Digital Geography

GDEM V3 vs SRTM 1: a comparison

Some time has past since I last wrote a DEM comparison, comparing ALOS World with SRTM 1 and GDEM V2 with SRTM 3. But as NASA and METI released the lates version of the ASTER GDEM dataset, I will compare this once again for a certain area in central Mongolia. But this time, the competitor will be SRTM 1.

Copernicus, Sentinel and your favourite GIS

The Copernicus Program provides an interesting alternative data source for your work with Landsat data… Sentinel images: Copernicus will deliver an unprecedented volume of free data, provide new operational services and foster new business opportunities and job creation. The data itself is collected since 2014 (Sentinel 1A) and the operation is scheduled to deliver data till 2020 at least. But how to get the data into the GIS of your choice.

A Digital Earth: the Potential of Data Brokers

Introduction In my previous two posts I introduced the Cloud based data broker technology ERDDAP and demonstrated how one can use it to obtain geo-spatial scientific environmental data: Access sensor data on an buoy located in the Irish Sea . Get and display weather forecast data from the Global Forecast System (GFS). The use of data brokers to unify data catalogues is an approach taken by both the National Oceanic and Atmospheric Administration of the USA (ERDDAP) and the intergovernmental Group on Earth Observation (GEO Discovery and Access Broker). In this post I discuss the potential impact of this type…

Short Announcement: New Sentinel Cloudless Atlas

Mapbox created a cloudless Landsat map in 2013. That was a huge step for all the webmapping enthusiasts as we got a composit image of the world with stunning ground resolution and still cloudless! Now EOX, a company based in Vienna, provided a similar product called Sentinel Cloudless. And it is “for free”.

How to start with “VANE language” API – MODIS example

If you are reading this post – you might know something about satellite imagery. This is a valuable source to power quite a lot of analytics and monitoring applications. In this post I’d like to give you an idea of how all this Big Data stuff can be obtained and processed online, using the single API called #VANE language. What is VANE? The VANE geospatial platform, that’s coming out of the Beta now, is a new project we started at Openweathermap, relying on our expertise in providing well-designed APIs for weather data which is widely used by devs community. The…

Description code for article “Using the Google Earth Engine (GEE) for Detection of Burned Areas”

I want to continue my article “Using the Google Earth Engine (GEE) for Detection of Burned Areas” (link) and describe in detail script for detection burned areas. I decided to post here code of this script with comments, shchems and illustrations of wotk this scrip Link to script on Google Earth Engine This script shows two variants for detection burned area: Calculating spectral index NBR for before and after forest fire images, download on your computer and compare these scenes in software using function change detection. Calculating spectral index NBR for after forest fire images and select burned areas using threshold. My…

Using the Google Earth Engine (GEE) for Detection of Burned Areas

Google Earth Engine ( GEE ) is a cloud platform for processing satellite imageries. This service includes images of Landsat 5, 7,8, Sentinel 1 and Sentinel 2. You can process them directly on Google servers and don’t need download the images. This opportunity does processing of satellite imageries faster then on a limited desktop PC. However, you should have programming skills, because this is based on JavaScript code and the Google Earth Engine API.

ALOS World 3D V1.1 vs. SRTM1

Some days ago a new version of the ALOS 30m DEM was released: Void pixels due to clouds and snow pixels within 60 deg. of north and south latitudes in Version 1 were complemented by existing DEMs. Out of the areas are same with Version 1 product. As we already compared ALOS with SRTM-1(I saw the ALOS DEM as “the winner”) I am now interested in how this performs in a another setting. We are changing our focus from Mongolia to Germany and check how the new ALOS DEM works compared with SRTM 1.

JuxtaposeJS and the Death (and Re-Birth) of Bogoslof Island

This post is just a quick update on a unique event unfolding in my home state of Alaska and a cool new tool to help you post image sliders on the web.  First, let’s start with the event. The Eruption of Bogoslof Island Over the past few weeks, a volcano has been erupting in Alaska.  This by itself is not that unique, as we have lots of volcanoes and they tend to erupt pretty frequently.  You can check out the current activity for yourself at the Alaska Volcano Observatory.  This most recent eruption is a bit different though.  The island is…

Some ways to produce topographic swath profiles

For a geomorphological study that I am working on I want to produce topographic swath profiles across a mountain range, that is, I want the average elevation along a profile plus the min and max values within a certain distance of said profile. I have used three different methods to achieve that and found some nice resources that I’d like to share with you: GMT – Generic Mapping Tools GMT is a powerful suite of command-line small programs to manipulate all kinds of geographic data (Wessel and Smith, 1998; Wessel et al., 2013). A walk through on how to produce…

Observing deforestation with Sentinel-1

While preparing for an upcoming presentation at the annual meeting of the American Geophysical Union (AGU) I came across a topic that I thought might make an interesting blog post.  The presentation is about using data from the Sentinel-1 mission for Earth Science applications.  The Sentinel-1 spacecraft are C-band SAR systems launched and operated by the European Space Agency (ESA).  An innovative aspect of this mission is that the collection scenario devised by ESA is systematic and very broad in coverage.  Using Sentinel-1 we can monitor Earth using SAR data like never before.

QGIS 2.16 tutorial: georeferencing images

Since our last tutorial regarding georeferencing images in QGIS is 4 years old, let us have a second look at this task in the current times of QGIS 2.16. For this tutorial we will use a Soviet map of Crewe in England to see changes in city structure with a snapshot from 1957. We will use simple and quite easy affine transformations for this purpose.