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es_2021

This repository contains the code for the manuscript, submitted to the "Ecosystem Services" journal

es_inequality

Ecosystem Service/Inequality project

es_optimisation_amazonia

Optimising ecosystem services (timber production, carbon retention, biodiversity) in Amazonian production forests

escape-demo

Tutorials eSCAPE

esd

An R-package designed for climate and weather data analysis, empirical-statistical downscaling, and visualisation.

esd.test

ESD - Climate analysis and empirical-statistical downscaling R package

esda_cee690-02

Environmental Spatial Data Analysis

esdl

Experiments with the Earth System Data Cube for detection of regime shifts and identification of cascading effects.

esdl.jl

Julia interface for Reading from the Earth System Datacube

esds_book

esgf-config

Test repository for new configuration file management

esgf-globus-download

CLI scripts to search and initiate Globus transfers

esgf_climatedownloads

URL's for generating bash scripts for downloading ESGF climate data

esgfreports

Code for querying and plotting CMIP information from the ESGF indexes

esmvaltool

ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP

esmvaltool-ar6-originalcode-finalfigures

Original ESMValTool code used to produce IPCC figures. This repository will be made public shortly after the publication of the IPCC report

esmvaltool-jupyterlab

Examples and instructions for using ESMValTool in a Jupyter environment

espfusion

Data fusion for downscaling Earth Surface Properties

espon-data

ess-python-tutorial

Repository for the UCI ESS Python tutorial series

essvalpa

Ecosystem services valuation in protected areas

estimatehabitat

Methods for estimating the effect of climate change on physical drivers of marine ecosystems at high latitudes

estuarinemorphologyestimator

Empirical assessment tool for bathymetry, flow velocity and salinity in estuaries based on tidal amplitude and remotely-sensed imagery

eucface_run

run and plot

europe_floods

This is meant to reproduce the main results of 'Changing climate both increases and decreases European river floods' by Blöschl et al. (2019) (https://doi.org/10.1038/s41586-019-1495-6). europe_data.csv contains the data and analysis_code performs the analysis in the programming language R.

evaluation-and-conservation-of-national-landscape

国土景观评价与保护网络课堂

evaluation-of-a-spatially-adaptive-approach-

C Code from Paper entitled Evaluation of a Spatially Adaptive Approach for Land Surface Classification from Digital Elevation Models published in International Journal of Geographical Information Science

evaluation_project-global_power_plant_database_test

Aim: Need To Predict Primary Fuel And Capacity_mw For Global Power Plant Dataset. Problem Statment: An affordable, reliable, and environmentally sustainable power sector is central to modern society. Governments, utilities, and companies make decisions that both affect and depend on the power sector. For example, if governments apply a carbon price to electricity generation, it changes how plants run and which plants are built over time. On the other hand, each new plant affects the electricity generation mix, the reliability of the system, and system emissions. Plants also have significant impact on climate change, through carbon dioxide (CO2) emissions; on water stress, through water withdrawal and consumption; and on air quality, through sulfur oxides (SOx), nitrogen oxides (NOx), and particulate matter (PM) emissions. The Global Power Plant Database is an open-source open-access dataset of grid-scale (1 MW and greater) electricity generating facilities operating across the world. The actual Database currently contains nearly 35000 power plants in 167 countries, representing about 72% of the world's capacity. Entries are at the facility level only, generally defined as a single transmission grid connection point. Generation unit-level information is not currently available. But in our study we will be working on the dataset only for INDIA. The data set contains only 908 rows and 25 columns. The data set provides information of all the power plant situated at diffrent loactions in india. Features of dataset: country: symbolic country Name country_long: Full country Name name : Name of the Power Plant gppd_idnr : 10-12 character type ID of the power plant capacity_mw : Electricity generating capacity in megawatts latitude : Geo location of plant in decimal degerees longitude : Geo location of plant in decimal degerees primary_fuel : Primary fuel used for electricity genrration. other_fuel1 : Energy source used in electricity generation or export other_fuel2 : Energy source used in electricity generation or export other_fuel3 : Energy source used in electricity generation or export commissioning_year: year of opertaion of power plant or when the power plant start. owner : Majority shareholder of the power plant source: Entity reporting the data url : Web document corresponding to the sourcefield geolocation_source :Attribution for geolocation information wepp_id : A reference to a unique plant identifier in the widely-used PLATTS-WEPP database. year_of_capacity_data: year the capacity information was reported generation_gwh_2013 : electricity generation in gigawatt-hours reported for the year 2013 generation_gwh_2014 : electricity generation in gigawatt-hours reported for the year 2014 generation_gwh_2015 : electricity generation in gigawatt-hours reported for the year 2015 generation_gwh_2016 : electricity generation in gigawatt-hours reported for the year 2016 generation_gwh_2017 : electricity generation in gigawatt-hours reported for the year 2017 generation_data_source : electricity generation in gigawatt-hours reported for the year 2014 estimated_generation_gwh : attribution for the reported generation information

everyday

everyday scripts

evi

The enhanced vegetation index (EVI) is an 'optimized' index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a de-coupling of the canopy background signal and a reduction in atmosphere influences.