python-visualization/folium v0.12.1

Filipe,; Journois, Martin; Story, Rob; Gardiner, James; Bird, Andrew; Lima, Antonio C. S.; Cano, Joshua; Leonel, Juliana; Welsh, Ben; Reades, Jonathan; Kong, Qingkai; Odovad,; Dumas, Raphaël; Harris, George; Acosby,; Kenmatsu,; Nogueira, Tales Paiva; Wilson, Nat; Giessel, Andrew J.; Soymsk,; Sampson, Tim; Signell, Richard P.; Duke, J. A.; Patil, Anand P.; Sgvandijk,; Wasserman, Jacob L; Andrade, Elliott Sales de; Shin, Edwin; Ahmadia, Aron; Pah, Adam R.

doi:10.5281/zenodo.4447642

Cited by 3 publications

(1 citation statement)

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“…WaSAR builds mainly on GeoPandas (Jordahl et al, 2021) and Pandas (Reback et al, 2020) for the spatio-temporal time series analysis and data storage, and make use of Matplotlib (Hunter, 2007) and Folium (Filipe et al, 2021) for the data and spatial visualization, respectively. The use of Folium package allows the user an interactive visualization of any of the model variables, and the possibility of representing them in different background layers, such as the satellite image or Google maps layers.…”

Section: Integrated Analysis Compiled In a Python Package: Wasarmentioning

confidence: 99%

Analysis of Aquifer‐System Deformation in the Doñana Natural Space (Spain) Using Unsupervised Cloud‐Computed InSAR Data and Wavelet Analysis

González-Jiménez

Guardiola‐Albert

Ezquerro

et al. 2023

Water Resources Research

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This work is focused on the Almonte‐Marismas aquifer located within Doñana Natural Space (SW Spain); this aquifer is threatened by droughts, irrigation‐driven groundwater overexploitation, urban use, and the potential reactivation of gas extraction and storage projects. We present ground deformation measurements from Sentinel‐1 Interferometric Synthetic Aperture Radar (InSAR) data ranging from 1‐2.5 cm, covering ∼2,500 km2 from 2014‐2020. Detecting spatially distributed ground deformation over this agricultural area is challenging due to the low‐coherence radar signals; consequently, the ground movement results are on the same order of magnitude as the errors associated with InSAR data. We have approached this issue by considering auxiliary information such as groundwater levels, climatic time series, and pumping rates and analyzing their spatio‐temporal connections to ground displacements. We correlate InSAR and hydrogeological information through wavelet analysis, developing a Python package that allows applying the same methodology in other similar study areas. For the first time in the Doñana area, a significant relationship between distances to pumping wells and the displacement extent is detected. Moreover, other subsidence‐related triggering factors are identified, such as the soil moisture balance, clay shrinking‐swelling processes, and creep of geological formations. These results are highly valuable to support aquifer management decisions in the Doñana Natural Space; in this border region, three groundwater bodies were officially declared overexploited in 2020. Our findings provide a ground motion baseline assessment to help differentiate historical variations from any future anthropogenic effect in this complex marsh land ecosystem.

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Section: Integrated Analysis Compiled In a Python Package: Wasarmentioning

confidence: 99%

Analysis of Aquifer‐System Deformation in the Doñana Natural Space (Spain) Using Unsupervised Cloud‐Computed InSAR Data and Wavelet Analysis

González-Jiménez

Guardiola‐Albert

Ezquerro

et al. 2023

Water Resources Research

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Interactive mapping and geospatial analysis with Leafmap and Jupyter

2021

Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science

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Leafmap: A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment

Wu¹

2021

JOSS

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Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package (Wu, 2020), which was designed specifically to work with Google Earth Engine (GEE) (Gorelick et al., 2017). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium (Filipe et al., 2021)and ipyleaflet (Renou et al., 2021) (for creating interactive maps), WhiteboxTools (Lindsay, 2018) and whiteboxgui (for analyzing geospatial data), and ipywidgets (Grout & et al., 2021) (for designing interactive graphical user interface [GUI]). Leafmap has a toolset with various interactive tools that allow users to load vector and raster data onto the map without coding. In addition, users can use the powerful analytical backend (i.e., WhiteboxTools) to perform geospatial analysis directly within the leafmap user interface without writing a single line of code. The WhiteboxTools library currently contains 468 tools for advanced geospatial analysis, such as GIS Analysis, Geomorphometric Analysis, Hydrological Analysis, LiDAR Data Analysis, Mathematical and Statistical Analysis, and Stream Network Analysis.

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python-visualization/folium v0.12.1

Cited by 3 publications

References 0 publications

Analysis of Aquifer‐System Deformation in the Doñana Natural Space (Spain) Using Unsupervised Cloud‐Computed InSAR Data and Wavelet Analysis

Analysis of Aquifer‐System Deformation in the Doñana Natural Space (Spain) Using Unsupervised Cloud‐Computed InSAR Data and Wavelet Analysis

Interactive mapping and geospatial analysis with Leafmap and Jupyter

Leafmap: A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment

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