Exploring Vector and Raster Data Formats for Geospatial Visualization With Python

Advances in geospatial technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 163 - 186

Published: May 16, 2024

The chapter uses Python to explore vector and raster data formats within geospatial visualization. It highlights their pivotal role across diverse environmental science, urban planning, natural resource management domains. A nuanced comprehension of these is deemed essential for proficient visualization in Python, as they facilitate the storage manipulation spatial data. Vector accurately represent points, lines, polygons a coordinate system. In contrast, are tailored depict continuous surfaces or grids An array libraries tools outlined exploring visualizing each serving distinct functionalities ranging from systematically introduces concept visualization, elucidates disparities application scenarios formats, subsequently various conducive

Language: Английский

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Analysing Spatiotemporal Variability of Chlorophyll-a Concentration and Water Surface Temperature in Coastal Lagoons of the Ebro Delta (NW Mediterranean Sea, Spain)

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(6), P. 941 - 941

Published: June 3, 2024

Coastal lagoons are highly productive transitional water bodies threatened by human factors and vulnerable to global climate change effects. Monitoring biophysical parameters in these ecosystems is crucial for their preservation. In this work, we used Sentinel-2 Landsat imagery combined with situ data (1) develop preliminary algorithms retrieving the Chl-a concentration surface temperature of six located Ebro Delta (NE Mediterranean Sea, Spain), (2) compute maps trend lines analysing spatiotemporal evolution from 2015 2022. Our findings showed that algorithms’ accuracy ranged 72% 78% had limited potential under high regimes. Even so, they revealed lagoons’ trophic status, usual fluctuations, deviations both attributed seasonal (i.e., light temperature) short-term physical winds) forcing, as well valuable spatial patterns potentially useful conservation efforts land use planning. Future work will focus on acquisition a larger sample range environmental conditions improve robustness, which turn allow investigation natural controlling dynamics two investigated parameters.

Language: Английский

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UAV Communication for Various Learning Approaches in Metaverse Healthcare Analysis Using Cloud Computing

Advances in medical technologies and clinical practice book series, Journal Year: 2024, Volume and Issue: unknown, P. 239 - 251

Published: Aug. 6, 2024

The revolutionary integration of unmanned aerial vehicle (UAV) communication, metaverse technology, learning techniques, and cloud computing in the healthcare industry is investigated this chapter. Unmanned vehicles (UAVs) are capable collecting a wide variety data, which can then be viewed metaverse. In order to detect illnesses at an earlier stage, machine powered by computing. At same time that ethical concerns regulatory problems being highlighted, necessity international collaboration emphasized. Applications real world illustrate future medical care not limited geographic boundaries; it will possible receive treatment remotely education on global scale. chapter representation collective aspiration make fundamental human right, so rewriting history compassion advancement technology.

Language: Английский

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A method for extracting buildings from remote sensing images based on 3DJA-UNet3+

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 17, 2024

Building extraction aims to extract building pixels from remote sensing imagery, which plays a significant role in urban planning, dynamic monitoring, and many other applications. UNet3+ is widely applied images. However, it still faces issues such as low segmentation accuracy, imprecise boundary delineation, the complexity of network models. Therefore, based on model, this paper proposes 3D Joint Attention (3DJA) module that effectively enhances correlation between local global features, obtaining more accurate object semantic information enhancing feature representation. The 3DJA models interdependence vertical horizontal dimensions obtain map spatial encoding information, well channel increase dependent graphs. In addition, bottleneck constructed reduce number parameters improve model training efficiency. Many experiments are conducted publicly accessible WHU,INRIA Massachusetts dataset, benchmarks, BOMSC-Net, CVNet, SCA-Net, SPCL-Net, ACMFNet, MFCF-Net selected for comparison with 3DJA-UNet3+ proposed paper. experimental results show achieves competitive three evaluation indicators: overall mean intersection over union, F1-score. code will be available at https://github.com/EnjiLi/3DJA-UNet3Plus .

Language: Английский

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Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: Dec. 26, 2024

Mosaicking of Unmanned Aerial Vehicles (UAV) imagery over featureless water bodies has been known to be challenging, and poses a significant impediment monitoring applications. Techniques such as Structure-from-motion typically fail under conditions due the lack distinctive features in scene, direct georeferencing is currently only practical solution, albeit lower accuracy expected. However, hardware issues, particularly typical time delay between GPS unit image capture, can lead systematic misalignment further reducing accuracy. The arises recording geographical coordinates by may not precisely correspond exact moment exposure, exposure always occur at mid-exposure time. Hardware solutions mitigate this issue but require technical expertise resources. Alternatively, software address problem without necessitating any modifications. This study introduces an open-source solution for correction alignment accounting distance discrepancy measurements capture. method was validated with field UAV surveys conducted various flight configurations (different altitudes overlap ratios), effective obtained using proposed which reduced error around 67.7%. Specifically, RMSE = 1.409 m σ 0.6356 achieved use ground control points (GCPs). Finally, demonstrated study, low (e.g. 15 m) should discouraged errors could amplify limited GPS, resulting visual artefacts.

Language: Английский

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