{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mapping-access-to-water-and-sanitation-in","title":"Mapping Access to Water and Sanitation in Colombia using Publicly Accessible Satellite Imagery, Crowd-sourced Geospatial Information and RandomForests","arxiv_id":"2111.04134","date":"2021-11-07","proceeding":null,"authors":["Niccolo Dejito","Ren Avell Flores","Rodolfo de Guzman","Isabelle Tingzon","Liliana Carvajal","Alberto Aroca","Carlos Delgado"],"abstract":"Up-to-date, granular, and reliable quality of life data is crucial for humanitarian organizations to develop targeted interventions for vulnerable communities, especially in times of crisis. One such quality of life data is access to water, sanitation and hygeine (WASH). Traditionally, data collection is done through door-to-door surveys sampled over large areas. Unfortunately, the huge costs associated with collecting these data deter more frequent and large-coverage surveys. To address this challenge, we present a scalable and inexpensive end-to-end WASH estimation workflow using a combination of machine learning and census data, publicly available satellite images, and crowd-sourced geospatial information. We generate a map of WASH estimates at a granularity of 250m x 250m across the entire country of Colombia. The model was able to explain up to 65% of the variation in predicting access to water supply, sewage, and toilets. The code is made available with MIT License at https://github.com/thinkingmachines/geoai-immap-wash.","url_abs":"https://arxiv.org/abs/2111.04134v1","url_pdf":"https://arxiv.org/pdf/2111.04134v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"mapping-access-to-water-and-sanitation-in","repo_url":"https://github.com/thinkingmachines/geoai-immap-wash","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2111.04134","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.04134"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/thinkingmachines/geoai-immap-wash","reach":null}],"summary":{"ran_draft_wrong":2},"by_repo_kind":{"official":{"samples":2,"ran":2,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"081ab37dbbcd9611","entry":"calculate_metrics","repo":"thinkingmachines/geoai-immap-wash","repo_kind":"official","path":"utils/modelutils.py","file_url":"https://github.com/thinkingmachines/geoai-immap-wash/blob/HEAD/utils/modelutils.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"081ab37dbbcd9611"}},{"code_sha256_prefix":"3647ee1f828e432e","entry":"find_ind","repo":"thinkingmachines/geoai-immap-wash","repo_kind":"official","path":"utils/modelutils.py","file_url":"https://github.com/thinkingmachines/geoai-immap-wash/blob/HEAD/utils/modelutils.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3647ee1f828e432e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}