Airborne Laser Scanning and the Archaeological Interpretation of Ireland’s First World War Landscape”:The Case Study of Randalstown Training Camp

The training of Irish soldiers for service in the British Army during the First World War required the establishment of training camps across the island, such as at Shane’s Castle Estate, close to Randalstown in County Antrim, Northern Ireland. The camp saw active use from 1914 to 1918 but after the war it was demilitarised and returned to use as farmland. Archaeological investigations have revealed that earthwork traces of the camp can still be identified in the modern landscape. Comparison of a map of the camp from 1915, Airborne Laser Scanning data and aerial photographs has enabled the footprint of the camp to be re-established, while also helping to identify the location of specific elements such as the remains of barrack huts, stores, mess halls and officers’ quarters.

Assessing modern ground survey methods and airborne laser scanning for digital terrain modelling:A case study from the Lake District, England

This paper compares the applicability of three ground survey methods for modelling terrain: one man electronic tachymetry (TPS), real time kinematic GPS (GPS), and terrestrial laser scanning (TLS). Vertical accuracy of digital terrain models (DTMs) derived from GPS, TLS and airborne laser scanning (ALS) data is assessed. Point elevations acquired by the four methods represent two sections of a mountainous area in Cumbria, England. They were chosen so that the presence of non-terrain features is constrained to the smallest amount. The vertical accuracy of the DTMs was addressed by subtracting each DTM from TPS point elevations. The error was assessed using exploratory measures including statistics, histograms, and normal probability plots. The results showed that the internal measurement accuracy of TPS, GPS, and TLS was below a centimetre. TPS and GPS can be considered equally applicable alternatives for sampling the terrain in areas accessible on foot. The highest DTM vertical accuracy was achieved with GPS data, both on sloped terrain (RMSE 0.16. m) and flat terrain (RMSE 0.02. m). TLS surveying was the most efficient overall but veracity of terrain representation was subject to dense vegetation cover. Therefore, the DTM accuracy was the lowest for the sloped area with dense bracken (RMSE 0.52. m) although it was the second highest on the flat unobscured terrain (RMSE 0.07. m). ALS data represented the sloped terrain more realistically (RMSE 0.23. m) than the TLS. However, due to a systematic bias identified on the flat terrain the DTM accuracy was the lowest (RMSE 0.29. m) which was above the level stated by the data provider. Error distribution models were more closely approximated by normal distribution defined using median and normalized median absolute deviation which supports the use of the robust measures in DEM error modelling and its propagation. © 2012 Elsevier Ltd.

Optimizaci��n de la Exactitud Geométrica al Integrar Diversas Fuentes de Datos en Proyectos de Inventario Forestal Basados en Escaneo Laser Aerotransportado=Optimizing Geometric Accuracy in Data Source Integration for Airborne Laser Scanning-based Forest Inventory Projects

La mayoría de las aplicaciones forestales del escaneo laser aerotransportado (ALS, del inglés airborne laser scanning) requieren la integraci��n y uso simultaneo de diversas fuentes de datos, con el propósito de conseguir diversos objetivos. Los proyectos basados en sensores remotos normalmente consisten en aumentar la escala de estudio progresivamente a lo largo de varias fases de fusi��n de datos: desde la informaci��n más detallada obtenida sobre un área limitada (la parcela de campo), hasta una respuesta general de la cubierta forestal detectada a distancia de forma más incierta pero cubriendo un área mucho más amplia (la extensi��n cubierta por el vuelo o el satélite). Todas las fuentes de datos necesitan en ultimo termino basarse en las tecnologías de sistemas de navegaci��n global por satélite (GNSS, del inglés global navigation satellite systems), las cuales son especialmente erróneas al operar por debajo del dosel forestal. Otras etapas adicionales de procesamiento, como la ortorectificaci��n, tambi��n pueden verse afectadas por la presencia de vegetaci��n, deteriorando la exactitud de las coordenadas de referencia de las imágenes ópticas. Todos estos errores introducen ruido en los modelos, ya que los predictores se desplazan de la posici��n real donde se sitúa su variable respuesta. El grado por el que las estimaciones forestales se ven afectadas depende de la dispersi��n espacial de las variables involucradas, y tambi��n de la escala utilizada en cada caso. Esta tesis revisa las fuentes de error posicional que pueden afectar a los diversos datos de entrada involucrados en un proyecto de inventario forestal basado en teledetecci��n ALS, y como las propiedades del dosel forestal en sí afecta a su magnitud, aconsejando en consecuencia métodos para su reducci��n. Tambi��n se incluye una discusi��n sobre las formas más apropiadas de medir exactitud y precisi��n en cada caso, y como los errores de posicionamiento de hecho afectan a la calidad de las estimaciones, con vistas a una planificaci��n eficiente de la adquisici��n de los datos. La optimizaci��n final en el posicionamiento GNSS y de la radiometría del sensor óptico permiti�� detectar la importancia de este ultimo en la predicci��n de la desidad relativa de un bosque monoespecífico de Pinus sylvestris L. ABSTRACT Most forestry applications of airborne laser scanning (ALS) require the integration and simultaneous use of various data sources, pursuing a variety of different objectives. Projects based on remotely-sensed data generally consist in upscaling data fusion stages: from the most detailed information obtained for a limited area (field plot) to a more uncertain forest response sensed over a larger extent (airborne and satellite swath). All data sources ultimately rely on global navigation satellite systems (GNSS), which are especially error-prone when operating under forest canopies. Other additional processing stages, such as orthorectification, may as well be affected by vegetation, hence deteriorating the accuracy of optical imagery’s reference coordinates. These errors introduce noise to the models, as predictors displace from their corresponding response. The degree to which forest estimations are affected depends on the spatial dispersion of the variables involved and the scale used. This thesis reviews the sources of positioning errors which may affect the different inputs involved in an ALS-assisted forest inventory project, and how the properties of the forest canopy itself affects their magnitude, advising on methods for diminishing them. It is also discussed how accuracy should be assessed, and how positioning errors actually affect forest estimation, toward a cost-efficient planning for data acquisition. The final optimization in positioning the GNSS and optical image allowed to detect the importance of the latter in predicting relative density in a monospecific Pinus sylvestris L. forest.

Quality Assessment of a Forest Inventory Based on Airborne Laser Scanning

In this study, a quality assessment method based on sampling of primary laser inventory units (microsegments) was analysed. The accuracy of a laser inventory carried out in Kuhmo was analysed as a case study. Field sample plots were measured on the sampled microsegments in the Kuhmo inventory area. Two main questions were considered. Did the ALS based inventory meet the accuracy requirements set for the provider and how should a reliable, cost-efficient and independent quality assessment be undertaken. The agreement between control measurement and ALS based inventory was analysed in four ways: 1) The root mean squared errors (RMSEs) and bias were calculated. 2) Scatter plots with 95% confidence intervals were plotted and the placing of identity lines was checked. 3) Bland-Altman plots were drawn so that the mean difference of attributes between the control method and ALS-method was calculated and plotted against average value of attributes. 4) The tolerance limits were defined and combined with Bland-Altman plots. The RMSE values were compared to a reference study from which the accuracy requirements had been set to the service provider. The accuracy requirements in Kuhmo were achieved, however comparison of RMSE values proved to be difficult. Field control measurements are costly and time-consuming, but they are considered to be robust. However, control measurements might include errors, which are difficult to take into account. Using the Bland-Altman plots none of the compared methods are considered to be completely exact, so this offers a fair way to interpret results of assessment. The tolerance limits to be set on order combined with Bland-Altman plots were suggested to be taken in practise. In addition, bias should be calculated for total area. Some other approaches for quality control were briefly examined. No method was found to fulfil all the required demands of statistical reliability, cost-efficiency, time efficiency, simplicity and speed of implementation. Some benefits and shortcomings of the studied methods were discussed.

Comparison of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based on Lorenz Curves

The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

Canonical Correlation Analysis for Interpreting Airborne Laser Scanning Metrics along the Lorenz Curve of Tree Size Inequality

Canonical Correlation Analysis for Interpreting Airborne Laser Scanning Metrics along the Lorenz Curve of Tree Size Inequality

A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data

This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

Detecção de regi��es de via integrando dados de varredura a LASER aerotransportado e imagens de alta resolução

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Alikasvoksen mittaus ja kartoitus laserkeilauksella

Tasaikäisen metsän alle muodostuvilla alikasvoksilla on merkitystä puunkorjuun, metsänuudistamisen, näkemä-ja maisema-analyysien sekä biodiversiteetin ja hiilitaseen arvioinnin kannalta. Ilma-aluksista tehtävä laserkeilaus on osoittautunut tehokkaaksi kaukokartoitusmenetelmäksi varttuneiden puustojen mittauksessa. Laserkeilauksen käyttöönotto operatiivisessa metsäsuunnittelussa mahdollistaa aiempaa tarkemman tiedon tuottamisen alikasvoksista, mikäli alikasvoksen ominaisuuksia voidaan tulkita laseraineistoista. Tässä työssä käytettiin tarkasti mitattuja maastokoealoja ja kaikulaserkeilausaineistoja (discrete return LiDAR) usealta vuodelta (1–2 km lentokorkeus, 0,9–9,7 pulssia m-2). Laserkeilausaineistot oli hankittu Optech ALTM3100 ja Leica ALS50-II sensoreilla. Koealat edustavat suomalaisia tasaikäisi�� männiköitä eri kehitysvaiheissa. Tutkimuskysymykset olivat: 1) Minkälainen on alikasvoksesta saatu lasersignaali yksittäisen pulssin tasolla ja mitkä tekijät signaaliin vaikuttavat? 2) Mikä on käytännön sovelluksissa hyödynnettävien aluepohjaisten laserpiirteiden selitysvoima alikasvospuuston ominaisuuksien ennustamisessa? Erityisesti haluttiin selvittää, miten laserpulssin energiahävi��t ylempiin latvuskerroksiin vaikuttavat saatuun signaaliin, ja voidaanko laserkaikujen intensiteetille tehdä energiahävi��iden korjaus. Puulajien väliset erot laserkaiun intensiteetissä olivat pieni�� ja vaihtelivat keilauksesta toiseen. Intensiteetin käyttömahdollisuudet alikasvoksen puulajin tulkinnassa ovat siten hyvin rajoittuneet. Energiahävi��t ylempiin latvuskerroksiin aiheuttivat alikasvoksesta saatuun lasersignaaliin kohinaa. Energiahävi��iden korjaus tehtiin alikasvoksesta saaduille laserpulssin 2. ja 3. kaiuille. Korjauksen avulla pystyttiin pienentämään kohteen sisäistä intensiteetin hajontaa ja parantamaan kohteiden luokittelutarkkuutta alikasvoskerroksessa. Käytettäessä 2. kaikuja oikeinluokitusprosentti luokituksessa maan ja yleisimmän puulajin välillä oli ennen korjausta 49,2–54,9 % ja korjauksen jälkeen 57,3–62,0 %. Vastaavat kappa-arvot olivat 0,03–0,13 ja 0,10–0,22. Tärkein energiahävi��itä selittävä tekijä oli pulssista saatujen aikaisempien kaikujen intensiteetti, mutta hieman merkitystä oli myös pulssin leikkausgeometrialla ylemmän latvuskerroksen puiden kanssa. Myös 3. kaiuilla luokitustarkkuus parani. Puulajien välillä havaittiin eroja siinä, kuinka herkästi ne tuottavat kaiun laserpulssin osuessa puuhun. Kuusi tuotti kaiun suuremmalla todennäköisyydellä kuin lehtipuut. Erityisen selvä tämä ero oli pulsseilla, joissa oli energiahävi��itä. Laserkaikujen korkeusjakaumapiirteet voivat siten olla riippuvaisia puulajista. Sensorien välillä havaittiin selvi�� eroja intensiteettijakaumissa, mikä vaikeuttaa eri sensoreilla hankittujen aineistojen yhdistämistä. Myös kaiun todennäköisyydet erosivat jonkin verran sensorien välillä, mikä aiheutti pieni�� eroavaisuuksia kaikujen korkeusjakaumiin. Aluepohjaisista laserpiirteistä löydettiin alikasvoksen runkolukua ja keskipituutta hyvin selittävi�� piirteitä, kun rajoitettiin tarkastelu yli 1 m pituisiin puihin. Piirteiden selitysvoima oli parempi runkoluvulle kuin keskipituudelle. Selitysvoima ei merkittävästi alentunut pulssitiheyden pienentyessä, mikä on hyvä asia käytännön sovelluksia ajatellen. Lehtipuun osuutta ei pystytty selittämään. Tulosten perusteella kaikulaserkeilausta voi olla mahdollista hyödyntää esimerkiksi ennakkoraivaustarpeen arvioinnissa. Sen sijaan alikasvoksen tarkempi luokittelu (esim. puulajitulkinta) voi olla vaikeaa. Kaikkein pienimpi�� alikasvospuita ei pystytä havaitsemaan. Lisää tutkimuksia tarvitaan tulosten yleistämiseksi erilaisiin metsiköihin.

Grand Rapids Contingent. Second U of M Training Detachment

Image cracked from folds. On verso: Grand Rapids, Mich Contingent, 2nd U of M Training detachment, World War I; 3d Row Second from left Henry Bursma

Telephone Electricians - The Cable Room

Student Army Training Corps - World War I - Photograph LA 50

Telephone Electricians - Pole Climbing

Student Army Training Corps - World War I - Photograph LA 64 - shows class in pole-climbing int he course for Telephone Elecetricians, with some of their instructors