Mobiusi

Vehicle Occupancy on Green Spaces and Public Areas Detection Dataset

#object detection #image classification #urban traffic monitoring #parking management #environmental protection
  • 10000 records
  • 1.5G
  • JPG/PNG/JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-04-16

AI Analysis & Value Prop

In the current transportation industry, the acceleration of urbanization poses severe challenges to the management of public spaces and green areas, especially regarding vehicle occupancy issues. Existing solutions often rely on manual monitoring, which is inefficient and prone to errors, resulting in a failure to respond promptly to vehicle occupancy events. This dataset aims to assist researchers and developers in increasing the accuracy and efficiency of algorithms in object detection tasks by providing high-quality image data. The dataset consists of images showing vehicles occupying green spaces and public areas from various urban environments, captured with high-resolution cameras to ensure the clarity and usability of each image. In terms of quality control, multiple rounds of annotation and expert review mechanisms have been implemented to ensure consistency and accuracy in annotations. Data is stored in JPEG format, with a clear organizational structure to facilitate subsequent processing and analysis.

Dataset Insights

Sample Examples

1de28c25**.jpg|1080*1440|470.64 KB

b7ef8596**.jpg|1080*1440|475.84 KB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
vehicle_typestringThe type of vehicle present in the image, such as a sedan, SUV, truck, etc.
vehicle_countintThe number of vehicles detected in the image.
green_space_occupancybooleanIndicates whether the vehicles in the image are occupying green spaces.
public_space_occupancybooleanIndicates whether the vehicles in the image are occupying public spaces.
environment_typestringThe type of environment where the image is captured, such as urban, suburban, rural, etc.
daytime_nighttimestringThe time period when the image is taken, such as daytime or nighttime.
weather_conditionstringThe weather condition at the time the image was taken, such as sunny, cloudy, rainy, etc.
license_plate_visibilitybooleanIndicates whether the license plate on the vehicles in the image is visible.
obstruction_levelintThe level of obstruction to green or public spaces by vehicles in the image, ranging from 0 to 10.

Compliance Statement

Authorization TypeProprietary - Commercial AI Training License (No Redistribution)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What kind of traffic management research is this dataset suitable for?
This dataset is suitable for research on the phenomenon of vehicle violations occupying green spaces and public areas in urban environments, promoting the development of effective traffic management strategies and policies.
How can this dataset be used to improve environmental protection measures?
This dataset can be used to identify common patterns of violation behavior, and develop corresponding intervention measures to protect urban green spaces and public areas, thereby enhancing urban environmental quality.
How were the image data in the dataset collected?
The image data in the dataset are usually collected by installing cameras in different urban environments to record the actual occupation of green spaces and public areas by vehicles, ensuring the authenticity and diversity of the data.
What is the value of object detection datasets in the traffic sector?
Object detection datasets can assist in automatically identifying and monitoring vehicle violations, improving traffic regulation efficiency, and providing foundational data support for the development of intelligent transportation systems.
Why does vehicle occupation of green and public spaces impact traffic?
Vehicle occupation of green and public spaces can lead to reduced traffic flow, increased risk of traffic accidents, and disruption of urban planning order, affecting residents' living environments and travel convenience.

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Cite this Work

@dataset{Mobiusi2025,
  title={Vehicle Occupancy on Green Spaces and Public Areas Detection Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/0467111407d864ecfe3b92efa43269c8},
  urldate={2025-09-15},
  keywords={vehicle occupancy detection, green space management, public area monitoring, object detection datasets},
  version={1.0}
}

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