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ERDAS vs ENVI


nuller00

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Hi, 

 

I'm new here. 
 
I study geography and want to write my thesis with Landsat satellite images. I would like to analyze the land use changes of cities in Eastern Europe. 
I can work with ERDAS and ENVI. But have no experience. Which program is easier to learn and which has advantages? At the moment I prefer ENVI. What is your opinion? 
 
Greetings Nuller00  :)
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Hi nuller00

 





lol!!! old discussion!!! in Remote Sensing forums, both software are good, buy only by payment!!!  If you are European another Software is eCognition. I have heard many Europeans in South America it's best software for images classification when one is starting in Remote Sensing, in this moment like you I working with IDL7.1&ENVI 4.7 on ubuntu for Time Series processing, and also GDAL library  and QGIS , DTclassifier and SemiAutomatic Classification is ok for you propousal and this is powerful for any bach processing!!!

 

bye

 

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You cannot compare two software bluntly. ERDAS Imagine has it's own user group in commercial resource management and exploration sector. ENVI also has it's loyal customers in universities and private research groups.

 

The reason ERDAS is so popular in Asia and other places because they have a very good marketing department set in these places. The reason why ENVI can't get out of the wish list is most of the American and EU graduates can't give up using IDL for so many engineering and technical studies. IDL is awfully interesting for geeks, sometime as powerful as Matlab. ITT corp has their money flow steady by its global network of big scale industries, ie. aerospace, transportation, defense, energy and industrial markets. Now ITT is one of 100 top contractor in USA. 

 

Intergraph corp is more focused in engineering and geospatial solution since it's beginning (may be that's why they are good at selling their products). ERDAS Imagine, being an adopted son for so many parents over time (starting from the universities of America and Canada) ended up with Intergraph after touching many big names in its path. During its journey the software inherits codes and ideas from many experts, started its algorithms written in Fortran and later rewritten to C, sometimes Python.  

 

Being closely tied with a robust Fortran-derived interactive language, ENVI is a cross-platform image processing monster hugely popular among academicians, engineers, geospatial analysts, modelers and programmers. If you are a novice image analyst, ENVI is your thing. If you are a power user, application builder, environmental model maker/ tester, medical scientist, even a rocket scientist you will find ENVI sitting in you pc. But remember, great power comes with great responsibilities;)

 

If you are a white-collar GIS analyst, ERDAS Imagine is your thing. This software has it's charm in doing small things quickly and in a stereotyped way. In Imagine, things are easy once you learn the names of the buttons. Every function has only one wizard so learning curve is flatter. If you are a hobbyist, professional with little or no geospatial background, lousy professor then Imagine is your tool. Consider taking a peek to the other big names attached (ie. GeoMedia) to know how Intergraph deals the 'other-part' of geospatial industry. 

 

As you can see, every one has their own vice and virtues. Choose wisely. 

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On 13/11/2014 at 2:11 AM, rahmansunbeam said:

You cannot compare two software bluntly. ERDAS Imagine has it's own user group in commercial resource management and exploration sector. ENVI also has it's loyal customers in universities and private research groups.

 

The reason ERDAS is so popular in Asia and other places because they have a very good marketing department set in these places. The reason why ENVI can't get out of the wish list is most of the American and EU graduates can't give up using IDL for so many engineering and technical studies. IDL is awfully interesting for geeks, sometime as powerful as Matlab. ITT corp has their money flow steady by its global network of big scale industries, ie. aerospace, transportation, defense, energy and industrial markets. Now ITT is one of 100 top contractor in USA. 

 

Intergraph corp is more focused in engineering and geospatial solution since it's beginning (may be that's why they are good at selling their products). ERDAS Imagine, being an adopted son for so many parents over time (starting from the universities of America and Canada) ended up with Intergraph after touching many big names in its path. During its journey the software inherits codes and ideas from many experts, started its algorithms written in Fortran and later rewritten to C, sometimes Python.  

 

Being closely tied with a robust Fortran-derived interactive language, ENVI is a cross-platform image processing monster hugely popular among academicians, engineers, geospatial analysts, modelers and programmers. If you are a novice image analyst, ENVI is your thing. If you are a power user, application builder, environmental model maker/ tester, medical scientist, even a rocket scientist you will find ENVI sitting in you pc. But remember, great power comes with great responsibilities;)

 

If you are a white-collar GIS analyst, ERDAS Imagine is your thing. This software has it's charm in doing small things quickly and in a stereotyped way. In Imagine, things are easy once you learn the names of the buttons. Every function has only one wizard so learning curve is flatter. If you are a hobbyist, professional with little or no geospatial background, lousy professor then Imagine is your tool. Consider taking a peek to the other big names attached (ie. GeoMedia) to know how Intergraph deals the 'other-part' of geospatial industry. 

 

As you can see, every one has their own vice and virtues. Choose wisely. 

Any thought on eCognition sir?? We are intending to buy license one of them, but not sure which one would be more suitable for our use. All types of satellite imageries, multispectral images such as hyperspectral, SAR etc and LiDAR point cloud are to be processed for doing forest monitoring. I would appreciate for your suggestions. thanks!

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7 hours ago, AmitHaldar said:

Any thought on eCognition sir?? We are intending to buy license one of them, but not sure which one would be more suitable for our use. All types of satellite imageries, multispectral images such as hyperspectral, SAR etc and LiDAR point cloud are to be processed for doing forest monitoring. I would appreciate for your suggestions. thanks!

eCognition is for OBIA only, and very expensive. You'll need Erdas/ ENVI or other software which can do basic operations. eCognition can handle multiple image for single instance, so no worries. eCongition Developer can even do batch and distributed processing. I used OBIA for vegetation mapping and baseline assessment but haven't tried monitoring. If you can come up with a 'rule-set' for each observation, monitoring should get easy. Before that you'll need the imageries processed and ready. 

If you have experts who knows python and C++, I would suggest to spend this money on cloud services (ie AWS or similar). Now-a-days there is no point spending money for expensive software and PC, cloud is offering unlimited storage and processing power. Consider this app, Matt Hansen is using App Engine to classify forest loss of the whole world using Landsat image .

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And remember that you will also need to learn how to use the softwares.

eCognition Developer it has a lot of algorithms and functions, good for change detection using high resolution images (under 5 m, from commercial satellites and images from UAV/drones).

 

Edited by Arhanghelul
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I couldn't agree more with rahmansunbeam, especially if you are applying image processing to civil source remote sensing data.  Google Earth Engine provides every function incorporated in a standard remote sensing software package, plus a host of "shallow" machine learning algorithms for map classification, and petabytes of data in their catalog.  The only resources that a user needs is a web browser and some knowledge of JavaScript, but their API documentation and examples are easy to follow.  If you need to go further, and coding expertise and funding is available, you can fire up an EC2 instance on AWS.  I run all of my deep learning and machine vision analysis using a multi-GPU EC2 instance and the pricing is nominal.  

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