构建800张航拍水体数据集，助力农业区智能水体分割研究。
AIWR: Aerial Image Water Resource Dataset for Segmentation Analysis
- 基于谷歌地图构建东北泰国产区航拍水体数据集
- 含专家标注真值，支持水体分割算法训练与评估
- 适用于遥感、计算机视觉及智慧农业研究者
在泰国东北部等农业地区，沙质土壤保水能力差，有效水资源管理至关重要。为此，本文构建了航拍水体资源（AIWR）数据集，包含800张聚焦自然与人工水体的航拍图像，数据源自Bing Maps，并遵循基本地理数据集（FGDS）标准。所有图像均经遥感专家验证标注，具备高质量真值标签，为地理信息科学、计算机视觉与人工智能领域提供宝贵资源。该数据集面临水体大小、颜色、形状差异大，且常与其它用地类型相似等挑战，旨在推动先进人工智能方法在水体分割中的应用，应对数据复杂性与样本量有限问题。本研究有助于开发新型水体分析算法，支持类似地区可持续农业实践。
原文摘要 · Abstract (English)
Effective water resource management is crucial in agricultural regions like northeastern Thailand, where limited water retention in sandy soils poses significant challenges. In response to this issue, the Aerial Image Water Resource (AIWR) dataset was developed, comprising 800 aerial images focused on natural and artificial water bodies in this region. The dataset was created using Bing Maps and follows the standards of the Fundamental Geographic Data Set (FGDS). It includes ground truth annotations validated by experts in remote sensing, making it an invaluable resource for researchers in geoinformatics, computer vision, and artificial intelligence. The AIWR dataset presents considerable challenges, such as segmentation due to variations in the size, color, shape, and similarity of water bodies, which often resemble other land use categories. The objective of the proposed dataset is to explore advanced AI-driven methods for water body segmentation, addressing the unique challenges posed by the dataset complexity and limited size. This dataset and related research contribute to the development of novel algorithms for water management, supporting sustainable agricultural practices in regions facing similar challenges.
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