Eyal Ben-Dor Department of Geography Tel Aviv University
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1 Spectral Imaging of Soils: past present and future Eyal Ben-Dor Department of Geography Tel Aviv University 2nd International Conference on Airborne Research for the Environment, DLR - the German Aerospace Research Center, in Oberpfaffenhofen, July 2017
2 OUTLINE Definitions Soil Spectroscopy and its information Deep Learning to extract soil attributes Soil Imaging and field spectroscopy, big data issues Soil Spectral libraries and importance Soil standardization Image visualization Interests New Spectral dimensions Sensors and Platforms (airborne): big to light maned aircraft to drones (VNIR only ) Satellites program Conclusion
3 Definition 1 Soil The upper layer of the earth ( 0-2m) represent its loose surface material which is dug, plowed and being a medium for plants to grow. (Thompson 1957) medium for plants to grow
4 Strong Link between Point and Image Spectroscopy Image Spectroscopy Geology Vegetation Water Point Spectroscopy Soil
5 Soil Spectrum An elegant wat to simplest the complexity of the soil system Iron Oxides Clays Hygroscopic Organic Water Matter Calcite Organic Matter Wavelength (mm)
6 Quantitative spectroscopy Chemometrics
7 First article on soil spectra quantification 1965 demonstrated the power of soil spectroscopy Clayey Soil and Soil Moisture Bowers and Hanks, 1965
8 1980 First Soil Spectral Library 5 spectral types in USA Around 4000 spectra Stoner, E.R. and M.F., Baumgardner, Characteristic variations in reflectance of surface soils. Soil Science Society of American Journal 45:
9 Common method Multiple Linear Regression Analyses calibration
10 Advanced in Agronomy 2015
11 Today: Supervised Machine Learning for data mining Limited output The Unscrumbler SPSS Drawbacks Limited configuration Matlab Requires Programming knowledge No Automation for Pre-processing Tomorrow : Automated Deep Leering Aproach PARACUDA One click button No need to be expert in machine learning approach Extracting the best model Image application
12 Software for data mining and image illustration Paracuda-II An automated data mining machine for soil chemometric analysis (point and imaging) E. Ben Dor 2015 FAST & AUTOMATICS
13 2017 and tomorrow 1. Find the code 2. Acquire the right hardware 3. Set up the environment Steps 1 to 6 are already configured, Just And see the results! 4. Import the right files 5. Installing all dependencies...packages, versions, OS etc 6. Errors.. Debugging.. Errors.. Debugging 7. Run 8. Results
14 Spectral Archive
15 Soil Spectral Library : chemistry and spectroscopy Soil Attributes Soil Spectra Files Sample Location OM Clay Lime. A1 34, % 34% 23.4% 36,654,32
16 Past : 1980 First Soil Spectral Library Around 4000 spectra
17 Today: World Soil Spectral Libraries (no measurement protocols) many users Estimation of total number of soil spectra : 400,000 (1980 4,000)
18 Today
19 Past no protocol for spectral measurements
20 Present and future : a new standard and protocol for global soil spectral library Standardization Reducing Non Systematic Soil Internal Standard Reducing Systematic Effects
21 Tomorrow : New Standard world wide Soil Spectral Library
22 Thematic Areas Adaptation to Climate Change (ACC) Improved Food Security Water Extremes Management Access to Raw Materials (ARM) Access to Energy (SENSE) (IFS) Protocol, SSL
23 WP 4 TAU-i-BEC mission To establish a soil spectral library SSL for the North Africa, Middle East and Balkans To establish a basic foundation to use the SSL for EO means (from field, air and domains) To built a data base with a GEOSS sharing regulation
24 Spectral Sensors laboratory and field
25 Field Spectrometer and Accessories Past PERS 1974 ASD 1994
26 Today and tomorrow : Many instruments
27 Today: Field soil measurement is leaning on the sun radiation
28 Today: Close moving chamber for 27/7 option
29 Tomorrow : Close chamber compatible with all spectrometers and easy to use Soil field Probe (SoilPRO ) Laboratory quality in field measurements Bare fiber SoilPRO
30 Past: Soil spectral Profiling
31 Tomorrow: Merging profiling spectroscopy with surface data
32 Imaging Systems
33 from heavy (past) to light sensors (present and future) Petri SPECIM March 23, 2015 we have sold now way over 4000 spectrographs, of which ~110 have gone into airborne AISA systems!
34 From point and scanning (past) to snap shot systems (present and future)
35 Imaging Platforms (air borne)
36 Past: Heavy aircrafts and complicated constructions (airborne) ASD
37 Present: light aircraft and UAVs (airborne)
38 Tomorrow: Combination between airborne and satellite 20 Km 4 Weeks
39 Interest
40 Number of papers and Patents Interest How point spectroscopy driven the image spectroscopy of soils Point Spectroscopy Past & Present Future Image Spectroscopy Year
41 Past: Special Issues on Soil (Field) Spectroscopy 2013 Impact Factor= As for March 27, 2015 In Total (11) Under Review (2) Pending Major Revisions (2) Revised Version Review (2) Pending Editor Decision (1) Published (3) Rejected & Archived (3)
42 Special Issues on Soil (Field) Spectroscopy Impact Factor= 2.72 As for March 27, 2015 In Total (11) Under Review (2) Pending Major Revisions (2) Revised Version Review (2) Pending Editor Decision (1) Published (3) Rejected & Archived (3)
43 the Remote Sensing Handbook (Volume I, II, III) Past Will be published by Taylor and Francis Inc. CRC Press, September 2015 Prasad T, Editor pp: Eyal Ben-Dor Tel Aviv University Jose A.M. Dematte University of Sao Paulo
44 Tomorrow
45 About 150 members visnir community Professional Groups VNIR-SWIR-TIR community 320 > 300 members
46 Tomorrow
47 Spectral Region
48 Today Tomorrow SPECTRAL REGION FOR HSR
49 Du, C., & Zhou, J. (2009). Evaluation of soil fertility using infrared spectroscopy: a review. Environmental Chemistry Letters, 7(2), Mid IR for soil P (soluble and solid)
50 Space Programs
51 Space Programs
52 Hyperspectral HSR Orbital Missions Launch and Lifetime Past Present Tomorrow 2018/ /24 ESA SENTINEL 10
53 Soil monitoring from space are playing a major role in SHALOM and SENTINEL 10 missions
54 Model from SSL Tomorrow s vision
55 Conclusions Soil Hyperspectal Remote Sensing is a growing field with a growing recognition Soil Hyperspectral Remote Sensing has a great potential in many directions. The future is bright in soil spectral imaging base on the knowhow already accumulated and on the forthcoming advance technology (sensors, accessories, platforms)
56 Thank You for Your Attention
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