Analysis of Local and Remote Mappers’ Open Geographic Data Contribution to Oil Spill Disaster Response in Niger Delta Region, Nigeria Open mapping leverages on volunteer mappers mobilized and engaged from the public. volunteers most often are trained and coordinated virtually to carry out dedicated mapping task, irrespective of their geographic location, professional and academic background. In this study volunteer mappers engaged are categorized into two namely: the Local Volunteer Mappers (LVM) comprising of all the potential and actual mappers resident in Nigeria and the Remote Volunteer Mappers (RVM) comprising of all potential and actual mappers not resident in Nigeria. The study sampled 2 Local Government Areas (LGAs) of River State from the 4 vulnerable oil spill disaster LGAs of Ogoni land communities. Ogoni land is a major oil spill disaster vulnerable area of Nigeria, being the major host communities of crude oil exploitation in the Niger Region of Nigeria. Following the hazardous impact and damage of Ogoni land by oil Spill disaster over the years of oil exploitation in Niger Delta, UNEP assessed that the environmental restoration of Ogoni land would require coordinated efforts on the part of government agencies at all levels, industry operators and communities. UNEP also presented its recommendations as a major opportunity to bring new investment, employment opportunities and a culture of cooperation to Ogoni land in addition to driving improvements in the environmental and health situation on the ground. To effectively implement the UNEP recommendations for restoration of Ogoni land, there is a need for a geographic data that provides critical building footprint in the area, especially, to identify and access the vulnerable oil spill communities. Maps produced would be used by government agencies and other stakeholders working to implement UNEP report on Ogoni land restoration as well sustainable development. Consequently, the study engaged volunteer mappers to respond to sampled Oil spill communities viz-viz 3 LGAs in Rivers State, Niger Delta Region of Nigeria. To assess the level of participation of Local (mappers in Nigeria) and Remote Mappers (Not Resident in Nigeria), two mapping projects were created in HOT tasking manager for local and remote mappers respectively. For the purpose of campaigning for Volunteer Mappers the 2 project tasks were tagged ‘’ Mapathon Battle for Vulnerable Oil Spill Disaster Communities in Niger Delta’’ respectively. Project task 6358 was created exclusively for remote mappers outside Nigeria to map Tai LGA, while, project task 6359 was created exclusively local mappers resident Nigeria to map Gokana LGA in a Mapathon battle challenge. Project task 6358 had a total grided cells of 825 mapping tasks for online engagement of mappers while project task 6359 had an automated grided cells of 706 mapping tasks due to differences in the size of the area. The Mapathon unveiled the following research results. Engagement of remote mappers for project task 6358-Tai LGA shows that out of the 583 tasks completely mapped, only 13 were yet to be validated after 2 years of creating the project. This is as a result of archiving the project and diversion of attention to urgent tasks. The project recorded a total of about 16,416 edits comprising of 13,552 buildings and 858km of roads mapped in Tai LGA within the timeline of the study. Demographic characteristics of the contributors to project 6358 on the basis of HOT Tasking Manager users by experience and level shows that 50% were advance mappers and 100 % has more than 1 year mapping experience .The project engaged a total of 56 contribtors by mapping and validation. All mappers and validators by experience has used the tasking manager for more than 1 year while their mapping levels ranges between 40% for beginner mapper, 10 % for intermediate and 50 % for advanced mappers. The project timeline as illustrated by the graph shows that mapping and validation of the Tai LGA task commenced on the same date: 6th August,2019 at the rate of 12% mapping and 2 % validation. Mapping progressively ascended to 64% on the 4th day and got to its peak on the 9th day being 15th August with 99% of the entire task mapped. However, validation of the mapping task had a straight curve with the highest peak of validation being the 12th of September with 95% of the task being validated. By 8th January ,2020, being 6th months of the project,100% of the tasks were completely mapped while 13 of the 596 tasks were yet to be validated. The timeline statistics also shows that an average of 20mintes 46 seconds was the time spent per task to map a total of 583 tasks of 16,416 edits. Also, an average of 6minutes 16seconds was spent for validation per task leaving about 1hour 21minutes 29seconds to finish up the validation of 13 tasks left unvalidated due to a shift to other project tasks and less passion for the project under study. However, the analysis of local mappers engaged in HOT Project Task 6359 Gokana LGA also unveiled the following: The study shows that 706 (100%) of the tasks were completely mapped except for validation of 473(67%) tasks which requires further coordination of mappers. There is no record of bad imagery and tasks left unmapped. The project also recorded a total of about 2064 changesets for mapping a total of about 18,367 edits, comprising of 14,983 buildings and 521 km of roads. The project also recoded a total of 173 contributors comprising of 169 mappers and 8 validators. These mappers (100%) had more than 1year experience in online mapping with OpenStreetMap and are categorized into beginner mappers (72%), intermediate (6%) and advance mappers (21%). The entire project timeline by mapping and validation took a period of about 2years 4months(28months) from 6th August 2019 to 27th December ,2021 as at the time of writing this report. Conclusively, there is a lacuna worthy of research investigation in the mapping response level and capability of remote mappers from other countries and local mappers from Nigeria in crowdsourced rapid response mapping using OpenStreetMap.