Hasil untuk "Cartography"

Corrado Pisani

The Earth Observation sector is undergoing a structural transformation driven by the convergence of large satellite constellations, historical data archives and in-orbit artificial intelligence. Solutions such as ImageryPack enable seamless access to multi-source satellite imagery through a flexible credit-based model, supporting a wide variety of operational needs. At the same time, the AI-eXpress in-orbit processing platform dramatically shortens the traditional EO value chain by executing analytics directly in space, reducing latency and data transmission requirements. These innovations turn Earth Observation into an actionable geo-intelligence capability for public administrations, infrastructure operators, environmental monitoring, urban planning and emergency management.

Soomin Hwang, Hyunyoung Choi, Yoojin Kang et al.

Atmospheric carbon dioxide (CO2), a long-lived and well-mixed greenhouse gas, is a key driver of global warming. Accurate, long-term monitoring of its spatiotemporal variability is essential for understanding carbon dynamics. While the Orbiting Carbon Observatory-2 (OCO-2) satellite provides one of the most precise column-averaged CO2 (XCO2) measurements, its limited spatial coverage and short record since 2014 constrain long-term global analysis. Many studies thus highly rely on chemical transport models (e.g. Copernicus Atmosphere Monitoring Service (CAMS) and CarbonTracker) when applying machine learning (ML) approaches. However, their coarse resolutions often lead to spatial smoothing. In this context, we present a novel ML-based framework based on residual learning with the Light Gradient Boosting Machine (LGBM) to reconstruct global, gap-free XCO2 at 0.1° resolution for the period 2003–2019. By explicitly modeling the residuals between high precision OCO-2 observations and the coarse resolution CAMS-EGG4 reanalysis, the proposed framework mitigates spatial smoothing effects and enables the extension of XCO2 estimates beyond the temporal coverage of the OCO-2 mission. The resulting product was strictly validated through internal cross-validation (random, spatial, and temporal) and external in situ validation, showing strong agreement with OCO-2 satellite observations (R2 = 0.93–0.96, RMSE = 0.80–1.11 ppm) and ground-based measurements (R2 = 0.98, RMSE = 1.17 ppm), respectively. Compared to CAMS-EGG4, the LGBM-based XCO2 product also outperforms by offering higher accuracy and resolving the spatial smoothing limitations caused by its coarse resolution. By bridging gaps in satellite data across space and time, this high-resolution XCO2 product enhances applications in climate research, emission source attribution, and greenhouse gas policy assessment.

María Pierina Lucco García, Pablo Andrés Pérez Gutiérrez, Enith Johana Pacheco Casadiegos et al.

This study explores the cultural, productive, territorial, and organizational practices of cacao-producing families in Lebrija, Santander (Colombia), within the broader context of rural sustainability and peasant identity in Latin America. In response to recent national and international frameworks recognizing the rights of peasants, the research aims to document local knowledge systems and community-based strategies that sustain rural livelihoods. Through a qualitative ethnographic approach, including participatory workshops, semi-structured interviews, and social cartography, the study collected narratives, practices, and territorial dynamics over the course of one year. The results reveal that cacao production is not only an economic activity, but a deeply embedded cultural process that intertwines with memory, family ties, lunar cycles, and environmental stewardship. Participants described conflicts related to water access, deforestation, poultry farming, and the expansion of urban infrastructure. Despite these pressures, families demonstrated adaptive capacities through agrodiversity, traditional knowledge, and associative work. The study concludes that these cacao-based practices offer valuable insights into bottom-up strategies for resilience and territorial sustainability and calls for greater inclusion of peasant knowledge in rural development agendas.

Jinyang Han, Jie Zhang, Shiming Zhong et al.

In the processing of Precise Point Positioning (PPP) data, the receiver clock is approached with nearly infinite uncertainty, rendering it difficult to fulfill the requirements of high-precision time frequency applications. Therefore, a receiver clock model is essential. In this study, we first analyze the “over-constraint” problem in the existing clock model and subsequently propose a new clock model, called the Adaptive Clock Constraint (ACC) model, which relies on a sliding window to update covariance and frequency characteristics parameters in real-time. To verify the robustness of the ACC model, three experiments were conducted, and the results show that the ACC model not only is suitable for different types of atomic clock stations but also has superior frequency stability and time transfer precision in contrast to the BIPM PPP, the IGS products and White Noise (WN) model results. Using the optical fiber results as a time reference, the STD of the time difference between the ACC model and optical fiber results is 0.13 ns and the frequency stability is 1.28 × 10−16 on average for one week, representing improvements of more than 10% and 15% compared with the BIPM PPP results.

Yi Xiao, Qiangqiang Yuan, Jiang He et al.

Global and local modeling is essential for image super-resolution tasks. However, current efforts often lack explicit consideration of the cross-scale knowledge in large-scale earth observation scenarios, resulting in suboptimal single-scale representations in global and local modeling. The key motivation of this work is inspired by two observations: 1) There exists hierarchical features at the local and global regions in remote sensing images, and 2) they exhibit scale variation of similar ground objects (e.g. cross-scale similarity). In light of these, this paper presents an effective method to grasp the global and local image hierarchies by systematically exploring the cross-scale correlation. Specifically, we developed a Cross-scale Self-Attention (CSA) to model the global features, which introduces an auxiliary token space to calculate cross-scale self-attention matrices, thus exploring global dependency from diverse token scales. To extract the cross-scale localities, a Cross-scale Channel Attention (CCA) is devised, where multi-scale features are explored and progressively incorporated into an enriched feature. Moreover, by hierarchically deploying CSA and CCA into transformer groups, the proposed Cross-scale Hierarchical Transformer (CHT) can effectively explore cross-scale representations in remote sensing images, leading to a favorable reconstruction performance. Comprehensive experiments and analysis on four remote sensing datasets have demonstrated the superiority of CHT in both simulated and real-world remote sensing scenes. In particular, our CHT outperforms the state-of-the-art approach (TransENet) in terms of PSNR by 0.11 dB on average, but only accounts for 54.8% of its parameters.

Jacek Rapiński, Dariusz Tomaszewski, Renata Pelc-Mieczkowska

This study examines the influence of multipath errors on Global Navigation Satellite System (GNSS) measurements collected at ASG-EUPOS reference stations between 2010 and 2021. Multipath occurs when GNSS signals reflect off surrounding objects before reaching the receiver antenna, leading to positioning errors. In the case of reference stations, all available mitigation techniques were used to minimize the impact of multipath. However, it is still detectable and affects the measurement results. For carrier phase differential positioning, it increases the ambiguous search space, which results in a decrease in determining rover—reference station vector accuracy. The study employs two linear combinations (Code-Minus-Carrier and Multipath Pseudorange Observable) to quantify the multipath effect on both pseudorange and carrier phase measurements. Based on the research, it was found that the multipath values changed depending on the change of the receiver and the terrain around the reference stations. The study observed a gradual decrease in multipath errors from 2010 to 2021, likely due to technological advancements in receiver design. No significant increase in multipath errors was observed due to environmental changes around the stations, suggesting a minimal influence from new reflecting objects nearby. Based on the analyses conducted, it is also recommended to perform periodic tests to detect incorrect receiver configuration or operation.

Amani Michael Uisso, Aliefendioğlu (Tanrıvermiş) Yeşim, Md Moynul Ahsan et al.

context and background Despite the robustness of various land instruments and legal and institutional regulations on various sectors, Tanzania’s land distribution-related policy implementation and practice is facing numerous challenges. Tanzania is not only experiencing poor land conditions, but also poor land management and ineffective policy implementation. Areas of concern includes public policy actions on land conflicts; settlements and housing problems; and conflicting demand for land for mining, large scale agriculture, conservation, tourism, ranching and pastoral nomadism. This study highlights that the land sector in Tanzania is in a state of instability due to inability to secure rights to land, issues around transparency and ongoing disputes and misunderstanding within society as demand for land increases. Goal and Objectives: The study tries to find out the potential of land and available related policies incongruent with the future land distribution and land use for sustainable land use in Tanzania by recommending the proper land distribution policy directions for feasible outcomes. Methodology: Secondary data analysis was applied to support the existing scenario in land policies regarding land use and the land distribution paradox. A review of land use, distribution, ownership in Tanzania has been conducted by focusing on land use and land cover distribution, size of public land, land claims by major sectors, and land ownership in Tanzania. Results: The study recommends that the government should go beyond land reforms and new legal regulations, but rather concentrate on innovative, participatory, and sustainable land development policy approaches. More emphasis on the operational land market, land information system, land rights, and security of tenure should instead be heightened. Again, effective coordination with relevant sectoral agencies can enhance the implementation of existing policies toward achieving sustainable land and resource management.. 

Jiaxin Dong, Siwei Li, Lina Huang et al.

As a special branch of global trade, the trade of agricultural products has an important impact on food security and the environment. In this paper, we studied international trade network of agricultural products from 2000 to 2016 as a whole and in part. We explored the overall characteristics of the network, analyzed the evolution of communities and identified core countries of the communities. The results show that the structure of the trade network became increasingly complex and the trade relations became closer over time. There were four major communities in the network, whose primary core countries were Germany, the United States, Brazil, and China. Since 2007, the community represented by China has disappeared, and the community pattern of the network has been in a three-pillar state and basically stable. We discuss the actual roles of certain trading countries, the formation of communities and the impact of economic events on agricultural products trade. This paper reveals the underlying patterns of the agricultural products trade and provides a way to track its evolution over time.

Miguel Ángel Maté-González, Cristina Sáez Blázquez, Pedro Carrasco García et al.

This research focuses on the study of the ruins of a large building known as “El Torreón” (the Tower), belonging to the Ulaca <i>oppidum</i> (Solosancho, Province of Ávila, Spain). Different remote sensing and geophysical approaches have been used to fulfil this objective, providing a better understanding of the building’s functionality in this town, which belongs to the Late Iron Age (ca. 300–50 BCE). In this sense, the outer limits of the ruins have been identified using photogrammetry and convergent drone flights. An additional drone flight was conducted in the surrounding area to find additional data that could be used for more global interpretations. Magnetometry was used to analyze the underground bedrock structure and ground penetrating radar (GPR) was employed to evaluate the internal layout of the ruins. The combination of these digital methodologies (surface and underground) has provided a new perspective for the improved interpretation of “El Torreón” and its characteristics. Research of this type presents additional guidelines for better understanding of the role of this structure with regards to other buildings in the Ulaca <i>oppidum</i>. The results of these studies will additionally allow archaeologists to better plan future interventions while presenting new data that can be used for the interpretation of this archaeological complex on a larger scale.

P. Knoefel, D. Herrmann, M. Sindram et al.

The research and development project named Landscape Change Detection Service (German abbreviation: LaVerDi) was initiated by the German Federal Agency for Cartography and Geodesy (BKG). Within the scope of the project a monitoring service for landscape changes was developed and implemented using free Copernicus satellite data for an automated derivation of potential land cover change. This change indication is meant to be used to update or continue BKG in-house products, such as the Digital Land Cover Model Germany (LBM-DE), in a comprehensive and uniform quality. The results can be further used for numerous applications or as change information for administration and planning, and for the compilation of spatial statistics. It satisfies the users' need for a national service for open data on land cover changes and thus represents the first automatic and verified national satellite product for land cover changes in Germany. As input data the service uses pre-processed Sentinel-2 data from the European Copernicus satellite program, as well as an image segmentation approach to extract change objects. Using an improved cloud mask algorithm, Sentinel-2 tiles with up to maximum cloud coverage of 60% can be used for analysis. The service (data processing, change detection, visualisation) runs on the German “Copernicus Data and Utilization Platform” (CODE-DE). As of December 2020, the INSPIRE-compliant LaVerDi web service is operational. The thematic accuracy of the generated change layers is above the given requirements (minimum of 80%), considering the 95% confidence interval for all relevant land cover classes in certain test areas. The transferability of the methodology has been successfully shown by a prototypic nationwide demonstrator in early 2020 and is therefore expected to reliably detect both long-term and seasonal changes.

Lin Yang, Yehua Sheng, Anping Pei et al.

Mound tombs, popular in the south Yangzi River area in Shang and Zhou Dynasties, are regional cultural remains in China. With the aims of protecting and scientifically analysing cultural relics, laser scanning technology was adopted to study Zhaihuatou mound tombs located in Nonglin Village in Tianwang town, Jiangsu Province. Multiple tombs are held within one mound in good keep and with the typical construction of centripetalism. Accurate tomb LiDAR (Light Detection And Ranging) data were acquired by applying terrestrial laser scanning technology to the field mound excavation. Subsequently, a spatial morphological analysis of the tombs was conducted on the basis of archaeological rules and GIS spatial data processing methods. Using the theory of centripetalism construction of multi-tomb-one-mounds, we proposed an algorithm to determine the concentrated area of the geometric directions of tombs, and centripetalism theory was scientifically validated in comparing results with the excavation data. Spatial data clustering methods were used to analyse and deduce the spatial distribution characteristics of the tombs. We propose and demonstrate that the burial system is in the form of family-clan aggregation, and is useful for developing research on regional burials. Experimental data show that the proposed method is a novel example of how spatial analysis can foster more precise field archaeological excavations on a large scale, and it is significant to study various types of tombs, relics and ruins.

Esperanza Mateos

The Kyoto protocol officially recognised the role of forests as carbon sinks in the mitigation of global climate change factors, basically by reducing the atmospheric concentrations of CO2. The utilization of forest biomass residues for bio-energy can help meet the need for renewable energy production. The aim of this research work is the development of a methodology to quantify and yield cartography of the prospective energy production of residual biomass from the most representative forest species of Biscay, province of the Autonomous Community of the Basque Country (ACBC, Spain), using a Geographic Information System (GIS) computer tool. A model of indirect estimation has been used in order to estimate the evolution of forest masses throughout in any area of Biscay. In the study area, residues from forest represent a large biomass potential. The stock of total forest biomass (aboveground and underground) (TB) existing in the forests of the province of Biscay in the year 2016 amounted to 16.380 Tg of dry material, which implies a sequestration of 29.874 Tg of CO2. The results obtained after the statistical analyses of the data showed that the amount of mean forest biomass residue achieved with a 95% confidence interval was 73,216.7 Mg year−1. The estimation of biomass quantities that may generate forest activity will allow us to accomplish its planned exploitation, taking into account both economic and environmental aspects, with the aim of determining which the optimum location for setting up an energy production plant is.

C. M. López

<p>This article offers an empirical account of the emotionally charged processes involved in the social production of territory. I draw from ethnographic interviews with displaced leaders of socio-territorial movements in Medellín, Colombia, who are resisting what I call double displacement. First, they were displaced from the Colombian countryside due to conflict and now, decades later, they are again being displaced, this time from their informal settlements due to urban development. Founders of settlements are now leaders of social movements, who reside on the periphery of the city and make claims to their neighborhoods using the slogan that they have a “right to the territory”. I examine this case of double displacement to demonstrate the emotional and political aspects of re-territorialization by non-state actors at the urban scale. I argue that by applying a socio-territorial approach to examining the impact of double displacement, we recognize non-state territorialization as a realization and expansion of social power.</p>

Solomon G. Tesfamichael, Solomon W. Newete, Elhadi Adam et al.

One of the challenges in fighting plant invasions is the inefficiency of identifying their distribution using field inventory techniques. Remote sensing has the potential to alleviate this problem effectively using spectral profiling for species discrimination. However, little is known about the capability of remote sensing in discriminating between shrubby invasive plants with narrow leaf structures and other cohabitants with similar ecological niche. The aims of this study were therefore to (1) assess the classification performance of field spectroradiometer data among three bushy and shruby plants (Artemesia afra, Asparagus laricinus, and Seriphium plumosum) from the coexistent plant species largely dominated by acacia and grass species, and (2) explore the performance of simulated spectral bands of five space-borne images (Landsat 8, Sentinel 2A, SPOT 6, Pleiades 1B, and WorldView-3). Two machine-learning classifiers (boosted trees classification and support vector machines) were used to classify raw hyperspectral (n = 688) and simulated multispectral wavelengths. Relatively high classification accuracies were obtained for the invasive species using the original hyperspectral bands for both classifiers (overall accuracy, OA = 83–97%). The simulated data resulted in higher accuracies for Landsat 8, Sentinel 2A, and WorldView-3 compared to those computed for bands simulated to SPOT 6 and Pleiades 1B data. These findings suggest the potential of remote-sensing techniques in the discrimination of different plant species with similar morphological characteristics occupying the same niche.

Yahya Zefri, Achraf ElKettani, Imane Sebari et al.

Being sustainable, clean, and eco-friendly, photovoltaic technology is considered as one of the most hoped solutions face to worldwide energetic challenges. Morocco joins this context with the inauguration of numerous clean energy projects. However, one key factor in making photovoltaic installations a profitable investment are regular and effective inspections in order to detect occurred defects. Unmanned aerial vehicles (UAV) are increasingly used in various inspection fields. In this respect, this work focuses on the use of thermal and visual imagery taken by UAV in the inspection of photovoltaic installations. Visual and thermal images of photovoltaic modules, obtained by UAV, from different installations, and with different acquisition conditions and parameters, were exploited to generate orthomosaics for inspection purposes. The methodology was tested on a dataset we have acquired by a mission in Rabat (Morocco), and also on external datasets acquired in Switzerland. As final results, several visual defects were detected in visual RGB and thermal orthomosaics, such as cracks, soiling, and hotspots. In addition, a procedure of semi-automatic hotspots&#8217; extraction was also developed and is presented within this work. On the other side, various tests were conducted on the influence of some acquisition and processing parameters (images&#8217; overlap, the ground sampling distance, the flying height, the use of ground control points, the internal camera parameters&#8217; optimization) on the detection of defects and the quality of visual and thermal generated orthomosaics. In the end, the potential of UAV thermal and visual imagery in the inspection of photovoltaic installations was discussed in function of various parameters. On the basis of the discussion feedback, UAV were concluded as advantageous tools within the thematic of this project, which proves the necessity of their implementation in this context.

Denis Eckert, Sophie Lambroschini

J. Harley

Christopher B. Jones

J. Vallée

Aluir Porfírio Dal Poz

Este artigo apresenta um método para o refinamento fotogramétrico de contornos tridimensionais de telhado de edifício extraídos de dados de varredura a laser aerotransportado (VLA). A hipótese principal assumida é que as faces planares de um telhado de edifício, acuradamente extraídas de dados de VLA, e o contorno do mesmo telhado, acuradamente extraído de uma imagem aérea de altíssima resolução, podem ser combinados para melhorar o correspondente contorno de telhado extraído de dados de VLA. O método proposto baseia-se em três etapas. Inicialmente polígonos representando contornos de telhados são extraídos de imagens aéreas de alta-resolução. Na sequência, os segmentos de reta que compõem cada polígono de telhado de edifício são projetados sobre as correspondentes faces de telhado extraídas de dados de VLA, usando um novo modelo fotogramétrico. Finalmente, a reconstrução de cada contorno tridimensional de telhado é realizada através da conexão de todos os pares adjacentes de segmentos de reta obtidos na etapa anterior. Os resultados obtidos mostraram que a integração de uma imagem aérea de altíssima resolução e dados de VLA permite a obtenção de melhores resultados, quando comparados com os correspondentes resultados gerados usando apenas dados de VLA.