海拔和距离马鞍的山脉数据库(作为梯度的代理)-地球科学堆栈交换江南电子竞技平台江南体育网页版 最近30个来自www.hoelymoley.com 2023 - 03 - 30 - t08:14:35z //www.hoelymoley.com/feeds/question/16294 https://creativecommons.org/licenses/by-sa/4.0/rdf //www.hoelymoley.com/q/16294 2 海拔和距离马鞍的山地数据库(作为梯度的代理) Damo Frankcom //www.hoelymoley.com/users/15251 2019 - 02年- 20 - t01:20:15z 2019 - 03 - 01 - t06:30:13z 我对做关于山脉的数据可视化项目很感兴趣。

我们有来自http://www.peaklist.org/ultras.html由Aaron Maizlish(我们试图联系谁,但不确定他的联系方式这些天?)

他正在管理的数据包含姓名,海拔,坐标和关键鞍。我们需要的关键数据是从海拔高度到关键鞍点或海平面的距离,以获得非常粗略的形状轮廓。

我不确定这样的数据是否存在,或者我们必须从一些地形数据库中获得它?有没有人能告诉我们如何获取这些数据,或者如何获取免费的地形数据,以便我们能够以某种方式匹配?< / p >

I've attached the below artwork that inspired this project - while we wouldn't necessarily look to get all the shape types here, it would be nice to have some different natural shapes.

The idea being somewhere in between pure Art & pure geography

Thanks, Damian.

enter image description here

//www.hoelymoley.com/questions/16294/-/16312#16312 1 由Camilo Rada回答海拔和距离马鞍的山区数据库(作为梯度的代理) 卡米洛·Rada //www.hoelymoley.com/users/11908 2019 - 02年- 22 - t21:35:00z 2019 - 02年- 22 - t21:35:00z 看起来对于你的应用程序来说,你想要的不仅仅是山的高度和关键的鞍,而是地形概况(就像图中所示的那样)。< / p >

To create such topographical profiles you can download a Digital Elevation Model of the area of interest and analyze it with specialized GIS software like QGis, Global Mapper or ArcGis. A recommended global digital elevation dataset is SRTM, but as it doesn't cover the polar areas should be combined with ArcticDEM, and REMA. Alternatively ASTER GDEM is a good one with global coverage or ALOS W3D.

If you don't want to download data and use specialized software. You might be able to get what you want from a online topographic profiling service like ArcGIS Profile geoprocessing service. This service allows you to draw a line anywhere in the world and get its topographic profile. For example, a profile I just made there of mount Aconcagua looks like this:

enter image description here

If you still want to calculate key saddles, you have to download the Digital Elevation Model and use even more specialized software, like winprom.

//www.hoelymoley.com/questions/16294/-/16361#16361 2 Damo Frankcom对海拔和距离马鞍的山区数据库的回答(作为梯度的代理) Damo Frankcom //www.hoelymoley.com/users/15251 2019 - 02 - 28 - t23:17:43z 2019 - 03 - 01 - t06:30:13z 在研究了一些选项和数据之后,我认为STRM是最好的选择。我找不到一个地方可以下载文件中的数据,我可以读入一些我熟悉的软件中DEM文件是二进制格式的,我努力把它准备成R,所以我开始用jpg把这些读成R中的光栅图像,我遇到了一些障碍,关于如何查询,把它带回纬度。

最后,我发现了R包:rgbif:全球'生物多样性'信息设施API接口有了这个包,你可以查询特定的lat &长而归高,以米为单位!另外,你还可以获得一些生物多样性的信息。它连接到geonames数据库其他有客户端连接到数据的软件可以找到here

#这里是POC的一些R代码:#install.packages("rgbif")库(rgbif) #你需要注册到你自己的Geonames帐户,你每小时可以免费获得1000次查询,每天最多30k用户<- Sys.getenv("GEONAMES_USER") #我以0.005间隔在峰值两侧取15个纬度点& lt; - c (-17.3991666666667, -17.4041666666667, -17.4091666666667, -17.4141666666667, -17.4191666666667, -17.4241666666667, -17.4291666666667, -17.4341666666667, -17.4391666666667, -17.4441666666667, -17.4491666666667, -17.4541666666667, -17.4591666666667, -17.4641666666667, -17.4691666666667, -17.3941666666667, -17.3891666666667, -17.3841666666667, -17.3791666666667, -17.3741666666667, -17.3691666666667, -17.3641666666667, -17.3591666666667, -17.3541666666667, -17.3491666666667, -17.3441666666667, -17.3391666666667, -17.3341666666667, -17.3291666666667)经度& lt; - c (145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333, 145.818333333333)#Use the elevation function to return the elevations Bartle <- elevation(latitude=Latitude, longitude=Longitude, username = user) #Order my co-ordinates for the plot Bartle <- Bartle[order(Bartle$latitude),] plot(x=Bartle$latitude, y=Bartle$elevation_geonames, main = "BARTLE FRERE, SOUTH PEAK") lines(x=Bartle$latitude, y=Bartle$elevation_geonames) polygon(cbind(c(min(Bartle$latitude), Bartle$latitude, max(Bartle$latitude)), c(min(Bartle$elevation_geonames), Bartle$elevation_geonames, min(Bartle$elevation_geonames))), col="#00CC66") 

Bartel Frere Example

So I hope to work on this over the next couple of weeks and hope to update further - but here is the start just localised to Australia

Example of basic Tableau Viz

Thanks Again Camilo!

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