ritviksahajpal
Dr. Ritvik Sahajpal is Associate Research Professor, Department of Geographical Sciences at University of Maryland, crop condition co-lead at NASA Harvest
University of Maryland
Pinned Repositories
agate
A Python data analysis library that is optimized for humans instead of machines.
agera5tools
Tools for manipulating (exporting, extracting) AgERA5 data
CropRotations
EPIC
Framework to create EPIC input files, run the model and extract outputs
geeet
Evapotranspiration (ET) models for use in python and with integration into Google Earth Engine
geoprepare
A Python package to prepare (download, extract, process input data) for GEOCIF and related models
GlobalCropRotations
GrasslandLoss_WimberlyPNAS2013
Grassland Loss
pygeoutil
yield_forecasting
ritviksahajpal's Repositories
ritviksahajpal/geeet
Evapotranspiration (ET) models for use in python and with integration into Google Earth Engine
ritviksahajpal/agera5tools
Tools for manipulating (exporting, extracting) AgERA5 data
ritviksahajpal/agoro-field-boundary-detector
Detect field boundaries using satellite imagery.
ritviksahajpal/api-examples
Repository of sample scripts with which one consumes data from Agrimetrics' Data Platform
ritviksahajpal/BreizhCrops
A Satellite Time Series Dataset for Crop Type Identification
ritviksahajpal/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities.
ritviksahajpal/decode
Python code for the DECODE method and mxnet code for Fractal ResUNet
ritviksahajpal/engn3903
ENGN3903 - Environmental Sensing, Mapping and Modelling
ritviksahajpal/EuroCrops
The official repository for the EuroCrops dataset.
ritviksahajpal/gee_s1_ard
Creates an analysis ready sentinel-1 SAR image collection in Google Earth Engine by applying additional border noise correction, speckle filtering and radiometric terrain normalization.
ritviksahajpal/GEEGPRPhenoDemos
Google Earth Engine demo codes from the article "Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression"
ritviksahajpal/GlobalUrbanHeat
Repository for Tuholske et al. (2020). "Global Urban Extreme Heat Exposure" & Global High Resolution Daily Urban Extreme Heat Exposure (UEH-Daily) 1983 - 2016 dataset
ritviksahajpal/GridFree
An App counts the number of components in an image.
ritviksahajpal/jdeskew
Document Image Skew Estimation, Skew Correction, Deskew
ritviksahajpal/merf
Mixed Effects Random Forest
ritviksahajpal/MLCAS2021teamQU
ritviksahajpal/MLforCropYieldForecasting
Implementation of Machine learning baseline for large-scale crop yield forecasting
ritviksahajpal/OutlierConf2021
⭕ Slides and hands-on codes for my talk "ggplot Wizardry: My Favorite Tricks and Secrets for Beautiful Plots in R" at the 1st OutlierConf, February 4–7 2021.
ritviksahajpal/PyAEZ
PyAEZ is a python package consisted of many algorithms related to Agro-ecalogical zoning (AEZ) framework.
ritviksahajpal/PyData-Global-2021-Causal-Inference-Talk
Slides and code for "Sliding Into Causal Inference" talk
ritviksahajpal/Pyspatialml
Machine learning modelling for spatial data
ritviksahajpal/Python
All Algorithms implemented in Python
ritviksahajpal/STREAM-RS
ritviksahajpal/suboptimal
Seriously Unnecessary Baffling Obscure Perplexing Terms In MAchine Learning
ritviksahajpal/sustainbench
ritviksahajpal/WheatGbyE
Scripts for GxE analysis and plotting of nursery
ritviksahajpal/Workshop2022
Using Earth observation for Crop Monitoring (iEOCM) Workshop
ritviksahajpal/basic_training
Basic training notebooks
ritviksahajpal/DeepCropMapping
Official implementation of "DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping".
ritviksahajpal/Landsat-LAI
Employing a data-driven approach to generate Leaf Area Index (LAI) maps from Landsat images over CONUS