Minor Update: Semi-Automatic Classification Plugin v. 3.1.5

This post is about a minor update for the Semi-Automatic Classification Plugin for QGIS, version 3.1.5.



Following the changelog:
-fixed regression in Accuracy tab

GIS, Satellites, and Space: an Overview of Free Resources for Understanding Orbits and Distances

We are all enthusiast about the recent success of the Rosetta mission by ESA, which has reached the Comet 67P/Churyumov-Gerasimenko after a journey of ten years, travelling a distance of more than five times Earth’s distance from the Sun. This is the result of a huge work of astronomy, physics and engineering involving the trajectory of the Rosetta spacecraft and the orbit of the Comet 67P/Churyumov-Gerasimenko.

In my previous posts I have illustrated several applications about environmental monitoring though remote sensing, especially with satellite images. Thinking about satellites we can only imagine how far they are from the Earth surface. However, I have always been fascinated by their altitude, their orbit in the space, considering that the Earth itself is a satellite.
In this post I would like to share some interesting resources for understanding the size of our Solar System, in terms of orbit and distance from the Earth.

This blog is named From GIS to Remote Sensing, in fact between GIS (i.e. the information about the Earth) and Remote Sensing (i.e. the technology and science that allows for acquiring information remotely) there is really a long way. For instance several satellites such as Landsat are orbiting at about 705km altitude. Other satellites for the observations of meteorological phenomena have a geosynchronous orbit at about 36,000km altitude.
Satellite altitude is small if compared with Earth-Moon distance (i.e. about 363,100km). And Earth-Moon distance is very small if compared to Earth-Sun distance (i.e. about 150,000,000km). However, it is difficult to imagine such long distances.
An interesting perspective about these distances and orbits is provided in the following web applications and programs.

This is an online satellites viewer developed by NASA using the very interesting JavaScript library Cesium. This 3D GIS allows for viewing of the position of NASA satellites in real time.
The user can pan and zoom interactively, and select a specific satellite, showing information about position, altitude and velocity thereof. For instance, at this link you can see where is Landsat 8 right now, and the area of Earth surface that it is acquiring.


Minor Update: Semi-Automatic Classification Plugin v. 3.1.4

This post is about a minor update for the Semi-Automatic Classification Plugin for QGIS, version 3.1.4.


Following the changelog:
-fixed bug if using non-ASCII characters for ROI information
-fixed bug during signature calculation if ROI is smaller than pixel

Landsat Images: an Overview of Worldwide Data Access

Landsat is a family of satellites developed by NASA which provide since 1972 (launch of Landsat 1) remote sensing images with inestimable value for worldwide environmental monitoring (see this page).
With the launch of Landsat 8 in 2013, NASA assured the continuity of data acquisition for the next few years. Landsat 8 has the new sensor OLI (Operational Land Imager) which improves the quality of images and therefore allows for better land cover monitoring. A comparison of band designation for the Landsat satellites is described here.
At least 400 scenes are collected daily, placed into the USGS archive and made available at no charge; in the past 40 years of Landsat acquisition over 3 million images were collected in a huge archive of data, and millions of images were downloaded.

Over 20 Million Landsat Scenes Downloaded (from USGS http://landsat.usgs.gov/images/gallery/360_L.jpg)

Landsat images are delivered in several ways, and through several web sites. In fact, images are also collected by the USGS International Cooperator ground stations, which are the primary source of distributing data collected at their location (see http://landsat.usgs.gov/about_ground_stations.php)

This post is an overview about where Landsat images can be downloaded for free.

New release: Semi-Automatic OS v. 3.1.0

A new version of the Semi-Automatic OS has been released.

The Semi-Automatic OS v. 3.1.0 is a lightweight virtual machine based on Debian for the land cover classification of remote sensing images. It includes the Semi-Automatic Classification Plugin v. 3.1.2 and the brand new QGIS 2.6, already configured along with all the required dependencies (OGR, GDAL, Numpy, SciPy, and Matplotlib).


Welcome to QGIS 2.6

The new version of QGIS 2.6 'Brighton' has been released.
A big thank you to the QGIS developers for their effort in improving this great open source GIS software.
I am also happy to see that the Semi-Automatic Classification Plugin works well in QGIS 2.6.
The Semi-Automatic Classification Plugin in the new QGIS 2.6

Minor Update: Semi-Automatic Classification Plugin v. 3.1.3

This post is about a minor update for the Semi-Automatic Classification Plugin for QGIS, version 3.1.3.


Following the changelog:
-fixed bug when clipping raster in Windows

Newer posts Older posts