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Natural State Documentation
Glossary
NS Glossary
AGOL Data Workflows
Extract data from GEE
Import to GDBs
Upload to AGOL
Non-standard layers
AGOL_Azure Blob_Connection
GEE_Azure Blob_Connection
Analyses
Natural State (NS) Applications
WSL2 Application
VS Code Application
Docker Application
Helm Application
Data Build Tool (DBT)
Azure
Azure Storage Creation
Azure Blob Storage Container Creation
Creating a Databricks Secret Scope
CVAT
Data Annotation Process
Assigning tasks
Automatic annotation
Data build tool
Installation
Activation
Defining data models
Documentation
Models in dbt
Running models
Generating project documentation
Other dbt commands
Annotation Platform
Kubernetes
CI/CD
Data Standards
Data Ingress & Egress
Data Tiers
Data Visualization
Data Visualization using Docker
Data Visualization using Helm
Databricks
Introduction
Workspace browser
Catalog
Workflows
Compute
SQL Editor
Queries
Dashboards
Alerts
Query history
SQL Warehouses
End-to-end Databricks project
Design Documents
Bird Point Counts
LLBN Carbon-Biodiversity Project
Regenerative Grazing Experiments at Kupona Farm
Oblique Aerial Surveys
Rangeland Baseline Survey
Arid Biocredit Pilot
Home
Kutuma
Kutuma Installation
Kutuma Usage
Kutuma on Azure
Lakehouse
Initial Setup
Github
Great Expectations
Data Ingestion
New Great Expectations Format
New Data Ingestion Process
Great Expectations (GX) Validation
ArcGIS Online Settings
Versioning
Data ingestion in staging
XPrize ML Classification
VS Code Setup
Docker Setup
Rancher-Desktop Setup
XPrize Machine Learning (ML) Classifiers
Overview of Docker `run` command
Transfering from SD Card to Kutuma through External Drive
Running Classifiers on External Drive
Troubleshooting
Object Detection
∞
Species Classification
Data Preparation
Data Aggregation
Data Download
COCO Annotation
JSONL Conversion
Datastore
Training
Inference
Nuclio
Standard Operating Procedures
Rangelands passive acoustic monitoring of biodiversity
Below ground AudioMoth testing
Bird point counts
LLBN carbon-biodiversity project
Rangelands camera-trapping of medium and large mammals
Rangelands invertebrate pitfall trap survey
Arid lands passive acoustic monitoring of biodiversity
Arid lands camera-trapping of medium and large mammals
Templates
Template README
Design Document – Template
Standard Operating Procedure Template
Study Area Descriptions
uKweli Impact Portal
Kubernetes
CI/CD
Access and Permissions Documentation for AML Workspace
BirdNet Custom Training Pipeline Architecture
BirdNet Custom Training Pipeline Setup Instructions
BirdNet Pipeline Architecture
BirdNet Pipeline Post-Processing and Data Transfer (Segmentation Step)
BirdNet Pipeline Setup Instructions
BirdNet Pipeline on Azure Machine Learning (AML)
Commands for Verifying AML Workspace Permissions
Dependencies for AML Workspace Role Assignments
Developer Guidelines for BirdNet Custom Training Pipeline
Developer Guidelines for BirdNet Pipeline
Developer Guidelines for MegaDetector Pipeline
Group Structure for AML Workspace Access
Machine Learning Infrastructure Terraform Configuration
MegaDetector Pipeline Architecture
MegaDetector Pipeline Post-Processing and Data Transfer (Phases 2 & 3)
MegaDetector Pipeline Setup Instructions
MegaDetector Pipeline on Azure Machine Learning (AML)
Post-Processing and Data Transfer Documentation
Purpose
Role Assignments for AML Workspace Access
Training a BirdNet Object Classifier on Azure Machine Learning (AML)
Troubleshooting BirdNet Pipeline
Troubleshooting MegaDetector Pipeline
Using the BirdNet Custom Training Pipeline on AML
Using the BirdNet Pipeline on AML
Using the MegaDetector Pipeline on AML
Natural Impact Portal
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Table of contents
Kubernetes
CI/CD