Evaluation of Sentinel-2 bands over the spectrum
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1 Evaluation of Sentinel-2 bands over the spectrum S.E. Hosseini Aria, M. Menenti, Geoscience and Remote sensing Department Delft University of Technology, Netherlands 1
2 outline ointroduction - Concept odata - Data preparation omethodology - Spectral Region Splitting (SRS) oresult oconclusion 2
3 Introduction o Improvement in surface monitoring - higher amount of spectral bands - narrower width o the precise spectral location and width of each band is important to recognize objects or phenomena on the earth accurately. o In this approach - first, a new method is introduced to select the most informative spectral regions of the electro-magnetic spectrum on hyperspectral images. - Second, the given divisions were compared with designed S2 bands to assess the location and width of them in terms of information content. 3
4 Introduction o Sentinel-2 will carry an optical payload with visible, near infrared and shortwave infrared sensors and provide enhanced continuity of SPOT- and Landsat-type data. Landsat SPOT Sentinel-2 4
5 Introduction Sentinel-2 SPOT-5 sensor Green Red NIR SWIR-1 Pan Band spectral bands (nm) Landsat 7 (ETM+ sensor) spectral bands (nm) Blue Green Red NIR SWIR SWIR Thermal Pan Band
6 Concept o the most informative spectral regions of the spectrum ( nm) o applied on hyperspectral images o over three different types of area including vegetation, water types and bare soil. The information theory developed by Shannon o This theory answers two fundamental questions about data compression and ultimate transmission rate of communication. o It expresses implicitly that by having more independent data, information content is increasing. o The method finds the regions of the spectrum which have the minimum relation with other regions to maximize the information content. o This set of bands can reconstruct and approximate the mean reflectance spectrum of the entire scene as well. 6
7 Data o Hyperspectral image o AVIRIS (Airborne Visible/InfraRed Imaging Spectrometer). o in 224 contiguous spectral channels (bands) o with wavelengths from 400 to 2500nm o 10 nm intervals across the solar reflected spectrum o "imaging spectroscopy or "imaging spectrometer data" rather than "hyperspectral. 7
8 Data otwo hyperspectral datasets acquired by AVIRIS othe left from Moffett Field over vegetation/urban/water region othe second dataset (right) from Cuprite, suitable for mineralogy investigation. o three different areas: vegetation, Water type, bare soil. odata preparation: after removing noisy channels Moffett Field has 195 bands, and Cuprite has199 bands. Figure 1. True color images from Moffett Field (left) and Cuprite (right). 8
9 Methodology Spectral Region Splitting (SRS) o The question of how the sampling of the spectrum can be optimized without losing significant spectral information has been studied by SRS method. o having more independent data, information content is increasing o SRS method starts with a single very wide spectral band covering the complete measured spectral range. o advantage: the wide band will have a much better signal to noise ratio than the individual channels. o disadvantage: all spectral details are lost 9
10 Methodology Spectral Region Splitting (SRS) -the optimum location of the split should be determined by measuring the dependency between the new bands, and by selecting that location where this is minimum. 10
11 Methodology Spectral Region Splitting (SRS) o The correlation coefficient random distribution, - the strength of a linear relationship between two variables with o Mutual information - a quantitative measurement between two random variables that can be thought of as the reduction in uncertainty about one random variable given knowledge of another 11
12 Methodology One band 31 bands 2 bands 71 bands Result of SRSc on vegetation area 12
13 Methodology oterminate point - Final result can reconstruct the mean reflectance graph for each area with more than 99% accuracy. o Removing highly correlated bands 13
14 Final result of SRS method - Vegetation area 19 divisions - water area 27 divisions - Bare soil area 17 divisions Vegetation - Vegetation area 16 division - water area 18 divisions - Bare soil area 15 divisions Water Bare soil 14
15 Comparison between S2 and SRS results The spectral divisions selected by SRS that cover Sentinel-2 bands entirely have been extracted from six datasets. 15
16 Information Content o Entropy shows the amount information in each band 6 5 information content of each band has almost a direct relation with the amount of its reflectance Vgt BSl Wtr 16
17 Information Content information content of S2 bands and selected spectral divisions by SRS method for three environmental applications vegetation, soil and water- entropy of those bands and corresponded divisions were calculated 17
18 Result points: 1- looking at the propose of designing each band mentioned in Sentinel-2 document (Sentinel-2 Mission Requirements Document) 2- one of the main mission of this satellite is to improve ground surface monitoring, beside detecting and mapping land cover/change, we focused more on surface phenomena, not atmospheric issues. information content in Sentinel-2 bands are usually more than SRS bands SRS method selected bands as wider as possible, however S2 bands are usually located in peak part of the spectrum in each region (such as Band-11 ( nm), and 12) The benefit of wider bands is that they have much better signal to noise ratio than narrow bands 18
19 Result o Band-12 ( ) is useful for Assessment of Mediterranean vegetation conditions, distinction of clay soils, monitoring of soil erosion, distinction between live biomass, dead biomass and soil o On bare soil area, this band was covered by two divisions in both SRS method ( nm, nm). There is a sudden drop in this part of soil reflectance. This drop is also observed in woody vegetation reflectance - It seems this part should divide into two bands for soil study. The second division ( nm) has advantages for investigating Calcite and Calcium Carbonate. This part is also sensitive to combination mode of OH in clay lattice. 19
20 Result o Six bands in near infrared plateau of vegetation in Sentinel-2 bands (5,6,7,8,8a,9) o have advantages for vegetation and biomass study such as Leaf Area Index(LAI), sensitive to total chlorophyll, and red edge retrieval o SRS method chose a very wide band consisting whole NIR plateau approximately between nm It shows in this region does not have very independent narrow bands, and many of the vegetation indices can be computed by this wide band, like LAI or NDVI. 20
21 Result - Bands 4, 5, and 6 were selected to reconstruct the red edge of vegetation reflectance - In general, we need three bands to reconstruct red edge; - In red (around 650nm), red edge, around 700, and one band in NIR plateau It seems a narrow band in trough part of red can reconstruct red edge more precisely as there is a drop near the end of the red region in vegetation reflectance. SRSMI is also selected a narrow band in this spectral part ( nm). 21
22 Result o Band-3 (centered 560) was designed in the green peak of the chlorophyll reflectance. o The location of green peak is between 530 to 570-nm, and it depends on chlorophyll contents of canopies. - SRS also selected a narrow division in this part on vegetation area centered in There is also another division in green-yellow region of vegetation area chosen by SRS. This division centered in 580nm most sensitive to pigment concentration in most leaves and canopies. These bands can be also useful to investigate about the stress on canopies 22
23 Result oband-1 and 2 centered in blue, which band-2 covers some part of green as well. osrs selected one wide band in vegetation area which cover almost blue region entirely. Band-2 in nm is sensitive, browning and soil background. Band-2 was covered with more than 2 divisions by SRS in bare soil area. It means for soil study this part should resample with narrower bands. 23
24 Conclusion An evaluation of Sentinel-2 spectral sampling in terms of information content This assessment was provided by a comparison with the most informative spectral regions of electromagnetic spectrum between nm The informative regions were selected by newly developed method called spectral region splitting method. It was specified that designed Sentinel-2 narrow bands were chosen in the parts of the spectrum which almost have high information content wider bands would also be responsible in some application like canopy studies and have their own advantages (higher SNR). 24
25 Thank you for your attention 25
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