# FPCD: An Open Aerial VHR Dataset for Farm Pond Change Detection

## TL;DR

This paper introduces a new open dataset for farm pond detection and change analysis from aerial imagery, enabling improved land use monitoring and policy assessment over a 14-year period.

## Contribution

It provides a novel annotated dataset for farm pond detection and change detection, along with benchmarking of multiple detection and segmentation methods.

## Key findings

- Benchmarking results for detection and segmentation methods.
- Analysis of farm pond changes over 14 years.
- Public availability of the dataset for research.

## Abstract

Change detection for aerial imagery involves locating and identifying changes associated with the areas of interest between co-registered bi-temporal or multi-temporal images of a geographical location. Farm ponds are man-made structures belonging to the category of minor irrigation structures used to collect surface run-off water for future irrigation purposes. Detection of farm ponds from aerial imagery and their evolution over time helps in land surveying to analyze the agricultural shifts, policy implementation, seasonal effects and climate changes. In this paper, we introduce a publicly available object detection and instance segmentation (OD/IS) dataset for localizing farm ponds from aerial imagery. We also collected and annotated the bi-temporal data over a time-span of 14 years across 17 villages, resulting in a binary change detection dataset called \textbf{F}arm \textbf{P}ond \textbf{C}hange \textbf{D}etection Dataset (\textbf{FPCD}). We have benchmarked and analyzed the performance of various object detection and instance segmentation methods on our OD/IS dataset and the change detection methods over the FPCD dataset. The datasets are publicly accessible at this page: \textit{\url{https://huggingface.co/datasets/ctundia/FPCD}}