5 research outputs found

    KOMPARASI DATA DIGITAL ELEVATION MODEL (DEM) RESOLUSI MENENGAH DALAM MENGESTIMASI KETINGGIAN LAHAN DI KABUPATEN MANOKWARI PROVINSI PAPUA BARAT

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    Saat ini telah tersedia data Digital Elevation Model (DEM) dalam berbagai resolusi, yaitu resolusi rendah hingga resolusi tinggi. Pada umumnya data DEM tersebut memiliki akurasi yang baik dalam mengestimasi ketinggian suatu lahan. Penelitian ini bertujuan untuk membandingkan 4 (empat) DEM resolusi menengah dalam mengestimasi ketinggian lahan di Kabupaten Manokwari Provinsi Papua Barat yaitu; Space Shuttle Radar Topography Mission (SRTM), ASTER Global DEM, Jaxa’s Global ALOS 3D World, dan Copernicus Digital Elevation Model. Secara umum penelitian ini terdiri atas 3 (tiga) tahapan utama yaitu inventarisasi data DEM, ekstraksi nilai ketinggian dari data DEM, dan komparasi data DEM. Komparasi data dilakukan secara pixel to pixel pada 400 titik sampel yang dipilih secara acak. Disamping itu dilakukan uji T dan uji korelasi untuk mengetahui tingkat perbedaan dan korelasi data DEM. Hasil penelitian menunjukkan bahwa Copernicus GLO-30 Digital Elevation Model memberikan nilai ketinggian lebih tinggi dibandingkan SRTM, ASTER Global Digital Elevation Model, dan Jaxa’s Global ALOS 3D World. Sedangkan Jaxa’s Global ALOS 3D World memberikan nilai ketinggian lebih rendah dibandingkan SRTM, ASTER Global Digital Elevation Model, dan Copernicus GLO-30 Digital Elevation Model. Berdasarkan uji T, terdapat perbedaan yang signifikan antara SRTM, ASTER Global Digital Elevation Model, Jaxa’s Global ALOS 3D World, dan Copernicus GLO-30 Digital Elevation Model dalam mengestimasi ketinggian lahan di Kabupaten Manokwari Provinsi Papua Barat. Meskipun memiliki perbedaan yang signifikan, namun keempat DEM tersebut memiliki korelasi yang kuat dengan nilai koefisien korelasi rata-rata sebesar 0,96

    Evaluation of Different Digital Elevation Models (DEMs) for Geospatial Applications: A Case Study of Ibadan, Nigeria.

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    Context and backgroundDigital elevation models (DEMs) are essential tools for a wide range of scientific and geospatial applications, providing critical data for elevation and terrain analysis. While remote sensing DEMs have gained popularity due to their extensive spatial coverage and detailed spectral characteristics, assessing their accuracy is crucial for ensuring the reliability of the information they provide. Goal and Objectives:This study aims to evaluate the accuracy and performance of various Digital Elevation Models (DEMs) for geospatial applications in Ibadan, Nigeria. The specific objectives are to assess the DEMs' accuracy using GPS point survey data and to identify the most suitable DEM for reliable topographic representation in the study area.Methodology:Seven DEMs were evaluated: Shuttle Radar Topography Mission with 30 m and 90 m resolution (SRTM30 and SRTM90), NASADEM with 30 m resolution, Copernicus DEM with 30 m and 90 m resolution (COP30 and COP90), Advanced Land Observing Satellite World 3D with 30 m resolution (AW3D30), and ALOS PALSAR with 12.5 m resolution. The DEMs' accuracy was assessed using mean error (ME), mean absolute error (MAE), standard deviation (STDE), and linear error metrics, validated against GPS point survey data.Results:The analysis revealed that AW3D30 consistently provided the highest accuracy, closely representing the actual terrain of Ibadan. NASADEM exhibited the lowest ME and MAE values, indicating high precision, while ALOS PALSAR demonstrated the greatest deviations, despite its STDE and linear error metrics being comparable to other models. This study underscores the importance of accuracy assessment for DEMs in geospatial applications and serves as a valuable reference for selecting appropriate DEMs for various geospatial tasks in Ibadan, Nigeria

    Geomorphometry 2020. Conference Proceedings

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    Geomorphometry is the science of quantitative land surface analysis. It gathers various mathematical, statistical and image processing techniques to quantify morphological, hydrological, ecological and other aspects of a land surface. Common synonyms for geomorphometry are geomorphological analysis, terrain morphometry or terrain analysis and land surface analysis. The typical input to geomorphometric analysis is a square-grid representation of the land surface: a digital elevation (or land surface) model. The first Geomorphometry conference dates back to 2009 and it took place in Zürich, Switzerland. Subsequent events were in Redlands (California), Nánjīng (China), Poznan (Poland) and Boulder (Colorado), at about two years intervals. The International Society for Geomorphometry (ISG) and the Organizing Committee scheduled the sixth Geomorphometry conference in Perugia, Italy, June 2020. Worldwide safety measures dictated the event could not be held in presence, and we excluded the possibility to hold the conference remotely. Thus, we postponed the event by one year - it will be organized in June 2021, in Perugia, hosted by the Research Institute for Geo-Hydrological Protection of the Italian National Research Council (CNR IRPI) and the Department of Physics and Geology of the University of Perugia. One of the reasons why we postponed the conference, instead of canceling, was the encouraging number of submitted abstracts. Abstracts are actually short papers consisting of four pages, including figures and references, and they were peer-reviewed by the Scientific Committee of the conference. This book is a collection of the contributions revised by the authors after peer review. We grouped them in seven classes, as follows: • Data and methods (13 abstracts) • Geoheritage (6 abstracts) • Glacial processes (4 abstracts) • LIDAR and high resolution data (8 abstracts) • Morphotectonics (8 abstracts) • Natural hazards (12 abstracts) • Soil erosion and fluvial processes (16 abstracts) The 67 abstracts represent 80% of the initial contributions. The remaining ones were either not accepted after peer review or withdrawn by their Authors. Most of the contributions contain original material, and an extended version of a subset of them will be included in a special issue of a regular journal publication

    Archaeological investigations along the Ruby Pipeline.

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    405 pages : illustrations (some color), maps ; 26 cm.The Ruby Pipeline originates in Opal, Wyoming, travels westward across Utah and Nevada, and terminates in Malin, Oregon. Almost 360 miles of the line is in Nevada, where it crosses through some of the most remote, sparsely populated land in the lower 48 states. Despite the remote nature of this corridor, it has produced a rich archaeological record reflecting a dynamic history of land-use pattern changes over a period of at least 13,000 years. Archaeological excavations were conducted at 578 prehistoric sites prior to construction of the pipeline. The sites were distributed across four ecological regions, including (from west to east): the High Rock Country, Upper Lahontan Basin, Upper Humboldt Plains, and Thousand Springs Valley. First evidence of human occupation dates to the Paleoindian (14,500-12,800 cal b.p.) and Paleoarchaic (12,800-7800 cal b.p.) periods, when people spent most of their time in the High Rock Country where important economic resources reached their highest densities. Paleoindian findings are limited to a series of Great Basin Concave Base projectile points and small obsidian flaked stone concentrations. Paleoarchaic sites are much more common, and tend to be represented by Great Basin Stemmed projectile points, bifaces, and a limited number of other flaked stone tools. Most of these assemblages reflect small groups of hunters refurbishing their tool kits as they traveled through the area. An important exception to this pattern was found at Five Mile Flat along the west end of pluvial Lake Parman where two significant habitation sites dating to 11,180 cal b.p. were discovered. One of these sites includes a house floor, which is the oldest ever found in the Great Basin. Despite the warm-dry conditions that characterized much of the middle Holocene, it appears that human populations nearly doubled during the Post-Mazama Period (7800-5700 cal b.p.). Most activity remained concentrated in the High Rock Country, but evidence for occupation begins to trickle out into the Upper Lahontan Basin and Upper Humboldt Plains regions as well. Most of the artifact assemblages remain rather narrow, often composed of Northern Side-notched and Humboldt Concave Base points, bifaces, and debitage, and reflect use of the region by mobile groups of hunters. Major changes took place with the arrival of the Early Archaic (5700-3800 cal b.p.) and continued forward into the Middle Archaic Period (3800-1300 cal b.p.). Early Archaic projectile points are largely represented by Humboldt and Gatecliff forms. It appears that population densities increased almost fourfold from the preceding interval, and all four regions experienced significant occupation for the first time. Simultaneous to this population increase and dispersal, a full complement of site types began to emerge, with large-scale residential areas becoming significant for the first time. This trend continued forward into the Middle Archaic Period where the relative frequency of residential sites almost doubled compared with the Early Archaic interval. Plant macrofossil and archaeofaunal assemblages also become more abundant and diversified at this time, probably marking a broadening of the diet breadth. This general trajectory extends into the Late Archaic (1300-600 cal b.p.) and Terminal Prehistoric periods, as people continued to expand into a wider range of habitats. This was particularly case for the latter interval, as the habitat preferences that made sense for over 12,000 years were upended, with population densities highest in the Upper Humboldt Plains and Thousand Springs Valley. This reorientation corresponds to the arrival of Numic speaking populations, especially the Western Shoshone who appear to have reached northern Nevada much earlier than the Northern Paiute, and is probably linked to a greater emphasis on small-seeded plants that are abundantly present in their territory. Although low ranked compared to many other foods, with the proper technology and work organization, small seeds could support higher population densities than was the case earlier in time. Finally, the discovery of obsidian in multiple Terminal Prehistoric sites from sources located much further away than any other time in the past may signal the earliest use of horses in northern Nevada

    Uncertainties in Digital Elevation Models: Evaluation and Effects on Landform and Soil Type Classification

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    Digital elevation models (DEMs) are a widely used source for the digital representation of the Earth's surface in a wide range of scientific, industrial and military applications. Since many processes on Earth are influenced by the shape of the relief, a variety of different applications rely on accurate information about the topography. For instance, DEMs are used for the prediction of geohazards, climate modelling, or planning-relevant issues, such as the identification of suitable locations for renewable energies. Nowadays, DEMs can be acquired with a high geometric resolution and over large areas using various remote sensing techniques, such as photogrammetry, RADAR, or laser scanning (LiDAR). However, they are subject to uncertainties and may contain erroneous representations of the terrain. The quality and accuracy of the topographic representation in the DEM is crucial, as the use of an inaccurate dataset can negatively affect further results, such as the underestimation of landslide hazards due to a too flat representation of relief in the elevation model. Therefore, it is important for users to gain more knowledge about the accuracy of a terrain model to better assess the negative consequences of DEM uncertainties on further analysis results of a certain research application. A proper assessment of whether the purchase or acquisition of a highly accurate DEM is necessary or the use of an already existing and freely available DEM is sufficient to achieve accurate results is of great qualitative and economic importance. In this context, the first part of this thesis focuses on extending knowledge about the behaviour and presence of uncertainties in DEMs concerning terrain and land cover. Thus, the first two studies of this dissertation provide a comprehensive vertical accuracy analysis of twelve DEMs acquired from space with spatial resolutions ranging from 5 m to 90 m. The accuracy of these DEMs was investigated in two different regions of the world that are substantially different in terms of relief and land cover. The first study was conducted in the hyperarid Chilean Atacama Desert in northern Chile, with very sparse land cover and high elevation differences. The second case study was conducted in a mid-latitude region, the Rur catchment in the western part of Germany. This area has a predominantly flat to hilly terrain with relatively diverse and dense vegetation and land cover. The DEMs in both studies were evaluated with particular attention to the influence of relief and land cover on vertical accuracy. The change of error due to changing slope and land cover was quantified to determine an average loss of accuracy as a function of slope for each DEM. Additionally, these values were used to derive relief-adjusted error values for different land cover classes. The second part of this dissertation addresses the consequences that different spatial resolutions and accuracies in DEMs have on specific applications. These implications were examined in two exemplary case studies. In a geomorphometric case study, several DEMs were used to classify landforms by different approaches. The results were subsequently compared and the accuracy of the classification results with different DEMs was analysed. The second case study is settled within the field of digital soil mapping. Various soil types were predicted with machine learning algorithms (random forest and artificial neural networks) using numerous relief parameters derived from DEMs of different spatial resolutions. Subsequently, the influence of high and low resolution DEMs with the respectively derived land surface parameters on the prediction results was evaluated. The results on the vertical accuracy show that uncertainties in DEMs can have diverse reasons. Besides the spatial resolution, the acquisition technique and the degree of improvements made to the dataset significantly impact the occurrence of errors in a DEM. Furthermore, the relief and physical objects on the surface play a major role for uncertainties in DEMs. Overall, the results in steeper areas show that the loss of vertical accuracy is two to three times higher for a 90 m DEM than for DEMs of higher spatial resolutions. While very high resolution DEMs of 12 m spatial resolution or higher only lose about 1 m accuracy per 10° increase in slope steepness, 30 m DEMs lose about 2 m on average, and 90 m DEMs lose more than 3 m up to 6 m accuracy. However, the results also show significant differences for DEMs of identical spatial resolution depending on relief and land cover. With regard to different land cover classes, it can be stated that mid-latitude forested and water areas cause uncertainties in DEMs of about 6 m on average. Other tested land cover classes produced minor errors of about 1 – 2 m on average. The results of the second part of this contribution prove that a careful selection of an appropriate DEM is more crucial for certain applications than for others. The choice of different DEMs greatly impacted the landform classification results. Results from medium resolution DEMs (30 m) achieved up to 30 % lower overall accuracies than results from high resolution DEMs with a spatial resolution of 5 m. In contrast to the landform classification results, the predicted soil types in the second case study showed only minor accuracy differences of less than 2 % between the usage of a spatial high resolution DEM (15 m) and a low resolution 90 m DEM. Finally, the results of these two case studies were compared and discussed with other results from the literature in other application areas. A summary and assessment of the current state of knowledge about the impact of a particular chosen terrain model on the results of different applications was made. In summary, the vertical accuracy measures obtained for each DEM are a first attempt to determine individual error values for each DEM that can be interpreted independently of relief and land cover and can be better applied to other regions. This may help users in the future to better estimate the accuracy of a tested DEM in a particular landscape. The consequences of elevation model selection on further results are highly dependent on the topic of the study and the study area's level of detail. The current state of knowledge on the impact of uncertainties in DEMs on various applications could be established. However, the results of this work can be seen as a first step and more work is needed in the future to extend the knowledge of the effects of DEM uncertainties on further topics that have not been investigated to date
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