Migrant settlements being exploited for work have been spotted with satellite imagery by researchers led by the University of Nottingham in partnership with the Greek government. The study was published in Production Operations Management.
The strawberry fields of Nea Manolada in southern Greece have been under human rights watch since May 2013, where local field guards shot and injured 30 Bangladeshi migrant workers. Court proceedings in 2017 found that the workers had been subjected to forced labor. Since then, the Greek authorities have ramped up their fight against labor exploitation.
As fighting labor exploitation involves time-intensive fieldwork, the researchers say that remote sensing using satellite technology for real-time data collection could help humanitarian missions find more swiftly find areas of exploitation and organize interventions.
For the study, the researchers did just this- they used remote sensing from satellites to identify areas of labor exploitation. Once identified by satellite imagery, settlements were then investigated by inspection teams on the ground, who collected information via questionnaires.
The researchers then used Multi-Criteria Decision Analysis (MCDA) to assess the information collected by the inspection team and rank each settlement in order of priority for intervention. The analysis also helped them allocate resources among the most vulnerable workers to improve their living conditions.
"We have demonstrated how remote sensing data enables the identification and location of informal settlements of workers in potential situations of labor exploitation over a large geographic area (140km2)," says Dr. Doreen Boyd, one of the paper's co-authors.
She continued to say that the approach could be replicated in other areas where labor exploitation might be happening. Future studies, she said, could investigate migration flows and assess risks among settlements of forcibly displaced people in conflict situations such as those in South Sudan or the Democratic Republic of Congo.
Sources: Production Operations Management, University of Nottingham, EurekAlert
