# deepTerra -- AI Land Classification Made Easy

Source: [deepTerra -- AI Land Classification Made Easy](<https://www.sota2.com/research/paper/68fa76971e209131cea6dfb5>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T03:58:19.729Z

Authors: Andrew Keith Wilkinson

Published: 2025-01-14T05:55:20.000Z

## Abstract

deepTerra is a comprehensive platform designed to facilitate the classification of land surface features using machine learning and satellite imagery. The platform includes modules for data collection, image augmentation, training, testing, and prediction, streamlining the entire workflow for image classification tasks. This paper presents a detailed overview of the capabilities of deepTerra, shows how it has been applied to various research areas, and discusses the future directions it might take.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2501.07859>)

[PDF](<https://arxiv.org/pdf/2501.07859.pdf>)