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MTA Transit Oriented Development (TOD) Data

MTA · *** DISCLAIMER - This web page is a public resource of general information.

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MTA Transit Oriented Development (TOD) Data

*** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. *** This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. ** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.

번역은 이해를 돕기 위한 미검수 초벌 또는 구조화 안내입니다. 계약·의료·법률 판단에는 원문을 확인하세요.
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카탈로그 수집2026. 7. 28.출처 연결됨

아직 수집하지 않음실측 품질 · 가격 · 인증 · 지역 · 공식 여부 · 수명주기무엇을 확인하고 무엇을 남겨 두는지

SELECTION SUMMARY

도입 판단 요약

*** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. *** This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. ** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.

이 제품의 적합 용도와 제한 조건은 아직 검수하지 않았습니다. 태그와 카테고리는 찾아가는 길이지 적합성 보증이 아닙니다.

EVIDENCED ADVANTAGES

API 특·장점

공급자·카탈로그·실측·편집 근거가 있는 신호만 표시하며, 근거 유형을 함께 밝힙니다.

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재배포 정책과 기본 식별 조건을 통과해 검색할 수 있지만 편집 승인은 아직 완료되지 않았습니다.

평가 2026. 07. 28. 13:05

같은 목적의 대체 API

같은 카테고리에서 공개 상태와 품질 근거를 우선해 표시합니다.

MDOT Performance Dashboard - Monthly DataMaryland Department of Transportation

Contains monthly commercial passenger data at BWI Thurgood Marshall Airport.

전남광주통합특별시 곡성군_도로안전표지 정보 데이터 조회 서비스전남광주통합특별시 곡성군

도로안전표지일련번호, 도로종류, 도로노선번호, 도로노선명 등의 도로안전표지 데이터 정보를 제공하는 전라남도 곡성군 도로안전표지 정보 데이터 조회 서비스

Ambito - API OGC StradarioComune di Marzabotto

Archivio banca dati grafo stradale (OGC)

SINIESTRALIDAD VÍAL DEL MUNICIPIO DE CHÍAAlcaldía de Chita, Boyacá

Registro general de accidentalidad vial del municipio de Chía.

인천국제공항공사_여객편 운항현황(다국어)인천국제공항공사

인천국제공항에 운항하는 여객기 항공편의 당일 운항 현황에 대한 다국어 데이터로 조회시간, 출발지 공항(IATA ) 편명, 항공사(IATA)를 기준으로 항공기 운항 타입, 항공사 한글명, 편명, 예정시간, 변경시간, 출발지공항, 도착게이트 번호, 수하물수취대 번호, 도시코드, 코드쉐어, 마스터편명, 출구 번호, 현황 코드, 출발공항코드(IATA),터미널,소요시간,경유지 공항코드, 경유지공항이름 등을 제공합니다. 조회 당일에 대한 데이터를 제공합니다. 개발 계정 일 1000 트래픽, 운영 계정 신청 시 일 1000000트래픽을 제공합니다.

국토교통부_주의운전구간 정보국토교통부

고속도로 교통안전도우미는 운전자의 안전운전을 지원하기 위해 국토교통부가 제공하는 통합 교통안내 서비스입니다. 이 시스템은 고속도로에서 발생할 수 있는 사고, 공사, 돌발상황, 기상 악화, 차량 정체 등의 정보를 실시간으로 수집하고 분석하여 운전자에게 제공함으로써 사고 예방과 원활한 소통을 돕습니다. 또한 구간별 주의 운전 안내, 우회 경로 추천, 정체 해소 정보 등을 제공하며, 교통전광판, 내비게이션, 모바일 앱 등 다양한 채널을 통해 정보를 전달합니다. 교통안전도우미는 실시간성과 정확성을 기반으로 국민의 안전한 이동을 적극 지원하는 서비스입니다.