Dr. Thomas Astor (neé Möckel)

Dr. Thomas Astor

Address Universität Kassel
Ökologische Agrarwissenschaften
Grünlandwissenschaft und Nachwachsende Rohstoffe
Steinstrasse 19
37213 Witzenhausen
Building: Labor- und Hörsaalgebäude
Room
Telephone +49 561 804-1337
Telefax +49 561 804-1230
E-mail address thastor@uni-kassel.de
Picture of Dr. Thomas  Astor

Introduction

Thomas Astor is a researcher at the section of Grassland and Renewable Plant Resources at the University Kassel. His research interests are the remotely sensed identification and evaluation of agricultural areas. He studied Geoecology at the University Bayreuth with the main subject’s biogeography and biogeochemistry of terrestrial soils. He did his dissertation at the Department of Physical Geography and Ecosystem Analysis at the University of Lund, Sweden. His topic was the estimation of ecological parameters like diversity and land use continuity of grassland. Currently, his main research is the drone-based estimation of various plant parameters (e.g. biomass, nitrogen, water content) in grassland and other agricultural systems. He has a focus on the combination of various sensor systems (hyperspectral, multispectral, thermal, RGB).

Research Interests:

  • Estimation of vegetation parameters in agriculture
  • Measurement of diversity and the effect of invasive species in grasslands
  • Analysis of spatial and temporal pattern in agricultural systems

 Projects:

Completed Projects:

  • ZFF Project: Projekt zur Erfassung von Lupinen im Grünland mittels TLS Daten

Teaching:

  • L19 Fernerkundung und GIS (Summer term, German only)
  • I14M Remote Sensing and GIS in agriculture (Winter term, English only) 

Curriculum vitae

Curriculum Vitae

Study Program:

  • 07/2015 - heute Wissenschaftl. Mitarbeiter Universität Kassel
  • 05/2015 - Abschluss: PhD
  • 10/2010 - 05/2015 Promotionsstudium an der Universtät Lund (Schweden)
  • 09/2009 Abschluss: Diplom Geoökologe
  • 2004 - 2009 Studium der Geoökologie an der Universität Bayreuth

Publications in peer reviewed journals

2020

Gruener E., Wachendorf M., Astor T. (2020) The potential of UAV-borne spectral and textural information for predicting aboveground biomass and N fixation in legume-grass mixtures.  PLoS One https://doi.org/10.1371/journal.pone.0234703 PDF

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 PDF

THE BENEFIT OF SPECTRAL AND POINT-CLOUD DATA FOR HERBAGE YIELD AND QUALITY ASSESSMENT OF GRASSLANDS 2019 DOI: 10.5194/isprs-archives-XLII-2-W16-267-2019 

2019

Dayananda S., Astor T., Wijesingha J., Thimappa S.C., Chowdappa H.D., Mudalagiriyappa, Nidamanuri R.R., Nautiyal S., Wachendorf M. (2019): Multi-Temporal Monsoon Crop Biomass Estimation Using Hyperspectral Imaging. Remote Sensing, 11 (15), 1771 PDF

Grüner E., Astor T., Wachendorf M. (2019): Biomass Prediction of Heterogeneous Temperate Grasslands Using an SfM Approach Based on UAV Imaging. Agronomy 2019, 9(2), 54. PDF

Kyere I., Astor T., Graß R., Wachendorf M. (2019): Multi-temporal Agricultural Land-Cover Mapping Using Single-Year and Multi-Year Models Based on Landsat Imagery and IACS Data. Agronomy 2019, 9 (6), 309. PDF

Schulze-Brüninghoff D., Hensgen F., Wachendorf M., Astor T. (2019): Methods for LiDAR-based estimation of extensive grassland biomass. Computer and Electronics in Agriculture 156, 693-699. PDF

Wijesingha J, Moeckel T., Hensgen F., Wachendorf M. (2019): Evaluation of 3D point cloud-based models for the prediction of grassland biomass. International Journal of Applied Earth Observation and Geoinformation 78, 352-359. PDF


2018

Löfgren O., Prentice H. C., Möckel T., Schmid B. C., Hall K. (2018): Landscape history confounds the ability of the NDVI to detect fine-scale variation in grassland communities. Methods in Ecology and Evolution. doi: 10.1111/2041-210X.13036 

Möckel T., Dayananda S., Nidamanuri R.R., Nautiyla S., Hanumaiah N., Buerkert A., Wachendorf M. (2018): Estimation of Vegetable Crop Parameters by Multi-temporal UAV-Borne Images. Remote Sensing 2018, 10, 805. PDF

2017

Hoffmann E.M., Jose M., Nölke N., Möckel T. (2017): Construction and Use of a Simple Index of Urbanisation in the Rural-Urban Interface of Bangalore, India. Sustainability 2017, 9, 2146. PDF

Moeckel T., Safari H., Reddersen B., Fricke T., Wachendorf M. (2017): Fusion of Ultrasonic and Spectral Sensor Data for Improving the Estimation of Biomass in Grasslands with Heterogeneous Sward Structure. Remote Sens. 2017 9(1), 98. PDF

Wachendorf M., Fricke T., Möckel T. (2017): Remote sensing as a tool to assess botanical composition, structure, quantity and quality of temperate grasslands. Grass and Forage Science, 1-14. PDF

2016

Möckel T., Dalmayne J., Schmid B., Prentice H, Hall K (2016): Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands. Remote Sensing 02/2016; 8 (2): 133 DOI:10.3390/rs8020133

Möckel T., Löfgren O., Prentice H.C., Eklundh L., Hall K. (2016): Airborne hyperspectral data predict Ellenberg indicator values for nutrient and moisture availability in dry grazed grasslands within a local agricultural landscape. Ecological Indicators 66, 503-516.   DOI: 10.1016/j.ecolind.2016.01.049

Safari H., Fricke T., Reddersen B., Möckel T., Wachendorf M. (2016): Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system. J. Sens. Sens. Syst. 5, 301-312. PDF

2015

Möckel T. (2015): Hyperspectral and multispectral remote sensing for mapping grassland vegetation. Dissertation 05/2015. DOI: 10.13140/RG.2.1.2745.4564

2014

Möckel T., Dalmayne J., Prentice H., Eklundh L., Purschke O., Schmidtlein S., Hall K. (2014): Classification of Grassland Successional Stages Using Airborne Hyperspectral Imagery. Remote Sensing 08/2014; 6:7732-7761. DOI:10.3390/rs6087732

2013

Dalmayne J., Möckel T.,  Prentice H.,  Schmid B.C., Hall K. (2013): Assessment of fine-scale plant species beta diversity using WorldView-2 satellite spectral dissimilarity. Ecological Informatics 11/2013; 18:1–9. DOI:10.1016/j.ecoinf.2013.05.004

 

other publications

2018

Dayananda S., Möckel T., Wachendorf M. (2018): Multi-Temporal Biomass Estimation of Vegetable Crops Using Unmanned Aerial Vehicles. In: Tropentag 2018: Global food security and food safety: the role of universities Tielkes, E. (ed.) 1. Aufl. - Weikersheim: Margraf Publishers GmbH, 2018. PDF

Grüner E., Möckel T., Wachendorf M. (2018): Biomasseabschätzung im Feldfutterbau mittels drohnengestützten RGB-Aufnahmen. In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 30, 65-66.

Grüner E., Möckel T., Graß T., Wachendorf M. (2018): Using RGB remote sensing for biomass prediction in temperate grassland. In: Sustainable meat and milk production from grasslands. Eds. Horan B., Hennessy D., O'Donovan M., Kennedy E., McCarthy B., Finn J.A., O'Brien B.; Grassland Science in Europe Vol. 22, 848-850.

Kyere I., Möckel T., Graß R., Wachendorf M. (2018): Multi-temporal Analysis of Agricultural Land cover in Northern Hesse using satellite data. In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 30, 169-170.

Hensgen F., Schulze-Brüninghoff D., Möckel T., Wachendorf M. (2018): Biomasseertrag und Lupinenanteil in Bergmähwiesen des Biosphärenreservates Rhön in Abhängigkeit vom Ertezeitpunkt. In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 30, 221-222.

Möckel T., Fricke T, Wachendorf M. (2018): Multi-temporal estimation of forage biomass in heterogenous pastures using static and mobile ultrsonic and hyperspectral measurment. In: Sustainable meat and milk production from grasslands. Eds. Horan B., Hennessy D., O'Donovan M., Kennedy E., McCarthy B., Finn J.A., O'Brien B.; Grassland Science in Europe Vol. 22, 813-815.

Schulze-Brüninghoff D., Möckel T., Hensgen F., Wachendorf M. (2018): LiDAR-based estimation of extensive grassland biomass invaded by large-leaved lupine (Lupinus polyphyllus Lindl.).  In: Sustainable meat and milk production from grasslands. Eds. Horan B., Hennessy D., O'Donovan M., Kennedy E., McCarthy B., Finn J.A., O'Brien B.; Grassland Science in Europe Vol. 22, 854-856.

Schulze-Brüninghoff D., Hensgen F., Möckel T., Wachendorf M. (2018): Methoden zur lasergestützen Abschätzung extensiver Grünlandbestände.  In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 30, 67-68.

Seeger J.N., Ziebell H., Amari K., Then C., Möckel T., Grüner E., Sturm B., Nasirahmadi A., Shrestha L., Böhm H., Saucke H. (2018): Charakterisierung der Symptomatik neuartiger Nanovirus-Infektionen in Körnerleguminosen mit Hilfe fernoptischer Methoden. In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 30, 61-62.

Wijesingha J., Möckel T., Hensgen F., Wachendorf M. (2018): Grassland biomass modelling from remote sensing 3D point clouds.  In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 30, 37-38.

2017

Hensgen F., Möckel T., Wachendorf M. (2017): Using 3-D laser measurements for biomass estimation in seminatural grasslands invaded by Lupinus polyphyllus. In: Grassland resources for extensive farming systems in marginal lands: major drivers and future scenarios. Eds. Porqueddu C., Franca A., Lombardi G., Molle G., Peratoner G., Hopkins A.; Grassland Science in Europe Vol. 22, 560-562.

Möckel T., Fricke T., Wachendorf M. (2017): Abschätzung der raumzeitlichen Verteilung von Grünlandbiomasse in einem Weidenmanagementsystem mittels mobiler Ultraschall- und Hyperspektraler Sensoren.  In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 29, 86-87.

Schulze-Brüninghoff D., Hensgen F., Möckel T., Wachendorf M. (2017): Fernerkundliche Abschätzung der Biomasse von Lupinus polyphyllus invadierten Bergmähwiesen im Biosphärenreservat Rhön unter Nutzung eines terrestrischen 3D Lasers.  In: Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften. Bd. 29, 200-201.