Hasil untuk "Cartography"

Santiago Mora Van Cauwelaert

La cumbia, la madre cumbia, desborda los límites de lo que entendemos por un simple fenómeno musical. En esta edición 112 de Revista Cartográfica, la portada invita a sumergirnos en lo que hoy puede considerarse un verdadero movimiento cultural que atraviesa el continente americano. ...

Rujia Wang, Chen Shi

In machine learning-based fractional cover estimation, the fractional cover distribution in training samples critically influences model construction and, consequently the accuracy of the estimations. While some studies have descriptively compared the accuracies of machine learning-based estimations across training sets derived from different sampling methods, a significant gap remains in quantitatively analyzing how the fractional cover distribution in training samples affects accuracy. This study aims to bridge this gap by introducing descriptors for fractional cover distribution in the training set and establishing mathematical relationships between these descriptors and the accuracy of fractional cover estimation. We employed the Dirichlet distribution to characterize the joint fractional cover of multiple land classes and the Beta distribution for single-class cover. Subsequently, two descriptors were developed: the Kullback-Leibler (KL) divergence, measuring the similarity of fractional cover distributions for the target class between the training and test sets, and the geometric angle, representing the fractional cover distributions of the target class in the training set at the same KL divergence. Fractional cover estimation was performed using random forest regression, with accuracy assessed on an independent test set. The relationships between the KL divergence and accuracy, and between the geometric angle and accuracy at the same KL divergence, were modeled using univariate linear models and harmonic models, respectively. The combined effects of these descriptors on accuracy were further analyzed using coupled harmonic analysis and generalized additive models. Our experimental results, using both simulated and real data, demonstrated the effectiveness of these models. Given the strong explanatory power of the KL divergence in the accuracy of fractional cover estimation, we encourage researchers to report detailed statistical information of both training and test sets, enriching the understanding of model performance in fractional cover estimation.

Andrés Barrios-Rubio

Despite the predominance of traditional radio in Colombia, particularly in terms of its role as a medium, podcasting is gaining significance due to its flexibility, personalisation, and use of shorter formats. The research presented here seeks to delineate the sound ecosystem present in Colombia in order to recognise and evaluate its status and transcendence in the digital sonosphere. The study corpus comprised 160 podcasts, encompassing sound material from production companies, radio stations, other media outlets, and independent podcasters. This paper proposes an innovative content analysis of a corpus, with a methodology combining three categories of analysis. The production logics of podcasting bear a strong resemblance to those of radio broadcasting, largely due to the significant presence of operators within this industry who have established themselves as production companies or independent podcasters. The growth of the industry from 2020 to 2024 positions Colombia as a regional benchmark in digital audio consumption and production.

Anh Phan, Hiromichi Fukui

ABSTRACTWe investigate the impact of NO2 emissions reduction on O3 and CH4 levels in 14 metropolitan areas of Japan in 2020. To account for meteorological variations, we employ business-as-usual air quality time series generated by machine learning models. Additionally, we use satellite observations and biogeochemical model simulations to analyse air quality changes. During the lockdown period from April 7 to May 25 in 2020, we observed a NO2 reduction that equated to a decrease equivalent to 3.4 and 5 years of the corresponding trends in roadside and ambient air quality recorded from 2010 to 2019. After meteorological normalization, NO2 decreased by 14.5% at ambient air stations and 19.1% at roadside stations. Surprisingly, the NO2 reduction did not immediately lead to increased O3. Instead, O3 levels rose after the lockdown, specifically in August due to favorable sunny conditions. This finding is important for Japan and has not been reported in previous studies. We found that changes in NO2 and CO marginally contributed to variations in CH4 levels across the study areas. It is recommended to simultaneously reduce NOx as well as non-methane volatile organic compounds to mitigate their adverse effects on future policies.

B. Korf, E. Rothfuß, U. Wardenga

Bingxuan Guo, Yingwei Ge, Xiongwu Xiao et al.

ABSTRACTFast and high-precision urban scene 3D modeling is the foundational data infrastructure for the digital earth and smart cities. However, due to challenges such as water-area matching difficulties and issues like data redundancy and insufficient observations, existing full-automatic 3D modeling methods often result in water-area missing and many small holes in the models and insufficient local-model accuracy. To overcome these challenges, full-automatic high-precision scene 3D reconstruction method with water-area intelligent complementation on depth maps and mesh optimization is proposed. Firstly, SfM was used to calculated image poses and PatchMatch was used to generated initial depth maps. Secondly, a simplified GAN extracted water-area masks and ray tracing was used achieve high-precision auto-completed water-area depth values. Thirdly, fully connected CRF optimized water-areas and arounds in depth maps. Fourthly, high-precision 3D point clouds were obtained using depth map fusion based on clustering culling and depth least squares. Then, mesh was generated and optimized using similarity measurement and vertex gradients to obtain refined mesh. Finally, high-precision scene 3D models without water-area missing or holes were generated. The results showed that: to compare with the-state-of-art ContextCapture, the proposed method enhances model completeness by 14.3%, raises average accuracy by 14.5% and improves processing efficiency by 63.6%.

Asnake Mekuriaw Amera, Sewnet Habtamu

This study aimed to assess the current land data acquisition system, data sharing mechanism and major challenges in Ethiopia. A total of 26 institutions working mainly on land data collection, management, dissemination, and use were purposively selected. Data were collected from these institutions using face-to-face interviews, focus group discussions and observations. Besides, international standards were reviewed. The data were analysed using descriptive statistics and qualitative techniques. The results showed that all the surveyed institutions have some land data produced by themselves or other institutions. However, the data is not in compliance with any of the geospatial data standards. Moreover, some institutions do not have clear information about the source and accuracy of their data holding. Data storage systems, e.g., data warehouses and server were practiced by some institutions. Data duplication, lack of data sharing protocol and limited cooperation between institutions are the major challenges of land data management in Ethiopia. 

Paolo De Fioravante, Andrea Strollo, Francesca Assennato et al.

The study involved an in-depth analysis of the main land cover and land use data available nationwide for the Italian territory, in order to produce a reliable cartography for the evaluation of ecosystem services. In detail, data from the land monitoring service of the Copernicus Programme were taken into consideration, while at national level the National Land Consumption Map and some regional land cover and land use maps were analysed. The classification systems were standardized with respect to the European specifications of the EAGLE Group and the data were integrated to produce a land cover map in raster format with a spatial resolution of 10 m. The map was validated and compared with the CORINE Land Cover, showing a significant geometric and thematic improvement, useful for a more detailed and reliable evaluation of ecosystem services. In detail, the map was used to estimate the variation in carbon storage capacity in Italy for the period 2012–2020, linked to the increase in land consumption

Niccolò Iandelli, Massimo Coli, Tessa Donigaglia et al.

The conservation of a primary importance historical building requires organization, management, continuous updating, comparison, and visualization of a large amount of data of different nature and origin. In relation to these aspects the use of a GIS brings various advantages including single and univocal management of the entire amount of existing data in a relational, dynamic, updatable and queryable way. The integration of a mobile solution permits the updating of the dataset and checking on site all information. The workflow presented uses opensource solutions, desktop and mobile, which allows the creation of an unconventional lithological Field Mapping activity: starting from photo interpretation and in situ survey, all the coating materials (stone, etc.) of some monuments of primary historical and cultural interest have been mapped (i.e., Duomo di Firenze, Duomo di Prato). The product can be considered as a lithological cartography, vertically oriented, processed by field surveys, geognostic surveys and photo interpretation. All combined to create a “lithological” mapping of the coatings of the various monuments; the advantage is a new approach for conservation and restoration of Cultural Heritage. The proposed workflow involves a mobile solution, opensource, that allows the verification and management of the database in the field.

Fabian Brondi Rueda, Gabriele Garnero, Giovanni Righetti et al.

The study and analysis of climate change is a global challenge against which environmental, but also economic and social changes, will be measured. This memorandum illustrates the recent activities carried out by the IGN Peru in collaboration with European institutions.

Claire Burch, Rebecca Loraamm, Thomas Unnasch et al.

ABSTRACTEastern Equine Encephalitis virus (EEEV) is a virus found predominantly east of the Mississippi River in the United States that can be fatal to both equines and humans. The disease has previously been most prolific in states like Florida, but there has been an increase in the prevalence in other states further up north on the east coast of the United States in recent years. The purpose of this research is to use the ecological niche modelling program Maxent to model EEEV habitat suitability probability. This research utilized data of fatality incidence in equine hosts, versus sentinel chicken infection data, the spatial data traditionally utilized for mapping EEEV. This research produced a map of habitat suitability, which expanded on previous risk models by utilizing additional environmental factors. It confirmed areas of higher probability identified by previous models but identified more narrow areas of higher probability as well. This model adds to the literature applying ecological modelling techniques to spatial epidemiology. It highlights spaces that represent the culmination of environmental factors for the transmission of EEEV. Considering these environmental factors identified can assist in identifying places where there is a higher risk of EEEV as new cases begin to appear.

Gustavo Fluminense Carneiro, Matheus Pinheiro Ferreira, Carlos Frederico de Sá Volotão

It is challenging to map the spatial distribution of natural and planted forests based on satellite images because of the high correlation among them. This investigation aims to increase accuracies in classifications of natural forests and eucalyptus plantations by combining remote sensing data from multiple sources. We defined four vegetation classes: natural forest (NF), planted eucalyptus forest (PF), agriculture (A) and pasture (P), and sampled 410,251 pixels from 100 polygons of each class. Classification experiments were performed by using a random forest algorithm with images from Landsat-8, Sentinel-1, and SRTM. We considered four texture features (energy, contrast, correlation, and entropy) and NDVI. We used F1-score, overall accuracy and total disagreement metrics, to assess the classification performance, and Jeffries–Matusita (JM) distance to measure the spectral separability. Overall accuracy for Landsat-8 bands alone was 88.29%. A combination of Landsat-8 with Sentinel-1 bands resulted in a 3% overall accuracy increase and this band combination also improved the F1-score of NF, PF, P and A in 2.22%, 2.9%, 3.71%, and 8.01%, respectively. The total disagreement decreased from 11.71% to 8.71%. The increase in the statistical separability corroborates such improvement and is mainly observed between NF-PF (11.98%) and A-P (45.12%). We conclude that combining optical and radar remote sensing data increased the classification accuracy of natural and planted forests and may serve as a basis for large-scale semi-automatic mapping of forest resources.

Fangli Guan, Zhixiang Fang, Tao Yu et al.

A salient scene is an area within an image that contains visual elements that stand out from surrounding areas. They are important for distinguishing landmarks in first-person-view (FPV) applications and determining spatial relations in images. The relative spatial relation between salient scenes acts as a visual guide that is easily accepted and understood by users in FPV applications. However, current digitally navigable maps and location-based services fall short of providing information on visual spatial relations for users. This shortcoming has a critical influence on the popularity and innovation of FPV applications. This paper addresses the issue by proposing a method for detecting visually salient scene areas (SSAs) and deriving their relative spatial relationships from continuous panoramas. This method includes three critical steps. First, an SSA detection approach is introduced by fusing region-based saliency derived from super-pixel segmentation and the frequency-tuned saliency model. The method focuses on a segmented landmark area in a panorama. Secondly, a street-view-oriented SSA generation method is introduced by matching and merging the visual SSAs from continuous panoramas. Thirdly, a continuous geotagged panorama-based referencing approach is introduced to derive the relative spatial relationships of SSAs from continuous panoramas. This information includes the relative azimuth, elevation angle, and the relative distance. Experiment results show that the error for the SSA relative azimuth angle is approximately ± 6° (with an average error of 2.67°), and the SSA relative elevation angle is approximately ± 4° (with an average error of 1.32°) when using Baidu street-view panoramas. These results demonstrate the feasibility of the proposed approach. The method proposed in this study can facilitate the development of FPV applications such as augmented reality (AR) and pedestrian navigation using proper spatial relation.

Panecki Tomasz

The author’s aim is to reflect on the cartographic modelling of historical borders based on the example of the series “Historical Atlas of Poland. Detailed maps of the 16th century” (HAP). HAP presents secular (state, palatinate, district) and religious borders (dioceses, archdeaconry, deanery, parish). The belonging of historic settlements to administrative units is determined on the basis of written sources. During work on the current volumes of HAP, the borders were reconstructed through their manual interpolation (the so-called linear model). Digital tools enable the automatic generation of administrative units based on settlements in point geometry (Thiessen polygons) or the use of modern divisions (precincts [obręby ewidencyjne]) as a reference to them (semi-automatic method). The article compares and assesses the three mentioned methods of determining historical borders and the possibilities of harmonizing them in relation to contemporary administrative divisions. The source material consisted of 18,357 settlements from the volumes of HAP published so far and 235 parishes for detailed analyses. Precincts were adopted as reference areas due to the possibilities of data harmonization.

K. Clarke, Michael Johnson, T. Trainor

ABSTRACT We review recent developments in cartographic research in North America, in the context of informing the 29th International Cartographic Conference, and 18th General Assembly in 2019. The titles of papers published since 2015 in four leading cartographic journals yielded a corpus of 245 documents containing 1109 unique terms. These terms were analyzed using Latent Dirichlet Allocation and by visual analytics to produce 14 topic groups that mapped onto five classes. These classes were named as information visualization, cartographic data, spatial analysis and applications, methods and models, and GIScience. The classes were then used as themes to discuss the recent cartographic literature more broadly, first, to review recent trends in the research and to identify research gaps, and second, to examine prospects for new research over the next 20 years. A conclusion draws some broad findings from the review, suggesting that cartographic research in the future will be aimed less at dealing with data, and more at generating insight and knowledge to better inform society about global challenges.

Wendy Harding

Federico Capriuoli, Davide Colangelo, Luca Curto et al.

QUIRINALE 3D VR is a software for the navigation in virtual reality of the Quirinale Palace. It is the result of an innovative 3D reconstruction project developed by the Italian companies Geocart and Digital Lighthouse aiming to the enhancement of the Quirinale through the most innovative techniques of Digital Heritage field. The project, based on the integration of existing methodologies and novel processes for cultural heritage digitization supported by computer graphics, has created a unique result in terms of user involvement, also by means of immersive experience.

R. Rogers, Natalia Sánchez-Querubín, Aleksandra Kil

L. Costa

This paper presents introductory clues about the use of cartography in the universe of research. Think cartography while another mode or way to search. It di...

A. Petrov