Semua tulisan dari kampar

Born in small village, Penyasawan, 13 km East of Bangkinang, Capital of Kampar Regency, or 47km West of Pekanbaru, Campital of Riau Province, Indonesia. He traveled 300 km away from his family to pursue his high school education in SMU 1Padang, the Capital City of West Sumatera Province, Indonesia. He then continue his tertiary education in Universitas Padjajaran (being accepted in Faculty of Medicine) but later next year he enrolled Computer Science in Universitas Indonesia, Depok, West Java. In 2008, He continue his study and pursuing Master of Information Systems from University of Wollongong, NSW, Australia. He is now a father of three lovely daughters and live in East Salo, Kampar, Riau. If you meet him, he can speak with you in English, Minang, Malay, Ocu, or Bahasa.

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Analyzing Pedestrian Accessibility Using QGIS and OpenStreetMaps Data

tag TODO …

Ricky Maps

Current transportation planning practices are shifting toward a focus on accessibility – the ease in which a person can reach destinations given the available transportation network – for all modes of transportation including walking, bicycling, and using public transit. This article will explain different methods of measuring accessibility and how to adapt those methods for pedestrian travel. Much previous work on the subject suggests that you need to buy expensive data and software packages like ArcGIS Network Analyst Extension, but free open-source options can provide a suitable alternative. The article will conclude with a walkthrough of using QGIS with data from OpenStreetMaps (OSM) to calculate pedestrian accessibility, using the example of accessibility to restaurants for buildings in the Capitol Complex of St. Paul, Minnesota where I currently work.

Background

What is accessibility?

“Transportation researchers generally refer to accessibility as a measurement of the spatial distribution of activities about a point…

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Masjid Gg. Manunggal Perbatasan Pekanbaru melenceng jauh #kiblat nya

#Masjid ini (saya lupa namanya), saya sering sholat di sini, karena ada di perbatasan Pekanbaru-Kampar. Sayangnya kiblatnya melenceng cukup jauh. Posisi ada di Zona Militer 47NQA6225050712, atau kalau menggunakan koordinat DD adalah Latitude: 0.4584538280225544, sedangkan Longitude nya: 101.3562399945501 ; Garis merupakan arah kiblat seharusnya. Gambar diambil dari GEP, tanggal citra satelit mata-mata DigitalGlobe 29 Mei 2017.

Kiblat Masjid di Riau yang masih banyak melenceng [Eps: Masjid Bat Inf 312]

Yang paling parah ternyata ada di Batalion Infanteri 312, padahal masjidnya ramai dikunjungi musafir lintas PKU-PDG. Terlihat di Google Earth masjid selama ini malah mengarah jauh ke Afrika Selatan, bukannya ke Kaabah, Makkah, KSA. Ada yang tahu pengurus masjidnya? Kasihan selama ini masjid popular ini malah salah kiblat. Garis adalah kiblat seharusnya, sedangkan arah sholat selama ini menghadap jauh ke selatan (Barat Daya).

Posisi Masjid ada di Koordinat Militer 47N QA 2179 03 5956 (terlihat pada gambar di bawah. Gambar adalah citra satelit mata-mata DG tertanggal 9 April 2015

2018-04-25_16-42-20

Latitude: 0.325328°, Longitude: 100.993200°

Elevation Google Earth sepertinya sedang error, bukan 0m dari rerata-permukaan-laut, tapi sekitar 52meter dari MSL (sumber: SRTM)

Tactical Pilotage Charts

barangkali ada yang ingin iseng convert beberapa peta TPC dari Univ Texas di Austin, jadiin ubin / tile, sehingga bisa menjadi basemap dari WebGIS (misalnya: leafletJS atau Google Maps API)? Saya bersedia mengajarkan caranya, tapi tolong serius kerjanya dan didokumentasikan … hehehehe … maksudnya biar yang lain juga bisa ngikutin …

btw, peta Meranti tahun 80’an ini sepertinya bagus juga … 

 

Making shaded relief from digital elevation models (DEMs) in QGIS: a British Columbia perspective

reblog-ed from Wandering Cartographer, sedikit tentang DEM, SRTM, EPSG, QGIS blending

The Wandering Cartographer

Who would not agree with Tom Patterson, creator of the fabulous shadedrelief.com website, when he said, “There is no more important component of a map than the shaded relief.”

But the topic of creating your own shaded relief from a DEM is rather complex, so I’ve made a few assumptions in this how-to. I’m assuming:

  • you know your way around QGIS (I am using QGIS 2.18 for this post)
  • you’re familiar with the idea of projections, and re-projecting raster data
  • you know that each projection/datum combination has an EPSG number, which is a convenient way to refer to it. For example
    • Lat/Long/WGS84 = 4326
    • UTM Zone 9N/WGS84 = 32609
    • BC Albers = 3005

If that’s the case, there are really only three things you need to know in order to made your own hillshades:  where to get the data, how to transform it, and what pitfalls to avoid.

Why…

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