Permukaan gesekan global ini mencantumkan kecepatan perjalanan berbasis darat untuk semua piksel darat antara 85 derajat utara dan 60 derajat selatan untuk tahun nominal 2019. Fitur ini juga mencakup kecepatan perjalanan "khusus jalan kaki", yang hanya menggunakan alat transportasi non-bermotor.
Peta ini dibuat melalui kolaborasi antara MAP (University of Oxford), Telethon Kids Institute (Perth, Australia), Google, dan University of Twente, Belanda.
Project ini dibangun berdasarkan pekerjaan sebelumnya yang dipublikasikan oleh Weiss et al 2018 (doi:10.1038/nature25181). Weiss et al (2018) menggunakan set data untuk jalan (yang terdiri dari penggunaan set data jalan Google dan Open Street Map skala global pertama), jalur kereta api, sungai, danau, lautan, kondisi topografi (kemiringan dan elevasi), jenis tutupan lahan, dan batas negara. Setiap set data ini dialokasikan kecepatan perjalanan dalam hal waktu untuk melintasi setiap piksel jenis tersebut. Kumpulan data tersebut kemudian digabungkan untuk menghasilkan "permukaan gesekan"; peta yang setiap pikselnya dialokasikan kecepatan perjalanan keseluruhan nominal berdasarkan jenis yang terjadi dalam piksel tersebut. Untuk project saat ini, permukaan gesekan yang diperbarui dibuat untuk menggabungkan peningkatan terbaru dalam data jalan OSM.
Perbedaan antara permukaan hambatan ini dan versi 2015 (Weiss et al. 2018) tidak selalu menunjukkan perubahan infrastruktur (misalnya, pembangunan jalan baru). Perbedaan tersebut cenderung terkait dengan peningkatan kualitas data, khususnya pembaruan yang dilakukan pada cakupan jalan OSM. Oleh karena itu, perbandingan antara permukaan gesekan dan peta waktu tempuh yang dihasilkan harus dilakukan dengan hati-hati dan umumnya tidak ditafsirkan sebagai perubahan akses dari waktu ke waktu.
Peta ini menunjukkan kecepatan perjalanan dari proses alokasi ini, yang dinyatakan dalam satuan menit yang diperlukan untuk menempuh satu meter. Set data ini membentuk set data pokok di balik peta aksesibilitas layanan kesehatan global yang dijelaskan dalam dokumen yang dirujuk.
Kredit set data sumber adalah seperti yang dijelaskan dalam makalah yang menyertainya.
Band
Ukuran Piksel 927,67 meter
Band
Nama
Unit
Min
Maks
Ukuran Piksel
Deskripsi
friction
menit/meter
0,000429
87,3075
meter
Kecepatan perjalanan darat.
friction_walking_only
menit/meter
0,012
87,3075
meter
Kecepatan perjalanan darat menggunakan transportasi non-bermotor.
D.J. Weiss, A. Nelson, C.A. Vargas-Ruiz, K. Gligorić, S. Bavadekar,
E. Gabrilovich, A. Bertozzi-Villa, J. Rozier, H.S. Gibson, T. Shekel,
C. Kamath, A. Lieber, K. Schulman, Y. Shao, V. Qarkaxhija, A.K. Nandi,
S.H. Keddie, S. Rumisha, E. Cameron, K.E. Battle, S. Bhatt, P.W. Gething.
Peta global waktu perjalanan menuju fasilitas layanan kesehatan. Nature Medicine (2020).
Permukaan gesekan global ini mencantumkan kecepatan perjalanan berbasis darat untuk semua piksel darat antara 85 derajat utara dan 60 derajat selatan untuk tahun nominal 2019. Fitur ini juga mencakup kecepatan perjalanan "khusus jalan kaki", yang hanya menggunakan alat transportasi non-bermotor. Peta ini dibuat melalui kolaborasi antara MAP (University of Oxford), Telethon …
[null,null,[],[[["\u003cp\u003eThis dataset provides a global friction surface, representing land-based travel speed for all land pixels between 85 degrees north and 60 degrees south for the year 2019.\u003c/p\u003e\n"],["\u003cp\u003eIt includes both overall travel speed and "walking-only" travel speed, using non-motorized means of transportation.\u003c/p\u003e\n"],["\u003cp\u003eThe friction surface was created by combining datasets for roads, railways, rivers, lakes, oceans, topographic conditions, landcover types, and national borders, assigning each a speed of travel.\u003c/p\u003e\n"],["\u003cp\u003eDeveloped through a collaboration between the Malaria Atlas Project (MAP), Telethon Kids Institute, Google, and the University of Twente.\u003c/p\u003e\n"],["\u003cp\u003eIt is important to note that differences between this friction surface and previous versions may be due to improved data quality rather than actual infrastructure changes.\u003c/p\u003e\n"]]],[],null,["# Global Friction Surface 2019\n\nDataset Availability\n: 2019-01-01T00:00:00Z--2020-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Malaria Atlas Project](https://malariaatlas.org/research-project/accessibility-to-cities/)\n\nTags\n:\n [accessibility](/earth-engine/datasets/tags/accessibility) [jrc](/earth-engine/datasets/tags/jrc) [map](/earth-engine/datasets/tags/map) [oxford](/earth-engine/datasets/tags/oxford) [population](/earth-engine/datasets/tags/population) [twente](/earth-engine/datasets/tags/twente) \nfriction \n\n#### Description\n\nThis global friction surface enumerates land-based travel speed for all land pixels between 85 degrees north and 60 degrees south for a nominal year 2019. It also includes \"walking-only\" travel speed, using non-motorized means of transportation only.\nThis map was produced through a collaboration between MAP (University of Oxford), Telethon Kids Institute (Perth, Australia), Google, and the University of Twente, Netherlands.\nThis project builds on previous work published by Weiss et al 2018 ([doi:10.1038/nature25181](https://doi.org/10.1038/nature25181)). Weiss et al (2018) utilised datasets for roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce a \"friction surface\"; a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel. For the current project, an updated friction surface was created to incorporate recent improvements within OSM roads data.\nDifferences between this friction surface and the 2015 version (Weiss et al. 2018) are not necessarily indicative of changes in infrastructure (e.g., new roads being built). Such discrepancies are far more likely to be associated with improved data quality, in particular updates made to OSM road coverage. As a result, comparisons between the friction surfaces and resulting travel time maps should be done cautiously and generally not interpreted as representing changes in access over time.\nThis map represents the travel speed from this allocation process, expressed in units of minutes required to travel one meter. It forms the underlying dataset behind the global healthcare accessibility map described in the referenced paper.\n\nSource dataset credits are as described in the accompanying paper.\n\n### Bands\n\n\n**Pixel Size**\n\n927.67 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|-------------------------|---------------|----------|---------|------------|--------------------------------------------------------|\n| `friction` | minutes/meter | 0.000429 | 87.3075 | meters | Land-based travel speed. |\n| `friction_walking_only` | minutes/meter | 0.012 | 87.3075 | meters | Land-based travel speed using non-motorized transport. |\n\n### Terms of Use\n\n**Terms of Use**\n\nThis work is licensed under a [Creative Commons Attribution\n4.0 International License](https://creativecommons.org/licenses/by/4.0/).\n\n### Citations\n\nCitations:\n\n- D.J. Weiss, A. Nelson, C.A. Vargas-Ruiz, K. Gligorić, S. Bavadekar,\n E. Gabrilovich, A. Bertozzi-Villa, J. Rozier, H.S. Gibson, T. Shekel,\n C. Kamath, A. Lieber, K. Schulman, Y. Shao, V. Qarkaxhija, A.K. Nandi,\n S.H. Keddie, S. Rumisha, E. Cameron, K.E. Battle, S. Bhatt, P.W. Gething.\n Global maps of travel time to healthcare facilities. Nature Medicine (2020).\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('Oxford/MAP/friction_surface_2019');\nvar landBasedTravelSpeed = dataset.select('friction');\nvar visParams = {\n min: 0.0022,\n max: 0.04,\n palette: [\n '313695', '4575b4', '74add1', 'abd9e9', 'e0f3f8', 'ffffbf', 'fee090',\n 'fdae61', 'f46d43', 'd73027', 'a50026'\n ],\n};\nMap.setCenter(43.55, 36.98, 4);\nMap.addLayer(landBasedTravelSpeed, visParams, 'Land-based travel speed');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/Oxford/Oxford_MAP_friction_surface_2019) \n[Global Friction Surface 2019](/earth-engine/datasets/catalog/Oxford_MAP_friction_surface_2019) \nThis global friction surface enumerates land-based travel speed for all land pixels between 85 degrees north and 60 degrees south for a nominal year 2019. It also includes \"walking-only\" travel speed, using non-motorized means of transportation only. This map was produced through a collaboration between MAP (University of Oxford), Telethon ... \nOxford/MAP/friction_surface_2019, accessibility,jrc,map,oxford,population,twente \n2019-01-01T00:00:00Z/2020-01-01T00:00:00Z \n-60 -180 85 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://malariaatlas.org/research-project/accessibility-to-cities/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/Oxford_MAP_friction_surface_2019)"]]
