Nova automatska metoda za poboljšanje točnosti fotogrametrijskog DTM-a u šumama

Accuracy of a Digital Terrain Model (DTM) in a complex forest environment is critical and yet challenging for accurate forest inventory and management, disaster risk analysis, and timber utilization. Reducing elevation errors in photogrammetric DTM (DTMPHM), which present the national standard in many countries worldwide, is critical, especially for forested areas. In this paper, a novel automated method to detect the errors and to improve the accuracy of DTMPHM for the lowland forest has been presented and evaluated. This study was conducted in the lowland pedunculate oak forest (Pokupsko Basin, Croatia). The DTMPHM was created from three-dimensional (3D) vector data collected by aerial stereo-photogrammetry in combination with data collected from existing maps and field surveys. These data still present the national standard for DTM generation in many countries, including Croatia. By combining slope and tangential curvature values of raster DTMPHM, the proposed method developed in open source Grass GIS software automatically detected 91 outliers or 3.2% of the total number of source points within the study area. Comparison with a highly accurate LiDAR DTM confirmed the method efficiency. This was especially evident in two out of three observed subset areas where the root mean square error (RMSE) values decreased for 8% in one and 50% in another area after errors elimination. The method could be of great importance to other similar studies for forested areas in countries where the LiDAR data are not available.Digitalni model reljefa (DTM, engl. Digital Terrain Model) ima široku i važnu primjenu u mnogim djelatnostima, uključujući i šumarstvo. Međutim, precizno modeliranje terena, odnosno izrada DTM-a u šumama, bilo korištenjem terenskih metoda ili metoda daljinskih istraživanja, izazovan je i vrlo zahtjevan zadatak. U većini razvijenih zemalja svijeta, zračno lasersko skeniranje (ALS, engl. Airborne Laser Scanning) bazirano na LiDAR (engl. Light Detection and Ranging) tehnologiji trenutno predstavlja glavnu metodu za izradu DTM-a. Uslijed mogućnosti laserskog zračenja da penetrira kroz krošnje drveća, LiDAR tehnologija se pokazala kao efektivna i brza metoda za izradu DTM-a u šumskim područjima s vrlo velikom točnošću. Međutim, u mnogim zemljama svijeta, uključujući i Hrvatsku, zračno lasersko skeniranje nije u potpunosti provedeno, tj. samo su manji dijelovi zemlje pokriveni s podacima zračnog laserskog skeniranja. U tim slučajevima, DTM temeljen na stereo-fotogrametrijskoj izmjeri aerosnimaka potpomognut s terenskim podacima najčešće predstavlja glavni izvor informacija za izradu DTM-a. Poznato je da tako izrađen DTM u šumskim predjelima ima manju točnost od DTM-a dobivenog na temelju zračnog laserskog skeniranja zbog pokrivenosti terena vegetacijom. Također, u okviru nedavno provedenog istraživanja (Balenović i dr., 2018) utvrđeno je da takvi službeni fotogrametrijski digitalni podaci terena u šumskim predjelima sadrže određen broj tzv. grubih grešaka, koje mogu značajno utjecati na točnost izrađenog DTM-a. Nakon vizualnog detektiranja i manualnog uklanjanja tih pogrešaka, Balenović i dr. (2018) utvrdili su značajno poboljšanje točnosti fotogrametrijskog DTM-a.Stoga je glavni cilj ovoga rada razviti automatsku metodu za detekciju i eliminaciju vertikalnih pogrešaka u fotogrametrijskim digitalnim podacima terena te na taj način poboljšati točnost fotogrametrijskog DTM-a u nizinskim šumskim područjima Hrvatske. Ideja je razviti brzu, jednostavnu i učinkovitu metodu koja će biti primjenjiva i za druga šumska područja sličnih karakteristika, a za koja ne postoje DTM dobiven zračnim laserskim skeniranjem. Istraživanje je provedeno u nizinskim šumama na području gospodarske jedinice Jastrebarski lugovi, u neposrednoj blizini Jastrebarskog (Slika 1). Istraživanjem je obuhvaćena površina od 2.005,74 ha, na kojoj su u najvećoj mjeri zastupljene jednodobne sastojine hrasta lužnjaka (Quercus robur L.), a u ma­njoj mjeri jednodobne sastojine poljskog jasena (Fraxinus angustifolia L.) te jednodobne sastojine običnoga graba (Carpinus betulus L.). Nadmorska visina područja istraživanja kreće se u rasponu od 105 do 121 m.Fotogrametrijski DTM (DTMPHM) je izrađen iz digitalnih vektorskih podataka terena (prijelomnice, linije oblika, markantne točke terena i pravokutne mreže visinskih točaka) nabavljenih iz Državne geodetske uprave (Slika 2). Ti podaci predstavljaju nacionalni standard i jedini su dostupni podaci za izradu DTM-a u Hrvatskoj. Detaljan opis vektorskih podataka dan je u radu Balenović i dr. (2018). Prvo je iz digitalnih terenskih podataka izrađena nepravilna mreža trokuta, koja je potom linearnom interpolacijom pretvorena u rasterski DTMPHM prostorne rezolucije (veličine piksela) 0,5 m. Automatska metoda za detekciju i eliminaciju vertikalnih pogrešaka fotogrametrijskog DTM-a u nizinskim šumskim područjima razvijena je u slobodnom programskom paketu Grass GIS (Slika 3). Kombinacijom vrijednosti nagiba i tangencijalne zakrivljenosti terena rasterskog DTMPHM (Slika 4), automatskom metodom su detektirane 91 grube greške (engl. outliers). Drugim riječima, utvrđeno je da 91 točkasti vektorski objekt pogrešno prikazuje stvarnu visinu terena. Navedeni broj čini 3,2 % od ukupnog broja točkastih objekata korištenih za izradu DTMPHM-a. Nakon eliminacije detektiranih pogrešaka izrađen je novi, korigirani fotogrametrijski DTM (DTMPHMc). Za ocjenu vertikalne točnosti izvornog (DTMPHM) i korigiranog DTM-a (DTMPHMc) korišten je visoko precizni DTM dobiven zračnim laserskim skeniranjem (DTMLiD). U tu svrhu su izrađeni rasteri razlika između DTMPHM i DTMLiD, te između DTMPHMc i DTMLiD. Kako je preliminarnom analizom utvrđeno da vertikalne razlike između DTMPHM i DTMLiD nisu normalno distribuirane (Slika 5), za ocjenu točnosti su uz normalne mjere točnosti korištene i tzv. robusne mjere točnosti (Tablica 2). Dobiveni rezultati ukazuju na poboljšanje vertikalne točnosti fotogrametrijskog DTM-a primjenom razvijene automatske metode. To je posebice uočljivo na podpodručjima 2 i 3 (Slika 6 i 7) u kojima se nakon uklanjanja detektiranih grešaka, korijen srednje kvadratne pogreške (RMSE, engl. root mean square error) smanjio za 8 % odnosno 50 % (Tablica 2). Na temelju dobivenih rezultata i usporedbe s DTMLiD, može se zaključiti da predložena metoda uspješno detektira i eliminira vertikalne pogreške fotogrametrijskog DTM-a u nizinskim šumskim područjima, te slijedom toga poboljšava njegovu vertikalnu točnost

Sampling Strategy and Accuracy Assessment for Digital Terrain Modelling

In this thesis, investigations into some of the problems related to three of the main concerns (i. e. accuracy, cost and efficiency) of digital terrain modelling have been carried out. Special attention has been given to two main issues - the establishment of a family of mathematical models which is comprehensive in theory and reliable in practice, and the development of a procedure for the determination of an optimum sampling interval for a DTM project with a specified accuracy requirement. Concretely, the following discussions or investigations have been carried out:- i). First of all, a discussion of the theoretical background to digital terrain modelling has been conducted and an insight into the complex matter of digital terrain surface modelling has been obtained. ii). Some investigations into the improvement of the quality of DTM source data have been carried out. In this respect, algorithms for gross error detection have been developed and a procedure for random noise filtering implemented. iii). Experimental tests of the accuracy of DTMs derived from various data sources (i. e. aerial photography, space photography and existing contour maps) have been carried out. In the case of the DTMs derived from photogrammetrically measured data, the tests were designed deliberately to investigate the relationship between DTM accuracy and sampling interval, terrain slope and data pattern. In the case of DTMs derived from digital contour data, the tests were designed to investigate the relationship between DTM accuracy and contour interval, terrain slope and the characteristics of the data set. iv). The problems related to the reliability of the DTM accuracy figures obtained from the results of the experimental tests have also been investigated. Some criteria have also been set for the accuracy, number and distribution of check points. v). A family of mathematical models has been developed for the prediction of DTM accuracy. These models have been validated by experimental test data and evaluated from a theoretical standpoint. Some of the existing accuracy models have also been evaluated for comparison purposes. vi). A procedure for the determination of the optimum sampling interval for a DTM project with a specified accuracy requirement has also been proposed. Based on this procedure, a potential sampling strategy has also been investigated

Semi-automated geomorphological mapping applied to landslide hazard analysis

Computer-assisted three-dimensional (3D) mapping using stereo and multi-image (“softcopy”) photogrammetry is shown to enhance the visual interpretation of geomorphology in steep terrain with the direct benefit of greater locational accuracy than traditional manual mapping. This would benefit multi-parameter correlations between terrain attributes and landslide distribution in both direct and indirect forms of landslide hazard assessment. Case studies involve synthetic models of a landslide, and field studies of a rock slope and steep undeveloped hillsides with both recently formed and partly degraded, old landslide scars. Diagnostic 3D morphology was generated semi-automatically both using a terrain-following cursor under stereo-viewing and from high resolution digital elevation models created using area-based image correlation, further processed with curvature algorithms. Laboratory-based studies quantify limitations of area-based image correlation for measurement of 3D points on planar surfaces with varying camera orientations. The accuracy of point measurement is shown to be non-linear with limiting conditions created by both narrow and wide camera angles and moderate obliquity of the target plane. Analysis of the results with the planar surface highlighted problems with the controlling parameters of the area-based image correlation process when used for generating DEMs from images obtained with a low-cost digital camera. Although the specific cause of the phase-wrapped image artefacts identified was not found, the procedure would form a suitable method for testing image correlation software, as these artefacts may not be obvious in DEMs of non-planar surfaces.Modelling of synthetic landslides shows that Fast Fourier Transforms are an efficient method for removing noise, as produced by errors in measurement of individual DEM points, enabling diagnostic morphological terrain elements to be extracted. Component landforms within landslides are complex entities and conversion of the automatically-defined morphology into geomorphology was only achieved with manual interpretation; however, this interpretation was facilitated by softcopy-driven stereo viewing of the morphological entities across the hillsides.In the final case study of a large landslide within a man-made slope, landslide displacements were measured using a photogrammetric model consisting of 79 images captured with a helicopter-borne, hand-held, small format digital camera. Displacement vectors and a thematic geomorphological map were superimposed over an animated, 3D photo-textured model to aid non-stereo visualisation and communication of results

Evaluation of high quality topographic data for geomorphological and flood impact studies in upland area: North York Moors, UK

A flash flood on 19th June 2005 caused more than one hundred landslides in the North-western North York Moors uplands, UK. This project aims to 1) assess digital elevation models (DEMs) in terms of statistical terrain analysis and 2) explore the sensitivity of a 2D FLOWMAP model response to DEMs input data. A variety of topographic data were acquired, generated and processed. These included high-resolution aerial photographs, Ordnance Survey (OS) DEMs, topographic maps, InSAR DEMs, LiDAR data and ground survey data. These DEMs of different horizontal and vertical resolutions were analysed through key topographic parameters calculated using three different software packages. Key topographic attributes such as slope, aspect, profile curvature and the Topographic Wetness Index (TWI) were studied. Results demonstrate that DEMs from different sources or at different resolutions provide different representations of topographic parameters especially in areas where large topographic changes take place. Algorithms used in different packages also had an effect. Degradation in the representation of topographic information is larger between 10 m and 50 m DEMs than between 5 m and 10 m DEMs. Finer resolution and smaller filter size have the same type of impact on slope and aspect. In addition, DEMs at finer horizontal resolutions have smaller minimum profile curvatures and larger maximum values and standard deviations in profile curvature. The TWI is more sensitive to the horizontal resolution than DEM data source and finer DEMs calculate smaller minimum and mean TWI and larger maximum TWI and standard deviations. Modelled hydrological responses are sensitive to both DEM resolution and its data source. Model showed different results when using 5 m LİDAR DEM and 5 m InSAR DEM of the same area, which meant DEM source had impacts on modelling These differences reduced with a larger magnitude flooding. Producing a better representative surface model from the LİDAR data has much larger impact on model response than adjusting a constant roughness coefficient

Object-Based Greenhouse Classification from GeoEye-1 and WorldView-2 Stereo Imagery

Remote sensing technologies have been commonly used to perform greenhouse detection and mapping. In this research, stereo pairs acquired by very high-resolution optical satellites GeoEye-1 (GE1) and WorldView-2 (WV2) have been utilized to carry out the land cover classification of an agricultural area through an object-based image analysis approach, paying special attention to greenhouses extraction. The main novelty of this work lies in the joint use of single-source stereo-photogrammetrically derived heights and multispectral information from both panchromatic and pan-sharpened orthoimages. The main features tested in this research can be grouped into different categories, such as basic spectral information, elevation data (normalized digital surface model; nDSM), band indexes and ratios, texture and shape geometry. Furthermore, spectral information was based on both single orthoimages and multiangle orthoimages. The overall accuracy attained by applying nearest neighbor and support vector machine classifiers to the four multispectral bands of GE1 were very similar to those computed from WV2, for either four or eight multispectral bands. Height data, in the form of nDSM, were the most important feature for greenhouse classification. The best overall accuracy values were close to 90%, and they were not improved by using multiangle orthoimages

LEAST SQUARES MATCHING FOR COMPARISON OF DIGITAL TERRAIN MODELS AND ITS APPLICATION POTENTIAL FOR THE BRAZILIAN MODELS AND THE SRTM MODEL

Digital Terrain Models are being used for planning and hydrological applications, but also for visualization and many other tasks. For all applications, it is necessary to know the model quality, because it has an impact on the quality of the decisions that are drawn from the terrain model applications. In this paper we present a method that is suitable for comparing two terrain models to each other. Vertical, but also horizontal displacement of terrain features can be found automatically, which are systematic errors and are in the main focus of this paper. However, random errors can be quantified, too. This method allows establishing a vector field of differences between two models, measuring the deviation from one to the other. These deviations are a measure of quality of one model against the other. Emphasis will be put on comparing terrain model from NASAs Shuttle Radar Topographic Mission to terrain models of known quality in Brazil

The efficient use of data from different sources for production and application of digital elevation models

The emphasis of the investigation reported in this thesis is on the use of digital elevation data of two resolutions originating from two different sources. The high resolution DEM was captured from aerial photographs (first source) at a scale of 1:30,000 and the low resolution DEM was captured from SPOT images (second source). It is well known that the resolution of DEM data depends a great deal on the scale of the images used. The technique for capturing DEMs is static measurement of the spot heights in a regular grid. The grid spacing of the high resolution DEM was 30 m, and of the low resolution DEM was 100 m. The aims of this thesis are as follows: 1. To assess the feasibility of using SPOT stereodata as a source of height information and merged with data from aerial photography. This is carried out by comparison of the elevation data derived from SPOT with the digital elevation data derived from aerial photography. From the comparison of these two sources of height information, some results are derived which show the possible heighting accuracy levels which can realistically be achieved. A systematic error in the estimated average of the elevation differences was found and many tests have been carried out to find the reasons for the presence of this systematic error. 2. To develop methods to manipulate the captured data. 2.1. Gross error (blunder) detection. Blunders made during the data capturing procedure affect the accuracy of the final product. Therefore it is necessary to trap and to remove them. A pointwise local self-checking blunder detection algorithm was developed in order to check the grid elevation data, particularly those which are derived from the second source. 2.2. Data coordinates transformation. The data must be transformed into a common projection in order to be directly comparable. The projection and coordinate systems employed are studied in this project, and the errors caused by the transformations are estimated. 2.3. Data merging. Data of different reliability have to be merged into a single set of data. In this project data from two different sources are merged in order to create a final product of known and uniform accuracy. The effect of the lower resolution source on the high resolution source was studied, in dense and in sparse form. 2.4. Data structure. To structure the data by changing the format in order to be in an acceptable form for DEM creation and display, through the commercially available Laser-Scan package DTMCREATE. 3. DEM production and contouring. To produce DEMs from the initial data and that derived from the two merged sources, and to find the accuracy of the interpolation procedure by comparing the derived interpolated data with the high resolution DEM which has been derived from aerial photography. Finally to interpolate contours directly from the "raw" SPOT data and to compare them with those derived from the aerial photography in order to find out the feasibility and capability of using SPOT data in contouring for topographic maps

Bedmap2: improved ice bed, surface and thickness datasets for Antarctica

We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60 S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved datacoverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72m lower and the area of ice sheet grounded on bed below sea level is increased by 10 %. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets