Outerview/global-trash-and-debris-index

--- license: cc-by-4.0 pretty_name: Outerview Global Trash & Debris Dataset task_categories: - image-classification - object-detection task_ids: - multi-class-image-classification tags: - computer-vision - image-classification - geospatial - mapping - earth-observation - urban-analytics - environment - sustainability - waste - trash - debris - litter - street-view - open-data annotations_creators: - Paul Wynter source_datasets: - original language: - en size_categories: - 10K<n<100K --- # Outerview Global Trash & Debris Dataset A large-scale geospatial dataset of trash, litter, and environmental debris with latitude and longitude. This dataset is part of Outerview’s mission to organize the world’s physical environment and make it searchable, measurable, and actionable. --- ## 🌍 Overview - **Feature:** Trash, litter, and debris - **Scope:** Global - **Entries:** 30,000 - **Total Dataset:** Millions of locations (full dataset) - **Formats:** Parquet / CSV / GeoJSON This dataset represents a **subset of a much larger global system** tracking visible environmental conditions across the planet. Each row corresponds to a real-world observation of waste or debris at a specific location. --- ## 🌎 Why This Dataset Exists Understanding **where trash is accumulating — and where it is improving — is critical** for cities, researchers, and communities. This dataset is designed to help build a **global snapshot of environmental cleanliness over time**, enabling: - Detection of waste accumulation hotspots - Measurement of cleanup progress - Monitoring of environmental change at street level - Better decision-making for urban and environmental planning Our goal is simple: **make the state of the physical world visible and trackable to everyone.** --- ## 📊 Dataset Schema | Column | Description | |--------------|------------| | id | Unique identifier | | latitude | Latitude coordinate | | longitude | Longitude coordinate | | region | Administrative region | | source | Data source | --- ## 🧠 Data Sources & Labeling - **Imagery Source:** Mapillary - **Label Generation:** Outerview AI models All detections were generated using Outerview’s computer vision systems trained on large-scale real-world imagery. --- ## 🧪 Example Use Cases - Train models for trash and debris detection - Build environmental monitoring systems - Identify illegal dumping or waste accumulation zones - Support sustainability and cleanup initiatives - Enhance geospatial search and world modeling systems --- ## 🚀 About Outerview Outerview is a research lab focused on building world models that help understand and index the physical world. Our system is trained on billions of images, videos, and location data, enabling anyone to search and analyze real-world conditions globally. --- ## 🔗 API & Full Dataset Access This is a sample dataset. The full platform provides: - Millions of additional locations - **Temporal data (track changes over time)** - Access to **billions of real-world images and video streams** - Real-time querying of environmental conditions Access the full dataset and API: 👉 https://outerview.ai View API documentation: 👉 https://outerview.ai/developers/docs --- ## 🔄 Updates This dataset is actively maintained and updated **biweekly** with new observations and improvements. --- ## 💬 Feedback We welcome feedback from researchers, developers, and communities. If there are additional environmental features you'd like to see (e.g. recycling, illegal dumping, pollution indicators), let us know. --- ## 📜 License This dataset is released under the **CC-BY-4.0 license**. Free for research and commercial use with attribution. --- ## ⚠️ Notes - This dataset is a sampled subset of a larger global system - The full dataset includes additional metadata such as timestamps - Coverage and density may vary by region - Detection accuracy may vary depending on environmental conditions ------ 许可证：CC-BY-4.0 数据集名称：Outerview全球垃圾与碎屑数据集 任务类别： - 图像分类 - 目标检测 任务子项： - 多类别图像分类 标签： - 计算机视觉 - 图像分类 - 地理空间 - 测绘 - 地球观测 - 城市分析 - 环境 - 可持续性 - 废弃物 - 垃圾 - 碎屑 - 杂物 - 街景 - 开放数据 标注创建者： - 保罗·温特（Paul Wynter） 源数据集： - 原创数据集 语言： - 英语 样本量范围： - 1万 < 样本量 < 10万 --- # Outerview全球垃圾与碎屑数据集 这是一个包含经纬度坐标的大规模地理空间垃圾、杂物与环境碎屑数据集。 本数据集隶属于Outerview的使命：整理全球实体环境，使其具备可检索、可量化与可行动性。 ## 🌍 概览 - **核心特征**：垃圾、杂物与碎屑 - **覆盖范围**：全球 - **子集条目数**：30000条 - **完整数据集**：包含数百万个观测点位（完整版） - **数据格式**：Parquet / CSV / GeoJSON格式 本数据集是一个更大规模全球系统的子集，该系统用于追踪全球范围内可见的环境状况。 每一行数据对应特定地理位置的真实废弃物或碎屑观测记录。 ## 🌎 数据集研发初衷 明晰**垃圾积聚点与环境改善区域**，对城市、研究人员与社区而言至关重要。 本数据集旨在构建**全球环境清洁度随时间变化的全景图景**，可支持： - 垃圾积聚热点区域检测 - 清理工作进展量化 - 街面级环境变化监测 - 为城市与环境规划提供更科学的决策依据 我们的目标十分明确： **让全球实体环境的状态可被所有人看见并追踪。** ## 📊 数据集架构 | 列名 | 说明 | |--------------|------------| | id | 唯一标识符 | | latitude | 纬度坐标 | | longitude | 经度坐标 | | region | 行政区域 | | source | 数据来源 | ## 🧠 数据来源与标注流程 - **影像来源**：Mapillary（马皮拉里） - **标签生成**：Outerview人工智能模型 所有检测结果均由Outerview的计算机视觉系统生成，该系统基于大规模真实世界影像训练得到。 ## 🧪 典型应用场景 - 训练垃圾与碎屑检测模型 - 构建环境监测系统 - 识别非法倾倒或垃圾积聚区域 - 支持可持续发展与清理行动 - 优化地理空间搜索与全球建模系统 ## 🚀 关于Outerview Outerview是一家专注于构建全球实体环境理解与索引模型的研究实验室。 我们的系统基于数十亿张图像、视频与位置数据训练而成，可支持任何人在全球范围内检索与分析真实世界的环境状况。 ## 🔗 API与完整数据集访问 本数据集为样本子集。 完整平台提供： - 数百万个额外观测点位 - **时序数据（支持随时间追踪变化）** - 数十亿张真实世界图像与视频流访问权限 - 环境状况的实时查询功能 访问完整数据集与API： 👉 https://outerview.ai 查看API文档： 👉 https://outerview.ai/developers/docs ## 🔄 更新机制 本数据集处于持续维护与更新状态，**每两周**会新增观测数据并进行功能优化。 ## 💬 反馈建议 我们欢迎研究人员、开发者与社区群体提出反馈。 若您希望新增其他环境特征（如可回收物、非法倾倒、污染指标等），请随时与我们联系。 ## 📜 许可证 本数据集采用**CC-BY-4.0许可证**发布。 可免费用于研究与商业用途，但需注明原作者。 ## ⚠️ 注意事项 - 本数据集为更大规模全球系统的抽样子集 - 完整数据集包含更多元数据，如时间戳信息 - 各区域的覆盖范围与数据密度可能存在差异 - 检测精度可能随环境条件变化而有所不同