There are many programs that can be used for data analysis in remote sensing, but, what is the best software for data analysis in this field?
Concerning free software, I would suggest the BEAM open-source toolbox.
It has many functionalities (including customisable band math like ENVI), can be easily batch programmed (also integrating with other languages) and has a very active community which usually gives very fast support.
Concerning commercial software, I agree with the ENVI choice, putting it at the same level of ERDAS Imagine. Both GUI offers many functions allowing to do/reach more or less similar results, even if I would advice ENVI to someone who better understands processing principles, while ERDAS Imagine for who wants to have the results without too many steps and settings.
Concerning programming ENVI has IDL, which is a real programming language: very powerful to whom is expert in programming. ERDAS Imagine has the new Spatial Modeler which allows to make "visual programming", less powerful, but nevertheless very easy to be used and also programmable using Python.
Dr.Richard, from your point of view, which one between these 3 big names is best if I want to make a geo-referenced image, mosaiking and image classifications...
For the above mentioned works, you can use any RS software (since these are basic functionality), but ERDAS will be easier for beginners, however, in ENVI you have more flexibility and options...Moreover these 3 basic tasks can be also done in ArcGIS, GRASS and QGIS....Its your convenience which software you want to use.
I find ENVI to be the most useful for my work - which involves similar steps. Plus we use the SARSCAPE module with ENVI.
If I needed to prepare maps etc. I would probably prefer ERDAS Imagine.
For this type of application I think that ERDAS Imagine is the best. ERDAS has connectivity with specific photogrammetric software like Leica Photogrammetric Suite (LPS) in order to process another types of imagery datasets.
In my point of view ENVI is the best option to work with remote sensing data process. However you can try in ERDAS imagine also. These two are user compatible versions. But in the big data volume you can try with matlab which is used by globally. But is programme oriented need to be learn
Based on my experiences, ENVI is the most powerfull, however IDRISI also provides many modules for land use land cover analysis. If you want to learn open source and free software, please try GRASS and ILWIS. At the end of the day, its all depend on the objective of your study.
It completely depends on your analysis (vector based or raster based) analysis. The Image processing software (ERDAS, LPS, ENVI, GEOMATICA, etc) supports raster analysis, while ArcGIS, Quantum GIS, etc. supports vector based analysis. So choose first what kind of analysis you want to do, then go for the software support. There are many software products available in the market as demo, open source and complete license version.
I am also voting for ENVI if you have access to it.
If you are on a budget (as in, looking for a free software package), I recommend MultiSpec. I've used it on some of my unfunded side projects for basic image rectification, processing, spectral band math, principal component analysis, and image classification. I was using Landsat ETM+ with it. It can handle most image formats. Download and resource information is available at: https://engineering.purdue.edu/~biehl/MultiSpec/
It is a pre-compiled program that runs without issues on MacOS and Windows.
In India most popular software which are widely used for the data analysis are ArcView and Erdas. Erdas is popularly use for digital image processing and analysis while ArcView is used for Digitization and further strategic purposes
I don't think ArcGIS is a very good choice for remote sensing image analysis. My recommendation is ENVI or MIPS.
Idrisi is lovely to use and I think quite good value for money. ERDAS is top end but complicated, ArcGIS is more an all round GIS not great for RS but not bad. Free options are usually expensive in time as no one has been paid to write the manual. You pays your money you takes your choice.
Do you know ER MAPPER? it is also the good software for the remote sensing analysis.
an another very useful RS software , and free of charge, is SPRING a product of Brazil's National Institute for Space Research (INPE/DPI (Image Processing Division ), which include a very useful tools for images segmentation. Info and download, after registration, at
http://www.dpi.inpe.br/spring/english/download.php
I think that IDL and MAtlab have the highest performances in data analisys, graphics, algorithm and ruotine. Unfortunately they are not free. GDL, the gnu version of IDL is open source, and it should be, for these reasons, the best software in RS analisys. Obviously, it depends on what kind of analisys you have to do and for this purpose I prefer to use the specific sw for the particular kind of analisys; At the moment I haven't yet found the sw that can do everything and well.
As somebody above hinted there is no correct answer ......it depends on what is your input (raw data, pre-processed images, higher order products), what type of sensors/combination you plan to use and what are your objectives ...I personally use several packages such as ENVI, (mosaicing, atmospheric corrections, visualization, co-registraion cross-check, etc.), Gamma RS and/or PolSARPro (for radar data processing), Ecognition (object based classification), ERDAS (orthorectification of very high resolution optical), Matlab (modelling and custom processing of some radar datasets), etc.
Probably I could use less packages (i.e., some software can perform multiple tasks) but for me it is easy to just use what I already know instead of loosing time learning a different software package. In the end what counts is presenting your results to the scientific community and the faster you get there the better.
It depends on your research/work... different packages have their own advantages as well as disadvantages.
It depends on your application and sensors. The sound capability of ENVI is IDL interface; therefore you can easily manipulate codes and even add your desirable menu.
However in case of polarimetry and SAR (particurlarly InSAR), PolSAR, DORIS and ROI_PACK are needed.
Some of the algorithms (such as image-based atmospheric corrections or calculation of emissivity) are too superficial in ENVI. If you want to propose an innovative idea, you have to start coding.
Good luck
Concerning free software, I would suggest the BEAM open-source toolbox.
It has many functionalities (including customisable band math like ENVI), can be easily batch programmed (also integrating with other languages) and has a very active community which usually gives very fast support.
Concerning commercial software, I agree with the ENVI choice, putting it at the same level of ERDAS Imagine. Both GUI offers many functions allowing to do/reach more or less similar results, even if I would advice ENVI to someone who better understands processing principles, while ERDAS Imagine for who wants to have the results without too many steps and settings.
Concerning programming ENVI has IDL, which is a real programming language: very powerful to whom is expert in programming. ERDAS Imagine has the new Spatial Modeler which allows to make "visual programming", less powerful, but nevertheless very easy to be used and also programmable using Python.
I would like to suggest you the open source SPRING software developed by the INPE (Brazilian Space Research Centre). It is very good and at front edge, with advanced tools. You can download it from Inpe site:
http://www.dpi.inpe.br/spring/
I also got used to using R project packages for advanced statistical analysis on matrix data.
Hope to help.
All the best
Marco
If you are searching for an open source then I recommend SAGA GIS, otherwise you can use ERDAS Imagine, I found it friendly and easier than ENVI. it leads you step by step since data pre-preparation into data preparation into data processing. also it offers Model Bilder to fit your special tasks.
There are many softwares for RS analysis. As a mention, depending on our purposes because each software has advantage and disadvancetage. To start for RS image processing, i suggest that u should use ENVI, it have many functions as well as friendly interface to use for common processing.
ERDAS IMAGINE / ENVI for the optical images and POLSARPRO for Microwave products
R is great if you do not have to process huge amount of data. If you work on long time series and very big matrices I would rather recommend Python or IDL. If it is not a case, R and only R!
If you want to use open source programs (which I would suggst) try out gvSIG ce (http://gvsigce.org/) which includes SAGA, GRASS GIS and SEXTANTE! But I´m not sure how it works handling big amounts of data. But why not try it out?
I would also recommend R, of course.
If your have the licences, I suggest Erdas Imagine 2013. The new Model Editor seems to be really handy.
I've used R and several packages for manipulating and classifying satellite images using unsupervised (k-means) and supervised (random forest and support vector machine) methods.
My work flow typically include image reading, atmospheric and topographic correction, image crop and mask, export single and stack files, k-means, RF and SVM classification and classification validation.
I've added the workflow to github (https://github.com/PauloEduardoCardoso/RLandsat)
The ENVI /IDL GUI is far superior to many off the shelf available RS data analysis software packages. It is useful both for multispectral as well as hyperspectral data analysis.
Use ERDAS IMAGINE (commercial ) and SAGA GIS for Remote Sensing data analysis, imagine can handle larger data ,where as saga multiple options avalible
ENVI / IDL works well, especially with large raster data sets. And Python (numpy, geopy, gdal, etc. for relevant libraries).
Hello Saeed,
I would like to suggest the best data analysis for Remote Sensing Data especially for hyperspectral data you can use E Cognition Software, it is the best s/w for Object Based Classification and for Mixed Pixel Problems compared to ERDAS and ENVI Software
ERDAS and ENVI are the top of the heap, followed by PCI Geomatics. For freeware, GRASS and SAGA-GIS have some OK functionality. ArcGIS has just enough functionality to completely frustrate you - and force you to get a dedicated remote sensing package.
Most software don't cater 100% of our need, then you need to write your own programs either in Matlab or in IDL - ENVI (as mentioned by Giulio Ceriola).
I write all my code in R. Lately I started using QGIS, and I think it's superior to ArcGIS in some respects. Its ability to interface with R is great.
You may visit this intergraph website for free version: http://download.intergraph.com/download-portal,
I suggest you NASA-SeaDAS. I generated the color maps in the following publication, using this software:
Conference Paper Investigation the Behavior of MODIS Ocean Color Products und...
I use open source QGIS and SAGA. Open source have large community support. If you have money, I think you better spend it to support an open source project. A lot more people will benefit from it, especially the less fortunate. In times of crisis and calamities, open source is the way to go. Better spend your money for other more important tasks.
I would like to suggest you the open source SNAP software developed by the ESA. SNAP is the successor and evolution of BEAM.
Please note that BEAM is not further developed. It will remain under maintenance until mid of 2016, at least. During this maintenance phase we will continue our user support. We encourage all BEAM users to use SNAP from now on. SNAP is the successor and evolution of BEAM.
In my own personal experience, I recommend:
R, Python, Octave (replacement to COTS MATLAB, etc.)
QGIS, SNAP, SAGA-GIS, GRASS (replacement for COTS ENVI, PCI, ArcGIS)
I'd suggest you a reading on Free R and QGIS resources available for Data Analysis in Remote Sensing.
R Package RSToolbox
R Package caret
QGIS Semi Automatic Classification Plugin
http://topepo.github.io/caret/index.html
https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html
All the open source software useful are and powerful environment but the comercial s\w will crashface the license problems. I prefer R package and Matlab toolbox
The only and only one is MATLAB and thereafter ERDAS, GeoMatica .
I suggest you to use SNAP by ESA and SeaDAS by NASA. Both are free data processing softwares.
Dear Saeed there are many software such as SNAP, ENVI, ERDAS, GeoMatica, Arc GIS ...... and so on but from my experience I work a lot with there softwares but the best to me is ARC GIS
My regards
According to Demand of Analysis, you can choose the specific software..
Suppose:
1. For Classification: ERDAS IMAGINE 2014
2. For GIS Analysis of Quantification: ArcGIS 10.3
3. For Hyperspectral Analysis: ENVI
4. For Making Spatial Graphs: TerrSet
According to Demand of Analysis, you can choose the specific software..
Suppose:
1. For Classification: ERDAS IMAGINE 2014
2. For GIS Analysis of Quantification: ArcGIS 10.3
3. For Hyperspectral Analysis: ENVI
4. For Making Spatial Graphs: TerrSet
A good option (free software) is the SNAP toolbox that is distributed by the Copernicus Program (ESA).
User friendly & simple workflow with integrated powerful GIS (Goe_spatial/statistical) functionalities: ENVI & ArcGIS.
ARC-GIS and ENVI is good but recently R is best platform for RS data analysis. Google earth Engine is one best Cloud based RS data processing Platform.
Erdas Imagine (followed by ENVI, Ilwis, some modules of the ArcGIS)
ENVI, ERDAS, eCognition, PCI Geomatica, PolSARpro, SARProz, SARSCape, QGIS, ILWIS, GRASS, SNAP
There are a number of useful remote sensing software available, it also depends on the task. R is known to be good, ERDAS IMAGINE and ENVI are good softwares.
Due to the abundance of satellite imagery with a lot of spatial resolutions and due to the analysis and processing desired software is very usable. Software such as ENVI, pci geomatica, eognition, global mapper, erdas, ... are available. The most important point in selecting software is to specify the purpose of the task, the necessary preprocessing, the desired output, and the satellite data used.
I personally think R, Python, MATLAB, ArcGIS, ENVI, Global mapper can address all your needs!
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