Questions related to Hyperspectral Image Analysis
Hi I'm looking for some mineral and rock spectra repositories to use in the interpretation of remote sensing images and spectral mapping for mineral prospecting and research.
Hi, I am currently willing to work in Hyperspectral image classification. I am a beginner in the research domain. Please Anyone suggests narrow down the latest trends suitable for further work. Please help me in that matter.
I have hyperspectral data of Indian pines and the ground truth related to that. Now I want the spectral signature(information) of the material present in the Indian pines. I have tried searching the standard libraries like NASA's JPL but some materials more precisely plants like alfalfa are not present in there. can anyone help?
indian pines source
I've come across a couple of publicly available hyperspectral image datasets from the website http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes
Now, my concern is regarding whether or not we can use these datasets directly for building machine learning based models.
Are these datasets geometrically and atmospherically correct? Or do these datasets further require atmospheric and geometric corrections prior to building any machine learning based model?
Also, how can one be assured that a captured hyperspectral image scene is atmospherically and geometrically correct?
I have acquired some plant hyperspectral images (roots, fruit, leaves) from various environmental conditions and now want to explore the data cubes to detect possible differences and plan to study plant physiology and chemometrics in future. The built-in software with the camera (Specim IQ studio) is not serving the purpose.
Any suggestion for easy-to-use and simple interface software or analysis pipeline for such exploration and making classifier models? Preferably open-source but commercial suggestions are also welcomed.
Many thanks in anticipation.
I need to get a satellite image from a site in the northern part of Iran for remote sensing research usage. I wonder where I can find such data?
A friend suggested these websites, but they didn't cover 1-meter hyperspectral imagery from the expected region: "Open Aerial Map, Google Earth Pro, Airbus."
The final goal is to collect data for ecological services calculation (O2 release Co2, No2, So2 absorbance) of vegetation of the specified region. If you know a better way to doing so, also very helpful.
I am trying to implement object detection using C++. I have hyperspectral data in the form of .bil file along with header file. Can anyone help me in accessing .bil files using C++?
Can mercury pollution in waterbodies be detected using hyperspectral imagery?
Thinking along the lines of detecting evidence of gold mining.
Any feedback or paper recommendations you have would be great, thanks!
I am using autoencoder networks for deep learning based feature extraction purpose for spectral images. For the time being, the number of hidden nodes in the network is randomly chosen.
Is there any way to optimize this parameter so that the best feature representation is achieved?
I have a hyperspectral database consisting of spectral signals between 350-1050 nm.
I calculated the simple formulas (Simple Ratio and NDVI)
But i have a big problem about creating all possible two (or three) band combinations.
I have no idea what script i should use.
Could you advice me a document which hepls me create NDVI, SR and TVI using all possible two band combinations?
I need hyperspectral data for my project. how I can download free hyperspectral data Preferably with ground data?
PS: I know I can download Hyperion data from "earthexplorer" but I need ground data too.
I need to extract endmembers in a hyperspectral image, MESMA (Multiple Endmember Spectral Mixture Analysis) is a prevalent algorithm in the unmixing analysis. but I have no idea how to run it. does anybody have a tutorial video or pdf? and another question: can I conduct MESMA in ENVI software?
I am working on hyperspectral image analysis. I want to apply PCA on my hyperspectral dataset to reduce spectral dimensions. My question is Why do we need to center the hyperspectral data(mean subtraction) before applying Principal component analysis(PCA)? Is this step is mandatory? What will happen if we did not center the hyperspectral data before applying PCA.
When i googled about this I got following links.
From these links, I feel data centering is required to maintain same scale for all features before applying PCA. But coming to hyperspectral data cube, generally all spectral bands will be in same scale.
So, Do we need to center the hyperspectral data before applying Principal component analysis(PCA)?? What will happen if we did not center the hyperspectral data?
I need to know the emissivity values of vegetation cover and water bodies from a MODIS product MOD11A2 and there are two bands 31 and 32, which one to be used and what is the difference between them both? Also, is there any better product for the emissivity?
There are spectra collected by asd spectroradiometer in lab environment with one source lamp on. Snapshot imaging done on the same sample with a different source lamp in the same lab environment. Extracted spectra from the snapshot images and continuum removed spectra of both asd and snapshot are compared. Although they match in absorption features, they show a certain difference in the spectra. How will I model it? Is there a way to do some quantitative analysis between the spetra of these two sensors. Attached are the images of plots showing thick lines representing asd and dashed lines representing the snapshot imager. The samples used were different beach sand samples.
Can you please provide me the remote sensing sattelite data set for landcover change analysis of sundarban mangrove forest bd,india location ?
If possible then send me the prepossessed dataset in TIFF or MAT format.
You can provide me the source link..
I tried to plot entropy of all bands for AVIRIS dataset (Indian Pines) in MATLAB, however it shows zero value entropy for all bands. Even after scaling of the data, it shows zero value for almost all bands.
i am working with hyperspectral pixel mixtures and i want to create a netowkr that maps the abundance values of the mixtures to the spectral signatures.
Basically my input vector is 1x11 and output vector is 1x91
1x11 represents the mixture values for example [0.25,0,0,0.5,0,0,0,0.25,0,0,0] and the output label is the 1x91 spectral values or a 1x91 dimensional vector of normalized values
As you can see the input values contain many zeros and i want to create a mapping between these input mixture values to the output reflectance values.
Should i use dense layers in this case or approach it in another way?
We require hyperspectral imagery data for Haryana region to carry out a preliminary analysis. If it is available with anyone kindly share the data with us or a link from where data can be acquired.
Your contribution will be highly acknowledged.
I want to do spectral unmixing for the hyperspectral images. In one paper they have used abundance matrix for the spectral unmixing. I did not find any materiel which explains it step by step. please help me...
We do not consider the relative spatial location, and simply classify them based on the similarity of pixels.
For example, we get a hyper-spectral image, and then we disturb the spatial distribution of pixels. We only consider the similarity of the spectra. How can I classify pixels based only on the similarity of the spectra, so that the spectral differences in the class of classification results obtained are small, and the spectral differences between the classes are very large.
* i have collected soil samples during hyperion pass over the study area and chemical analysis was done.
* Lab spectral signatures has not taken.
* How can i correlate the chemical analysis results to hyperion data after preprocessing?
Anyone knows about research-related or industrial applications of CNN for HSI data in the food science field? Unlike SVM, KNN, and other "shallow" machine learning algorithms, the CNN enables taking advantages of the spatial information of HSI data.
Most published papers deal with extraction of deep spatial features for architecture classification and other domains. But in the literature, I don't find applications of this deep learning technique on food/agricultural products!
Thank you !
Can compression (before classification) increased the classification acuracy?
How can we improve the classification accuracy of remote sensing image(RSI) by the help of compression?
Dear respective researchers can you please help me by providing the related articles link or your valuable opinion for these issue.
I am doing research in content based image retrieval using hyperspectral image. I seen many of the websites block the hyperspectral image. Can someone send me link in hyperspectral image dataset.
While spatial, spectral and temporal advantages of multitemporal hyperspectral sounder (SAR) images provide opportunities for advancing the compression and classification techniques. So I need multitemporal remote sensing SAR images for evaluating the performance of my 4D compression techniques. Currently, I evaluate my methods by multitemporal multiapectral data.
So, if you know the source of Multitemporal SAR images then please give the link here.
Thanks & Regards
Masud Ibn Afjal
I want to do unmixing about the hyperspectral image by NMF( Nonegative matrix factorization ), because of the nonconvexity
of the cost function C(W, H) with respect to both W and H, it is
impossible to obtain the global optimal solution. How to get a resonbled regularized term about the NMF?
Does anyone know where can I find a HSI database for any object or material, but with more than 25 spectral images (i.e. 25 *x*y*lambda)?
It would be nice, if somebody could propose a HSI database for agricultural, medical, food, and circuits. Thanks!
Feel free to share your database with me, I have no problem to cite your database.
Thanks in advance.
I need HYDICE Urban Data Set or other similar data set for Hyperspectral anomaly detection. can any one help me? please inform me for this emergent need?
I tried all the conventional techniques provided in literature, but doesn't seem to be working well for required results.
What are the latest restrictions by the FAA on using UAVs ( fixed wing and rotary wing, e.g quadcopters) for purely scientific investigations?
Max.altitude, line-of-sight, permits, coastal and urban areas, etc.
I want to use hypespectral data for mapping. Is there any remote Hyperspectral data available free or paid. anyone knows please post the links? Thank you
Hyperspectral Image Analysis - Two Assumptions:
1. Existence of Pure Pixel
2. Absence of pure pixel (Presence of mixel pixels alone)
Moreover, mixed Pixed - Can use either Linear Mixture Model/ Non-Linear Mixing Model for unmixing.
My query is:
- Pure Pixel Assumption : Does it comes under Hyperspectral Unmixing problem?
-whether Xi = Sai + ni => Linear Mixing Formula has to be considered for Pure Pixel Assumption problems.
Kindly clarify my doubts.
Hello all. I have RGB and infrared images taken with a drone. These images are in digital number (DN). Does anyone has a suggestion on how to convert the spectral bands to reflectance for calculation of vegetation indices? No reflectance panel was used onsite for any measurements.
After creation of the different VIs, what is the principle (or on what criteria and basis) does the forest health tool classify the different VIs into a single classified image?
I want to generate the test & train data samples from the hyperspectral image of indian pines & pavia university.
I also want to know a single pixel have multiple values due to bands. Which value is taking for training & testing process.
I am using Matlab as a simulation tool.
Hi everyone, what would be a good image fusion method for multispectral images, such as NIR (near infrared) and SWIR (short wave infrared) images? Or in general across the light spectrum? I would really appreciate if you can give some insights and provide/share the codes. Thanks.
I will be thankful somebody that can attached my needed file hear or in my email adress:
Or Please guide me, how can I request some free space born hyperspectral data of my needed area with attached coordinate ?
I attached KMZ Google earth file of my needed coordinate area.
Thanks every body.
I want to know the maximum possible value at each of the 220 spectral bands of AVIRIS? is there a way to know it? FWHM is available but i dont understand what is it??
I want to calculate Photosynthetically Active Radiation (PAR) from band1 values of MOD02QKM to be used in satellite model.
I want to download only the panchromatic band of Landsat 8 for ~10 images instead of downloading the whole 10 images (each ~1 GB )
Thanks in advance
For quantitative purposes, hyperspectral imaging seems to lead to a bigger prediction error when comparing its prediction ability to traditional NIR instruments. Despite its advantages and potential, this seems to me a relevant issue for a full implementation of this technology.
Which factors are in your opinion the most important ones in leading to lower performance? There might be the effect of sample position, illumination condition, the difference which is obtained when looking at single pixel level or averaging areas (especially when applying the calibrations!), the fact that the sample is moving (in a push-broom system, for example), and further error is obtained when looking at single objects instead of average batches.
Thus, are there actual benefits of using HSI over traditional instrumentation to study the composition of food and agricultural products?
I want to know how to differentiate the spectral profile of Tea from other Land uses. Is reflectance of tea leaves have any distinct qualities in NIR region than other vegetation, forest , soil and water?
I have the ground truth map of indian pine and the pavia university images, but this ground truth is for classification not for segmentation
the current cloud removal algorithms are almost aim to the multispectral or pan remote sensing image,i want to know that does these methods suitable for hyperspectral image.
I am simulating multispectral sensors to acquire multispectral images from hyperspectral data. What type of noise should be modeled during the acquisition? There is already some noise in the hyperspectral data so only Gaussian noise may not be sufficient for such a model?
I am undertaking a project into the identification of tree species using satellite data, namely the hyper spectral data generated by Sentinel 2. Is there a way to use this data to identify trees to a species level or failing that identify whether a tree is broadleaved/coniferous etc?
I want to create a realistic instance with the help of STK (Satellite Tool Kit) Consisting of 6 identical satellites moving on the same orbit (circular, altitude 668 K.M, and sun-synchronous) with a phase shift of 120 degrees between each satellite. The provided instance is artificially generated, with 800 tasks (target for imaging), 1500 strips, and 912 opportunities. (these numbers just for instance).
Hello every one, in my current research, i am working with AVIRIS data for rock mapping and also mineral prospectivity determination by mineral potential zones mapping. In this case there are lot of issues regarding data processing and interpretations, I have applied MNF, CEM SID but i did not make a good result in output. so in this regard if anyone can help me , i will be highly obliged...thank you
I have a query and a request; query about how to make effective per-processing steps in AVIRIS (Hyper- spectral) data processing? I have done some steps like empirical calibration, MNF and some more. But i could not remove noises from radiance data. So in this situation, my kind request to you all if anybody has experience, knowledge or expertise, please en-light me with yours wisdom.
Add on: If you can please attach some link or literature of good publications related to pre-processing of AVIRIS data.
Since iron oxides are one of the best key indices for mineral exploration. In addition integrating spectral imagery data can provided effective discrimination and mapping of exposed rocks. So I decided to design and apply a UAV malutispectral imagery system. For this reason, I want to know, is it correct applying Parrot SEQUOIA multispectral camera on drone?
What is Extended Morphological Profiles in hyperspectral imaging. I need to apply in pavia dataset (Mat file). Detail of the file is present in the below link.
It is known that FLAASH and QUAC atmospheric correction not suitable for thermal bands. So what is an ideal method of atmospheric correction of Landsat 8 thermal bands (TIRS)?
I have downloaded level 1Gst and level 1T hyperion hyperspectral data for my study area, in order to use in mineral mapping, however, every time I try use FLAASH for atmospheric correction it gives an errors or bad results. Should I use the toolkit then subset (removeing bad bands) then FLAASH or not? Also should I put specific advanced paramters in FLAASH?
How I use FLAASH atmospheric correction using ENVI (what ideal parameters for such data sets)?