Hasil untuk "Cartography"

J. Veefkind, I. Aben, K. McMullan et al.

Graham R. Walden

This volume is the first of two volumes that address the most recent ten years (1997-2006) of focus group studies and research literature. Volume one provides coverage of the arts and humanities, social sciences, and the nonmedical sciences, and volume two concentrates on the medical and health sciences. These volumes cover the English-language academic literature (books, chapters in books, journal articles, and significant pamphlets) available in libraries via interlibrary loan and online. A variety of materials are included: instructional guides, handbooks, reference works, textbooks, and academic journal literature. In Focus Groups, Volume I, the following subject disciplines have been considered: in the arts and humanities_linguistics, music, religion, and sports and leisure studies; in the social sciences_anthropology, business, cartography, communication, demography, education, law, library science, political science, psychology, and sociology; and in the non-medical sciences_agriculture, biology, engineering, environmental sciences, and physics. The selected entries have a minimum of four pages, and include 29 books, 50 book chapters, 349 articles, and 10 pamphlets, for a total of 438 entries. An appendix includes the titles of the 245 journals cited, along with the appropriate entry numbers for each. Author and subject indexes provide access to the contents, with the subject index providing access to unique terms. The detailed contents pages are designed to enable the reader to quickly find appropriate entries through the use of extensive and detailed subheadings.

N. Logothetis

P. Rosen, S. Hensley, I. Joughin et al.

R. Snow, C. Guerra, A. Noor et al.

Mingyang Lei, Huifang Li, Liying Xu et al.

The existence of thin clouds within remote sensing images results in the loss of image information. The removal of thin clouds is crucial for enhancing data quality and increasing the application scope of remote sensing imagery. A method that combines model-driven homomorphic filtering and data-driven diffusion models for thin cloud removal is proposed in this paper. Homomorphic filtering guidance and spatial domain guidance are employed to transform the generation process of a pre-trained unconditional cloud-free remote sensing images generative model from random to directed, thereby generating a cloud-free image that corresponds to the provided thin-cloud image. Unlike most existing data-driven methods, this approach requires only cloud-free images for model training, thus avoiding the difficulties associated with dataset construction. Additionally, the prior knowledge obtained from the diffusion model is used to compensate for the inherent color loss in homomorphic filtering, addressing the limitations of traditional model-based methods. Comparative experiments were conducted by training on 655 cloud-free GaoFen-2 satellite scenes and testing on 68 simulated and 20 real thin-cloud scenes. On the simulated set, the proposed method achieved an average Peak Signal to Noise Ratio (PSNR) of 26.0 dB and Structural Similarity Index (SSIM) of 0.873. On real scenes, it raised image sharpness and color saturation by 22% and 40%, respectively, while preserving ground features more effectively than competing methods. These results demonstrate the effective removal of thin clouds and the superior generalization capability of the proposed approach.

Tao Liu, Shiqi Geng, Yucheng Fu et al.

Acquiring sufficient visual information for the three-dimensional (3D) reconstruction of ships in navigation is particularly challenging. With the evolution of 3D reconstruction methodologies predicated on neural rendering, the computational pipeline for 3D reconstruction has undergone enhancements and optimizations. However, this pipeline necessitates a substantial corpus of input images. Research into 3D reconstruction from monocular images is in its nascent stages, and to date, no unsupervised deep learning approach for 3D reconstruction of ships from single-view UAV imagery exists within the realm of navigation. This paper introduces a novel network architecture for reconstructing 3D representations of ships from single-view UAV images. Initially, a priori statistical analysis of the dataset is conducted to harness color distribution information for noise generation. Subsequently, a novel generator and mask module are engineered to produce optimized feature outputs. Plus, discriminator and encoder networks, coupled with a tailored loss function, are formulated to direct model optimization. Ultimately, to demonstrate the effectiveness of our proposed method for single-view 3D reconstruction, we conducted experiments across three distinct datasets from various domains. Our method's FID value of 10.61 is impressive. At the same time, it yields an LPIPS value of 0.091, which is the best among the six different methods.

A. Martyn

Стаття пропонує цілісну рамку подолання пострадянської інерції у взаємодії землеустрою та топографо-геодезичної діяльності в Україні. Показано, що радянська освітньо-професійна традиція звузила геодезію до вимірювально-інженерних практик і водночас маргіналізувала європейське розуміння землеустрою як проєктно-правової діяльності з формування меж та режимів користування, що мають юридичні наслідки. На основі аналізу міжнародних рамок (FIG, CLGE, INSPIRE, LADM), чинного українського законодавства та довготривалих спостережень автора за професійними дискусіями у соціальних мережах обґрунтовано: (1) необхідність термінологічної уніфікації (surveyor як родове поняття, з розмежуванням land/cadastral surveyor → «землевпорядник», engineering/topographic surveyor → «інженер-геодезист/топограф», «геодезист» — не синонім surveyor); (2) переосмислення функціональних ролей: топографо-геодезична діяльність є інфраструктурним інструментом створення доданої вартості в інших секторах, тоді як землеустрій безпосередньо формує нові об’єкти нерухомості, планувальні структури та управляє цінністю майна через RRR-підходи; (3) інституційну інтеграцію даних і процесів на основі моделей INSPIRE/LADM. Визначено структурні причини «кризи» галузі після 1991 р.: різке скорочення державного попиту на «централізовану геодезію» та технологічна автоматизація вимірювань (GNSS, ДЗЗ, БПЛА, ГІС). Запропоновано модернізацію вищої освіти за спеціальністю G18 («Геодезія та землеустрій») через міждисциплінарні навчальні траєкторії (геодезія × землеустрій × кадастр × просторове планування × оцінка), впровадження семантичних моделей даних, етики та процедур публічної довіри до меж, а також розвиток постійних професійних комунікацій як механізму зняття уявних конфліктів між спільнотами. Ключові слова: землеустрій; геодезія; топографо-геодезична діяльність; кадастр; межі; RRR (права-обмеження-обтяження); INSPIRE; LADM; термінологічна уніфікація; професійні кваліфікації; НІГД/NSDI; інституційна інтеграція; просторове планування; оцінка нерухомості.

Thanh Thach Luong, An Dinh Nguyen, Dinh Hai Nguyen et al.

The mean sea surface in different regions is non-equipotential, rendering Vietnam's traditional approach, which relies on the Hon-Dau tide gauge station as a reference, not yet scientifically invalid. To overcome this, our study utilized the Vietnam national mean dynamic topography model (MDTVN22) for depth observations, particularly in the Gulf of Tonkin. Covering 3430 monitoring sites in Hai Phong and 813 sites in Quang Ninh, our experiments highlighted a 5 to 6 mm difference between the mean sea surface and MDTVN22 references. • Our research establishes a resilient methodology, integrating shore tide gauge station data and the MDTVN22 model, aimed at enhancing precision in depth observations. • Validation experiments in Hai Phong demonstrate a minimal discrepancy of ±0.006 m between measurements obtained from the traditional mean sea surface and the MDTVN22 model. • These findings underscore the significance of adopting the MDTVN22 model for improved accuracy in assessing Vietnam's seabed topography.

Olivier Godard

Terry A. Slocum

Zhiwei Yang, Yingbiao Chen, Zihao Zheng et al.

Studying the structure of polycentric cities can promote a better understanding of urban development and contribute to urban planning. In this study, we identified polycentric cities in China and evaluated the urban centre development level of polycentric cities from new data and method. We used Luojia-1A night-time light (NTL) data, combined with the concept of natural cities (NCs), to identify urban centres and thus identify polycentric cities in China. In addition, we used the urban centre development index (UCDI) to quantify the urban centre development level (UCDL) that represents the overall urban centre development level within a polycentric city. The polycentric cities in China are characterized by the spatial distribution pattern of a larger number in the east and fewer in the west. There are a large number of polycentric cities in eastern China, and the closer to the coastal areas, the more polycentric cities there are. The distribution of UCDL in China’s polycentric cities is characterized by significant spatial heterogeneity. UCDLs are generally smaller in polycentric cities in western China. In addition, polycentric cities in northeastern China have smaller UCDL. Polycentric cities with high UCDL are concentrated in the central and coastal regions of China.

Lars Mewes, Tobias Ebert

Promoting entrepreneurial activities is crucial for regions to facilitate innovation and economic development. Yet, becoming an entrepreneur is not aspired by all people, and regions may differ considerably in their entrepreneurship potential. Assessing and providing accurate estimates of the entrepreneurship potential across fine-grained spatial scales is thus crucial to inform regional policymakers, but it still remains a major challenge due to data availability. Here we used the lab data set from the British Broadcasting Corporation (BBC) covering 368,364 individuals and providing high-resolution data about their residences to map the entrepreneurship potential across 9271 postcode sectors in Great Britain. We used a novel mapping approach that relies on a spatial smoothing function based on distance weights to utilize the most fine-grained spatial level available in the data. Our detailed maps show substantial difference in entrepreneurship potential across postcode sectors in Great Britain and within the largest cities: London, Birmingham and Manchester.

M. Nocente

<p>The question of porousness and liminality of prison has been the subject of a huge amount of research. This article focuses on the relationships, communications, and narratives that occur behind prison walls. It examines letter writing in relation to the construction of a bridge that connects the opacity of the inside with the outside, creating a counter-carceral liminal space. The article investigates the encounter between the outside, represented in OLGa (the political collective in which I participate), and the inside (the prisoners) through the process of letter writing. The article further draws upon my own positionality through an engaged discussion on the limitations of scholar activism and the problem of speaking for others.</p>

A. Leichter, M. Werner, M. Sester

Feature extraction from a range of scales is crucial for successful classification of objects of different size in 3D point clouds with varying point density. 3D point clouds have high relevance in application areas such as terrain modelling, building modelling or autonomous driving. A large amount of such data is available but also that these data is subject to investigation in the context of different tasks like segmentation, classification, simultaneous localisation and mapping and others. In this paper, we introduce a novel multiscale approach to recover neighbourhood in unstructured 3D point clouds. Unlike the typical strategy of defining one single scale for the whole dataset or use a single optimised scale for every point, we consider an interval of scales. In this initial work our primary goal is to evaluate the information gain through the usage of the multiscale neighbourhood definition for the calculation of shape features, which are used for point classification. Therefore, we show and discuss empirical results from the application of classical classification models to multiscale features. The unstructured nature of 3D point cloud makes it necessary to recover neighbourhood information before meaningful features can be extracted. This paper proposes the extraction of geometrical features from a range of neighbourhood with different scales, i.e. neighborhood ranges. We investigate the utilisation of the large set of features in combination with feature aggregation/selection algorithms and classical machine learning techniques. We show that the all-scale-approach outperform single scale approaches as well as the approach with an optimised per point selected scale.

Chin-Yo Lin, V. Vega, J. Thomsen et al.

Using a chromatin immunoprecipitation-paired end diTag cloning and sequencing strategy, we mapped estrogen receptor α (ERα) binding sites in MCF-7 breast cancer cells. We identified 1,234 high confidence binding clusters of which 94% are projected to be bona fide ERα binding regions. Only 5% of the mapped estrogen receptor binding sites are located within 5 kb upstream of the transcriptional start sites of adjacent genes, regions containing the proximal promoters, whereas vast majority of the sites are mapped to intronic or distal locations (>5 kb from 5′ and 3′ ends of adjacent transcript), suggesting transcriptional regulatory mechanisms over significant physical distances. Of all the identified sites, 71% harbored putative full estrogen response elements (EREs), 25% bore ERE half sites, and only 4% had no recognizable ERE sequences. Genes in the vicinity of ERα binding sites were enriched for regulation by estradiol in MCF-7 cells, and their expression profiles in patient samples segregate ERα-positive from ERα-negative breast tumors. The expression dynamics of the genes adjacent to ERα binding sites suggest a direct induction of gene expression through binding to ERE-like sequences, whereas transcriptional repression by ERα appears to be through indirect mechanisms. Our analysis also indicates a number of candidate transcription factor binding sites adjacent to occupied EREs at frequencies much greater than by chance, including the previously reported FOXA1 sites, and demonstrate the potential involvement of one such putative adjacent factor, Sp1, in the global regulation of ERα target genes. Unexpectedly, we found that only 22%–24% of the bona fide human ERα binding sites were overlapping conserved regions in whole genome vertebrate alignments, which suggest limited conservation of functional binding sites. Taken together, this genome-scale analysis suggests complex but definable rules governing ERα binding and gene regulation.

M. Gomarasca

A. M. G. Tommaselli, M. B. Campos, L. F. Castanheiro et al.

Low cost imaging and positioning sensors are opening new frontiers for applications in near real-time Photogrammetry. Omnidirectional cameras acquiring images with 360&deg; coverage, when combined with information coming from GNSS (Global Navigation Satellite Systems) and IMU (Inertial Measurement Unit), can efficiently estimate orientation and object space structure. However, several challenges remain in the use of low-cost sensors and image observations acquired by sensors with non-perspective inner geometry. The accuracy of the measurement using low-cost sensors is affected by different sources of errors and sensor stability. Microelectromechanical systems (MEMS) present a large gap between predicted and actual accuracy. This work presents a study on the performance of an integrated sensor orientation approach to estimate sensor orientation and 3D sparse point cloud, using an incremental bundle adjustment strategy and data coming from a low-cost portable mobile terrestrial system composed by off-theshelf navigation systems and a poly-dioptric system (Ricoh Theta S). Experiments were performed in an outdoor area (sidewalk), achieving a trajectory positional accuracy of 0.33&thinsp;m and a meter level 3D reconstruction.

J. Crampton