and its potential effects on the population. Doing so, the Sentinel-2 images are used for the calculation of vegetation indices to identify the active green period of different vegetation land covers. In addition to that, the three-dimensional appearance of vegetation is correlated with the green period to assume the relevance of green land covers for the general public. The results show that an appropriate selection of cloud-free satellite images is of importance for a greenspace analysis. The combination of high resolution 2D and 3D data sets, namely NDVI and plant height information, reveals the spatial distribution of well-equipped greenspace areas with high recreational and health potential as well as poorly-equipped areas in urban neighborhoods, that could be improved.

Cloud Detection in ZY-3 Multi-Angle Remote Sensing Images

Cloud pollution on remote sensing images seriously affects the actual use rate of remote sensing images. Therefore, cloud detection of remote sensing images is an indispensable part of image preprocessing and image availability screening. Aiming at the lack of short wave infrared and thermal infrared bands in ZY-3 high-resolution satellite images resulting in the poor detection effect, considering the obvious difference in geographic height between cloud and ground surface objects, this paper proposes a thick and thin cloud detection method combining spectral information and digital height model (DHM) based on multi-scale features-convolutional neural network (MF-CNN) model. To verify the importance of DHM height information in cloud detection of ZY-3 multi-angle remote sensing images, this paper implements cloud detection comparison of the data set with and without DHM height information based on the MF-CNN model. The experimental results show that the ZY-3 multi-angle image with DHM height information can effectively improve the confusion between highlighted surface and thin cloud, which also means the assistance of DHM height information can make up for the disadvantage of high-resolution image lacking short wave infrared and thermal infrared bands.

AVAILABILITY AND COMPARISON OF DATA FROM SENTINEL-1 SATELLITES IN AREAS OF INTEREST IN THE CZECH REPUBLIC AND SUDAN

The article is focused on the methodology of processing interferometric images and associated challenges with the processing. The article also contains useful links with explanations that can be used for processing data from the Sentinel-1 satellite. To emphasize the data limits of Sentinel-1, several areas of interest were chosen for comparison – in the home environment of the Czech Republic, the Bílina quarry area, and the Žatec area were selected. For subsequent comparison, arid areas with a rich history located in Sudan were selected. The colleagues of the author from the Faculty of The Environment of Jan Evangelista Purkyně University participate in expeditions there. Each of these locations is limited by different parameters – the areas in the Czech Republic are mainly limited by location because of occurring vegetation. Sudan's regions, on the other hand, are arid but are limited by insufficient coverage by capturing the Sentinel-1 satellite. To create digital height models from Sentinel-1 satellite data, it is necessary to search for data with sufficient coherence of images, and parameters of the amount of vegetation with a period between individual images play an important role. The areas were compared with each other and with the commonly available SRTM elevation model, both from a visual point of view – where digital height models and shaded surface models were created, as well as statistically using RMSE.

Photogrammetric 3D mobile mapping of rail tracks

Recent developments in the field of rail vehicles increased the demand for accurate and up-to-date 3D maps of rail track networks. Collision avoidance systems, semi-automated, or fully autonomous rail vehicles strongly benefit from such high quality maps. In this work, we present a fully automatic, photogrammetric method for the 3D reconstruction of rail track segments. More specifically, the center line of the rail track is reconstructed as a georeferenced and continuous 3D cubic spline. The main data inputs are collected while driving the rail vehicle along the segment: (a) images from a front-looking camera and (b) observations from a low-cost GNSS receiver. Optional data inputs can be used to increase the reconstruction accuracy, namely (c) an a priori rail track (e.g. from OpenStreetMap), (d) a digital height model (DHM), and (e) ground control points (GCPs). The rail track is estimated in post processing (offline) by a weighted least squares adjustment (LSA). The core of the LSA is the bundle adjustment of images. It is extended by additional geometric constraints which exploit the geometric relations between the rail track, the rail vehicle, and the camera trajectory. As a consequence, in contrast to many related methods, the rails need not to be visible in the images to map the rail track. We applied the method to reconstruct a 13km long tram line in Vienna (Austria). We found that the local geometry of the track can be well reconstructed from the image sequence. However, if the low-cost GNSS receiver is used as single georeferencing source, the track shows a strong drift behavior. This drift can significantly be minimized over the entire track if the above mentioned optional data inputs are used.

Estimation of roughness and zero-displacement heights over Baghdad utilizing remote sensing and GIS techniques

The objective of this study was to estimate the height of roughness element (ZH) and zero-displacement length (Zd) for Baghdad city using remote sensing and GIS techniques and resources such as DEM, DSM, and shapefile. The difference between DEM and DSM produced digital height model which represents the height of the roughness element for the region, which was used to determine the zero-displacement height. The results showed that the variations in Zd values depend strongly on ZH. Rusafa had the highest Zd (15.8 m) while Dora had the lowest values (4.7 m). Thus, Baghdad city has medium density classification according to the results of Zd and ZH values.

Quality of Height Models Covering Large Areas

Digital height models (DHM) are a basic requirement for several applications. The generation of DHM is time consuming and expensive, but some nearly worldwide covering height models are available free of charge or commercially and the number and quality are growing. For practical use it is important to have some information about the quality, the accuracy, accuracy characteristics, areas with problems, height definition as digital surface model with the height of the visible surface or as digital terrain model with heights of the bare ground, resolution (point spacing and correlation of neighboured height values), homogeneity and availability. Also morphologic details are important, depending upon the point spacing and relative height accuracy. An overview about the freely available and commercially nearly worldwide covering height models with a satisfying point spacing and accuracy is given. Changes in this area are fast, so only the current status can be described. A really worldwide covering DHM came with the commercial WorldDEM, based on TanDEM-X interferometric synthetic aperture radar (InSAR) from which now also a reduced, free version with 3 arcsec point spacing is available as TDM90. In addition to the highest accuracy in this field with 10 m point spacing, WorldDEM has also very good morphologic details with the exception of city areas. Quality files belonging to WorldDEM include information about areas with problems. Some height models have been analysed by comparison with satisfying reference height models. The characteristics are described as well as the problems of accuracy specifications with different accuracy figures and dependency upon terrain inclination and other parameters, to allow a selection corresponding to the individual requirements. This also includes horizontal shifts or even rotations and higher degree systematic differences between the reference and the analysed DHM.

AUTOMATED CHAIN FOR LARGE-SCALE 3D RECONSTRUCTION OF URBAN SCENES FROM SATELLITE IMAGES

Abstract. Automatic city modeling from satellite imagery is a popular yet challenging topic in remote sensing, driven by numerous applications such as telecommunications, defence and urban mamagement. In this paper, we present an automated chain for large-scale 3D reconstruction of urban scenes with a Level of Detail 1 from satellite images. The proposed framework relies on two key ingredient. First, from a stereo pair of images, we estimate a digital terrain model and a digital height model, by using a novel set of feature descriptors based on multiscale morphological analysis. Second, inspired by recent works in machine learning, we extract in an automatic way contour polygons of buildings, by adopting a fully convolutional network U-Net followed by a polygonization of the predicted mask of buildings. We demonstrate the potential of our chain by reconstructing in an automated way different areas of the world.

CNN-based estimation of pre- and post-earthquake height models from single optical images for identification of collapsed buildings

ABSTRACTIn this paper, a novel approach is proposed to identify collapsed buildings after an earthquake using pre-event satellite image as well as post-event satellite image and airborne LiDAR data. In this regard, a convolutional neural network-based method is proposed for estimating a DHM from a single satellite image. A structure reconstruction strategy is designed to improve estimated height values and objects geometry by using the local features of shallow layers and employing a progressive context fusion method. The post-event images and their corresponding LiDAR data are used to train the proposed network. Subsequently, the trained network is employed to estimate a digital height model (DHM) from the pre-event satellite image. Finally, by investigating the difference image of pre- and post-event DHMs, collapsed buildings are identified. It is observed that the quality, kappa coefficient and overall accuracy of the obtained results are 84.86%, 91.15% and 98.78%, respectively, demonstrating a promising performance of the proposed approach.

الحصاد المائي السطحي لحـوض وادي السهـل الغــربي بهضبة البطنان باستخدام نظم المعلومات الجغرافية

The study of drainage basins and networks of any area is important in geological and geomorphological studies. The results can be used to identify the hydrological characteristics of the basins and also to infer the water budget and the quantity of water that can be. The study aims at building a database of the morphometric and hydrological characteristics of the basin of the western valley of the plain, which is one of the most important basins that extend in the northeastern part of the plateau. In order to achieve the objectives of the basin study, the descriptive approach, the analytical method and the quantitative statistical method were used. And satellite images of the region, in addition to field observations, and also relied on the technology of remote sensing and information systems geography in order to identify and estimate the amount of surface salts and harvesting of surface saline water for the basin of the Valley of the Sahel, Hydrology and Water Budget of the Basin The morphometric parameters of Wadi Al-Sahl al-Gharbi were extracted. The digital height model (DEM) was calculated with a precision of 12 meters from the satellite vision by determining the basin boundary, to build basin net work by using Arc GIS programming.

Study of Hydrological Parameter with Respect to DEM Using GIS & RS in Nelliampathy Hill, Kerala

Digital elevation models (DEMs) represent the total topography, surface flow is one of the more important data sources for deriving variables used by numerous hydrologic models. A lot of research has been directed to address vulnerability related with error in digital height models (DEMs) and the spread of blunder to determined terrain parameters. This audit unites a discourse of research in major topical regions identified with DEM vulnerability that influence the utilization of DEMs for hydrologic applications. The work is to give some understanding into the characterization of elevation data quality and the relationship amongst topography and water assets models. A key characteristic of circulated displaying is the spatially factor portrayal of the watershed as far as topography, vegetative, or land use/cover, soils and impenetrable territories and the subordinate model parameters that represent the hydrologic procedures of infiltration, evapotranspiration, and runoff. In our study, application of DEM and deriving hydrological parameters using remote sensing and GIS technology at Nelliampathy hill, Kerala.

Alternatives to LiDAR-derived canopy height models for softwood plantations: a review and example using photogrammetry

ABSTRACTAirborne LiDAR data is now commonly acquired by the Australian plantation sector in order to generate accurate digital terrain models and canopy height models at high spatial resolution for resource assessment estimates. However, these airborne surveys are relatively expensive and there is a desire to identify more affordable options for collecting or updating this information. This review presents alternative approaches to deriving canopy height models, including the use of stereo optical imagery from satellites, manned and unmanned airborne platforms, and the use of synthetic aperture radar. In addition, we illustrate the potential of airborne photogrammetry with multi-view dense point matching to produce an accurate, hybrid photo-LiDAR canopy height model at high spatial resolution along a transect covering stands of several softwood tree species.

ANALYSIS AND CORRECTION OF SYSTEMATIC HEIGHT MODEL ERRORS

Abstract. The geometry of digital height models (DHM) determined with optical satellite stereo combinations depends upon the image orientation, influenced by the satellite camera, the system calibration and attitude registration. As standard these days the image orientation is available in form of rational polynomial coefficients (RPC). Usually a bias correction of the RPC based on ground control points is required. In most cases the bias correction requires affine transformation, sometimes only shifts, in image or object space. For some satellites and some cases, as caused by small base length, such an image orientation does not lead to the possible accuracy of height models. As reported e.g. by Yong-hua et al. 2015 and Zhang et al. 2015, especially the Chinese stereo satellite ZiYuan-3 (ZY-3) has a limited calibration accuracy and just an attitude recording of 4 Hz which may not be satisfying. Zhang et al. 2015 tried to improve the attitude based on the color sensor bands of ZY-3, but the color images are not always available as also detailed satellite orientation information. There is a tendency of systematic deformation at a Pléiades tri-stereo combination with small base length. The small base length enlarges small systematic errors to object space. But also in some other satellite stereo combinations systematic height model errors have been detected. The largest influence is the not satisfying leveling of height models, but also low frequency height deformations can be seen. A tilt of the DHM by theory can be eliminated by ground control points (GCP), but often the GCP accuracy and distribution is not optimal, not allowing a correct leveling of the height model. In addition a model deformation at GCP locations may lead to not optimal DHM leveling. Supported by reference height models better accuracy has been reached. As reference height model the Shuttle Radar Topography Mission (SRTM) digital surface model (DSM) or the new AW3D30 DSM, based on ALOS PRISM images, are satisfying. They allow the leveling and correction of low frequency height errors and lead to satisfying correction of the DSM based on optical satellite images. The potential of DHM generation, influence of systematic model deformation and possibilities of improvement has been investigated.

ANALYSIS AND CORRECTION OF SYSTEMATIC HEIGHT MODEL ERRORS

The geometry of digital height models (DHM) determined with optical satellite stereo combinations depends upon the image orientation, influenced by the satellite camera, the system calibration and attitude registration. As standard these days the image orientation is available in form of rational polynomial coefficients (RPC). Usually a bias correction of the RPC based on ground control points is required. In most cases the bias correction requires affine transformation, sometimes only shifts, in image or object space. For some satellites and some cases, as caused by small base length, such an image orientation does not lead to the possible accuracy of height models. As reported e.g. by Yong-hua et al. 2015 and Zhang et al. 2015, especially the Chinese stereo satellite ZiYuan-3 (ZY-3) has a limited calibration accuracy and just an attitude recording of 4 Hz which may not be satisfying. Zhang et al. 2015 tried to improve the attitude based on the color sensor bands of ZY-3, but the color images are not always available as also detailed satellite orientation information. There is a tendency of systematic deformation at a Pléiades tri-stereo combination with small base length. The small base length enlarges small systematic errors to object space. But also in some other satellite stereo combinations systematic height model errors have been detected. The largest influence is the not satisfying leveling of height models, but also low frequency height deformations can be seen. <br><br> A tilt of the DHM by theory can be eliminated by ground control points (GCP), but often the GCP accuracy and distribution is not optimal, not allowing a correct leveling of the height model. In addition a model deformation at GCP locations may lead to not optimal DHM leveling. Supported by reference height models better accuracy has been reached. As reference height model the Shuttle Radar Topography Mission (SRTM) digital surface model (DSM) or the new AW3D30 DSM, based on ALOS PRISM images, are satisfying. They allow the leveling and correction of low frequency height errors and lead to satisfying correction of the DSM based on optical satellite images. <br><br> The potential of DHM generation, influence of systematic model deformation and possibilities of improvement has been investigated.

The influence of topographic variation on forest structure in two woody plant communities: A remote sensing approach

Aim of study: The study aimed to characterise variation in structural attributes of vegetation in relation to variations in topographic position using LIDAR data over landscapes.Area of study: The study was conducted in open canopy eucalypt-dominated forest (Richmond Range National Park-RRNP) and closed canopy subtropical rainforest (Border Ranges National Park-BRNP) in north-eastern New South Wales, Australia.Material and Methods: one metre resolution digital canopy height model (CHM) was extracted from the LIDAR data and used to estimate maximum overstorey height and crown area. LIDAR fractional cover representing the photosynthetic and non-photosynthetic component of canopy was calculated using LIDAR points aggregated into 50 m spatial bins. Potential solar insolation, Topographic Wetness Index (TWI), slope and the elevation were processed using LIDAR derived digital elevation models.Main results: No relationship was found between maximum overstorey height and insolation gradient in the BRNP. Maximum overstorey height decreased with increasing insolation in the RRNP (R2 0.45). Maximum overstorey height increased with increasing TWI in the RRNP. Average crown area decreased with increasing insolation in both study areas. LIDAR fractional cover decreased with increasing insolation (R2 0.54), and increased with increasing TWI (R2 0.57) in the RRNP.Research highlights: The characterization of structural parameters of vegetation in relation to the variation of the topography was possible in eucalyptus dominated open canopy forest. No reportable difference in variation of structural elements of vegetation was detected with topographic variation of subtropical rainforest.

Interpretation of Forest Resources at the Individual Tree Level in Japanese Conifer Plantations Using Airborne LiDAR Data

More than 50% of the national lands in Japan have been surveyed by airborne laser scanning (ALS) data with different point densities; and developing an effective approach to take full advantage of these ALS data for forest management has thus become an urgent topic of study. This study attempted to assess the utility of ALS data for individual tree detection and species classification in a mixed forest with a high canopy density. For comparison, two types of tree tops and tree crowns in the study area were delineated by the individual tree crown (ITC) approach using the green band of the orthophoto imagery and the digital canopy height model (DCHM) derived from the ALS data, respectively. Then, the two types of tree crowns were classified into four classes—Pinus densiflora (Pd), Chamaecyparis obtusa (Co), Larix kaempferi (Lk), and broadleaved trees (Bl)—by a crown-based classification approach using different combinations of the three orthophoto bands with intensity and slope maps as follows: RGB (red, green and blue); RGB and intensity (RGBI); RGB and slope (RGBS); and RGB, intensity and slope (RGBIS). Finally, the tree tops were annotated with species attributes from the two best-classified tree crown maps, and the number of different tree species in each compartment was counted for comparison with the field data. The results of our study suggest that the combination of RGBIS yielded greater classification accuracy than the other combinations. In the tree crown classifications delineated by the green band and DCHM data, the improvements in the overall accuracy compared to the RGB ranged from 5.7% for the RGBS to 9.0% for the RGBIS and from 8.3% for the RGBS to 11.8% for the RGBIS. The laser intensity and slope derived from the ALS data may be valuable sources of information for tree species classification, and in terms of distinguishing species for the detection of individual trees, the findings of this study demonstrate the advantages of using DCHM instead of optical data to delineate tree crowns. In conclusion, the synthesis of individual tree delineation using DCHM data and species classification using the RGBIS combination is recommended for interpreting forest resources in the study area. However, the usefulness of this approach must be verified in future studies through its application to other forests.

A new method for generating canopy height models from discrete-return LiDAR point clouds

Tree height underestimation and occurrence of visible data pits are two major problems in light detection and ranging (LiDAR)-derived digital surface models and canopy height models (CHMs) in forested areas. To address the two major problems, a new method is proposed for generating CHMs from discrete-return LiDAR point clouds using a selecting and sorting mechanism based on a circle centred at the target point, followed by spatial interpolation. Test results from simulated and real LiDAR point clouds show that the new method outperformed three other methods in terms of treetop approximation, crown surface representation and data pit removal.