{"id":980,"name":"rivamap","description":"An Automated River Analysis and Mapping Engine.","url":"https://github.com/isikdogan/rivamap","last_synced_at":"2026-04-18T20:02:21.428Z","repository":{"id":57462103,"uuid":"43770660","full_name":"isikdogan/rivamap","owner":"isikdogan","description":"an automated river analysis and mapping engine","archived":false,"fork":false,"pushed_at":"2024-10-17T15:13:42.000Z","size":89,"stargazers_count":81,"open_issues_count":4,"forks_count":34,"subscribers_count":14,"default_branch":"master","last_synced_at":"2026-02-12T18:50:41.858Z","etag":null,"topics":["automated-river-analysis","mapping","river","river-networks"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/isikdogan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2015-10-06T18:35:53.000Z","updated_at":"2025-12-10T05:31:56.000Z","dependencies_parsed_at":"2024-11-05T23:01:13.553Z","dependency_job_id":"e5c28d9c-ed28-4c78-8cb6-ec5d8200f301","html_url":"https://github.com/isikdogan/rivamap","commit_stats":{"total_commits":73,"total_committers":2,"mean_commits":36.5,"dds":0.1917808219178082,"last_synced_commit":"8cdd9e952a161ec5891ef2c0685d4d4382b6fd6b"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/isikdogan/rivamap","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/isikdogan","download_url":"https://codeload.github.com/isikdogan/rivamap/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/sbom","scorecard":{"id":495588,"data":{"date":"2025-08-11","repo":{"name":"github.com/isikdogan/rivamap","commit":"8cdd9e952a161ec5891ef2c0685d4d4382b6fd6b"},"scorecard":{"version":"v5.2.1-40-gf6ed084d","commit":"f6ed084d17c9236477efd66e5b258b9d4cc7b389"},"score":1.4,"checks":[{"name":"Dangerous-Workflow","score":-1,"reason":"no workflows found","details":null,"documentation":{"short":"Determines if the project's GitHub Action workflows avoid dangerous patterns.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#dangerous-workflow"}},{"name":"Maintained","score":0,"reason":"0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0","details":null,"documentation":{"short":"Determines if the project is \"actively maintained\".","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#maintained"}},{"name":"Token-Permissions","score":-1,"reason":"No tokens found","details":null,"documentation":{"short":"Determines if the project's workflows follow the principle of least privilege.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#token-permissions"}},{"name":"Binary-Artifacts","score":10,"reason":"no binaries found in the repo","details":null,"documentation":{"short":"Determines if the project has generated executable (binary) artifacts in the source repository.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#binary-artifacts"}},{"name":"Pinned-Dependencies","score":-1,"reason":"no dependencies found","details":null,"documentation":{"short":"Determines if the project has declared and pinned the dependencies of its build process.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#pinned-dependencies"}},{"name":"Packaging","score":-1,"reason":"packaging workflow not detected","details":["Warn: no GitHub/GitLab publishing workflow detected."],"documentation":{"short":"Determines if the project is published as a package that others can easily download, install, easily update, and uninstall.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#packaging"}},{"name":"Code-Review","score":1,"reason":"Found 2/14 approved changesets -- score normalized to 1","details":null,"documentation":{"short":"Determines if the project requires human code review before pull requests (aka merge requests) are merged.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#code-review"}},{"name":"CII-Best-Practices","score":0,"reason":"no effort to earn an OpenSSF best practices badge detected","details":null,"documentation":{"short":"Determines if the project has an OpenSSF (formerly CII) Best Practices Badge.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#cii-best-practices"}},{"name":"Security-Policy","score":0,"reason":"security policy file not detected","details":["Warn: no security policy file detected","Warn: no security file to analyze","Warn: no security file to analyze","Warn: no security file to analyze"],"documentation":{"short":"Determines if the project has published a security policy.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#security-policy"}},{"name":"Fuzzing","score":0,"reason":"project is not fuzzed","details":["Warn: no fuzzer integrations found"],"documentation":{"short":"Determines if the project uses fuzzing.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#fuzzing"}},{"name":"License","score":0,"reason":"license file not detected","details":["Warn: project does not have a license file"],"documentation":{"short":"Determines if the project has defined a license.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#license"}},{"name":"Signed-Releases","score":-1,"reason":"no releases found","details":null,"documentation":{"short":"Determines if the project cryptographically signs release artifacts.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#signed-releases"}},{"name":"Branch-Protection","score":0,"reason":"branch protection not enabled on development/release branches","details":["Warn: branch protection not enabled for branch 'master'"],"documentation":{"short":"Determines if the default and release branches are protected with GitHub's branch protection settings.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#branch-protection"}},{"name":"SAST","score":0,"reason":"SAST tool is not run on all commits -- score normalized to 0","details":["Warn: 0 commits out of 18 are checked with a SAST tool"],"documentation":{"short":"Determines if the project uses static code analysis.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#sast"}},{"name":"Vulnerabilities","score":0,"reason":"42 existing vulnerabilities detected","details":["Warn: Project is vulnerable to: PYSEC-2018-34 / GHSA-2fc2-6r4j-p65h","Warn: Project is vulnerable to: PYSEC-2021-856 / GHSA-5545-2q6w-2gh6","Warn: Project is vulnerable to: PYSEC-2019-108 / GHSA-9fq2-x9r6-wfmf","Warn: Project is vulnerable to: PYSEC-2018-33 / GHSA-cw6w-4rcx-xphc","Warn: Project is vulnerable to: PYSEC-2021-857 / GHSA-f7c7-j99h-c22f","Warn: Project is vulnerable to: GHSA-fpfv-jqm9-f5jm","Warn: Project is vulnerable to: PYSEC-2017-1 / GHSA-frgw-fgh6-9g52","Warn: Project is vulnerable to: GHSA-267x-w5hx-8hjr","Warn: Project is vulnerable to: GHSA-33h2-69j3-r336","Warn: Project is vulnerable to: GHSA-3448-vrgh-85xr","Warn: Project is vulnerable to: GHSA-5rpc-gwh9-q9fg","Warn: Project is vulnerable to: GHSA-634c-v2xv-ffpg","Warn: Project is vulnerable to: GHSA-6v6p-p97v-g2p7","Warn: Project is vulnerable to: GHSA-83rh-hx5x-q9p5","Warn: Project is vulnerable to: GHSA-8849-5h85-98qw","Warn: Project is vulnerable to: GHSA-89rj-5ggj-3p9p","Warn: Project is vulnerable to: GHSA-8w3x-457r-wg53","Warn: Project is vulnerable to: GHSA-9g8h-pjm4-q92p","Warn: Project is vulnerable to: GHSA-c7gp-2pch-qh2v","Warn: Project is vulnerable to: GHSA-cvhw-2593-5j2q","Warn: Project is vulnerable to: GHSA-fffj-9qwg-qmh5","Warn: Project is vulnerable to: GHSA-fm39-cw8h-3p63","Warn: Project is vulnerable to: GHSA-fr58-2xhv-qp3w","Warn: Project is vulnerable to: GHSA-fvq6-392h-6mjj","Warn: Project is vulnerable to: GHSA-fw99-f933-rgh8","Warn: Project is vulnerable to: GHSA-hxfw-jm98-v4mq","Warn: Project is vulnerable to: GHSA-jcxv-2j3h-mg59","Warn: Project is vulnerable to: GHSA-jggw-2q6g-c3m6","Warn: Project is vulnerable to: GHSA-m43c-649m-pm48","Warn: Project is vulnerable to: GHSA-m6vm-8g8v-xfjh","Warn: Project is vulnerable to: GHSA-pqjj-6f5q-gqph","Warn: Project is vulnerable to: GHSA-q799-q27x-vp7w","Warn: Project is vulnerable to: GHSA-qr4w-53vh-m672","Warn: Project is vulnerable to: GHSA-rqxg-xvcq-3v2f","Warn: Project is vulnerable to: GHSA-vc29-rj92-gc7j","Warn: Project is vulnerable to: GHSA-w96g-3p64-63wr","Warn: Project is vulnerable to: GHSA-wq8f-wvqp-xvvm","Warn: Project is vulnerable to: GHSA-x3rm-644h-67m8","Warn: Project is vulnerable to: PYSEC-2023-183","Warn: Project is vulnerable to: PYSEC-2019-156 / GHSA-xp76-357g-9wqq","Warn: Project is vulnerable to: PYSEC-2023-102","Warn: Project is vulnerable to: PYSEC-2023-114"],"documentation":{"short":"Determines if the project has open, known unfixed vulnerabilities.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#vulnerabilities"}}]},"last_synced_at":"2025-08-19T20:21:57.228Z","repository_id":57462103,"created_at":"2025-08-19T20:21:57.229Z","updated_at":"2025-08-19T20:21:57.229Z"},"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29656589,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-20T09:27:29.698Z","status":"ssl_error","status_checked_at":"2026-02-20T09:26:12.373Z","response_time":59,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"owner":{"login":"isikdogan","name":"Leo Isikdogan","uuid":"11168605","kind":"user","description":"","email":"","website":"http://www.isikdogan.com","location":"Cupertino, CA","twitter":null,"company":null,"icon_url":"https://avatars.githubusercontent.com/u/11168605?u=a0970eb5f81375b4ae4ddabff24a1e8689deecc9\u0026v=4","repositories_count":9,"last_synced_at":"2024-06-11T15:38:47.285Z","metadata":{"has_sponsors_listing":false},"html_url":"https://github.com/isikdogan","funding_links":[],"total_stars":297,"followers":216,"following":2,"created_at":"2022-11-11T13:46:26.693Z","updated_at":"2024-06-11T15:38:49.181Z","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/isikdogan","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/isikdogan/repositories"},"packages":[{"id":2904212,"name":"rivamap","ecosystem":"pypi","description":"An automated river analysis and mapping engine.","homepage":"https://github.com/isikdogan/rivamap","licenses":null,"normalized_licenses":[],"repository_url":"https://github.com/isikdogan/rivamap","keywords_array":["remote sensing","landsat","satellite","river"],"namespace":null,"versions_count":2,"first_release_published_at":"2016-05-06T06:32:29.000Z","latest_release_published_at":"2023-08-20T12:34:35.491Z","latest_release_number":"1.1","last_synced_at":"2026-03-06T23:01:20.272Z","created_at":"2022-04-10T12:29:08.869Z","updated_at":"2026-03-06T23:01:20.272Z","registry_url":"https://pypi.org/project/rivamap/","install_command":"pip install rivamap --index-url https://pypi.org/simple","documentation_url":"https://rivamap.readthedocs.io/","metadata":{"funding":null,"documentation":null,"classifiers":["Development Status :: 4 - Beta","Programming Language :: Python :: 2.7","Topic :: Utilities"],"normalized_name":"rivamap","project_status":null},"repo_metadata":{"id":57462103,"uuid":"43770660","full_name":"isikdogan/rivamap","owner":"isikdogan","description":"an automated river analysis and mapping engine","archived":false,"fork":false,"pushed_at":"2024-10-17T15:13:42.000Z","size":89,"stargazers_count":71,"open_issues_count":3,"forks_count":33,"subscribers_count":14,"default_branch":"master","last_synced_at":"2024-10-29T20:33:27.361Z","etag":null,"topics":["automated-river-analysis","mapping","river","river-networks"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/isikdogan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-10-06T18:35:53.000Z","updated_at":"2024-10-17T15:13:59.000Z","dependencies_parsed_at":"2022-09-10T03:12:21.299Z","dependency_job_id":null,"html_url":"https://github.com/isikdogan/rivamap","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/isikdogan","download_url":"https://codeload.github.com/isikdogan/rivamap/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":222129293,"owners_count":16936292,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"},"owner_record":{"login":"isikdogan","name":"Leo Isikdogan","uuid":"11168605","kind":"user","description":"","email":"","website":"http://www.isikdogan.com","location":"Cupertino, CA","twitter":null,"company":null,"icon_url":"https://avatars.githubusercontent.com/u/11168605?u=a0970eb5f81375b4ae4ddabff24a1e8689deecc9\u0026v=4","repositories_count":9,"last_synced_at":"2024-06-11T15:38:47.285Z","metadata":{"has_sponsors_listing":false},"html_url":"https://github.com/isikdogan","funding_links":[],"total_stars":297,"followers":216,"following":2,"created_at":"2022-11-11T13:46:26.693Z","updated_at":"2024-06-11T15:38:49.181Z","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/isikdogan","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/isikdogan/repositories"},"tags":[{"name":"1.0","sha":"ca1c0f41982e4843ec21f3602e6bb766aa9863b0","kind":"commit","published_at":"2016-05-06T05:34:10.000Z","download_url":"https://codeload.github.com/isikdogan/rivamap/tar.gz/1.0","html_url":"https://github.com/isikdogan/rivamap/releases/tag/1.0","dependencies_parsed_at":null,"dependency_job_id":null,"tag_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/tags/1.0","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/tags/1.0/manifests"}]},"repo_metadata_updated_at":"2024-10-29T23:00:00.731Z","dependent_packages_count":0,"downloads":7,"downloads_period":"last-month","dependent_repos_count":4,"rankings":{"downloads":65.10574704020816,"dependent_repos_count":7.6846269967341865,"dependent_packages_count":7.373338280337238,"stargazers_count":8.458361371318967,"forks_count":6.997907536815508,"docker_downloads_count":null,"average":19.12399624508281},"purl":"pkg:pypi/rivamap","advisories":[],"docker_usage_url":"https://docker.ecosyste.ms/usage/pypi/rivamap","docker_dependents_count":null,"docker_downloads_count":null,"usage_url":"https://repos.ecosyste.ms/usage/pypi/rivamap","dependent_repositories_url":"https://repos.ecosyste.ms/api/v1/usage/pypi/rivamap/dependencies","status":null,"funding_links":[],"critical":null,"issue_metadata":{"last_synced_at":"2024-10-29T19:31:25.768Z","issues_count":8,"pull_requests_count":2,"avg_time_to_close_issue":7755865.8,"avg_time_to_close_pull_request":5382.5,"issues_closed_count":5,"pull_requests_closed_count":2,"pull_request_authors_count":1,"issue_authors_count":7,"avg_comments_per_issue":2.0,"avg_comments_per_pull_request":0.5,"merged_pull_requests_count":2,"bot_issues_count":0,"bot_pull_requests_count":0,"past_year_issues_count":1,"past_year_pull_requests_count":0,"past_year_avg_time_to_close_issue":null,"past_year_avg_time_to_close_pull_request":null,"past_year_issues_closed_count":0,"past_year_pull_requests_closed_count":0,"past_year_pull_request_authors_count":0,"past_year_issue_authors_count":1,"past_year_avg_comments_per_issue":2.0,"past_year_avg_comments_per_pull_request":null,"past_year_bot_issues_count":0,"past_year_bot_pull_requests_count":0,"past_year_merged_pull_requests_count":0,"issues_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/issues","maintainers":[],"active_maintainers":[]},"versions_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/packages/rivamap/versions","version_numbers_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/packages/rivamap/version_numbers","dependent_packages_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/packages/rivamap/dependent_packages","related_packages_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/packages/rivamap/related_packages","codemeta_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/packages/rivamap/codemeta","maintainers":[{"uuid":"isikdogan","login":"isikdogan","name":null,"email":null,"url":null,"packages_count":1,"html_url":"https://pypi.org/user/isikdogan/","role":null,"created_at":"2023-02-25T08:52:58.078Z","updated_at":"2023-02-25T08:52:58.078Z","packages_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/maintainers/isikdogan/packages"}],"registry":{"name":"pypi.org","url":"https://pypi.org","ecosystem":"pypi","default":true,"packages_count":810945,"maintainers_count":343120,"namespaces_count":0,"keywords_count":0,"github":"pypi","metadata":{"funded_packages_count":52584},"icon_url":"https://github.com/pypi.png","created_at":"2022-04-04T15:19:23.364Z","updated_at":"2026-03-08T05:19:32.291Z","packages_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/packages","maintainers_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/maintainers","namespaces_url":"https://packages.ecosyste.ms/api/v1/registries/pypi.org/namespaces"}}],"commits":{"id":651569,"full_name":"isikdogan/rivamap","default_branch":"master","total_commits":73,"total_committers":2,"total_bot_commits":0,"total_bot_committers":0,"mean_commits":36.5,"dds":0.1917808219178082,"past_year_total_commits":0,"past_year_total_committers":0,"past_year_total_bot_commits":0,"past_year_total_bot_committers":0,"past_year_mean_commits":0.0,"past_year_dds":0.0,"last_synced_at":"2026-03-03T17:23:19.013Z","last_synced_commit":"8cdd9e952a161ec5891ef2c0685d4d4382b6fd6b","created_at":"2023-03-09T09:27:56.377Z","updated_at":"2026-03-03T17:23:18.989Z","committers":[{"name":"Leo Isikdogan","email":"leo@isikdogan.com","login":"isikdogan","count":59},{"name":"jay","email":"jayaram.hariharan@utexas.edu","login":"elbeejay","count":14}],"past_year_committers":[],"commits_url":"https://commits.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/commits","host":{"name":"GitHub","url":"https://github.com","kind":"github","last_synced_at":"2026-03-04T00:00:12.294Z","repositories_count":6184573,"commits_count":930632487,"contributors_count":36043938,"owners_count":1146406,"icon_url":"https://github.com/github.png","host_url":"https://commits.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://commits.ecosyste.ms/api/v1/hosts/GitHub/repositories"}},"issues_stats":{"full_name":"isikdogan/rivamap","html_url":"https://github.com/isikdogan/rivamap","last_synced_at":"2026-02-18T15:00:33.637Z","status":"error","issues_count":10,"pull_requests_count":2,"avg_time_to_close_issue":6463234.0,"avg_time_to_close_pull_request":5382.5,"issues_closed_count":6,"pull_requests_closed_count":2,"pull_request_authors_count":1,"issue_authors_count":9,"avg_comments_per_issue":1.6,"avg_comments_per_pull_request":0.5,"merged_pull_requests_count":2,"bot_issues_count":0,"bot_pull_requests_count":0,"past_year_issues_count":2,"past_year_pull_requests_count":0,"past_year_avg_time_to_close_issue":75.0,"past_year_avg_time_to_close_pull_request":null,"past_year_issues_closed_count":1,"past_year_pull_requests_closed_count":0,"past_year_pull_request_authors_count":0,"past_year_issue_authors_count":2,"past_year_avg_comments_per_issue":0.0,"past_year_avg_comments_per_pull_request":null,"past_year_bot_issues_count":0,"past_year_bot_pull_requests_count":0,"past_year_merged_pull_requests_count":0,"created_at":"2023-05-09T10:37:43.696Z","updated_at":"2026-02-18T15:00:33.637Z","repository_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap","issues_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub/repositories/isikdogan%2Frivamap/issues","issue_labels_count":{},"pull_request_labels_count":{},"issue_author_associations_count":{"NONE":9,"CONTRIBUTOR":1},"pull_request_author_associations_count":{"CONTRIBUTOR":2},"issue_authors":{"unaschneck":2,"shCampos":1,"mossydidar":1,"OmiDeLmI":1,"lan-ling":1,"elbeejay":1,"huangjingyuan7":1,"LabSR-UT":1,"GustavoWillyNagel":1},"pull_request_authors":{"elbeejay":2},"host":{"name":"GitHub","url":"https://github.com","kind":"github","last_synced_at":"2026-02-28T00:00:37.339Z","repositories_count":13507305,"issues_count":35053462,"pull_requests_count":114277403,"authors_count":11175628,"icon_url":"https://github.com/github.png","host_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub/repositories","owners_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub/owners","authors_url":"https://issues.ecosyste.ms/api/v1/hosts/GitHub/authors"},"past_year_issue_labels_count":{},"past_year_pull_request_labels_count":{},"past_year_issue_author_associations_count":{"NONE":2},"past_year_pull_request_author_associations_count":{},"past_year_issue_authors":{"LabSR-UT":1,"lan-ling":1},"past_year_pull_request_authors":{},"maintainers":[],"active_maintainers":[]},"events":{"total":{"ForkEvent":1,"IssuesEvent":3,"WatchEvent":7,"PushEvent":1},"last_year":{"ForkEvent":1,"IssuesEvent":3,"WatchEvent":5}},"keywords":["automated-river-analysis","mapping","river","river-networks"],"dependencies":[{"ecosystem":"pypi","filepath":"requirements.txt","sha":null,"kind":"manifest","created_at":"2022-09-10T03:12:20.878Z","updated_at":"2022-09-10T03:12:20.878Z","repository_link":"https://github.com/isikdogan/rivamap/blob/master/requirements.txt","dependencies":[{"id":4356691431,"package_name":"scipy","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356691435,"package_name":"numpy","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356691437,"package_name":"matplotlib","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356691439,"package_name":"pyshp","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356691441,"package_name":"opencv-python","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false}]},{"ecosystem":"pypi","filepath":"setup.py","sha":null,"kind":"manifest","created_at":"2022-09-10T03:12:21.184Z","updated_at":"2022-09-10T03:12:21.184Z","repository_link":"https://github.com/isikdogan/rivamap/blob/master/setup.py","dependencies":[{"id":4356694171,"package_name":"numpy","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356694172,"package_name":"scipy","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356694173,"package_name":"matplotlib","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false},{"id":4356694174,"package_name":"gdal","ecosystem":"pypi","requirements":"*","direct":true,"kind":"runtime","optional":false}]}],"score":7.620705086838262,"created_at":"2023-09-11T11:54:36.550Z","updated_at":"2026-04-18T20:02:21.435Z","avatar_url":"https://github.com/isikdogan.png","language":"Python","category":"Natural Resources","sub_category":"Water Supply and Quality","monthly_downloads":7,"total_dependent_repos":4,"total_dependent_packages":0,"readme":"# RivaMap: An Automated River Analysis and Mapping Engine\n[![Build Status](https://travis-ci.com/elbeejay/rivamap.svg?branch=master)](https://travis-ci.com/elbeejay/rivamap) [![Coverage Status](https://coveralls.io/repos/github/elbeejay/rivamap/badge.svg?branch=master)](https://coveralls.io/github/elbeejay/rivamap?branch=master)\n## Related papers\n* F. Isikdogan, A.C. Bovik, and P. Passalacqua, \"RivaMap: an automated river analysis and mapping engine,\" *Remote Sensing of Environment, Special Issue on Big Remotely Sensed Data*, 2017. [[**Read at ScienceDirect**]](http://www.sciencedirect.com/science/article/pii/S0034425717301475), [[**PDF**]](http://www.isikdogan.com/files/isikdogan2017_rivamap.pdf)\n* F. Isikdogan, A.C. Bovik, and P. Passalacqua, \"Automatic channel network extraction from remotely sensed images by singularity analysis,\" *IEEE Geoscience and Remote Sensing Letters*, 12, 11, 2218-2221, 2015. [[**Read at IEEExplore**]](http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7192616), [[**PDF**]](http://live.ece.utexas.edu/publications/2015/Isikdogan_GRSL_2015_Channel_Network_Extraction.pdf)\n\n## Dependencies and Installation\n**Dependencies:**\n* OpenCV 2.4\n* Python 3.x\n* Numpy\n* Scipy\n* Matplotlib\n* GDAL\n* pyshp\n\n**Installing from PyPI:**\n\n    $ sudo pip install rivamap\n\n**Installing from GitHub:**\n\n    $ git clone https://github.com/isikdogan/rivamap.git\n    $ sudo python setup.py install\n\n**Example Use:**\n\nSee [example.ipynb](./examples/example.ipynb)\n\n## Example Results\n\n\u003ca href=\"http://live.ece.utexas.edu/research/rivamap/img/keithsburg.png\"\u003e\u003cimg src=\"http://live.ece.utexas.edu/research/rivamap/img/keithsburg.png\" alt=\"Example Result\" height=\"250\"\u003e\u003c/a\u003e\n\u003ca href=\"http://live.ece.utexas.edu/research/rivamap/img/waxlake.png\"\u003e\u003cimg src=\"http://live.ece.utexas.edu/research/rivamap/img/waxlake.png\" alt=\"Example Result\" height=\"250\"\u003e\u003c/a\u003e\n\u003ca href=\"http://live.ece.utexas.edu/research/rivamap/img/mississippi.png\"\u003e\u003cimg src=\"http://live.ece.utexas.edu/research/rivamap/img/mississippi.png\" alt=\"Example Result\" height=\"250\"\u003e\u003c/a\u003e\n\u003ca href=\"http://live.ece.utexas.edu/research/rivamap/img/ganges.png\"\u003e\u003cimg src=\"http://live.ece.utexas.edu/research/rivamap/img/ganges.png\" alt=\"Example Result\" height=\"250\"\u003e\u003c/a\u003e\n\n## Reference\n\n\u003ctable\u003e\n    \u003ctbody\u003e\n        \u003ctr\u003e\n            \u003cth\u003e\n                \u003cp\u003e\n                    Function\n                \u003c/p\u003e\n            \u003c/th\u003e\n            \u003cth\u003e\n                \u003cp\u003e\n                    Description\n                \u003c/p\u003e\n            \u003c/th\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    preprocess.mndwi\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Computes the modified normalized difference water index.\n                \u003c/p\u003e\n                \u003cp\u003e\n                     Inputs:\n                    \u003cbr/\u003e\n                     green: green band (e.g. Landsat 8 band 3)\u003cbr/\u003e\n                     mir: middle infrared band (e.g. Landsat 8 band 6)\n                \u003c/p\u003e\n                \u003cp\u003e\n                     Returns:\n                    \u003cbr/\u003e\n                     mndwi: mndwi response\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    preprocess.contrastStretch\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Applies contrast stretch to an input image. Inputs and outputs an image.\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    preprocess.im2double\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Converts image datatype to float. Inputs and outputs an image.\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    preprocess.double2im\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Converts double data array to image. Inputs and outputs an image.\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    singularity_index.SingularityIndexFilters\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Creates the filters that are needed for computing the modified multiscale singularity index response. The filters can be used for processing many input images once the filters are created.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Keyword arguments:\u003cbr/\u003e\n                    minScale: minimum scale sigma (default 1.2 pixels)\u003cbr/\u003e\n                    nrScales: number of scales (default 15)\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    singularity_index.applyMMSI\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Applies the filters to a given input image to compute the modified multiscale singularity index response. Estimates the width and the dominant orientation angle for each spatial location.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    I1: input image (e.g. Landsat NIR band or MNDWI)\u003cbr/\u003e\n                    filters: an instance of SingularityIndexFilters class that contains precomputed filters\u003cbr/\u003e\n                    togglePolarity: changes polarity, use if the rivers are darker than land in the input image (i.e. SAR images)\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    psi: the singularity index response\u003cbr/\u003e\n                    widthMap: estimated width at each spatial location (x,y)\u003cbr/\u003e\n                    orient: local orientation at each spatial location (x,y)\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    delineate.extractCenterlines\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Uses the previously computed singularity index response (psi) and the dominant orientation (orient) to extract centerlines.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs: (can be obtained by running applyMMSI function)\u003cbr/\u003e\n                    psi: the singularity index response\u003cbr/\u003e\n                    orient: local orientation at each spatial location (x,y)\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    nms: Non-maxima suppressed singularity index response (centerlines)\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    delineate.thresholdCenterlines\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Uses a continuity-preserving hysteresis thresholding to classify centerlines.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    nms: Non-maxima suppressed singularity index response\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Keyword Arguments:\u003cbr/\u003e\n                    bimodal: true if the areas of rivers in the image are sufficiently large that the distribution of psi is bimodal\u003cbr/\u003e\n                    tLow: lower threshold (automatically set if bimodal=True)\u003cbr/\u003e\n                    tHigh: higher threshold (automatically set if bimodal=True)\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    centerlines: a binary matrix that indicates centerline locations\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    georef.loadGeoMetadata\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Reads metadata from a GeoTIFF file.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    filepath: the path to the file\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    gm: metadata\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    georef.saveAsGeoTiff\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Saves a raster image as a GeoTIFF file\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    gm: georeferencing metadata\u003cbr/\u003e\n                    I: raster image\u003cbr/\u003e\n                    filepath: save destination\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    georef.pix2lonlat\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Convers pixel coordinates into longitude and latitude.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    gm: georeferencing metadata\u003cbr/\u003e\n                    x, y: pixel coordinates\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    lon, lat: longitude and latitude\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    georef.lonlat2pix\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Convers longitude and latitude into pixel coordinates.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    gm: georeferencing metadata\u003cbr/\u003e\n                    lon, lat: longitude and latitude\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    x, y: pixel coordinates\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    georef.exportCSVfile\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Exports (coordinate, width) pairs to a comma separated text file.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    centerlines: a binary matrix that indicates centerline locations\u003cbr/\u003e\n                    widthMap: estimated width at each spatial location (x,y)\u003cbr/\u003e\n                    gm: georeferencing metadata filepath: the path to the file\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n\t\u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    georef.exportShapeFile [NEW]\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Exports line segments to a ShapeFile.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    centerlines: a binary matrix that indicates centerline locations\u003cbr/\u003e\n                    widthMap: estimated width at each spatial location (x,y)\u003cbr/\u003e\n                    gm: georeferencing metadata filepath: the path to the file\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    visualization.generateRasterMap\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Generates a raster map of channels. It draws a line of length w(x, y) and orientation \u0026theta;(x, y) at each spatial location.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    centerlines: a binary matrix that indicates centerline locations\u003cbr/\u003e\n                    orient: local orientation at each spatial location (x,y)\u003cbr/\u003e\n                    widthMap: estimated width at each spatial location (x,y)\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Keyword Arguments:\u003cbr/\u003e\n                    thickness: thickness of the lines (default 3)\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    raster: the raster map\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    visualization.generateVectorMap\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Generates a vector map of channels. It draws a line of length w(x, y) and orientation \u0026theta;(x, y) at each spatial location.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    centerlines: a binary matrix that indicates centerline locations\u003cbr/\u003e\n                    orient: local orientation at each spatial location (x,y)\u003cbr/\u003e\n                    widthMap: estimated width at each spatial location (x,y)\u003cbr/\u003e\n                    saveDest: output figure save destination\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Keyword Arguments:\u003cbr/\u003e\n                    thickness: thickness of the lines (default 0.2)\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    None (saves the figure at saveDest)\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    visualization.quiverPlot\n                \u003c/p\u003e\n            \u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\n                    Generates a quiver plot that shows channel orientation and singularity index response strength.\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Inputs:\u003cbr/\u003e\n                    psi: singularity index response\u003cbr/\u003e\n                    orient: local orientation at each spatial location (x,y)\u003cbr/\u003e\n                    saveDest: output figure save destination\n                \u003c/p\u003e\n                \u003cp\u003e\n                    Returns:\u003cbr/\u003e\n                    None (saves the figure at saveDest)\n                \u003c/p\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n    \u003c/tbody\u003e\n\u003c/table\u003e\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/980","html_url":"https://ost.ecosyste.ms/projects/980"}