Documentation & Guide

Master the RegionSat Intelligence Engine. Step-by-step guides for extracting, analyzing, and exporting planetary data.

Getting Started

Account Registration

Creating an account ensures your extraction history is saved and allows for larger bulk downloads.

1
Navigate to Sign Up

Click the "Profile" icon in the top right or the "Register" button on the homepage.

2
Instant Verification

Enter your Organization Name and Email. Our system uses Auto-Verification, so you will be logged in immediately.

3
Legacy Users

If you have an older account, simply log in. The system will automatically detect and upgrade your account security.

The DataHub Interface

The extraction engine is split into two primary zones for efficiency.

Left Sidebar (Config)

This is your control center. Here you define:

  • Variables: Temp, Rain, Soil Moisture
  • Region: Lat/Lon Coordinates
  • Time: Date Range & Frequency
Right Panel (Vis)

The visualization engine.

  • Map: Interactive Leaflet map.
  • Chart: Instant time-series graph.
  • Citation: Auto-generated academic citations.

Step-by-Step Extraction

Step 1: Define Region

Choose between two modes on the sidebar:

  • Point Mode: Enter precise Latitude/Longitude. Ideal for single location analysis.
  • Box Mode: Draw a rectangle on the map. The system averages all grid points within this box.
REGION INPUT:
[X] Box Mode    [ ] Point Mode
Min Lat: 22.5   Max Lat: 24.0
Min Lon: 86.0   Max Lon: 88.5

Step 2: Select Variables & Source

Select your climate variables. The system has built-in intelligence:

  • If you select Temperature, it defaults to ERA5.
  • If you select Solar Radiation, it defaults to NASA POWER.
  • If you select Future Horizon, it switches to CMIP6 Models.

Step 3: Run Analysis

Click Run Analysis to fetch data. The graph will update instantly showing time-series trends.

Download & Export

We support four industry-standard formats for data egress.

Format Best Use Case Details
.xlsx (Excel) Business / Analysis Formatted sheets with metadata headers. Best for manual review.
.csv Data Science / Pandas Flat raw text file. Fastest for large bulk downloads.
.json Web Apps / APIs Key-value pair structure. Ideal for JavaScript/React integration.
.nc (NetCDF) GIS / Research Multi-dimensional array. Opens in QGIS, ArcGIS, or Python Xarray.

FAQ & Support

Ensure your selected date range matches the available data horizon. For example, selecting 2050 for "Observed" data will return nothing. Use "Future_CMIP6" for future dates.

Most data is downscaled to 0.1° x 0.1° (approx 9km at the equator). Native ERA5 is 30km, and NASA POWER is 0.5°. We interpolate to provide finer granularity.

In the visualization panel, click the "Citation" tab. We generate an APA style citation automatically based on the selected dataset (e.g., Copernicus ECMWF 2023).