Benthic Ecological Survey Data for Tanzania Mainland and Zanzibar

This dataset contains the results of the Benthic Ecological Survey (BES), a methodology refined by the Wildlife Conservation Society (WCS) during the USAID Heshimu Bahari project to map benthic substrates across the coastal waters of Tanzania, including Zanzibar. The survey was conducted as part of the Heshimu Bahari project, an initiative supported by USAID, to support the strengthening of climate resilience and productivity of reef fisheries, particularly through the creation of a network of Fishery Replenishment Zones (FRZs) along the Tanzanian coastline. Producing reliable maps of benthic substrates is identified as the crucial first step for this work. The BES methodology was developed by WCS to bridge a critical gap in data collection tools for benthic substrates, specifically targeting scales between approximately 10 km² and 100 km². This boat-based survey utilizes a photo-quadrat method, deploying a GoPro camera attached to a metal tripod to capture images of the benthos at predetermined, georeferenced sites without the need for divers. Images are subsequently analyzed using CoralNet, an online platform where experts label 25 random points per image into 21 substrate categories. The survey covered the entire Tanzanian coastline, including the islands of Zanzibar and Latham Island, for waters shallower than 50 meters. A regular grid of 1 km spacing was used for station selection, with 500m intervals for Latham Island. In total, the project surveyed 11,690 sites, collecting over 35,000 photoquadrats and covering an equivalent area of approximately 11,526 km² of coastline. The data is organized in several folders, analysis folder, containing the results in CSV and NetCDF format. The CSV format is in both summaries, with coordinates and data averaged over the 3 replicas per site, and full, with data for each replica. The NetCDF files are created using the data in summaries, mapped on the 500 m regular grid of the survey space for each label in the CoralNet label set. coralnet_medatadat folder, contains the annotation data for each sub-region and the corresponding metadata. For each sampled station we collected station ID, date, time, depth and GPS coordinates. These are linked to the labelled data from CoralNet to create the CSV files in the analysis folder.  A folder with the Python scripts we developed to process the data HB_WCS_BES_report.pdf, a technical report detailing the methodology and describing results from some preliminary analysis