Science topic

Hyperspectral Remote Sensing - Science topic

All remote sensing topics related to hyperspectral data.
Questions related to Hyperspectral Remote Sensing
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
I need Hyperspectral remote sensing data for land degradation assessment and Mineral exploration.
Relevant answer
Answer
There are tons of archived EO-1 Hyperion data at USGS Earth Explorer or you may order something from PRISMA.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
My purpose is to use in hyperspectral images.
Relevant answer
Answer
actually, I need a similar to this program for calculating the weather condition on my telecom system.
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
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.
  • asked a question related to Hyperspectral Remote Sensing
Question
2 answers
CI-110 Plant Canopy Imager gives two reading related to leaf area index (LAI) GF lai and PAR lai. Is these values are the final ones if I am trying to Effective leaf area index or do I need to do any other calculation ? if yes, then, Which values should I use as the effective leaf area index (GF lai / Par lai)? I am trying to work on lai prediction using remote sensing.
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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.
Relevant answer
Answer
Hyperspectral Document Image processing for Writer Identification
Ink Mismatch Detection using Hyperspectral Document Imaging
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
Are there books & papers dealing with methods to detect active fault by using hyperspectral remote sensing. Or does anyone have good idea?
Relevant answer
Answer
We have publish two paper which you can read.
1.Cui, J., Zhang, S., Zhang, J., Liu, X., Ding, R., Liu, H., 2016, Determining surface magnetic susceptibility of loess-paleosol sections based on spectral features: Application to a UHD 185 hyperspectral image. International Journal of Applied Earth Observation and Geoinformation,50: 159-169.
2.[1] Cui, J. , Zhang, S. , Wang, X. , Zhang, J. , & Dong, X. . (2021). One case study shows an important phenomenon: active fault can cause subtle spectral features change of soil. Natural Hazards Research.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
Hello,
I would like to ask what the recommended hyperspectral sensors are for mineral exploration? I apologize if the question is broad, but I am new to hyperspectral remote sensing.
Relevant answer
Answer
Hello I am processing EO1 data with these steps with two computer
1- Bad band removal
2- Thor destriping
3-FLAAS ATM Correction
But in atmospheric correction, the first computer is leptop gives memory error as
envi.error.unable.to.allocate.memory
Second computer is finishing flaash but all bands in reflectance data are black so it gives broken data
What can I do for this atm correction step in envi with two computers?
  • asked a question related to Hyperspectral Remote Sensing
Question
24 answers
The availability of low price hyperspectral images that can cover large area with  high spatial resolution has not matured yet. After the termination of the Hyperion mission on EO-1 satellite and the same for Hyperspectral Imager for the Coastal Ocean (HICO) the choices of hyperspectral satellites are decreasing. Do you think that this technology is going to extinct and give up to aerial hyperspectral technology or there is still hope?
Relevant answer
Answer
Thank you Dr Prateek Tripathi for your contribution
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
Full-time, benefited position with the Department of Viticulture & Enology/Viticulture and Enology Research Center through the California State University, Fresno Foundation. The Department of Viticulture & Enology/Viticulture and Enology Research Center is seeking a PostDoctoral Scholar who is experienced in computer vision or remote sensing and is passionate about Machine learning/Deep learning, automated and digital agriculture, and chemometrics. We are interested in working with a motivated scholar who can think creatively and practically about production-oriented remote sensing and “big data” applications in agriculture. Strong quantitative background is preferred (as demonstrated by publications), experience with unmanned aerial vehicle and hands-on electronic ability is a plus. This position is based within the Department of Viticulture & Enology/Viticulture and Enology Research Center, through the California State University, Fresno Foundation. The selected candidate will also have the opportunity to collaborate nationwide with scholars from other universities (Cornell, UC ANR) within multi-institution projects funded from USDA, CDFA and CSU-ARI. Within overarching project goals, the candidate will have intellectual freedom to develop and pursue the research directions they find most interesting. Mentorship will focus on helping the candidate meet their professional development goals, whether in academia or elsewhere. The position is 100% time (40 hours per week), benefited, and funded for 12 months initially, may be renewed based on funding and contingent on satisfactory progress.
PLEASE FIND THE FULL CALL AT THIS LINK:
Relevant answer
Answer
Hi, Dear Luca
I suggest you join the below website:
and also you can search on Twitter!
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
In microwave radiometry of soil moisture, what is the typical magnitude or range of errors introduced by variations in soil roughness and vegetation cover? Soil texture can also affect accuracy, but soil roughness and vegetation cover seem to be most important.
Relevant answer
Answer
I strongly suggest you reading our new article, which presented a reliable way to estimate soil moisture “Machine learning inversion approach for soil parameters estimation over vegetated agricultural areas using a combination of water cloud model and calibrated integral equation model”
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
I am looking for getting hyperspectral remotely sensed data from any satellite which covers Egyptian lands. please if any one knows how to get those images.
Relevant answer
Answer
Thank you so much to all for your great valuable suggestions
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
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
Relevant answer
Answer
Did you get the spectral signature of the ground truth of the Indiana pines data set.
please share it with me. I will be highly grateful to you.@
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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?
Relevant answer
Answer
As Mr Nasir Hameed suggested, if you are looking forward to inspecting individual spectral signatures in a hyperspectral image, the Digital Numbers (DN) are more than adequate to design an autonomous classification, while atmospheric and geographic corrections would be unnecessary for the framework.
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Spaceborne Hyperspectral observation (i.e. hyperspectral remote sensing in uv-visible-infrared spectral range) of Earth and for Planetary science, plays a very important role in improving scientific understanding, environmental and resource monitoring.
Signal to Noise ratio (SNR) is a very important parameter (or quality metric) of any Hyperspectral instrument indicating its potential to meets its desired observational goals.
Due to demanding need on higher spectral and spatial resolutions, it become challenging to good / high SNR to meet the desired observational goals.
In view of this I wish to discuss or seek suggestions of various options or ideas by which SNR of Hyperspectral instrument can be improved. Ideas or options may be either for instrument design aspects or for image or data processing aspects.
Relevant answer
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
Models that evaluate parameters to water quality. For example clorofila a, turbidity, DO, etc.
Models for lakes in the tropical zone.
Relevant answer
Answer
Six main public domain water quality models which are presently available for Rivers and streams are being captured in this article. These main models could produce important results if they are used in the correct manner, because they are different in terms of assumptions, strength and weaknesses, processes they represent, modeling capability and data input requirements. The Model review discussed includes, water quality analysis simulation program (WASP7), simulation catchment (SIMCAT), quality simulation along Rivers (QUASAR), and the temporal overall model for catchment (TOMCAT), QUAL2KW, QUAL2EU. The models are described individually according to a consistent set of criteria-conceptualization, model capability, model strengths, limitations, input data and how it utilized. The outcome showed that TOMCAT and SIMCAT are important in ASSESSING effect of point sources in a very simple way. The QUAL2KW, unlike the QUAL2EU where macrophytes play a major interaction, it can convert algal death to carbonaceous Biochemical Oxygen Demand (CBOD), thereby making it more suitable. In addition to the extensive requirement of data, it is expensive and time consuming to set up these complex models such as QUASAR and WASP7. Therefore, one model cannot be used for all the required functionalities. Choosing a model would depend on a specific application, financial cost and time availability. This article may be of help in choosing a suitable model for a specific water quality problem.
Article Water Quality Model for Streams: A Review
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
I want to extract RCS values or backscattering coefficients from available Radar imagery and create a Geospatial layer out of it.
Thank you.
Relevant answer
Answer
Gomal Amin Thank you for your response.
  • asked a question related to Hyperspectral Remote Sensing
Question
9 answers
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.
Relevant answer
Answer
Matthew Mabey Thank so much, Matthew. It's very help full. I appreciate it a lot.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
I am looking for hyperspectral images from UAV that captured forest or forest plantation. Do you know about some source where I can download some examples?
Thank you
Martin
Relevant answer
Answer
Martin, check out the GatorEye dataset, they have amazing high-quality UAV-LiDAR, etc. data available for researchers! Please reach out to Dr. Eben to get more details.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
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!
Cheers,
Sol
Relevant answer
Answer
Mercury pollution may be picked up by analyzing predatory fish at top of food chain. Mosquito fish (Ambrosia app.) have also been found to accumulate nitrogen. You might find added information from US National Mercury Lab. Wetlands in headwaters of black water streams have also been found to reduce mercury to toxic methyl mercury form.
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Where can i find open datasets regarding " Wheat/Maize Leaf Spectra with Associated water content, Potassium and Nitrogen Measurements" for machine learning research i.e. hyperspectral tabular data collected from a field spectroradiometer along with chemical parameters.
Relevant answer
Answer
Can look at EcoSIS
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
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?
Relevant answer
Answer
There are some practical ways to determine the best size, but it all comes to evaluations. The general rule is the optimal size of the hidden layer is usually between the size of the input and size of the output layers.
In sum, for most problems, one could probably get decent performance (even without a second optimization step) by setting the hidden layer configuration using just two rules: (i) number of hidden layers equals one; and (ii) the number of neurons in that layer is the mean of the neurons in the input and output layers.
Jeff Heaton, author of Introduction to Neural Networks in Java offers a few more.
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Hey,
I am looking into the feasibility of attaching a Specim FX17 sensor to a multi rotor system.
Specs wise it looks possible, sensor is 1.4kg and Matrice M600 max payload is approx 15kg.
Does anyone have any experience?
Many thanks,
Relevant answer
Answer
As far as I understand from the documentation of the camera, it is recommended to use it stationary in the laboratory.
However, I think you can use this camera with a drone but it’s not so easy to do it. I have little experience installing cameras to the drone in non-standard conditions.
First of all, you need to think about the power supply, this camera needs 12 DC. You can attach the additional battery. But, it seems the input of the connector for the lipo-battery will be difficult to find. Also, you can use a power source hub kit for M600, with a voltage converter if needed.
The most important thing is the GPS system. I am not sure about your sensor, but to use it with a drone you need georeference data on your image, I guess. I have experienced to work only with sensors that have a GPS antenna on board.
I think the manufacturer of these sensors should have a set to connect to the drone, since initially I do not see options for the simple use of these sensors with UAVs.
Thank you.
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
Is there any research papers about estimation of crop and air temperatures using thermal measurements?
Relevant answer
Answer
In addition to the recommended articles by Bachir Achour , you can also check out this article (see attached)
  • asked a question related to Hyperspectral Remote Sensing
Question
52 answers
If anyone knows, please tell me where I can get Village level administrative boundary (Level 4) of India in ESRI shapefile format?
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Is there any standard procedure/sequence of tools to process the hyperspectral tabular data before PLSR regression modeling.
example of tools are 1) De-resolve 2) second derivative 3)normalize 4) de-trending 5)baseline etc.
Application is for field spectroradiometer data of soil and crop.
Or the sequence of tools differ for different datasets ?
Relevant answer
Answer
The pre-treatments you use will depend on the sample set: noise, level(s) of analyte, number of samples, ranges, etc. In many cases, it is a case of start small (Absorbance data) and add treatments, as needed. Just remember, every treatment can hide/generate peaks and will have an effect on sensitivity.
  • asked a question related to Hyperspectral Remote Sensing
Question
8 answers
hello
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.
Relevant answer
Answer
USGS earth explorer - https://earthexplorer.usgs.gov/ for Landsat and Sentinel2data
Experimental satellite data by registering particular access site by registering with institutional mail ID
  • asked a question related to Hyperspectral Remote Sensing
Question
1 answer
hello
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?
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
Hi,
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?
Thanks.
Relevant answer
  • asked a question related to Hyperspectral Remote Sensing
Question
10 answers
Hi all,
I'm a student who is starting in the remote sensing field, specially in ocean and coastal studies.
Can someone explain me how to get the Remote Sensing Reflectance (Rrs) from Sentinel 2 images?
Until now I was using the pixel value as Rrs, but looking at
and
I realized that this assumption was clearly bad.
Thanks in advance
Relevant answer
Answer
I stumbled upon this thread and I see some confusion in it, so I would try to comment for the sake of other readers looking for similar information, although the question is a little old. I see Alfonso Hernandez is aware of this, but some of those responding are not: He uses L2A product, which means he already has product with atmospherically corrected reflectance, no need to recompute from radiance or use SNAP. The only thing which may be needed to use the product with some software, which supposes reflectance in the 0-1 range directly in pixel values is to divide all the values by the quantification coefficient mentioned by Prashant H Pandit - but other software may do it for you automatically by reading the metadata.
To the original question: Remote Sensing Reflectance (Rrs) is indeed the pixel value of the product divided by 1000 (the quantification coefficient). The term Surface reflectance only stresses the fact it is reflectance as if measured on the surface (i.e. atmospherically corrected, as opposed to term TOA reflectance), and the term Remote sensing reflectance similarly only stresses the method by which the reflectance is obtained (as opposed to reflectance obtained by in-situ measurement with a spectrometer - which should be more precise, usually is bidirectional, has also different form - only individual values for measured sites, while Rrs contains raster of values whose pixels contain average of reflectance over area of the pixel).
  • asked a question related to Hyperspectral Remote Sensing
Question
10 answers
 Concerning hyperspectral remote sensing. What is hyperspectral CASI imager and what is its specification ?
Relevant answer
Answer
Camila Souza dos Anjos : it depends. For instance, the data is recorded as uncorrected, uncalibrated DN, and if you want, then you can work with that. Typically you have to convert the image from its RAW format to (at least) something like an uncalibrated PIX format if you don't want it calibrated.
Their software (the one aware of) is called RCX and it is an IDL .sav file; I think (not sure about this) you don't ned an IDL license for it.
RCX allows you to apply necessary corrections (dark subtraction, 2nd order corrections, frame shift smear - any or all as requested, but typically the order is dark, frame shift smear, 2nd order) and calibration (if requested). You can choose if you want the data output as different data types. Most of the time we get scaled radiance, i.e., radiance in physical units * scale factor so we can store in two-byte signed ints. I'm pretty sure you can also output to float, but I'm not sure.
ITRES used to have Windows, Linux, and Mac versions of their software available, but I am not sure if they still do. They may have gone to the RCX method, which doesn't require different versions.
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Difference between Multispectral and hyperspectral image analysis in agriculture crops.
Relevant answer
Answer
Multispectral images have a very detailed and strict set of bands, while the Hyperspectral images have a lot of continues bands. The Pros and Cons really depends on what you are interested in observing.
Multispectral images are easier to use, because of the fewer amounts of bands. This means that if you can distinguish the features you are looking for using multispectral images, it makes more sense, since it will narrow down the amount of choices you have to make while using the bands.
Hyperspectral images however can detect other features that the multispectral can not, increasing the potential of making new discoveries, or connections not possible with the multispectral approach. If you can't detect specific features using multispectral images, you should try the hyperspectral images. Keep in mind that while the potential is larger, the options and choices are also more numerous, making it potentially more difficult and/or time-consuming to use.
  • asked a question related to Hyperspectral Remote Sensing
Question
9 answers
Hello everyone. I am working on sustainable infrastructures and my goal is to select the most optimum site for infrastructures in my area of interest to gain maximum sustainability. To achieve my goal i need to know whether the area of interest is contaminated by heavy metals, but for some reasons my priority is to use remote sensing to know the fact. Unfortunately remote sensing is not my expertise, so this is why i asked this question. Actually i need a clear and simple answer if it is possible.
Relevant answer
Answer
A comparative study could be made of the plant community in an uncontaminated ares and in contaminated ares with the same types of plants. Any change in spectral data might highlight some specific characteristics.
  • asked a question related to Hyperspectral Remote Sensing
Question
8 answers
I am trying to orthorectify an IRS 1C and an IRS 1D multi - spectral image using a DTM/ DEM. I have Cartosat 1 DEM of 1 Arc - Sec (30m). There are no RPCs provided by the vendor and I was told that the product isn't orthorectified nor geometrically corrected.
I use Erdas Imagine 2015 for working with Satellite Data. Any help on this will be highly appreciated.
Relevant answer
Answer
Hi When you do not have any of the RPC coefficients, you need to consider your work in several ways. One solution is to change the software used. I think you can use pci geomatica software and do it with DEM and polynomial rational function. The next solution is to use topographic maps either DTM or DEM to extract photographic control points. In this case you have to rectify your image with software like PCI or ERDAS.
  • asked a question related to Hyperspectral Remote Sensing
Question
2 answers
Hi ,
I am evaluating the potentials of using S2 imagery with spectral unmixing techniques to retrieve physical properties of beach sand, such as granulometry, humidity and possibly spectrafacies (intendend as discrete classes of mineral mixtures occurring along the Victorian coastline, Australia).
The endmembers I will use are processed based on my VNIR (350-1075 nm) field spectroscopy campaign (ongoing) and planned Vis-SWIR (350-2500 nm) lab-based spectroscopy of sand samples from cross-shore profiles.
I think I will use Linear Spectral Unmixing, depending of the level of intimate mix I will discover in my sand samples.
However, I find it hard to find good literature.
Any idea??
Regards,
Nicolas Pucino
Relevant answer
Answer
Nitesh Patidar Thx for your suggestions!
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
Hi,
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.
Regards,
Sundara
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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..
Relevant answer
Answer
DigitalGlobe "open Data Program" has very good high resolution images of India check it out https://www.digitalglobe.com/opendata/flooding-in-india/pre-event
And also you can download free data sets from Copernicus scihub (SAR (Sentinel-1A) and optical Sentinel-2) and usgs earthexplorer (Landsat TM, ETM and OLI).
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
I am trying to process the wheat crop data collected using ASD for reflectance. However, I see two different options in ViewSpecPro software- Absolute reflectance and reflectance(transmittance). May I know the difference between them and what should be appropriate in studying variation in leaf reflectance among wheat genotypes due to disease and stress?
Relevant answer
Answer
Hello,
Usually, one measures relative reflectance on the field and, when back to the office, calculates the absolute reflectance values. A nice step-by-step manual and Matlab code for this can be found in <https://www.research.ed.ac.uk/portal/en/publications/the-field-spectroscopy-facility-post-processing-toolbox-user-guide(b3f7f53d-c0e1-4cfa-a650-a842c8cade9e).html>.
We have used this methodology at our paper < >.
Hope it helps!
Good work.
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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.
Relevant answer
Answer
Obviously, as per the MATLAB scaling is needed. I.e. each band image need to be scaled to 256 bins (intensity range 0-255 uint8 format), then the simple "entropy()" can be used to find the entropy. If further the problem exists, let me know, I can share the MATLAB code.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
I am currently trying to focus ALOS Level 1.0 data using Sarscape 5.1 in order to do SBAS-InSAR work.
I have no experience in doing so. I am not happy with the result I obtain, please see an example of result here (over urban area)
The settings I use:
Data type: ALOS PALSAR Single Pol
Global and Other Parameters are set to default
Can you confirm the result I obtain are not what I am suppose to obtain ?
How can I improve the focusing ?
Regards
Relevant answer
Answer
You need a focussing module in ENVI SArscape which will cost you. Better use Sentinel (open source).
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
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.
Thanks.
Relevant answer
Answer
Thanks and good luck
  • asked a question related to Hyperspectral Remote Sensing
Question
1 answer
The IEEE GRSS data fusion challenge has a dataset with both HSI and LiDAR data. Any idea how to get them?
Relevant answer
Answer
Hi Debakanta,
You have to register in the IEEE GRS contest website to get the dataset. Check this URL:
Good Luck
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
I am gathering papers about intertidal sediment (sandy beaches) characterisation (facies mapping) based on spectroradiometry.
I am planning to go out in the field, collect sand samples from the swash zone to the backdune depositional environments, evaluate sediment charachteristics and relate them to their spectras.
The spectral profile of bare sand is almost featureless within the VIS range, however, by using a 300-1000 nm spectroradiometer, I hope I will get enough heterogeneity in spectral response to map different "sands" within a sandy beach.
The literature is full of papers about using spectra to get sediment granulometry, mineralogy, organic matter, humidity, and other variables.
However, I am looking into papers about sand classification with broader classes that intrinsically inherit the complex spectral response from their biophysical heterogeneity .
Any idea?
Nick
Relevant answer
Answer
Thank for sharing your views Harald G. Dill .
I will keep on investigating until I find an optimal solution.
Best Regards,
Nick
  • asked a question related to Hyperspectral Remote Sensing
Question
22 answers
Is it required to normalize the reflectance with respect to one another when spectra of the same object and same lighting conditions are obtained using two different sensors?
Relevant answer
Thats ok. I extracted drone spectra from several neighboring pixels.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
* 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?
Relevant answer
Answer
You need to model multi-variate regression (PLSR/PCR) between each laboratory obtained soil nutrient data of the sample points, keeping as dependent variable (Y) and spectral reflectance of the sampling points obtained from HYPERION data as independent variable (X). One usually predicts the nutrient value from the relationship between X and Y and cross-validates the predicted value through examining the precision of fit in linear regression between the actual and predicted values of nutrient.
You can learn about the MATLAB implementation of PLSR/PCR from the following link:
  • asked a question related to Hyperspectral Remote Sensing
Question
1 answer
External Parameter Orthogonalisation (EPO) algorithm is used to remove the effect of soil moisture from NIR spectra for the calibration of SOC (Soil Organic Carbon) content. This algorithm is used for pre-processing of spectra of soil taken from spectroradiometer and then PlS (Partial Least Square) regression is apllied.
Relevant answer
Answer
Never used EPO but there is a Thesis Dissertation by Nanning Cao that can help
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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 !
Relevant answer
Answer
Hi,
I found this paper that maybe related with your research
”"Variety Identification of Single Rice Seed Using Hyperspectral Imaging Combined with Convolutional Neural Network"
There are also several papers that discuss about plant disease recognition using HSI and CNN.
"Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps "
"Classifying Wheat Hyperspectral Pixels of Healthy Heads and Fusarium Head Blight Disease Using a Deep Neural Network in the Wild Field "
Hope it helps your research.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
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.
Regards
Relevant answer
Answer
Hello!
Yes! the careful examination/interpretation of remote sensing images by using various false color composites will help us to collect the signature of land use/land cover classes effectively.
You may refer following article for information about, how to achieve better classification accuracy.
All the best
  • asked a question related to Hyperspectral Remote Sensing
Question
6 answers
While spatial, spectral and temporal advantages of multitemporal hyperspectral images provide opportunities for advancing the compression and classification techniques. So I need multitemporal remote sensing hyperspectral data 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 hyperspectral images then please give the link here.
Relevant answer
Answer
Communicate and request to USGS for EO-1 hyperspectral scenes.
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
I am interested to work on the archaeological mound. So for the preparation of the digital map of the archaeological mound which software can be used?
Relevant answer
Answer
yes it is possible from using laser scanner like 3d laser scanner Trimble
regards
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
I have a image dataset (hyperspectral) & i am using matlab as a tool. I want to implement the PCA on this hyperpspectral image dataset.
Relevant answer
Answer
Here is a very good source of PCA including presentation and source code Presentation Principal Component Analysis (PCA) : An Overview Article Principal component analysis - a tutorial Alaa
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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
Relevant answer
  • asked a question related to Hyperspectral Remote Sensing
Question
6 answers
For review study, I need the name of latest existing techniques used for remote sensing satellite image compression for lossless, near lossless, lossy in all possible cases such as predictive based coding, transform based coding, dictionary based coding. hybrids coding etc.
Need your help or suggestion plz reply.
Relevant answer
Answer
Remote Sensing Image Compression: A Review , Shichao Zhou, Chenwei Deng, Baojun Zhao , Yatong Xia, Qisheng Li, and Zhenzhong Chen. 2015 IEEE International Conference on Multimedia Big Data.
  • asked a question related to Hyperspectral Remote Sensing
Question
13 answers
Dear Researchers,
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.
Best, Vivek
Relevant answer
Answer
Hi All, I tried to put all the references to the publicly available hyperspectral datasets. I hope it is of help, incase if I'm missing some, please let me know, I can update it. Thanks
best, Vivke
  • asked a question related to Hyperspectral Remote Sensing
Question
9 answers
is there some algorithm or technique to detect specific vegetation species using hyperpsectral remote sensing on the basis of there spectral signature?
Relevant answer
Answer
We need an excellent image interpretation technique...
  • asked a question related to Hyperspectral Remote Sensing
Question
8 answers
Geothermal Energy has long been regarded as Green Energy's silver bullet. And rightly so because of its potential as a stable, secure, environmentally friendly and a cheap Energy resource. But there are some obstacles.
Firstly, Not everyone lives on top of a Volcano! Unlike wind and solar installations which can be built more or less anywhere, Geothermal Power Plants can only be built on geological hotspots that exists less than 10 % of our planet. Secondly, even in hot spots like Iceland, Engineers must deal with the most daunting technical challenge facing geothermal. Drilling! That's because all successful Geothermal ventures require three vital elements. Hot Rock, Water and close proximity to the resource. Thirdly, money and potential exploration risks are additional issues to be dealt with.
Remote Sensing techniques have been aiding in identification of Geothermal Hot spots with thermal anomaly, geological and mineral mapping studies. Geophysical techniques such as resistivity, gravity, seismic and geodetic measurements are valuable in the exploration phase. Next, Geochemical sampling and analysis takes over. RS & GIS are also applicable in Environment Impact Assessments after a Geothermal Power Plant is set up. Recent developments have seen the arrival of Unmanned Aircraft Vehicles (UAVs) for geothermal exploration.
What are the challenges faced by the Geothermal Explorers in different locations such as Indonesia, Kenya, US, Philippines, Japan, Iceland, NZ, Aus., EU and elsewhere. Are there any potential hazards due to their proximity to Volcanic systems.  
Requesting all subject-matter experts to enlighten with their relevant answers.
Relevant answer
Answer
India has identified seven geothermal provinces with probable extraction of industrial scale. Challenges are many. First of all to delineate the shallow or deep reservoir, entire geothermal field needs to be mapped. The development of conceptual model of geothermal field is must. For this, geophysical exploration data will certainly be required so that predicted conceptual model is conceivable and acceptable. Once the conceptual model is accepted, next conceiving the heat transport mechanism properly corresponding to the identified reservoir in a geothermal field is must for proper estimation of extraction temperature.
  • asked a question related to Hyperspectral Remote Sensing
Question
19 answers
I am using arcGIS 10.3 and geotiff file from landsat 8.
Relevant answer
Answer
Loris, USGS provides a 'Spectral Characteristics Viewer' in order to figure out which Landsat 8 (and others) bands are most suited for the desired research application. If I were you, I would start with this tool first. In addition, I've added some other relevant links.
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
The Salinas scene hyperspectral data set can be found in the below link as a .mat file. The description says the values are in at-sensor radiance values. I need to convert them to surface reflectance for further analysis. Can anyone suggest a method and also mention the relevant sources used in the process.
Relevant answer
Answer
I want to know the exact method (also including any constant values) to convert the PARTICULAR hyperspectral image's Radiance values to Reflectance values. It is a famous image called 'Salinas Scene' The link to download the .mat file of that image below.
  • asked a question related to Hyperspectral Remote Sensing
Question
9 answers
I have high resolution aerial photography (12.5 cm) data which only has bands I, 2 and 3. I am trying to detect individual tree species.
How can I calculate a near infrared band for this data-set (the 12.5 cm resolution) using sentinel band 8 data (taken around the same date and time).
I am using Google Earth Engine to create a cloud free Mosaic for my study area.
Relevant answer
Answer
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
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
Relevant answer
Answer
You can search the EO Hyperion archive and download products on: https://earthexplorer.usgs.gov/
The satellite was decommissioned in March 2017, which means that no scenes will be addeded after that. https://lta.cr.usgs.gov/ALI
I also find the scene extents of roughly 40x7 km quite unfortunate...
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
Hi,
While using the HySpex camera, I am facing the problem of Keystone distortion across the scan line. Although I am using the camera for close range imaging, this is a well-known problem in remote sensing community and therefore, I will appreciate if someone can help me to correct it. I have the sensor model file as well, but I am not sure how to use it for correction...
Relevant answer
Answer
I noticed this post and would like to make some clarifying remarks from HySpex. As Haris correctly explained in his last post, the initial issue he raised had nothing to do with keystone (which is very small in our cameras….typically less than +\- 10 % of a pixel), but rather a variation in pixel size across the FOV which is normal to a large or small degree in any camera. The described variation in pixel size is characterized in great detail during production and these data (the sensor model) are supplied with the camera (along with all the other calibration data, detailed test report, etc), allowing the user to manipulate the data and sampling grid as preferred.
It should be straightforward to resample the images to get equal pixel size, e.g. in MatLab (by using the sensor model data).
So far, no-one else in our customer base has requested a dedicated SW tool to do this kind of resampling, so writing a MatLab script was what we originally proposed by email before the question was posted. Since we heard nothing after suggesting that, we assumed the problem had been solved and were a bit surprised that it was brought up in this forum, and even more surprised that it referred to a keystone effect.
For our airborne users, the sensor model has always been used directly in the georeferencing SW (e.g. PARGE) to georeference the data and resample to the chosen map grid, but the PARGE is not directly suitable for lab applications.
Based on Haris’ need, we have now developed a simple resampling SW tool for this purpose to use for lab measurements.
But we fully support Luis Alonso's approach as explained above....better to resample the processed data to the preferred grid after the data analysis, in order to preserve the best quality and full integrity of the data you are analyzing.
Regarding the “distortion” mentioned in the last post, this is could be due to a combination of sub-optimal acquisition settings (e.g. speed) and that the square samples were not aligned with the scan axis (which makes the object look skewed) during the scan. The camera could also be mounted with the linear FOV not being perpendicular to the scan axis, and/or the sample could have some height different from one end to the other. It seems like it has been elegantly solved in SW by Haris, but it is of course better to take care of this during the acquisition!
  • asked a question related to Hyperspectral Remote Sensing
Question
6 answers
The fusion of panchromatic images, providing high spatial resolution and multi/hyperspectral images of lower spatial, but high spectral resolution, is well known under the term of pansharpening. In several talks, I've often noted the statement, that spectral overlapping of PAN and MS/HS sensors is a requirement to apply pansharpening approaches. I would like to ask whether this spectral overlap is a strict and general requirement or if a high correlation of spatial information between a PAN image and upscaled MS/HS band visualizations or components is sufficient? Does it depend on the choice of the algorithm (CS, MRA) ? Looking forward to your answers. Kind regards, Chris.
Relevant answer
Answer
Dear Christoph,
As you correctly state yourself: pansharpening is an approach in which the spatial information of a high resolution panchromatic image is integrated with the spectral information from an image with a lower spatial resolution. However, panchromatic fusion can be accomplished by many different techniques, of which the IHS (Intensity Hue Saturation) pansharpening is the most used one.
Exactly this IHS pansharpening approach is very sensitive to colour or spectral distortion. This is because the RGB image is in most cases not an image created by spectral data from the visible Red, Green and Blue bands (but for instance a false colour image consisting of a red, near-infrared and thermal band). Second, the RGB to HIS transform is relying on the HIS or HSL or HSV colour models. All three are very simple and old colour models in which the intensity channel is seriously flawed in respect to human perception. This means that the HIS transform does not really properly separate the intensity component from the chromatic components of the image. As a result, considerable spectral distortion will occur if the spectral range of the three bands of the colour composite image are very different from the range of the panchromatic band.
Besides, there is also the very popular Brovey pansharpening approach. It achieves a similar result to that of the IHS pansharpening, it is just much faster. However, it also can introduce colour distortion.
Some of these fusion approaches use image histogram matching and channel normalisation to get imagery with less spectral differences from the original one, whereas others do not. So, very often, it is difficult to accurately compare pansharpening algorithms and depending upon the imagery, the algorithm and the use of histogram matching and channel normalisation, spectral distortion can be more or less pronounced.
There have been some developments in pansharpening to achieve a decent and robust preservation of the spectral characteristics of the colour image. One category is wavelet-based pansharpening, while another is Principal Component Analysis (PCA) based. Third, there is the smoothing filter‐based intensity modulation (SFIM) (Liu, J.G. 2000. Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details. International Journal of Remote Sensing, 21 (18), 3461–3472. ).
However, SFIM is based on a model of the solar radiation, so the technique is not applicable to pansharpen images with different imaging and illumination geometry.
I hope that helps a bit.
Cheers,
Geert
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
Hello.
Could you please share your experience on the interpretation of red edge data in UAV remote sensing.
We recently used a drone with a camera with green, red, NIR, red edge and RGB spectrums.
I am confused about the meaning of red edge data: That is to say;
Is the data from the red edge spectrum/ band a kind of reflectance at a specific band? If so what is the wavelength range?
Or Is it the wavelength at which the reflectance curve sharply rises from red band to NIR band?
And also how to interpret the data?
Thanks in advance.
Muharrem Keskin, Mustafa Kemal University
Relevant answer
Answer
The red edge refers to the wavelengths between approx. 0.7 and 0.8 µm, the region between the red, where reflectance from green vegetation is very low and the near infrared where the reflectance is very high.
Now, there are sensors which record wavelenghts within this spectrum like e.g. Sentinel-2 which has bands at 0.705 and at 0.74 µm. The information gives deeper insights in the biochemistry of the leafs as the reflectance in this spectrum is sensitive e.g. to the chlorophyl content. See for example this poster for getting an impression what can be done with this information: http://old.esaconferencebureau.com/docs/12c04_docs2/poster1_18_clevers.pdf
If your drone camera records in this spectrum, you can use this information for example as proxy for the chlorophyl content of the leaves. But the interpretation depends of course also on the scope of your study.
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
I intend to detect the absorption features of heavy metals or the proxy minerals in the range of 400-2500nm and I plan to start with artificial contaminated samples. Shall I mix pure metal (e.g., Zn, Pb, Cu) with soils/minerals or mix the compound/solution (metal cation like Zn(II), Pb(II), Cu(II)) with soils/minerals? Any suggestions and literatures/links are welcome.
Thanks in advance.
Relevant answer
Answer
No point adding metals since that would be a most unusual form for the elements to be present.   I suggest that it's worthwhile looking at the literature for naturally abundant chemical forms.of minerals and their spectroscopic properties.  
  • asked a question related to Hyperspectral Remote Sensing
Question
15 answers
I was performing the both classifiers for two different hyperspectral datasets. For one dataset SVM is performing better and for the other one RF is performing better. What could be the probable reasons for this results!
Relevant answer
Answer
Dear Subir,
First, study the basics of machine learning. Each method has different characteristics. Well, it is really up to the learning process of each method. However SVM is more popular for the analysis of hyperspectral data. The underlying reason of SVM’s popularity for classification is achieving the high classification accuracy with a small number of training data and able to outperform than other conventional methods such as ANN and ML classification (not everytime, of course). However in some cases, RF can outperform SVM depending upon the input data and training data. 
Therefore we can not say any of them is more powerful. Also look at the "no free lunch theorem" then you can understand better what we say. Hope it is clear.
See this paper: Ustuner, M., Sanli, F. B., and Abdikan, S.: BALANCED VS IMBALANCED TRAINING DATA: CLASSIFYING RAPIDEYE DATA WITH SUPPORT VECTOR MACHINES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 379-384, https://doi.org/10.5194/isprs-archives-XLI-B7-379-2016, 2016.  
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Are there any free hyperspectral image datasets available of image compression?
Relevant answer
Answer
Yes, Image compression are methods to reduce the size of images, there aren't specific data for image compression. you can test your own methods on such data.
  • asked a question related to Hyperspectral Remote Sensing
Question
7 answers
Doing research in HSI classification on SVM based classifier. I'm using standard data sets for classification. I want to validate the outcomes with other classifier. It's enough to compare with the existing works or need any specific? I'm confused in it. Advanced thanks for valuable comments.
Relevant answer
Answer
The Map Comparison Kit (MCK) is a software tool for the comparison of raster maps.
The program allows users to obtain a good understanding of the differences between pairs of maps, concerning   http://mck.riks.nl/
the overall extent of the differences
the spatial distribution of the differences
the nature of the differences
the measurement scale of the maps (nominal, ordinal, interval or ratio scale)
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
I 'd like to do band selection on hyperspectral images, i Found a lot of techniques in literature. which one is the most significant? and is there any libraries that can help me?
Relevant answer
Answer
Hi,
I agree with Rajasheker's comments because band selection usually depends on your application. For your consideration, please find below three papers using three different approaches: 
-Multispectral synthesis of daylight using a commercial digital CCD camera, J. L. Nieves, E.M. Valero, S.M.C. Nascimento, J.Hernández-Andrés and J. Romero, Applied Optics, Vol. 44, N. 27, pp. 5696-5703, (2005).
-Developing an optimum computer-designed multispectral system comprising a monochrome CCD camera and a liquid-crystal tunable filter, M.A. López-Álvarez, J. Hernández-Andrés, J. Romero, Applied Optics, vol. 47, 4381-4390 (2008).
-Evaluating a logarithmic kernel for spectral reflectance estimation - effects on model parametrization, training set size and number of sensor spectral channels, TT. Eckhard, E.M. Valero, J. Hernández-Andrés, V. Heikkinen, Journal of the Optical Society of America A, vol. 31, N.3, pp. 541-549 (2014).
Best,
Juan Luis
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
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
Relevant answer
Answer
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
Hi everyone,
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.
Thank you 
Relevant answer
Answer
Hi,
if you consider not geo-corrected radiance data we can give this approach http://dx.doi.org/10.3390/rs61111082 (most pushbroom sensors are affected by temporal variations of the dark current and related miscalibration) or this approach http://dx.doi.org/10.3390/s110606370 a try else there are some smoothing techniques as Atilio said.
Cheers, Chris
  • asked a question related to Hyperspectral Remote Sensing
Question
3 answers
in an equation for emissivity  calculation  i should to determine the value which is exactly boundary between soil and vegetation  and the value which is placed between mixture pixels(soil+vegetation) and full vegetation ones, on NDVI image using histogram.
Relevant answer
Answer
Which equation are you using to calculate emissivity? Do you have any reference that we can have a look at? Are you using emissivity for Land Surface Temperature (LST) estimation?
If you mean the NDVI based emissivity which Sobrino et al. (2004) talks about in his original research paper (link attached), they use NDVI < 0.2 as bare soil, NDVI > 0.5 as fully vegetated and NDVI values between 0.2 and 0.5 as a mixture of both. However, you should keep in mind that this is specific to a particular location and it may be different for your study area. In any case, have a look at the paper.
  • asked a question related to Hyperspectral Remote Sensing
Question
9 answers
I want to use aster L1T for Crop Identification.  ASTER L1T contains terrain correction, rediometric and geometric correction. I want to know whether it needs atmospheric correction or not?
Relevant answer
Answer
Cross-talk and geometric corrections are applied on ASTER L1T data. But the digital numbers are still radiance at sensor and not reflectance on ground. So, if you want to convert radiance at sensor to reflectance on ground, you have to do atmospheric correction.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
Whether hyperspectral sensor penetrate the surface of earth or it captures the surface level material?
Relevant answer
Answer
Hyperspectral data have been used to detect sub-soil features in various disciplines. The MIVIS sensor was used in Archaeology:
Traviglia, A. (2006). MIVIS Hyperspectral sensor for detection of subsoil archaeological sites and interpretation support GIS: an Italian case study. Digital Discovery. Exploring New Frontiers in Human Heritage, 18-26.
ARPA has a project going on mine detection using hyperspectral data:
DePersia, A. T., Bowman, A. P., Lucey, P. G., & Winter, E. M. (1995, June). Phenomenology considerations for hyperspectral mine detection. In SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics (pp. 159-167). International Society for Optics and Photonics.
Hyperspectral data was part of the input to this study on topsoil mapping:
Selige, T., Böhner, J., & Schmidhalter, U. (2006). High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures. Geoderma, 136(1), 235-244.
In this article are discussed methods to study and monitor soils with hyperspectral data:
Viscarra Rossel, R. A., Taylor, H. J., & McBratney, A. B. (2007). Multivariate calibration of hyperspectral γ‐ray energy spectra for proximal soil sensing. European Journal of Soil Science, 58(1), 343-353.
  • asked a question related to Hyperspectral Remote Sensing
Question
4 answers
I am looking for the most appropriate rockfall model from the most recent in-use rockfall models. The available information on rockfall hazard will be combined in a Geographic Information System with a map of the existing trail of Kinabalu National Park to identify the trail sections which are potentially subject to rockfalls and degrees of rockfall hazard.
Relevant answer
Answer
You can use a model in GIS for assessing the susceptibility or potential instability level of rocky masses, as Romana 1985 or Anbalagan 1992, in order to individuate the potential detachment zones. Subsequently, you can carried out a rockfall trajectory analysis.
  • asked a question related to Hyperspectral Remote Sensing
Question
5 answers
i am looking for HJ-1A HSI (Hyperspectral Imager) Data. Can anyone post the links or give information regarding this?
Relevant answer
Answer
The data that you are looking for seem to be available here,
Data access information :Data distributed by CRESDA."
The link above should give you "Error 403 : acces forbidden", until you have access granted by CRESDA.
Here are the CRESDA contact information I found here http://www.cresda.com/EN/gjhz/jwsjfz/7461.shtml :
 Address:No.5,Fengxian East Road,haidian District,Beijing
Tel: +86 10 58937035
+86 10 58937060
+86 10 57503328
Fax: +86 10 58937026
  • asked a question related to Hyperspectral Remote Sensing
Question
2 answers
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.
Relevant answer
Answer
Did you solve your problem meanwhile? Extended Morphological Profiles in Hyperspectral imaging means that the datasets available are more precise because of the integration with other datasets. For coding application check Github or this book might be helpful, although is a little outdated http://isp.uv.es/papers/rem_sens_im_proc_12_ch02.pdf
  • asked a question related to Hyperspectral Remote Sensing