Automate satellite data analysis and regulatory reporting with GPT-4 and Slack

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Built by Cheng Siong Chin Cheng Siong Chin
Created on June 05, 2026

Description

How It Works
This workflow automates satellite data processing by ingesting raw geospatial data, applying AI analysis, and submitting formatted reports to regulatory authorities. Designed for environmental agencies, research institutions, and compliance teams, it solves the challenge of manually processing large satellite datasets and preparing standardized submissions for government agencies. The system triggers on scheduled intervals or event webhooks, fetching satellite imagery and sensor data from ECC/climate APIs. Raw data flows through parsing and normalization stages, then routes to AI models for analysis—detecting environmental changes, calculating metrics, and identifying anomalies. Processed results are validated against agency specifications, formatted into SDQAR reports, and automatically stored in designated repositories. The workflow generates submission packages with required metadata, notifies stakeholders via Slack and email, and logs all activities to Google Sheets for audit trails. This eliminates hours of manual data processing, ensures compliance with submission standards, and accelerates environmental monitoring workflows.

Setup Steps
Configure ECC/climate API credentials for satellite data access
Set up webhook endpoints for event-driven data ingestion triggers
Add OpenAI API key for geospatial analysis and anomaly detection
Configure NVIDIA NIM API for specialized environmental modeling
Set Google Sheets credentials for audit logging and tracking
Connect Slack workspace and specify notification channels for submission updates
Configure Gmail OAuth for automated stakeholder notifications

Prerequisites
Active satellite data API access (ECC, NASA, ESA) with authentication credentials.
Use Cases
Automated climate monitoring with monthly regulatory submissions.
Customization
Modify AI analysis prompts for specific environmental parameters.
Benefits
Reduces satellite data processing time by 85% through end-to-end automation.

Nodes Used (8)

AI Agent
@n8n/n8n-nodes-langchain.agent
Code
n8n-nodes-base.code
HTTP Request
n8n-nodes-base.httpRequest
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Postgres
n8n-nodes-base.postgres
Send Email
n8n-nodes-base.emailSend
Slack
n8n-nodes-base.slack
Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured