Publications

Researchers at the Remote Sensing Laboratory have published over 250 papers in academic journals.

Recent Publications

Vicarious CAL/VAL Approach for Orbital Hyperspectral Sensors Using Multiple Sites

Daniela Heller Pearlshtien, Stefano Pignatti, Eyal Ben-Dor

The hyperspectral (HSR) sensors Earth Surface Mineral Dust Source Investigation (EMIT) of the National Aeronautics and Space Administration (NASA) and Environmental Mapping and Analysis Program (EnMAP) of the German Aerospace Center (DLR) were recently launched. These state-of-the-art sensors have joined the already operational HSR sensors DESIS (DLR), PRISMA (Italian Space Agency), and HISUI (developed by the Japanese Ministry of Economy, Trade, and Industry METI and Japan Aerospace Exploration Agency JAXA). The launching of more HSR sensors is being planned for the near future (e.g., SBG of NASA, and CHIME of the European Space Agency), and the challenge of monitoring and maintaining their calibration accuracy is becoming more relevant. We proposed two test sites: Amiaz Plain (AP) and Makhtesh Ramon (MR) for spectral, radiometric, and geometric calibration/validation (CAL/VAL). The sites are situated in the arid environment of southern Israel and are in the same overpass coverage. Both test sites have already demonstrated favorable results in assessing an HSR sensor’s performance and were chosen to participate in the EMIT and EnMAP validation stage. We first evaluated the feasibility of using AP and MR as CAL/VAL test sites with extensive datasets and sensors, such as the multispectral sensor Landsat (Landsat5 TM and Landsat8 OLI), the airborne HSR sensor AisaFENIX 1K, and the spaceborne HSR sensors DESIS and PRISMA. Field measurements were taken over time. The suggested methodology integrates reflectance and radiometric CAL/VAL test sites into one operational protocol.

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A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols

Nicolas Francos, Daniela Heller-Pearlshtien, José AM Demattê, Bas Van Wesemael, Robert Milewski, Sabine Chabrillat, Nikolaos Tziolas, Adrian Sanz Diaz, María Julia Yagüe Ballester, Asa Gholizadeh, Eyal Ben-Dor

Soil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmonization techniques to merge the data. In recent years, several techniques for harmonization have been proposed, among which the internal soil standard (ISS) protocol is the most largely applied and has demonstrated its capacity to rectify systematic effects during spectral measurements. Here, we postulate that a spectral transfer function (TF) can be extracted between existing (old) SSLs if a subset of samples from two (or more) different SSLs are remeasured using the ISS protocol. A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil samples from two existing SSLs. These SSLs had already been measured using different protocols without any ISS treatment the Brazilian (BSSL, generated in 2019) and the European (LUCAS, generated in 2009–2012) SSLs. To verify the TF’s ability to improve the spectral assessment of soil attributes after harmonizing the different SSLs’ protocols, RF spectral-based models for estimating organic carbon (OC) in soil were developed. The results showed high spectral similarities between the ISS and the ISS–TF spectral observations, indicating that post-ISS rectification is possible.

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Land use/land cover in view of earth observation: data sources, input dimensions, and classifiers—a review of the state of the art

Prem Chandra Pandey, Nikos Koutsias, George P Petropoulos,

Prashant K Srivastava, Eyal Ben Dor

Land use/land cover (LULC) is a fundamental concept of the Earth's system intimately connected to many phases of the human and physical environment. Earth observation (EO) technology provides an informative source of data covering the entire globe in a spatial and spectral resolution appropriate to better and easier classify land cover than traditional or conventional methods. The use of high spatial and spectral resolution imagery from EO sensors has increased remarkably over the past decades, as more and more platforms are placed in orbit and new applications emerge in different disciplines. The aim of the present review work is to provide all-inclusive critical reflection on the state of the art in the use of EO technology in LULC mapping and change detection.

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Google Scholar

Sharad Kumar Gupta

Eyal Ben-Dor

Nicolas Francos

More publications

Heller-Pearlshtien, D., Pignatti, S., Greisman-ran, Uri, Ben-Dor, E., 2021. PRISMA sensor evaluation: a case study of mineral mapping performance over Makhtesh Ramon, Israel . International Journal of Remote Sensing, 42, 5882-5914.

Heller-Pearlshtien, D., Ben-Dor, E., 2022. CalVal Evaluation of DESIS products in Amiaz Plain and Makhtesh Ramon Test sites , In Proceedings of the 1st DESIS User Workshop—Imaging Spectrometer Space Mission, Calibration and Valida- tion, Applications, Methods The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 13–21. https://doi.org/10.5194

Heller-Pearlshtien, D., Pignatti, S.,Ben-Dor, E., 2023.Vicarious CAL/VAL approach for orbital hyperspectral sensors using multiple sites. Remote Sensing, 15(3):771. https://doi.org/10.3390/rs15030771.

Heller .D., Ben-Dor .E., (Visible and Near-infrared analysis for in Situ Characterization of soil profile, Soil Science of American journal, 2007, Vol 72, p. 1113-1123.

Francos, N., Heller-Pearlshtien, D., Demattê, J.A.M., Van Wesemael, B., Milewski, R., Chabrillat, S., Tziolas, N., Sanz Diaz, A., Yagüe Ballester, M.J., Gholizadeh, A., Ben-Dor, E., 2023. A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols. Appl. Environ. Soil Sci. 2023, 1–17. https://doi.org/10.1155/2023/4155390.

Sutton .M.W., Weiersbye. I. Galpin. J.S., Heller. D. , A GIS-based history of gold mine residue deposits and risk assessments of post-mining land uses on the Witwatersrand basin South Africa, Mine Closure 2006, Proceedings of the First International Seminar on Mine Closure, eds. Fourie. A and Tibbett. M. 13-15 September, Perth, Australia, p 667-678.

Weiersbye. I., Margalit. N., Feingersh.T., Revivo.G., Stark.R., Zur.Y., Heller.D.,Braun.O., Cukrowska. E.M., (2006), Use of airborne hyperspectral remote sensing (HSRS) to focus remediation and monitor vegetation process on gold mining landscape in South Africa, Mine Closure 2006, Proceedings of the First International Seminar on Mine Closure, eds. Fourie. A and Tibbett. M. 13-15 September, Perth, Australia, p 601-611.

Ogen, Y., Zaluda, J., Francos, N., Goldshleger, N., Ben-Dor, E., 2019. Cluster-based spectral models for a robust assessment of soil properties. Geoderma 340, 175–184. https://doi.org/10.1016/j.geoderma.2019.01.022

Paruta, A., Ciraolo, G., Capodici, F., Manfreda, S., Sasso, S.F.D., Zhuang, R., Romano, N., Nasta, P., Ben-Dor, E., Francos, N., Zeng, Y., Maltese, A., 2020. A Geostatistical Approach to Map Near-Surface Soil Moisture Through Hyperspatial Resolution Thermal Inertia. IEEE Transactions on Geoscience and Remote Sensing 1–18. https://doi.org/10.1109/TGRS.2020.3019200

Su, Z., Zeng, Y., Romano, N., Manfreda, S., Francés, F., Ben Dor, E., Szabó, B., Vico, G., Nasta, P., Zhuang, R., Francos, N., Mészáros, J., Dal Sasso, S.F., Bassiouni, M., Zhang, L., Rwasoka, D.T., Retsios, B., Yu, L., Blatchford, M.L., Mannaerts, C., 2020. An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources. Water 12. https://doi.org/10.3390/w12051495

Francos, N., Notesco, G., Ben-Dor, E., 2021. Estimation of the Relative Abundance of Quartz to Clay Minerals Using the Visible–Near-Infrared–Shortwave-Infrared Spectral Region. Applied Spectroscopy, 0003702821998302. https://doi.org/10.1177/0003702821998302

Francos, N., Ogen, Y., Ben-Dor, E., 2021. Spectral Assessment of Organic Matter with Different Composition Using Reflectance Spectroscopy. Remote Sensing 13, 1549. https://doi.org/10.3390/rs13081549

Francos, N., Romano, N., Nasta, P., Zeng, Y., Szabó, B., Manfreda, S., Ciraolo, G., Mészáros, J., Zhuang, R., Su, B., Ben-Dor, E., 2021. Mapping Water Infiltration Rate Using Ground and UAV Hyperspectral Data: A Case Study of Alento, Italy. Remote Sensing 13, 2606. https://doi.org/10.3390/rs13132606

Francos, N., Ben-Dor, E., 2022. A transfer function to predict soil surface reflectance from laboratory soil spectral libraries. Geoderma 405, 115432. https://doi.org/10.1016/j.geoderma.2021.115432

Francos, N., Gholizadeh, A., Ben Dor, E., 2022. Spatial distribution of lead (Pb) in soil: a case study in a contaminated area of the Czech Republic. Geomatic, Natural Hazards and Risk, 13, 610–620. https://doi.org/10.1080/19475705.2022.2039786

Demattê, J.A.M., Paiva, A.F. da S., Poppiel, R.R., Rosin, N.A., Ruiz, L.F.C., Mello, F.A. de O., Minasny, B., Grunwald, S., Ge, Y., Ben Dor, E., Gholizadeh, A., Gomez, C., Chabrillat, S., Francos, N., Ayoubi, S., Fiantis, D., Biney, J.K.M., Wang, C., Belal, A., Naimi, S., Hafshejani, N.A., Bellinaso, H., Moura-Bueno, J.M., Silvero, N.E.Q., 2022. The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication. Remote Sensing 14, 740. https://doi.org/10.3390/rs14030740

Demattê, J.A.M., Paiva, A.F., Poppiel, R.R., Rosin, N.A., Ruiz, L.F., Mello, F.A., Minasny, B., Grunwald, S., Ge, Y., Ben Dor, E., Gholizadeh, A., Gomez, C., Chabrillat, S., Francos, N., Ayoubi, S., Fiantis, D., Biney, J.K., Wang, C., Belal, A., Naimi, S., Hafshejani, N.A., Bellinaso, H., Moura-Bueno, J.M., Silvero, N.E.Q., 2022. Correction: Demattê et al. The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication. Remote Sensing. 2022, 14, 740. Remote Sensing 14. https://doi.org/10.3390/rs14061459

Ben Dor, E., Francos, N., Ogen, Y., Banin, A., 2022. Aggregate size distribution of arid and semiarid laboratory soils (<2 mm) as predicted by VIS-NIR-SWIR spectroscopy. Geoderma 416, 115819. https://doi.org/10.1016/j.geoderma.2022.115819

Francos, N., Gholizadeh, A., Demattê, J.A.M., Ben-Dor, E., 2022. Effect of the internal soil standard on the spectral assessment of clay content. Geoderma 420, 115873. https://doi.org/10.1016/j.geoderma.2022.115873

Romano, N., Szabó, B., Belmonte, A., Castrignano, A., Ben-Dor, E., Francos, N., Nasta, P., 2023. Chapter 6: Mapping soil properties for unmanned aerial system–based environmental monitoring, in: Unmanned Aerial Systems for Monitoring Soil, Vegetation, and River Systems. Elsevier.

Francos, N., Heller-Pearlshtien, D., Demattê, J.A.M., Van Wesemael, B., Milewski, R., Chabrillat, S., Tziolas, N., Sanz Diaz, A., Yagüe Ballester, M.J., Gholizadeh, A., Ben-Dor, E., 2023. A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols. Applied and Environmental Soil Science 2023, 4155390. https://doi.org/10.1155/2023/4155390

Francos, N., Ogen, Y., Ben-Dor, E., 2021. Spectral Assessment of Organic Matter with Different Composition Using Reflectance Spectroscopy. Remote Sensing 13, 1549. https://doi.org/10.3390/rs13081549

Francos, N., Ben-Dor, E., 2022. A transfer function to predict soil surface reflectance from laboratory soil spectral libraries. Geoderma 405, 115432. https://doi.org/10.1016/j.geoderma.2021.115432

Francos, N., Heller-Pearlshtien, D., Demattê, J.A.M., Van Wesemael, B., Milewski, R., Chabrillat, S., Tziolas, N., Sanz Diaz, A., Yagüe Ballester, M.J., Gholizadeh, A., Ben-Dor, E., 2023. A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols. Applied and Environmental Soil Science 2023, 4155390. https://doi.org/10.1155/2023/4155390