Airborne laser scanning raster data visualization

This guide provides an insight into a range of visualization techniques for high-resolution digital elevation models (DEMs). It is provided in the context of investigation and interpretation of various types of historical and modern, cultural and natural small-scale relief features and landscape structures. It also provides concise guidance for selecting the best techniques when looking at a specific type of landscape and/or looking for particular kinds of forms.The three main sections – descriptions of visualization techniques, guidance for selection of the techniques, and visualization tools – accompany examples of visualizations, exemplar archaeological and geomorphological case studies, a glossary of terms, and a list of references and recommendations for further reading. The structure facilitates people of different academic background and level of expertise to understand different visualizations, how to read them, how to manipulate the settings in a calculation, and choose the best suited for the purpose of the intended investigation.A smaller amount of books is also available in hardcover (ISBN 978-961-05-0011-7, 24 EUR).Monografija nudi vpogled v nabor tehnik prikaza visokoločljivih modelov višin. Napisana je v kontekstu preučevanja in interpretacije različnih tipov zgodovinskih in modernih, kulturnih in naravnih majhnih reliefnih oblik. Daje jedrnate napotke za izbiro najboljših tehnik prikaza določenih tipov pokrajine in izrazitih oblik.Tri glavna poglavja – opis tehnik prikazovanja digitalnih modelov višin, napotki za njihovo izbiro in orodja za izračun prikazov –, spremljajo izbrani primeri tipičnih arheoloških in geomorfoloških študij, slovarček pojmov ter seznam literature in priporočenega branja. Posameznikom z različnih znanstvenih področij in z različnim predznanjem o tematiki je struktura v pomoč pri razumevanju različnih tehnik prikazov, kako jih brati, kako izbrati prave nastavitve pri njihovem izračunu in kako prepoznati najbolj primerne za namen zasnovane raziskave

Land Cover Mapping Using Landsat Satellite Image Classification in the Classical Karst - Kras Region

Such a diverse and sensitive eco-region as Karst needs to be managed with special attention and consideration of its natural and cultural resources. Land cover is an important indicator, which enables the analysis of their condition and development monitoring. Advanced satellite images classification represents an accurate and cost-effective alternative to the classical techniques of land cover mapping. The methods used to produce a reliable land cover map are presented in this paper. The complexity of the area requires a combination of various data such as Landsat satellite images, digital elevation model, digital orthophotos as well as existing topographic and thematic maps. The maximum likelihood algorithm was used as the main classifier and the accuracy of results was further improved by fuzzy classification, altitude and inclination filtering and auxiliary data integration

Transformation of the Jeruzalem Hills cultural landscape with modern vineyard terraces

The terraced landscape in the Jeruzalem Hills is the result of specific socioeconomic conditions under communism, and now its appearance is drastically changing for the second time in the last fifty years. This article examines the creation of the new landscape layer of modern cultivated terraces and studies their disappearance and the return to a condition similar to the original state. The analysis is based on interviews and visual interpretation of aerial laser scanning (lidar) data. It focuses on the state of the landscape before terracing, the creation of terraces and formation of a terraced landscape, and its most recent transformation into slopes without terraces. It is determined that, despite the recognized aesthetic value of terraces, legal protection in the form of a nature park has not impacted their preservation because 56% of them have already been leveled. With the conversion of vineyards to vertical plantations, a new challenge is arising: increased erosion

Confidence maps: a tool to evaluate archaeological data'srelevance in spatial analysis

Inventory data used in archaeology is often incomplete and heterogeneous. In the framework of the ArchaeDyn program, a method has been proposed to evaluate heterogeneity in archaeological inventories. The purpose of this work is to create a validation tool to interpret the results. This tool is called a “confidence map” and is produced by combining representation and reliability maps. The first step consists of generating representation maps to describe the clustering of archaeological items. The second step is based on reliability maps. Data providers are asked to define and outline the level of reliability of their data. Then the representation and reliability layers are combined using map algebra. The resulting maps allow for the comparison and analysis of data confidence

Vizuelizacija rasterskih podataka laserskog skeniranja iz zraka

The monograph is a translated and complemented edition of the book Airborne laser scanning raster data visualization: A Guide to Good Practice. It provides an insight into a range of visualization techniques for high-resolution digital elevation models (DEMs). It is provided in the context of investigation and interpretation of various types of historical and modern, cultural and natural small-scale relief features and landscape structures. It also provides concise guidance for selecting the best techniques when looking at a specific type of landscape and/or looking for particular kinds of forms.The three main sections – descriptions of visualization techniques, guidance for selection of the techniques, and visualization tools – accompany examples of visualizations, exemplar archaeological and geomorphological case studies, a glossary of terms, and a list of references and recommendations for further reading. The structure facilitates people of different academic background and level of expertise to understand different visualizations, how to read them, how to manipulate the settings in a calculation, and choose the best suited for the purpose of the intended investigation.Monografija nudi vpogled v nabor tehnik prikaza visokoločljivih modelov višin. Napisana je v kontekstu preučevanja in interpretacije različnih tipov zgodovinskih in modernih, kulturnih in naravnih majhnih reliefnih oblik. Daje jedrnate napotke za izbiro najboljših tehnik prikaza določenih tipov pokrajine in izrazitih oblik.Tri glavna poglavja – opis tehnik prikazovanja digitalnih modelov višin, napotki za njihovo izbiro in orodja za izračun prikazov –, spremljajo izbrani primeri tipičnih arheoloških in geomorfoloških študij, slovarček pojmov ter seznam literature in priporočenega branja. Posameznikom z različnih znanstvenih področij in z različnim predznanjem o tematiki je struktura v pomoč pri razumevanju različnih tehnik prikazov, kako jih brati, kako izbrati prave nastavitve pri njihovem izračunu in kako prepoznati najbolj primerne za namen zasnovane raziskave

Tool for Drought Monitoring in the Danube Region: – Methods and Preliminary Developments

Drought is a naturally recurring phenomenon of the climate system that affects virtually all regions of the world. During the past decades extreme droughts with extensive negative effects on ecosystems became evident also in the Danube region. At the moment regional capacity to monitor drought is still very diverse and not synchronised among different countries. In this is paper, we present a recently developed drought monitoring tool – the Drought User Service (DUS) for the Danube region using remote-sensing products which aims at offering a more accurate and in near-real-time monitoring via different drought indices. The DUS was created as the monitoring tool of the risk-based paradigm, which seeks to give information in near real-time about the location and severity of droughts throughout the Danube region. Satellite remote sensing products meet the requirements for operational monitoring because they are able to offer continuous and consistent measurements of variables, which can be used to assess the severity, spatial extent and impacts of drought. In the DUS three different variables – vegetation, soil moisture and precipitation – are monitored with earth observation products. The condition of vegetation and soil moisture is tracked with two simple indicators computed as long-term anomalies of the NDVI and SWI products made available through EU’s Copernicus Global Land Service. The importance of DUS and of the developed methods for faster detection of drought onset as useful foundation for establishing a better pro-active drought management in order to mitigate the negative effects of drought in the region is discussed

KLASIFIKACIJA VRSTA DRVEĆA U PRIRODNOJ URBANOJ ŠUMI KORISTEĆI WORLDVIEW-2 SATELITSKE SNIMKE I LIDAR

A detailed tree species inventory is needed to sustainably manage a natural, mixed, heterogeneous urban forest. An object-based image analysis of a combination of high-resolution WorldView-2 multi-spectral satellite imagery and airborne laser scanning (LiDAR) data was tested for classification of individual tree crowns of five different tree species. The model training data were obtained from a systematic grid of plots in the forest. In total, 304 coniferous (Norway spruce and Scots pine) and 270 deciduous (European beech, Sessile and Pedunculate oak (combined), and Sweet chestnut) trees were identified in the field. The classification was performed by applying the support vector machine model. An accuracy assessment was performed by calculating a confusion matrix to evaluate the accuracy of the classification output by comparing the classification result to the independent test data. The overall accuracy of the classification was 58 %.Osnovni zadatak gospodarenja šumama je provedba inventure drveća. Posebno se to odnosi na blisko prirodi gospodarene urbane šume. Cilj ovog istraživanja je provjeriti može li se metoda analize snimaka (tzv. object-based image analysis – OBIA) kombinacijom WorldView-2 multispektralnih satelitskih snimaka visoke prostorne rezulocije i laserskog skeniranja (LiDAR-a) koristiti za uspješnu klasifikaciju krošanja pojedinačnih stabala različitih vrsta drveća u prirodnim, mješovitim i heterogenim urbanim šumama u Ljubljani (Slika 1).Terenska klasifikacija vrsta drveća provedena je postavljanjem mreže kružnih ploha (100x100 m) veličine od 2000 m2. Na svakoj od 332 plohe, registrirana su stabla iz dominantnog i kodominantnog sloja drveća. Ukupno je za analizu izdvojeno 574 stabala, od čega 304 stabla četinjača (obična smreka, obični bor) i 270 stabala listača (obična bukva, hrast lužnjak i kitnjak, pitomi kesten). Polovica uzorkovanih stabala tj. njihovih krošanja korišteno je kao probni set podataka u nadgledanoj klasifikaciji, dok je druga polovica uzorkovanih stabala korištena za ocjenu točnosti provedene klasifikacije (tzv. testni podaci).Za klasifikaciju su korištene WorldView-2 multispektralne satelitske snimke (8-kanalne), tzv. ‘Red-Edge’ normalizirani razlikovni vegetacijski indeks (NDVI) izračunat pomoću rubnog crvenog i crvenog spektralnog kanala te digitalni model krošanja (tzv. Digital Canopy Model – DCM) dobiven iz LiDAR podataka. Prostorna rezolucija WorldView-2 satelitskih snimaka iznosila je 1 m.Klasifikacija je provedena pomoću Exelis ENVI 5 kompjuterskog programa, primjenjujući tzv. pomoćni vektorski model. Preciznost procjene izračunata je na temelju izračunate matrice pogreške, uspoređujući rezultate klasifikacije s testnim podacima. Također je provedena analiza glavnih komponenata, koja je pokazala da je najveća varijabilnost (oko 85 %) objašnjena pomoću rubnog crvenog spektralnog kanala (705–745 nm), bližeg infracrvenog kanala – 1 (770–895 nm) te bližeg infracrvenog spektralnog kanala – 2 (860–1040 nm) WorldView-2 snimaka.Metoda analize snimaka (OBIA) kombinacijom WorldView-2 satelitskih snimaka I LiDAR podataka korištena u ovom istraživanju pokazala je obećavajuće rezultate pri klasifikaciji vrsta drveća u gustim, mješovitim i heterogenim prirodnim urbanim šumama, u kojima često dolazi do isprepletanja krošanja. Najpouzdaniji dobiveni rezultati odnose se na razlikovanje četinjača i listača. Kod sastojina s gustim krošnjama, posebice kod listača kod kojih je teško napraviti delineaciju krošanja, otežana je i manualna i automatska delineacija (segmentacija) krošanja. Ovo istraživanje novi je dokaz kako se primjenom podataka dobivenih metodama daljinskih istraživanja pruža mogućnost uštede u vremenu pri inventarizaciji vrsta drveća.Ukupna preciznost identifikacije iznosila je 58 %, a Kappa koeficijent je iznosio 0.421 (Tablica 4). Za svaku vrstu drveća izračunata je preciznost na osnovi razlike između preciznosti koju navodi proizvođač (postotak točno identificiranih piksela u odnosu na ukupan broj piksela na probnim podacima) i preciznosti korisnika. Rezultati tako dobivene preciznosti iznosili su 80 % za smreku, 70 % za hrastove lužnjak i kitnjak, 50 % za obični bor, 38 % za bukvu, te manje od 1 % za pitomi kesten

Tranfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures on LiDAR Data

When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models. The application of transfer learning is frequently employed to mitigate this drawback. However, there is still a need to explore its effectiveness when applied across different archaeological datasets. This paper compares the performance of various transfer learning configurations using two semantic segmentation deep neural networks on two LiDAR datasets. The experimental results indicate that transfer learning-based approaches in archaeology can lead to performance improvements, although a systematic enhancement has not yet been observed. We provide specific insights about the validity of such techniques that can serve as a baseline for future works.Comment: Accepted to IEEE International Geoscience and Remote Sensing Symposium 2023 (IGARSS 2023) @IEEE copyrigh