Update Contributing (#34)

* Update README * Update Contributing
worldbank · Dec 12, 2023 · 2a0c671 · 2a0c671
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diff --git a/README.md b/README.md
@@ -2,15 +2,16 @@
 
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+[![downloads](https://static.pepy.tech/badge/blackmarblepy/month)](https://pepy.tech/project/blackmarblepy)
 [![GitHub Repo stars](https://img.shields.io/github/stars/worldbank/blackmarblepy)](https://github.com/worldbank/blackmarblepy)
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 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
-**BlackMarblePy** provides a simple and efficient way to retrieve and extract nighttime lights data from NASA's Black Marble project. [Black Marble](https://blackmarble.gsfc.nasa.gov) is a [NASA Earth Observatory](https://earthobservatory.nasa.gov) project that provides a product suite of daily, monthly and yearly global nighttime lights. This package automates the process of downloading all relevant tiles from the [NASA LAADS archive](https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5000/VNP46A3/) to cover a region of interest, converting the raw files (in HDF5 format), to georeferenced rasters, and mosaicing rasters together when needed.
+**BlackMarblePy** is a Python package that provides a simple way to use nighttime lights data from NASA's Black Marble project. [Black Marble](https://blackmarble.gsfc.nasa.gov) is a [NASA Earth Science Data Systems (ESDS)](https://www.earthdata.nasa.gov) project that provides a product suite of daily, monthly and yearly global [nighttime lights](https://www.earthdata.nasa.gov/learn/backgrounders/nighttime-lights). This package automates the process of downloading all relevant tiles from the [NASA LAADS DAAC](https://www.earthdata.nasa.gov/eosdis/daacs/laads) to cover a region of interest, converting the raw files (in HDF5 format), to georeferenced rasters, and mosaicing rasters together when needed.
 
 ## Features
 
-- Download daily, monthly, and yearly nighttime lights data  for user-specified region of interest and time range.
+- Download daily, monthly, and yearly nighttime lights data for user-specified region of interest and time.
 - Parallel downloading for faster data retrieval and automatic retry mechanism for handling network errors.
 - Access NASA Black Marble as a Xarray Dataset
   - Integrated data visualization with customization options
@@ -21,6 +22,11 @@
     - Calculate zonal statistics like mean and sum.
     - Plot time series of nighttime lights data.
 
+### Featured on
+
+- [Nighttime Lights Trends in Gaza and West Bank](https://datapartnership.org/gaza-israel-conflict-impact-analysis/notebooks/nighttime-lights/nighttime-lights.html)
+- [World Bank Support for Emergency Relief to Gaza](https://www.worldbank.org/en/news/press-release/2023/12/12/world-bank-support-for-emergency-relief-to-gaza)
+
 ## Installation
 
 **BlackMarblePy** is available on [PyPI](https://pypi.org) as [blackmarblepy](https://pypi.org/project/blackmarblepy) and can installed using `pip`:
@@ -54,6 +60,39 @@ For more detailed information and examples, please refer to the [documentation](
 
 Contributions are welcome! If you'd like to contribute, please follow our [contribution guidelines](CONTRIBUTING.md).
 
+### Contributors
+
+<a href="https://orcid.org/0000-0001-6530-3780">
+Gabriel Stefanini Vicente
+<img alt="ORCID logo" src="https://info.orcid.org/wp-content/uploads/2019/11/orcid_16x16.png" width="16" height="16" />
+</a>
+<br>
+<a href="https://orcid.org/0000-0002-3164-3813">
+Robert Marty
+<img alt="ORCID logo" src="https://info.orcid.org/wp-content/uploads/2019/11/orcid_16x16.png" width="16" height="16" />
+</a>
+
+## Citation
+
+When using **BlackMarblePy**, your support is much appreciated! Please consider using the following citation or download [bibliography.bib](bibliography.bib):
+
+```bibtex
+@misc{blackmarblepy,
+  title = {{BlackMarblePy: Georeferenced Rasters and Statistics of Nighttime Lights from NASA Black Marble}},
+  author = {Gabriel {Stefanini Vicente} and Robert Marty},
+  year = {2023},
+  note = {{BlackMarblePy} v0.2.1},
+  url = {https://worldbank.github.io/blackmarblepy},
+}
+```
+
+{cite:empty}`blackmarblepy`
+
+```{bibliography}
+:filter: docname in docnames
+:style: plain
+```
+
 ## License
 
 This project is open-source - see the [LICENSE](LICENSE) file for details
diff --git a/docs/bibliography.bib b/docs/bibliography.bib
@@ -1,3 +1,11 @@
+@misc{blackmarblepy,
+  title = {{BlackMarblePy: Georeferenced Rasters and Statistics of Nighttime Lights from NASA Black Marble}},
+  author = {Gabriel {Stefanini Vicente} and Robert Marty},
+  year = {2023},
+  note = {{BlackMarblePy} v0.2.1},
+  url = {https://worldbank.github.io/blackmarblepy},
+}
+
 @article{ROMAN2018113,
 title = {NASA's Black Marble nighttime lights product suite},
 journal = {Remote Sensing of Environment},
@@ -10,4 +18,4 @@ @article{ROMAN2018113
 author = {Miguel O. Román and Zhuosen Wang and Qingsong Sun and Virginia Kalb and Steven D. Miller and Andrew Molthan and Lori Schultz and Jordan Bell and Eleanor C. Stokes and Bhartendu Pandey and Karen C. Seto and Dorothy Hall and Tomohiro Oda and Robert E. Wolfe and Gary Lin and Navid Golpayegani and Sadashiva Devadiga and Carol Davidson and Sudipta Sarkar and Cid Praderas and Jeffrey Schmaltz and Ryan Boller and Joshua Stevens and Olga M. {Ramos González} and Elizabeth Padilla and José Alonso and Yasmín Detrés and Roy Armstrong and Ismael Miranda and Yasmín Conte and Nitza Marrero and Kytt MacManus and Thomas Esch and Edward J. Masuoka},
 keywords = {Suomi-NPP, JPSS, NASA black marble, VIIRS, Night lights, NTL, Urban dynamics, Long-term monitoring, Lunar BRDF, Albedo, Atmospheric correction},
 abstract = {NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 m resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.}
-}
+}