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Literature Review

Literature Review

Literature Review

Whether you are a researcher, scientist, or simply interested in learning more about applications of Cubert’s hyperspectral cameras, we invite you to explore the literature list, which is updated regularly with new research, so you can stay up-to-date with all of the latest developments in hyperspectral imaging.

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Application Fields

Until beginning of 2022 more than 160 scientific papers have been published, which are about studies with or about our hyperspectral snapshot cameras. The application fields are spread widely, ranging from remote sensing in agriculture to microscopic applications for life sciences. See an overview on which fields our cameras are used in.

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Water Spectroscopy & Aquatic Vegetation

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  • ≤ 2020

    Torti, E., Leon, R., La Salvia, M., Florimbi, G., Martinez-Vega, B., Fabelo, H., Ortega, S., Callicó, G.M. and Leporati, F., 2020. Parallel classification pipelines for skin cancer detection exploiting hyperspectral imaging on hybrid systems. Electronics, 9(9), p.1503.
    Tags: lesion, dermatology, on-invasive and non-ionizing technique

    Leon, R., Martinez-Vega, B., Fabelo, H., Ortega, S., Melian, V., Castaño, I., Carretero, G., Almeida, P., Garcia, A., Quevedo, E. and Hernandez, J.A., 2020. Non-Invasive Skin Cancer Diagnosis Using Hyperspectral Imaging for In-Situ Clinical Support. Journal of clinical medicine, 9(6), p.1662.
    Tags: early detection, non-invasive, skin cancer, pigmented skin lesions (PSLs)

    Fabelo, H., Melián, V., Martínez, B., Beltrán, P., Ortega, S., Marrero, M., ... & Almeida, P. (2019, November). Dermatologic Hyperspectral Imaging System for Skin Cancer Diagnosis Assistance. In 2019 XXXIV Conference on Design of Circuits and Integrated Systems (DCIS) (pp. 1-6). IEEE.
    Tags: skin cancer, diagnosis, clinical

    Giannoni, L., Lange, F., Davies, A. L., Dua, A., Gustavson, B., Smith, K. J., & Tachtsidis, I. (2018). Hyperspectral imaging of the hemodynamic and metabolic states of the exposed cortex: investigating a commercial snapshot solution. In Oxygen Transport to Tissue XL (pp. 13-20). Springer, Cham.
    Tags: Medical, Oxygen, Tissue, Surgery

    Spigulis, J. (2017). Multispectral, fluorescent and photoplethysmographic imaging for remote skin assessment. Sensors, 17(5), 1165.
    Tags: skin assessment, video, multispectral
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Mineral Exploration & Geology

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Sensors, Systems & Calibration

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Video Spectroscopy

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  • 2021

    Bajić, M. (2021). Modeling and Simulation of Very High Spatial Resolution UXOs and Landmines in a Hyperspectral Scene for UAV Survey. Remote Sensing, 13(5), 837.
    Tags: unexploded ordnances (UXOs), landmines (LMs), cluster munition (CM), improvised explosive devices (IEDs), homemade explosive (HME) devices, and explosive remnants of war (ERW)

    ≤ 2020

    Racek, F., Baláž, T., & Melša, P. (2019, May). Spectral Characterization of Natural Background in Virtue of Reconnaissance Possibilities. In 2019 International Conference on Military Technologies (ICMT) (pp. 1-8). IEEE.
    Tag: Reconnaissance, military, NATO, spectral

    Bajic, M., Ivelja, T., & Brook, A. (2017). Developing a Hyperspectral Non-Technical Survey for Minefields via UAV and Helicopter. J. Conv. Weapons Destr, 21(11).
    Tags: weapon detection, minefields, ordnance
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Cultural Heritage & Archeology

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Ren, Y., Huang, W., Ye, H., Zhou, X., Ma, H., Dong, Y., Shi, Y., Geng, Y., Huang, Y., Jiao, Q. and Xie, Q., 2021. Quantitative identification of yellow rust in winter wheat with a new spectral index: Development and validation using simulated and experimental data. International Journal of Applied Earth Observation and Geoinformation, 102, p.102384.
Tags: Wheat pigment, water body, PROSPECT-D, yellow rust optimal index (YROI)

Shi, Y., Han, L., Kleerekoper, A., Chang, S., & Hu, T. (2021). A Novel CropdocNet for Automated Potato Late Blight Disease Detection from the Unmanned Aerial Vehicle-based Hyperspectral Imagery. arXiv preprint arXiv:2107.13277.
Tags: Late blight disease, spectral feature-based approach, CropdocNet model

Changchun, L. I., Chunyan, M. A., Peng, C. H. E. N., Yingqi, C. U. I., Jinjin, S. H. I., & Yilin, W. A. N. G. (2021). Machine learning-based estimation of potato chlorophyll content at different growth stages using UAV hyperspectral data. Zemdirbyste-Agriculture, 108(2).
Tags: potato, chlorophyll (Chl) content, support vector machine (SVM)

Cui, L., Yan, L., Zhao, X., Lin, Y., Jin, J., & Zhang, J. (2021). Detection and Discrimination of Tea Plant Stresses Based on Hyperspectral Imaging Technique at a Canopy Level. Phyton, 90(2), 621.
Tags: plant stress, the quality of tea, successive projection algorithm (SPA), K-nearest neighbor (KNN), Random Forest (RF), Fisher discriminant analysis

Khairunniza-Bejo, S., Shahibullah, M. S., Azmi, A. N. N., & Jahari, M. (2021). Non-Destructive Detection of Asymptomatic Ganoderma boninense Infection of Oil Palm Seedlings Using NIR-Hyperspectral Data and Support Vector Machine. Applied Sciences, 11(22), 10878.
Tags: Ganoderma boninense Infection, support vector machine (SVM), operating characteristic curve (AUC)

Zhu, W., Sun, Z., Yang, T., Li, J., Peng, J., Zhu, K., Li, S., Gong, H., Lyu, Y., Li, B. and Liao, X., (2020). Estimating leaf chlorophyll content of crops via optimal unmanned aerial vehicle hyperspectral data at multi-scales. Computers and Electronics in Agriculture, 178, p.105786.
Tags: Leaf chlorophyll content (LCC), nutrition in crop plants, nitrogen (N)

Ma, H., Huang, W., Dong, Y., Liu, L., & Guo, A. (2021). Using UAV-Based Hyperspectral Imagery to Detect Winter Wheat Fusarium Head Blight. Remote Sensing, 13(15), 3024.
Tags: Fusarium head blight (FHB), wavelet features (WFs)

Feng, H., Tao, H., Zhao, C., Li, Z., & Yang, G. (2021). Comparison of UAV RGB Imagery and Hyperspectral Remote-sensing Data for Monitoring Winter-wheat Growth. Link
Tags: comprehensive growth index (CGI), modified green-red vegetation index(MGRVI)

Zhang, J., Tian, Y., Yan, L., Wang, B., Wang, L., Xu, J., & Wu, K. (2021). Diagnosing the symptoms of sheath blight disease on rice stalk with an in-situ hyperspectral imaging technique. Biosystems Engineering, 209, 94-105.
Tags: Rhizoctonia solani, stalk disease, Hyperspectral Feature Profile Scanning-based Scab Detection (HFPSSD)

Zhang, Y., Xia, C., Zhang, X., Cheng, X., Feng, G., Wang, Y., & Gao, Q. (2021). Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images. Ecological Indicators, 129, 107985.
Tags: aboveground biomass (AGB), Stepwise regression, random forest (RF) regression, XGBoost regression

Azmi, A. N., Bejo, S. K., Jahari, M., Muharam, F. M., & Yule, I. (2021). Differences between healthy and Ganoderma boninense infected oil palm seedlings using spectral reflectance of young leaf data. Basrah Journal of Agricultural Sciences, 34, 171-179.
Tags: basal stem rot (BSR), Ganoderma boninense

Zhao, Y., Sun, Y., Lu, X., Zhao, X., Yang, L., Sun, Z., & Bai, Y. (2021). Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures. Ecological Indicators, 122, 107267.
Tags: physiological traits, area-based content, mass-based concentration

Wijesingha, J., Dayananda, S., Wachendorf, M., & Astor, T. (2021). Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters. Sensors, 21(8), 2886.
Tags: monsoon crops, tropical regions, finger millet, maize, lablab

Yue, J., Zhou, C., Guo, W., Feng, H., & Xu, K. (2021). Estimation of winter-wheat above-ground biomass using the wavelet analysis of unmanned aerial vehicle-based digital images and hyperspectral crop canopy images. International Journal of Remote Sensing, 42(5), 1602-1622.
Tags: above-ground biomass (AGB), image wavelet decomposition (IWD), continuous wavelet transform (CWT)


Wang, L., Chen, S., Peng, Z., Huang, J., Wang, C., Jiang, H., Zheng, Q. and Li, D., (2021). Phenology Effects on Physically Based Estimation of Paddy Rice Canopy Traits from UAV Hyperspectral Imagery. Remote Sensing, 13(9), p.1792.
Tags: PROSAIL model, leaf area index (LAI), leaf cholorphyll content (LCC), canopy chlorophyll content (CCC)

Wang, L., Chen, S., Li, D., Wang, C., Jiang, H., Zheng, Q., & Peng, Z. (2021). Estimation of paddy rice nitrogen content and accumulation both at leaf and plant levels from UAV hyperspectral imagery. Remote Sensing, 13(15), 2956.
Tags: plant nitrogen content (PNC), leaf nitrogen accumulation (LNA), plant nitrogen accumulation (PNA)

Lu, J., Li, W., Yu, M., Zhang, X., Ma, Y., Su, X., Yao, X., Cheng, T., Zhu, Y., Cao, W. and Tian, Y., (2021). Estimation of rice plant potassium accumulation based on non-negative matrix factorization using hyperspectral reflectance. Precision Agriculture, 22, pp.51-74.
Tags: plant potassium accumulation (PKA), non-negative matrix factorization (NMF)

Guo, A., Huang, W., Dong, Y., Ye, H., Ma, H., Liu, B., Wu, W., Ren, Y., Ruan, C. and Geng, Y., (2021). Wheat yellow rust detection using UAV-based hyperspectral technology. Remote Sensing, 13(1), p.123.
Tags: exture features (TFs), leaf scale disease monitoring

Yue, J., Guo, W., Yang, G., Zhou, C., Feng, H., & Qiao, H. (2021). Method for accurate multi-growth-stage estimation of fractional vegetation cover using unmanned aerial vehicle remote sensing. Plant Methods, 17(1), 1-16.
Tags: Fractional vegetation cover (FVC), pixel dichotomy model (PDM), crop canopy chlorophyll content (CCC)

Zhao, Y., Sun, Y., Chen, W., Zhao, Y., Liu, X., & Bai, Y. (2021). The Potential of Mapping Grassland Plant Diversity with the Links among Spectral Diversity, Functional Trait Diversity, and Species Diversity. Remote Sensing, 13(15), 3034.
Tags: biodiversity, terrestrial ecosystem, semi-arid

Shu, M., Shen, M., Zuo, J., Yin, P., Wang, M., Xie, Z., Tang, J., Wang, R., Li, B., Yang, X. and Ma, Y., 2021. The Application of UAV-Based Hyperspectral Imaging to Estimate Crop Traits in Maize Inbred Lines. Plant Phenomics, 2021.
Tags: aboveground biomass (AGB), total leaf area (TLA), leaf chlorophyll content (LCC), thousand kernel weight (TWK)

Shu, M., Zuo, J., Shen, M., Yin, P., Wang, M., Yang, X., … & Ma, Y. (2021). Improving the estimation accuracy of SPAD values for maize leaves by removing UAV hyperspectral image backgrounds. International Journal of Remote Sensing, 42(15), 5864-5883.
Tags: narrowband, SPAD, maize, vegetation indices

Schulze‐Brüninghoff, D., Wachendorf, M., & Astor, T. (2021). Remote sensing data fusion as a tool for biomass prediction in extensive grasslands invaded by L. polyphyllus. Remote Sensing in Ecology and Conservation, 7(2), 198-213.
Tags: fresh and dry matter yield (FMY/DMY), Lupinus polyphyllus, terrestrial 3d laser scanner

Xu, X., Nie, C., Jin, X., Li, Z., Zhu, H., Xu, H., … & Feng, H. (2021). A comprehensive yield evaluation indicator based on an improved fuzzy comprehensive evaluation method and hyperspectral data. Field Crops Research, 270, 108204.
Tags: comprehensive yield evaluation indicator (CYEI), winter-wheat, Growth status and trend (GST)

Astor, T., & Wachendorf, M. (2021). Biomass Estimation of Vegetables—Can Remote Sensing Be a Tool for It?. In The Rural-Urban Interface (pp. 95-102). Springer, Cham.
Tags: crop height, vegetable crops, Bangalore in Bengaluru

Wang, T., Liu, Y., Wang, M., Fan, Q., Tian, H., Qiao, X., & Li, Y. (2021). Applications of UAS in Crop Biomass Monitoring: A Review.Frontiers in Plant Science, 12, 595.
Tag: nondestructive, smart agriculture, precision agriculture.

Sun, Z., Wang, X., Wang, Z., Yang, L., Xie, Y., & Huang, Y. (2021). UAVs as remote sensing platforms in plant ecology: review of applications and challenges.Journal of Plant Ecology, 14(6), 1003-1023.
Tags: review, plant ecology, systems, snapshot, costs


Lu, B., Dao, P. D., Liu, J., He, Y., & Shang, J. (2020). Recent advances of hyperspectral imaging technology and applications in agriculture.Remote Sensing, 12(16), 2659.
Tags: review, imaging technology, hyperspectral

Eskandari, R., Mahdianpari, M., Mohammadimanesh, F., Salehi, B., Brisco, B., & Homayouni, S. (2020). Meta-analysis of unmanned aerial vehicle (UAV) imagery for agro-environmental monitoring using machine learning and statistical models.Remote Sensing, 12(21), 3511.
Tags: Agriculture, forestry, grassland mapping, review

Vohland, M., & Jung, A. (2020). Hyperspectral imaging for fine to medium scale applications in environmental sciences.Link
Tags: special issue, multi sensor, image fusion, Lidar, 3D, underwater

Mishra, P., Lohumi, S., Khan, H. A., & Nordon, A. (2020). Close-range hyperspectral imaging of whole plants for digital phenotyping: Recent applications and illumination correction approaches.Computers and Electronics in Agriculture, 178, 105780.
Tags: Digital phenotyping, hyperspectral imaging (HSI)

Buehler, C., Schenkel, F., Gross, W., Schaab, G., & Middelmann, W. (2020). Strategic Optimization of Convolutional Neural Networks for Hyperspectral Land Cover Classification. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 363-369.
Tags: convolutional neural network (1D-CNN), Transfer Learning

Zhang, N., Wang, Y., & Zhang, X. (2020). Extraction of tree crowns damaged by Dendrolimus tabulaeformis Tsai et Liu via spectral-spatial classification using UAV-based hyperspectral images. Plant Methods, 16(1), 1-19.
Tags: Tree crown extraction is, support vector machine (SVM), edge-preserving filter (EPF), Dendrolimus tabulaeformis

Sobejano-Paz, V., Mikkelsen, T. N., Baum, A., Mo, X., Liu, S., Köppl, C. J., … & García, M. (2020).Hyperspectral and thermal sensing of stomatal conductance, transpiration, and photosynthesis for soybean and maize under drought. Remote Sensing, 12(19), 3182.
Tags: crop phenotyping, hydraulic traits, leaf conductance, phenology, photosynthetic CO2 assimilation rate

Li, D., Chen, J.M., Zhang, X., Yan, Y., Zhu, J., Zheng, H., Zhou, K., Yao, X., Tian, Y., Zhu, Y. and Cheng, T., (2020). Improved estimation of leaf chlorophyll content of row crops from canopy reflectance spectra through minimizing canopy structural effects and optimizing off-noon observation time. Remote Sensing of Environment, 248, p.111985.
Tags: LAI insensitive chlorophyll index (LICI), Leaf chlorophyll content (LCC)

Noor Azmi, A. N., Bejo, S. K., Jahari, M., Muharam, F. M., Yule, I., & Husin, N. A. (2020). Early Detection of Ganoderma boninense in Oil Palm Seedlings Using Support Vector Machines. Remote Sensing, 12(23), 3920.
Tags: Ganoderma boninense, basal stem rot (BSR), Support Vector Machine (SVM)

Zhang, J., Wang, C., Yuan, L., Liu, P., Zhang, Y., & Wu, K. (2020). Construction of a plant spectral library based on an optimised feature selection method. Biosystems Engineering, 195, 1-16.
Tags: plant spectral library, Spectral feature screening

Szalay, K., Keller, B., Rák, R., Péterfalvi, N., Kovács, L., Souček, J., Sillinger, F. and Jung, A., (2020). Artificial solar radiation protection of raspberry plantation. Progress in Agricultural Engineering Sciences, 16(S1), pp.141-150.
Tags: climate change, plant breeding, greenhouse, polytunnel solutions

Klos, F., Sut-Lohmann, M., Raab, T., & Hirsch, F. (2020, May). Innovative Drone-based Hyperspectral Detection of Heavy Metals (Ni, Zn, and Cu) in Plants cultivated for Phytomining. In EGU General Assembly Conference Abstracts (p. 9370).
Tags: soil contamination, the recycling of heavy metals, phytoremediation

Astor, T., Dayananda, S., Nautiyal, S., & Wachendorf, M. (2020). Vegetable crop biomass estimation using hyperspectral and RGB 3D UAV Data. Agronomy, 10(10), 1600.
Tags: predict fresh matter yield (FMY), growth stage, Bengaluru

Tao, H., Feng, H., Xu, L., Miao, M., Yang, G., Yang, X., & Fan, L. (2020). Estimation of the Yield and Plant Height of Winter Wheat Using UAV-Based Hyperspectral Images. Sensors, 20(4), 1231.
Tags: yield, extracted plant height HCSM, estimation model, winter wheat

WACHENDORF, M., ASTOR, T., & WIJESINGHA, J. (2020). Remotely sensed information for the protection and management of species-rich grasslands. Link
Tags: Acid detergent fibre (ADF), Crude protein (CP), nitrogen (N), neutral detergent fibre (NDF)

Yue, J., Feng, H., Tian, Q., & Zhou, C. (2020). A robust spectral angle index for remotely assessing soybean canopy chlorophyll content in different growing stages. Plant methods, 16(1), 1-18.
Tags: soybean, chlorophyll, plants, canopy

Zheng, Q., Huang, W., Ye, H., Dong, Y., Shi, Y., & Chen, S. (2020). Using continous wavelet analysis for monitoring wheat yellow rust in different infestation stages based on unmanned aerial vehicle hyperspectral images. Applied Optics, 59(26), 8003-8013.
Tags: wheat yellow rust, crop quality, wavelet, support vector machine (SVM)

Liu, M., Yu, T., Gu, X., Sun, Z., Yang, J., Zhang, Z., … & Li, J. (2020). The Impact of Spatial Resolution on the Classification of Vegetation Types in Highly Fragmented Planting Areas Based on Unmanned Aerial Vehicle Hyperspectral Images. Remote Sensing, 12(1), 146.
Tags: object-based image analysis (OBIA), eucalyptus, citrus, sugarcane

Wijesingha, J., Astor, T., Schulze-Brüninghoff, D., Wengert, M., & Wachendorf, M. (2020). Predicting Forage Quality of Grasslands Using UAV-Borne Imaging Spectroscopy. Remote Sensing, 12(1), 126.
Tags: Forage quality, grassland, crude protein (CP), acid detergent fibre (ADF)

Liu, H., Zhu, H., Li, Z., & Yang, G. (2020). Quantitative analysis and hyperspectral remote sensing of the nitrogen nutrition index in winter wheat. International Journal of Remote Sensing, 41(3), 858-881.
Tags: nitrogen nutrition index, winter wheat, crops


Jiménez, S. I. J., Bustamante, W. O., de Jesús, M., & Pablo, M. 2019: INFORMACIÓN DE DRONES Y SU ANÁLISIS EN LA AGRICULTURA DE PRECISIÓN.
Tags: plataformas web, cámaras digitales, aplicaciones

Zhang, X., Zhao, J., Yang, G., Liu, J., Cao, J., Li, C., … & Gai, J. (2019). Establishment of Plot-Yield Prediction Models in Soybean Breeding Programs Using UAV-Based Hyperspectral Remote Sensing. Remote Sensing, 11(23), 2752.
Tags: plot-yield prediction, soybean, breeding

Dayananda, S., Astor, T., Wijesingha, J., Chickadibburahalli Thimappa, S., Dimba Chowdappa, H., Nidamanuri, R. R., … & Wachendorf, M. (2019). Multi-Temporal Monsoon Crop Biomass Estimation Using Hyperspectral Imaging. Remote Sensing, 11(15), 1771.
Tags: Monsoon crop, biomass estimation, lablab, maize, finger millet

Zhu, W., Sun, Z., Huang, Y., Lai, J., Li, J., Zhang, J., … & Li, Y. (2019). Improving Field-Scale Wheat LAI Retrieval Based on UAV Remote-Sensing Observations and Optimized VI-LUTs. Remote Sensing, 11(20), 2456.
Tags: wheat, PROSAIL, NDVI-LUT, average leaf angle

Szalay, K., Keller, B., Kovács, L., Rák, R., Peterfalvi, N., Sillinger, F., … & Jung, A. (2019). Physical protection in experimental raspberry plantation. INMATEH-Agricultural Engineering, 57(1).
Tags: raspberry, climate change, spectroscopy

Wachendorf, M., & Astor, T. (2019). The Benefit Of Spectral and Point-Cloud Data for Herbage Yield and Quality Assessment of Grasslands. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences.
Tags: herbage yield, grassland quality assessment, crude protein or acid detergent fibre

Zhang, X., Han, L., Dong, Y., Shi, Y., Huang, W., Han, L., … & Sobeih, T. (2019). A deep learning-based approach for automated yellow rust disease detection from high-resolution hyperspectral UAV images. Remote Sensing, 11(13), 1554.
Tags: yellow rust disease, winter wheat, Puccinia striiformis f. sp. Tritici (Pst)

Yan, Y., Deng, L., Liu, X., & Zhu, L. (2019). Application of UAV-Based Multi-angle Hyperspectral Remote Sensing in Fine Vegetation Classification. Remote Sensing, 11(23), 2753.
Tags: BRDF, maize, soybean, weeds, mulberry, peach, ash trees

Zhao, H., Song, X., Yang, G., Li, Z., Zhang, D., & Feng, H. (2019). Monitoring of Nitrogen and Grain Protein Content in Winter Wheat Based on Sentinel-2A Data. Remote Sensing, 11(14), 1724.
Tags: vegetation indices (VIs), plant nitrogen accumulation (PNA), plant nitrogen content (PNC), leaf nitrogen accumulation (LNA), leaf nitrogen content (LNC), nitrogen and grain protein content, winter wheat , Sentinel-2A

Xu, N., Tian, J., Tian, Q., Xu, K., & Tang, S. (2019). Analysis of Vegetation Red Edge with Different Illuminated/Shaded Canopy Proportions and to Construct Normalized Difference Canopy Shadow Index. Remote Sensing, 11(10), 1192.
Tags: bare soil index (BSI), red edge (RE), NDCSI, LSMA

Li, Z., Li, Z., Fairbairn, D., Li, N., Xu, B., Feng, H., & Yang, G. (2019). Multi-LUTs method for canopy nitrogen density estimation in winter wheat by field and UAV hyperspectral. Computers and Electronics in Agriculture, 162, 174-182.
Tags: canopy nitrogen density (CND), winter wheat, hyperspectral

Yuan, L., Yan, P., Han, W., Huang, Y., Wang, B., Zhang, J., … & Bao, Z. (2019). Detection of anthracnose in tea plants based on hyperspectral imaging. Computers and Electronics in Agriculture, 167, 105039.
Tags: Tea plant, anthracnose, hyperspectral image

Jung, A., Vohland, M., Magyar, M., Kovács, L., Jung, T., Péterfalvi, N. & Szalay, K. (2019). Snapshot Hyperspectral Imaging for Field Data Acquisition in Agriculture (in Raspberry Plantation). Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation, 28, 1-7.
Tags: Raspberry, snapshot, hyperspectral, horticulture


Viljanen, N., Honkavaara, E., Näsi, R., Hakala, T., Niemeläinen, O., & Kaivosoja, J. (2018). A novel machine learning method for estimating biomass of grass swards using a photogrammetric canopy height model, images and vegetation indices captured by a drone. Agriculture, 8(5), 70.
Tags: biomass estimation, UAV, canopy height

Behmann, J., Acebron, K., Emin, D., Bennertz, S., Matsubara, S., Thomas, S. & Mahlein, A. K. (2018). Specim IQ: evaluation of a new, miniaturized handheld hyperspectral camera and its application for plant phenotyping and disease detection. Sensors, 18(2), 441.
Tags: phenotyping, plant disease, phytopathology

Aasen, H., & Bolten, A. (2018). Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers–From theory to application. Remote sensing of environment, 205, 374-389.
Tags: phenotyping, precision agriculture, vegetation indices, chlorophyll

Zhang, N., Zhang, X., Yang, G., Zhu, C., Huo, L., & Feng, H. (2018). Assessment of defoliation during the Dendrolimus tabulaeformis Tsai et Liu disaster outbreak using UAV-based hyperspectral images. Remote Sensing of Environment, 217, 323-339.
Tags: defoliation, Dendrolimus tabulaeformis, Tsai et Liu disaster, forest health

ÁRVAI, T. T. L. P. M., SIPOS, G., & KOVÁCS, K. B. Z. A. (2018): Review of research on salt-affected soils in the Debrecen agricultural high educational institutions, with special focus on the mapping of Hortobágy. Link. 
Tags: salt-affected soils, Hortobágy, Hungary

Robbins, J. A. (2018). Small unmanned aircraft systems (sUAS): An emerging technology for horticulture. Hortic. Rev, 45, 33-71.
Tags: horticulture, sensors, phytonutrients

Zhu, H., Liu, H., Xu, Y., & Guijun, Y. (2018). UAV-based hyperspectral analysis and spectral indices constructing for quantitatively monitoring leaf nitrogen content of winter wheat. Applied optics, 57(27), 7722-7732.
Tags: winter wheat, leaf nitrogen content, quantitative

Szalay, K., Keller, B., Rák, R., Péterfalvi, N., Kovács, L., Sillinger, F., & Jung, A. (2018). PHYSICAL PROTECTION AGAINST EXCESSIVE SOLAR RADIATION IN EXPERIMENTAL RASPBERRY PLANTATION. Link.
Tags: raspberry, solar radiation, climate change, shading, physical protection

Oehlschläger, J., Schmidhalter, U., & Noack, P. O. (2018, September). UAV-Based Hyperspectral Sensing for Yield Prediction in Winter Barley. In 2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) (pp. 1-4). IEEE.
Tags: winter barley, yield estimation, breeding

Tu, Y., Bian, M., Wan, Y., & Fei, T. (2018). Tea cultivar classification and biochemical parameter estimation from hyperspectral imagery obtained by UAV. PeerJ, 6, e4858.
Tags: Tea cultivar classification, tea polyphenols (TP), amino acids (AA)

Li, D., Zheng, H., Xu, X., Lu, N., Yao, X., Jiang, J., … & Cheng, T. (2018, July). BRDF Effect on the Estimation of Canopy Chlorophyll Content in Paddy Rice from UAV-Based Hyperspectral Imagery. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 6464-6467). IEEE.
Tags: Canopy Chlorophyll Content (CCC), paddy rice, hyperspectral

Jung, A., Michels, R., & Rainer, G. (2018). Portable snapshot spectral imaging for agriculture. 1-6. Debrecen University Proceeding.
Tags: UAV, snapshot, agriculture

Yue, J., Feng, H., Jin, X., Yuan, H., Li, Z., Zhou, C., … & Tian, Q. (2018). A comparison of crop parameters estimation using images from UAV-mounted snapshot hyperspectral sensor and high-definition digital camera. Remote Sensing, 10(7), 1138.
Tags: crop surface model, crop height, aboveground biomass, LAI


Perez-Sanz, F., Navarro, P. J., & Egea-Cortines, M. (2017). Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms. GigaScience, 6(11)
Tags: plant phenomics, phenology, pattern recognition

Zhao, X., Yang, G., Liu, J., Zhang, X., Xu, B., Wang, Y., … & Gai, J. (2017). Estimation of soybean breeding yield based on optimization of spatial scale of UAV hyperspectral image. Transactions of the Chinese Society of Agricultural Engineering, 33(1), 110-116.
Tags: soybean, breeding, China

Keller B., Jung A.,Nagy G. M., Dénes F., Péterfalvi N., Szalay K. (2017): HIPERSPEKTRÁLIS TÁVÉRZÉKELÉS ALKALMAZÁSI LEHETŐSÉGEINEK BEMUTATÁSA EGY MÁLNA ÜLTETVÉNY PÉLDÁJÁN KERESZTÜL. A Kutatói utánpótlást elősegítő program a Nemzeti Agrárkutatási és Innovációs Központban a Földművelésügyi Minisztérium támogatásával valósul meg. fiatalkutato. naik. hu, 63.
Tags: raspberry, climate change, Hungary

Livens, S., Pauly, K., Baeck, P., Blommaert, J., Nuyts, D., Zender, J., & Delauré, B. (2017). A Spatio-Spectral Camera for High Resolution Hyperspectral Imaging.  International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 42.
Tags: strawberry, potato, wheat, meteorit

Xia, L., Zhang, R. R., Chen, L. P., Wen, Y., Zhao, F., & Hou, J. J. (2017). Retrieving wheat Biomass by using a hyper-spectral device on UAV. Advances in Animal Biosciences, 8(2), 833-836. Link.
Tags: wheat biomass, UAV, animals

Yuan, H., Yang, G., Li, C., Wang, Y., Liu, J., Yu, H., … & Yang, X. (2017). Retrieving soybean leaf area index from unmanned aerial vehicle hyperspectral remote sensing: Analysis of RF, ANN, and SVM regression models. Remote Sensing, 9(4), 309.
Tags: LAI retrieval, hyperspectral remote sensing, sampling method

Yue, J., Yang, G., Li, C., Li, Z., Wang, Y., Feng, H., & Xu, B. (2017). Estimation of winter wheat above-ground biomass using unmanned aerial vehicle-based snapshot hyperspectral sensor and crop height improved models. Remote Sensing, 9(7), 708.
Tags: UAV, Crops

Rungpichayapichet, P., Nagle, M., Yuwanbun, P., Khuwijitjaru, P., Mahayothee, B., & Müller, J. (2017). Prediction mapping of physicochemical properties in mango by hyperspectral imaging. Biosystems Engineering, 159, 109-120.
Tags: Food sorting, Food Safety


Qin, Z., Chang, Q., Xie, B., & Shen, J. (2016). Rice leaf nitrogen content estimation based on hysperspectral imagery of UAV in Yellow River diversion irrigation district. Transactions of the Chinese Society of Agricultural Engineering, 32(23), 77-85.
Tags: Rice, nitrogen, irrigation

Aasen, H. (2016). The acquisition of Hyperspectral Digital Surface Models of crops from UAV snapshot cameras. Doctoral dissertation, Universität zu Köln.
Tags: surface models, crops, vegetation

Memic, E., Graeff-Hönninger, S., Claupein, W., Schomburg, H., & Brandes, A. Resource efficient plant protection based on a data driven multi-scale approach for the process chain-Diseases detection-decision support-demand specific fungicide application. Gesellschaft für Pflanzenbauwissenschaften e. V., 192., 2016
Tags: phytopathology, plant diseases, hyperspectral

≤ 2015

Jung, A., Vohland, M., & Thiele-Bruhn, S. (2015). Use of a portable camera for proximal soil sensing with hyperspectral image data. Remote Sensing, 7(9), 11434-11448.
Tags: soil spectroscopy, portable, land use, multivariate

Aasen, H., Burkart, A., Bolten, A., & Bareth, G. (2015). Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance. ISPRS Journal of Photogrammetry and Remote Sensing, 108, 245-259.
Tags: UAV, hyperspectral, vegetation, crops

Bareth, G., Aasen, H., Bendig, J., Gnyp, M. L., Bolten, A., Jung, A., … & Soukkamäki, J. (2015). Low-weight and UAV-based hyperspectral full-frame cameras for monitoring crops: Spectral comparison with portable spectroradiometer measurements. Photogrammetrie-Fernerkundung-Geoinformation, 2015(1), 69-79.
Tags: UAV, Crops, monitoring

Gebbers, R. (2014). Current crop and soil sensors for precision agriculture. In Congresso Brasileiro de Agricultura de precisao, Sao Pedro.
Tags: crops, sensors, precision agriculture

Jung, A., Vohland, M. (2014). Snapshot Hyperspectral Imaging for Soil Diagnostics–Results of a Case Study in the Spectral Laboratory. Photogrammetrie-Fernerkundung-Geoinformation, 2014(6), 511-522.
Tags: soil diagnostics, micro shadows, soil morphology

Jung, A., & Vohland, M. (2014). Spectral Mobile Mapping for Rapid Soil Diagnostics–Results of a Laboratory Based Feasibility Test. Gemeinsame Tagung 2014 der DGfK, der DGPF, der GfGI und des GiN (DGPF Tagungsband 23 / 2014)
Tags: soil diagnostics, soil spectroscopy, multivariate

Bareth, G., Aasen, H., Bendig, J., Gnyp, M. L., Bolten, A., Jung, A., … & Soukkamäki, J. (2014, April). Spectral comparison of low-weight and UAV-based hyperspectral frame cameras with portable spectroradiometer measurements. In Proceedings of the Workshop on UAV-basaed Remote Sensing Methods for Monitoring Vegetation (Vol. 94, pp. 1-6). Geographisches Institut der Universität zu Köln-Kölner Geographische Arbeiten.
Tags: UAV, crops, agriculture

Aasen, H., Bendig, J., Bolten, A., Bennertz, S., Willkomm, M., & Bareth, G. (2014). Introduction and preliminary results of a calibration for full-frame hyperspectral cameras to monitor agricultural crops with UAVs. In ISPRS Technical Commission VII Symposium (Vol. 40, pp. 1-8). Copernicus GmbH.
Tags: crops, agriculture, UAV

Jung, A., Michels, R., Graser, R. 2013: Non-scanning hyperspectral imaging camera for UAS platforms (Nichtscannende hyperspektrale Kamera für UAS Plattformen). Bornimer Agrartechnische Berichte (ISSN 0947-7314), 81,141-147.
Tags: non-scanning, agriculture, video spectroscopy

Full Image
Block Image Full
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≤ 2021

Dainelli, R., Toscano, P., Gennaro, S. F. D., & Matese, A. (2021). Recent advances in Unmanned Aerial Vehicles forest remote sensing—A systematic review. Part II: Research applications. Forests, 12(4), 397.
Tags: height, diameter at breast height (DBH), automatic processes, forestry stakeholders

Liu, M., Zhang, Z., Liu, X., Yao, J., Du, T., Ma, Y., & Shi, L. (2020). Discriminant Analysis of the Damage Degree Caused by Pine Shoot Beetle to Yunnan Pine Using UAV-Based Hyperspectral Images. Forests, 11(12), 1258.
Tags: Tomicus spp. (the pine shoot beetle, PSB) to Yunnan pine (Pinus yunnanensis Franch)

Takahashi Miyoshi, G., Imai, N. N., Garcia Tommaselli, A. M., Antunes de Moraes, M. V., & Honkavaara, E. (2020). Evaluation of Hyperspectral Multitemporal Information to Improve Tree Species Identification in the Highly Diverse Atlantic Forest. Remote Sensing, 12(2), 244.
Tags: tree species, atlantic forest, classification, identification

Cao, J., Liu, K., Liu, L., Zhu, Y., Li, J., & He, Z. (2018). Identifying mangrove species using field close-range snapshot hyperspectral imaging and machine-learning techniques. Remote Sensing, 10(12), 2047.
Tags: UAV, forest, mangrove area

Cao, J., Leng, W., Liu, K., Liu, L., He, Z., & Zhu, Y. (2018). Object-based mangrove species classification using unmanned aerial vehicle hyperspectral images and digital surface models. Remote Sensing, 10(1), 89.
Tags: UAV, forest, mangrove area

Jenal, A., Weber, I., Kneer, C., & Bongartz, J. (2015). Der Tragschrauber als Sensorplattform für die Fernerkundung. Publikationen der Deut. Gesellschaft für Photogrammetrie, Fernerkundung u. Geoinformation eV, 24, 226-231.
Tags: gyrocopter, forest, ecology, environment

Weber, I., Jenal, A., Kneer, C., & Bongartz, J. (2015). Gyrocopter-based Remote Sensing Platform. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 1333.
Tags: Gyrocopter, forestry, airborne

Weber, I., Kneer, C., Jenal, A., & Bongartz, J. (2015). Einsatz einer bildgebenden Hyperspektralkamera in einem Tragschrauber. In DGPF conference proceedings (Vol. 24, p. 2015).

Block Mixed

Water Spectroscopy & Aquatic Vegetation

Teague, J., Megson-Smith, D. A., Allen, M. J., Day, J. C., & Scott, T. B. (2021). A Review of Optical Techniques for Coral Monitoring & Introducing Low-Cost Hyperspectral Imaging. Link
Tags: health of coral reefs, coral monitoring, health diagnosis

Rowan, G. S., & Kalacska, M. (2021). A Review of Remote Sensing of Submerged Aquatic Vegetation for Non-Specialists.Remote Sensing, 13(4), 623.
Tags: Submerged aquatic vegetation (SAV), blue carbon, plant health

Liu, B., Liu, Z., Men, S., Li, Y., Ding, Z., He, J., & Zhao, Z. (2020). Underwater hyperspectral imaging technology and its applications for detecting and mapping the seafloor: a review.Sensors, 20(17), 4962.
Tags: seafloor surveying, deep-sea environment, deep-sea mineral exploration

Rowan, G., & Kalacska, M. (2020). Remote sensing of submerged aquatic vegetation: an introduction and best practices review.Link
Tags: Submerged aquatic vegetation (SAV), global climate change, anthropogenic disturbances

Seidel, M., Hutengs, C., Oertel, F., Schwefel, D., Jung, A., & Vohland, M. (2020). Underwater Use of a Hyperspectral Camera to Estimate Optically Active Substances in the Water Column of Freshwater Lakes. Remote Sensing, 12(11), 1745.
Tags: optically active substances (OAS), concentrations of chlorophyll a (CHLa), colored dissolved organic matter (CDOM)

Gilerson, A., Carrizo, C., Ibrahim, A., Foster, R., Harmel, T., El-Habashi, A., … & Ondrusek, M. (2020). Hyperspectral polarimetric imaging of the water surface and retrieval of water optical parameters from multi-angular polarimetric data. Applied Optics, 59(10), C8-C20.
Tags: Oceanography, water spectroscopy, polarization

Kern, J., & Schenk, A. (2019). A Multi-Modal System for Monitoring of Water Quality-Setup and First Results from Passauna Reservoir. Channels, 125(2500), 1.
Tags: water quality, turbidity, water surface temperature

Gilerson, A., Carrizo, C., Malinowski, M., Groetsch, P., Foster, R., & Estrella, E. H. (2019, October). Multi-and Hyperspectral Polarimetric Imaging of the Ocean Surface. In Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions.  International Society for Optics and Photonics. 2019. (Vol. 11150, p. 1115007).
Tags: Oceanography, water spectroscopy, polarization

Gilerson, A., Carrizo, C., Foster, R., Harmel, T., Golovin, A., El-Habashi, A., … & Wright, T. (2019, May). Total and polarized radiance from the ocean surface from hyperspectral polarimetric imaging. In Ocean Sensing and Monitoring XI (Vol. 11014, p. 110140F). International Society for Optics and Photonics.
Tags: Oceanography, water spectroscopy, polarization, Stokes vector, video camera, water optical properties

Carrizo, C. (2018). Hyperspectral and Polarimetric Imaging for Advanced Characterization of the Ocean Surface and Underwater Objects. Doctoral dissertation, The City College of New York.
Tags: water spectroscopy, underwater, oceanography, polarisation

Lodhi, V., Chakravarty, D., & Mitra, P. (2018). Hyperspectral imaging for earth observation: Platforms and instruments. Journal of the Indian Institute of Science, 98(4), 429-443.
Tags: underwater spectroscopy, water spectroscopy, UAV

Carrizo, C., Golovin, A., El-Habashi, A., Foster, R., Gray, D., Bowles, J., & Gilerson, A. (2018, May). Ocean surface characterization using snapshot hyperspectral polarimetric imager. In Ocean Sensing and Monitoring X (Vol. 10631, p. 1063107). International Society for Optics and Photonics.
Tags: Oceanography, water spectroscopy, polarization, Stokes vector, video camera, water optical properties

Caras, T., Hedley, J., & Karnieli, A. (2017). Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales. International journal of applied earth observation and geoinformation, 63, 68-77.
Tags: coral reef detection, water spectroscopy, underwater