Improved README opengeos#83

README.md

@@ -12,6 +12,7 @@
 [![image](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![image](https://img.shields.io/badge/YouTube-Channel-red)](https://www.youtube.com/c/QiushengWu)
 [![image](https://img.shields.io/twitter/follow/giswqs?style=social)](https://twitter.com/giswqs)
+[![status](https://joss.theoj.org/papers/b081afbd9bdaa4386475c787db8e370c/status.svg)](https://joss.theoj.org/papers/b081afbd9bdaa4386475c787db8e370c)
 
 **A Python package for geospatial analysis and interactive mapping in a Jupyter environment.**
 
@@ -24,21 +25,11 @@
 
 ## Introduction
 
-**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](https://geemap.org) Python package, which was designed specifically to work with [Google Earth Engine](https://earthengine.google.com) (GEE). 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 a number of open-source packages, such as [folium](https://github.com/python-visualization/folium), [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet), and [here-map-widget-for-jupyter](https://github.com/heremaps/here-map-widget-for-jupyter) (for creating interactive maps), [WhiteboxTools](https://github.com/jblindsay/whitebox-tools) and [whiteboxgui](https://github.com/giswqs/whiteboxgui) (for analyzing geospatial data), and [ipywidgets](https://github.com/jupyter-widgets/ipywidgets) (for designing interactive graphical user interface [GUI]). The WhiteboxTools library currently contains **470+** tools for advanced geospatial analysis, which are each grouped based on their main function into one of the following categories. Users can access these tools via whiteboxgui directly within the leafmap user interface without writing a single line of code.
-
--   [Data Tools](https://jblindsay.github.io/wbt_book/available_tools/data_tools.html)
--   [Geomorphometric Analysis](https://jblindsay.github.io/wbt_book/available_tools/geomorphometric_analysis.html)
--   [GIS Analysis](https://jblindsay.github.io/wbt_book/available_tools/gis_analysis.html)
--   [Hydrological Analysis](https://jblindsay.github.io/wbt_book/available_tools/hydrological_analysis.html)
--   [Image Processing Tools](https://jblindsay.github.io/wbt_book/available_tools/image_processing_tools.html)
--   [LiDAR Tools](https://jblindsay.github.io/wbt_book/available_tools/lidar_tools.html)
--   [Mathematical and Statistical Analysis](https://jblindsay.github.io/wbt_book/available_tools/mathand_stats_tools.html)
--   [Precision Agriculture](https://jblindsay.github.io/wbt_book/available_tools/precision_agriculture.html)
--   [Stream Network Analysis](https://jblindsay.github.io/wbt_book/available_tools/stream_network_analysis.html)
+**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](https://geemap.org) Python package, which was designed specifically to work with [Google Earth Engine](https://earthengine.google.com) (GEE). 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](https://github.com/python-visualization/folium) ]and [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) (for creating interactive maps), [WhiteboxTools](https://github.com/jblindsay/whitebox-tools) and [whiteboxgui](https://github.com/giswqs/whiteboxgui) (for analyzing geospatial data), and [ipywidgets](https://github.com/jupyter-widgets/ipywidgets) (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](https://jblindsay.github.io/wbt_book/available_tools/gis_analysis.html), [Geomorphometric Analysis](https://jblindsay.github.io/wbt_book/available_tools/geomorphometric_analysis.html), [Hydrological Analysis](https://jblindsay.github.io/wbt_book/available_tools/hydrological_analysis.html), [LiDAR Data Analysis](https://jblindsay.github.io/wbt_book/available_tools/lidar_tools.html), [Mathematical and Statistical Analysis](https://jblindsay.github.io/wbt_book/available_tools/mathand_stats_tools.html), and [Stream Network Analysis](https://jblindsay.github.io/wbt_book/available_tools/stream_network_analysis.html).
 
 ## Statement of Need
 
-There are a plethora of Python packages for geospatial analysis, such as [geopandas](https://github.com/geopandas/geopandas) for vector data analysis and [xarray](https://github.com/pydata/xarray) for raster data analysis. However, few Python packages provide interactive GUIs for loading and visualizing geospatial data in a Jupyter environment. It might take many lines to code to load and display geospatial data with various file formats on an interactive map, which can be a challenging task for novice users with limited coding skills. Leafmap provides many convenient functions for loading and visualizing geospatial datasets with only one line of code. Users can also use the interactive GUI to load geospatial datasets without coding. Anyone with a web browser and Internet connection can use leafmap to perform geospatial analysis and data visualization in the cloud with minimal coding.
+There are a plethora of Python packages for geospatial analysis, such as [geopandas](https://github.com/geopandas/geopandas) for vector data analysis and [xarray](https://github.com/pydata/xarray) for raster data analysis. However, few Python packages provide interactive GUIs for loading geospatial data in a Jupyter environment. It might take many lines to code to load and display geospatial data with various file formats on an interactive map, which can be a challenging task for novice users with limited coding skills. There are also some notable Python packages for visualizing geospatial data in a Jupyter environment, such as [plotly](https://github.com/plotly/plotly.py) and [kepler.gl](https://docs.kepler.gl/docs/keplergl-jupyter). However, plotly is designed for displaying static data, which lacks bidirectional communication between the front-end and the backend. Kepler.gl provides unique 3D functionality for visualizing large-scale geospatial datasets, but it lacks tools for performing geospatial analysis, such as hydrological analysis and LiDAR data analysis. In contrast, leafmap provides many convenient functions for loading and visualizing geospatial datasets with only one line of code. Users can also use the interactive GUI to load geospatial datasets without coding. Leafmap is intended for anyone who would like to analyze and visualize geospatial data interactively in a Jupyter environment. It is particularly suited for novice users with limited programming skills. Advanced programmers can also find leafmap a useful tool for analyzing geospatial data and building interactive web apps.
 
 Launch the interactive notebook tutorial for the **leafmap** Python package with Google Colab or Binder now:
 

docs/get-started.md

@@ -4,7 +4,7 @@ This Get Started guide is intended as a quick way to start programming with **le
 
 ## Important Note
 
-**Leafmap** has three plotting backends, including [folium](https://github.com/python-visualization/folium), [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet), and [here-map-widget-for-jupyter](https://github.com/heremaps/here-map-widget-for-jupyter) [@Kharude2021]. An interactive map created using one of the plotting backends can be displayed in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. By default, `import leafmap` in [Jupyter Notebook](https://gishub.org/leafmap-pangeo) and [JupyterLab](https://gishub.org/leafmap-binder) will use the `ipyleaflet` plotting backend, whereas `import leafmap` in [Google Colab](https://gishub.org/leafmap-colab) will use the `folium` plotting backend. Note that Google Colab does not yet support custom widgets, such as `ipyleaflet` and `heremap widget` ([source](https://github.com/googlecolab/colabtools/issues/498#issuecomment-695335421)). Therefore, interactive maps created using the `ipyleaflet` and `heremap widget` backends won't show up in Google Colab, even though the code might run successfully without any errors.
+**Leafmap** has three plotting backends, including [folium](https://github.com/python-visualization/folium), [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet), and [here-map-widget-for-jupyter](https://github.com/heremaps/here-map-widget-for-jupyter). An interactive map created using one of the plotting backends can be displayed in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. By default, `import leafmap` in [Jupyter Notebook](https://gishub.org/leafmap-pangeo) and [JupyterLab](https://gishub.org/leafmap-binder) will use the `ipyleaflet` plotting backend, whereas `import leafmap` in [Google Colab](https://gishub.org/leafmap-colab) will use the `folium` plotting backend. Note that Google Colab does not yet support custom widgets, such as `ipyleaflet` and `heremap widget` ([source](https://github.com/googlecolab/colabtools/issues/498#issuecomment-695335421)). Therefore, interactive maps created using the `ipyleaflet` and `heremap widget` backends won't show up in Google Colab, even though the code might run successfully without any errors.
 
 The three plotting backends do not offer equal functionality. The `ipyleaflet` plotting backend provides the richest interactive functionality, including the custom toolset for loading, analyzing, and visualizing geospatial data interactively without coding. For example, users can add vector data (e.g., GeoJSON, Shapefile, KML, GeoDataFrame) and raster data (e.g., GeoTIFF, Cloud Optimized GeoTIFF [COG]) to the map with a few clicks (see Figure 1). Users can also perform geospatial analysis using the WhiteboxTools GUI with 468 geoprocessing tools directly within the map interface (see Figure 2). Other interactive functionality (e.g., split-panel map, linked map, time slider, time-series inspector) can also be useful for visualizing geospatial data. The `ipyleaflet` package is built upon `ipywidgets` and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input ([source](https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a)). In contrast, `folium` has relatively limited interactive functionality. It is meant for displaying static data only. The `folium` plotting backend is included in this package to support using `leafmap` in Google Colab. Note that the aforementioned custom toolset and interactive functionality are not available for the `folium` plotting backend. Compared with `ipyleaflet` and `folium`, the `heremap widget` plotting backend provides some unique [3D functionality](https://github.com/heremaps/here-map-widget-for-jupyter#use-ipywidgets-controls-to-build-an-interactive-gui) for visualizing geospatial data. An [API key](https://developer.here.com/documentation/identity-access-management/dev_guide/topics/dev-apikey.html) from the [Here Developer Portal](https://developer.here.com/) is required to use `heremap`.