Earth Engine GPT-Geospatial Data Analysis

Example

var dataset = ee.ImageCollection('MODIS/006/MOD13Q1').filterDate('2022-01-01', '2022-12-31').select('NDVI');

Scenario

A researcher studying vegetation changes over time uses this function to access normalized difference vegetation index (NDVI) data for the year 2022, enabling them to analyze annual vegetation dynamics.

Example

var visualization = {min: 0.0, max: 9000.0, palette: ['blue', 'green', 'red']}; Map.setCenter(-95.845, 37.645, 4); Map.addLayer(dataset, visualization, 'NDVI');

Scenario

An environmental scientist visualizes NDVI data to communicate findings about vegetation health and land use changes to stakeholders in an accessible, visual format.

Example

var meanNDVI = dataset.reduceRegion({reducer: ee.Reducer.mean(), geometry: regionOfInterest, scale: 30});

Scenario

A policy maker leverages statistical analysis to understand the average NDVI value within a specific area, supporting evidence-based decision-making for land management policies.

Example

var timeSeries = ui.Chart.image.series(dataset, region, ee.Reducer.mean(), 500);

Scenario

Conservationists study the time series of NDVI data within a protected area to monitor ecosystem health over time, identifying trends and potential threats.