devalc

devalc's Stars

• nasa/gesdisc-tutorials

  Language:Jupyter Notebook5023

• SWOT-community/SWOT-Hydrology

  Hydrology-relevant tutorials and resources for the Surface Water and Ocean Topography (SWOT) Mission

  Language:Jupyter Notebook122

• podaac/tutorials

  The PO.DAAC Cookbook: A place to find data recipes and tutorials for PO.DAAC datasets, tools & services

  Language:Jupyter Notebook9243

• SWOTAlgorithms/RiverObs

  RiverTile processing algorithms for SWOT

  Language:Jupyter Notebook4617

• c-h-david/rrr

  Reproducible Routing Rituals (RRR)

  Language:Python1912

• geoglows/tdxhydro-postprocessing

  Language:Python21

• RadarCODE/awesome-sar

  A curated list of awesome Synthetic Aperture Radar (SAR) software, libraries, and resources.

  975293

• ASFOpenSARlab/opensarlab-notebooks

  Language:Jupyter Notebook143133

• kristianfoerster/melodist

  MELODIST is an open-source toolbox written in Python for disaggregating daily meteorological time series to hourly time steps. It is licensed under GPLv3 (see license file). The software framework consists of disaggregation functions for each variable including temperature, humidity, precipitation, shortwave radiation, and wind speed. These functions can simply be called from a station object, which includes all relevant information about site characteristics. The data management of time series is handled using data frame objects as defined in the pandas package. In this way, input and output data can be easily prepared and processed. For instance, the pandas package is data i/o capable and includes functions to plot time series using the matplotlib library.

  Language:Python3414

• gpxz/jpgis-dem

  Convert Japan xml DEM files to geotiff rasters.

  Language:Python163

• williamlidberg/Whitebox-tutorial

  This tutorial demonstrates how to extract streams and watersheds from high resolution digital elevation models

  Language:Jupyter Notebook24

• mikejohnson51/climateR

  An R 📦 for getting point and gridded climate data by AOI

  Language:R18140

• UU-Hydro/PCR-GLOBWB_model

  PCR-GLOBWB (PCRaster Global Water Balance) is a large-scale hydrological model intended for global to regional studies and developed at the Department of Physical Geography, Utrecht University (Netherlands). Contact: Edwin Sutanudjaja (E.H.Sutanudjaja@uu.nl).

  Language:Python11879

• giswqs/earthengine-py-notebooks

  A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping

  Language:Jupyter Notebook1.4k406

• google/earthengine-api

  Python and JavaScript bindings for calling the Earth Engine API.

  Language:JavaScript2.7k975