Surveys dataset of Local Indicators of Climate Change Impacts in Mafia Island, Tanzania, United Republic of

DOI

Quantitative dataset of the Site 'Mafia Island' collected by Fasco Chengula in Tanzania, United Republic of. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 2st - quantitative part of a 2 part dataset. Quantitative data collection includes household-level surveys with up to 125 randomly selected households and individual-level surveys of up to 175 individuals chosen by convenience sampling. More information on the project at https://licci.eu

LICCI Data Collection application / https://gitlab.com/licci/opentek_fe, v0.6.18 (partner)

Identifier
DOI https://doi.org/10.34810/DATA1573
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/DATA1573
Provenance
Creator Chengula, Fasco Idfonce ORCID logo; Reyes-García, Victoria ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Contributor Reyes-García, Victoria; Fasco Chengula
Publication Year 2024
Funding Reference https://ror.org/00k4n6c32 771056
Rights Condiciones de uso personalizadas para el dataset; info:eu-repo/semantics/openAccess; https://dataverse.csuc.cat/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.34810/data1573
OpenAccess true
Contact Reyes-García, Victoria (Universitat Autònoma de Barcelona)
Representation
Resource Type Survey data; Dataset
Format text/tab-separated-values; text/csv; text/plain
Size 69080; 10898; 20987; 48427; 13647; 9376; 18628; 426529; 62782; 71328; 57984; 22590; 62259; 57218; 38565; 24891
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Earth and Environmental Science; Environmental Research; Geosciences; Life Sciences; Natural Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences
Spatial Coverage (39.664W, -7.916S, 39.664E, -7.916N)