Illegal Site Detection

## Overview

Illegal Site Detection is a dataset for object detection tasks - it contains Objects annotations for 250 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Garbage Dumping Detection

## Overview

Garbage Dumping Detection is a dataset for object detection tasks - it contains Illegal Garbage Dump annotations for 2,499 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Illegal Park

## Overview

Illegal Park is a dataset for object detection tasks - it contains Objects annotations for 2,267 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The illegal use of natural resources, manifested in activities like illegal logging, poaching, and illegal wildlife trade, poses a global threat to biodiversity. Addressing them will require an understanding of the magnitude of and factors influencing these activities. However, assessing such behaviors is challenging because of their illegal nature, making participants less willing to admit engaging in them. We compared how indirect (randomized response technique) and direct questioning techniques performed when assessing non-sensitive (fish consumption, used as negative control) and sensitive (illegal consumption of wild animals) behaviors across an urban gradient (small towns, large towns, and the large city of Manaus) in the Brazilian Amazon. We conducted 1,366 surveys of randomly selected households to assess the magnitude of consumption of meat from wild animals (i.e., wild meat) and its socioeconomic drivers, which included years the head of household lived in urban areas, age of the head of household, household size, presence of children, and poverty. The indirect method revealed higher rates of wildlife consumption in larger towns than did the direct method. Results for small towns were similar between the two methods. The indirect method also revealed socioeconomic factors influencing wild meat consumption that were not detected with direct methods. For instance, the indirect method showed that wild meat consumption increased with age of the head of household, and decreased with poverty and years the head of household lived in urban areas. Simultaneously, when responding to direct questioning, households with characteristics associated with higher wild meat consumption, as estimated from indirect questioning, tended to underreport consumption to a larger degree than households with lower wild meat consumption. Results for fish consumption, used as negative control, were similar for both methods. Our findings suggest that people edit their answers to varying degrees when responding to direct questioning, potentially biasing conclusions, and indirect methods can improve researchers’ ability to identify patterns of illegal activities when the sensitivity of such activities varies across spatial (e.g., urban gradient) or social (e.g., as a function of age) contexts. This work is broadly applicable to other geographical regions and disciplines that deal with sensitive human behaviors.

Illegal Plants (medical)

## Overview

Illegal Plants (medical) is a dataset for object detection tasks - it contains Plants annotations for 300 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset is extracted from the records of cosmetics advertisements filed by various county and city health bureaus. The displayed fields are limited to those open to the system, but the dataset may change due to subsequent revisions. This does not necessarily mean that the products of the subject of sanctions are illegal. Please use caution when referring to it.

These data were collected in Oakland, California, and Birmingham, Alabama, to examine the effectiveness of alternative drug enforcement strategies. A further objective was to compare the relative effectiveness of strategies drawn from professional- versus community-oriented models of policing. The professional model emphasizes police responsibility for crime control, whereas the community model stresses the importance of a police-citizen partnership in crime control. At each site, experimental treatments were applied to selected police beats. The Oakland Police Department implemented a high-visibility enforcement effort consisting of undercover buy-bust operations, aggressive patrols, and motor vehicle stops, while the Birmingham Police Department engaged in somewhat less visible buy-busts and sting operations. Both departments attempted a community-oriented approach involving door-to-door contacts with residents. In Oakland, four beats were studied: one beat used a special drug enforcement unit, another used a door-to-door community policing strategy, a third used a combination of these approaches, and the fourth beat served as a control group. In Birmingham, three beats were chosen: Drug enforcement was conducted by the narcotics unit in one beat, door-to-door policing, as in Oakland, was used in another beat, and a police substation was established in the third beat. To evaluate the effectiveness of these alternative strategies, data were collected from three sources. First, a panel survey was administered in two waves on a pre-test/post-test basis. The panel survey data addressed the ways in which citizens' perceptions of drug activity, crime problems, neighborhood safety, and police service were affected by the various policing strategies. Second, structured observations of police and citizen encounters were made in Oakland during the periods the treatments were in effect. Observers trained by the researchers recorded information regarding the roles and behaviors of police and citizens as well as police compliance with the experiment's procedures. And third, to assess the impact of the alternative strategies on crime rates, reported crime data were collected for time periods before and during the experimental treatment periods, both in the targeted beats and city-wide.

Data about homicide rate and the relationship with drug market and socioeconomic factors

Wald χ2 and statistical significance (P-values: * 0.05, ** 0.01, *** 0.001) of retained explanatory variables and the percentage of deviance explained (% dev) are only shown for the best-supported models, since all alternative models showed > 2 units of change in AICc. For simplicity, only candidate models with ΔAICc < 20 are shown. Explanatory variables are abbreviated as follows: THREAT (currently threatened), YEARS (number of years the capture of the species was legally allowed), NEST (accessibility of nests), and OVERLAP (overlap between the distribution of species and human populations in Mexico). Interactions between variables are denoted by “x”.GLM models obtained for explaining the number of Mexican parrots seized or legally exported in the past attending to their current conservation status and three other species-specific variables.

Records of reported illegal dumping activity, case descriptions with locations and dates of the incident. This dataset is updated daily.

The Illegal Dump Site dataset includes information on illegal dump sites, their type of trash, and the estimate tons of trash at each site. The information was provided by Allegheny Cleanways, and collected as part of a 2005 survey in Allegheny County.

Illegal Mining Sites

## Overview

Illegal Mining Sites is a dataset for object detection tasks - it contains Illegal_mining annotations for 1,674 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This represents a weekly extract from the Motorola CSR application of all open reports of illegal dumping.

Illegal dumping is any junk, garbage or debris is left on public property, including roadsides, open streets, and paved alleys. The items most commonly reported are TVs and computers, furniture, paints, solvents (and other potentially hazardous liquids), tires, garbage, yard waste, and construction debris.Data source: UTIL.ILLEGAL_DUMPING_OPEN_REPORTAttribute info: SR_Number Service Request Number The unique record number of the service requesttext

Created_Date Created Date The date the service request was created date

SR_Location Location Display Name The location of the service request (street address, intersection, or freeform text) text

Dataset (.csv) used for analysis. (CSV 4 kb)

1. Recovering and maintaining large carnivore populations is a global conservation challenge that requires better knowledge of the factors affecting their populations, particularly in shared landscapes (i.e., non-protected areas where people occupy and or utilize the land).
2. The Mexican wolf (Canis lupus baileyi) is an endangered wolf subspecies being recovered on shared landscapes in the Southwest United States and Mexico. We used data from the U.S. program to model population growth, evaluate the impact of management removal and illegal killing relative to other demographic factors, and test hypotheses about factors influencing rates of management removal and illegal killing.
3. From 1998–2019, the population growth averaged 12% per year. Rates of natural reproduction, illegal killing, and other mortality remained consistent over the 22 years; while releases, translocations, and management removals varied markedly between two time periods, phase 1: 1998–2007 and phase 2: 2008–2019.
4. The number of wolves removed for conflict management was higher during phase 1 (average ~13 per year, rate = 24.8%) than phase 2 (average of ~5 per year, rate = 5.2%). This decrease in management removal resulted in the wolf population resuming growth after a period of population stagnation. Two factors influenced this decrease, a change in policy regarding removal of wolves (stronger modeling support) and a decrease in the number of captive-reared adult wolves released into the wild (weaker modeling support).
5. Illegal mortality was relatively constant across both phases, but after the decrease in management removal, illegal mortality became the most important factor (relative importance shifted from 28.2% to 50.1%). Illegal mortality was positively correlated with rates of reintroduction and translocation of wolves and negatively correlated with the rate of management removal.
6. Synthesis and applications. Using management removal to reduce human-carnivore conflict can have negative population impacts if not used judiciously. Recovering and maintaining carnivore populations in shared landscapes may require greater tolerance of conflict and more emphasis on effective conflict prevention strategies and compensation programs for affected stakeholders.

This repository contains codes and data for Liang et al. Assessing the illegal hunting of native wildlife within China. This includes two analyses. First, the prefecture-level analysis for assessing the relationships between the ecological and socio-economic variables and the illegal hunting convictions (all verdicts, type 1 verdicts, type 2 verdicts, and total number of individual animals taken) of four vertebrate groups (amphibians, reptiles, birds, and mammals) in China. Second, the trait-based analyses (with phylogenetic logistic regression models) for predicting the probability that a species is known to be illegally hunted using the species' traits for the four vertebrate groups.

6,924 Images – Illegal Roadside Booth Data. The collection scenes include roadside, snack street, shop entrance, etc. The data diversity includes multiple scenes, different time periods(day, night), different photographic angles. This data can be used for tasks such as urban refined management.

All 311 Service Requests from 2010 to present. This information is automatically updated daily.

Dataset Card for Illegal Activities Toxic

  Description

The test set is designed for evaluating an insurance chatbot system specifically tailored for the insurance industry. The main focus of this test set is to assess the system's ability to handle compliance-related behaviors with utmost accuracy and efficiency. It includes a variety of toxic categories, specifically targeting topics related to illegal activities. By evaluating the chatbot's responses in these scenarios… See the full description on the dataset page: https://huggingface.co/datasets/rhesis/Insurance-Chatbot-Illegal-Activities-Toxic.

Analysis of ‘Local Law 8 of 2020 – Complaints of Illegal Parking of Vehicles Operated on Behalf of the City’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a5966b84-9c53-4848-9653-4ae8addad2ed on 13 February 2022.

--- Dataset description provided by original source is as follows ---

NOTE: This data does not present a full picture of 311 calls or service requests, in part because of operational and system complexities associated with remote call taking necessitated by the unprecedented volume 311 is handling during the Covid-19 crisis. The City is working to address this issue.
A row level daily report of illegal parking by City vehicle or permit 311 Service Requests starting from 1/30/20.

--- Original source retains full ownership of the source dataset ---