Benjamin Brede

Benjamin Brede
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | GFZ

PhD

About

41
Publications
16,388
Reads
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805
Citations
Introduction
Benjamin Brede currently works at the Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research. Benjamin does research in Remote Sensing, Geoinformatics (GIS) and Geography.
Additional affiliations
March 2022 - present
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ
Position
  • PostDoc Position
July 2019 - February 2022
Wageningen University & Research
Position
  • PostDoc Position
March 2015 - June 2019
Wageningen University & Research
Position
  • PhD Student
Education
March 2015 - June 2019
Wageningen University & Research
Field of study
  • Vegetation Remote Sensing
September 2012 - February 2015
Wageningen University & Research
Field of study
  • Geo-Information Science & Remote Sensing
October 2008 - July 2012
Philipps University of Marburg
Field of study
  • Geography

Publications

Publications (41)
Article
Full-text available
Accurately quantifying tree and forest structure is important for monitoring and understanding terrestrial ecosystem functioning in a changing climate. The emergence of laser scanning, such as Terrestrial Laser Scanning (TLS) and Unoccupied Aerial Vehicle Laser Scanning (UAV-LS), has advanced accurate and detailed forest structural measurements. TL...
Article
Full-text available
The workflow for estimating the temperature in agricultural fields from multiple sensors needs to be optimized upon testing each type of sensor’s actual user performance. In this sense, readily available miniaturized UAV-based thermal infrared (TIR) cameras can be combined with proximal sensors in measuring the surface temperature. Before the two t...
Conference Paper
A description and test results for a new method for automatically isolating individual trees from UAV LiDAR point clouds is presented. The isolation method is based on shortest path computations with height from the ground working as a restriction. The method is tested on a 4 ha tropical forest plot, which is also scanned with TLS to provide compar...
Data
TLS and UAV-LS point clouds for the 2017 Speulderbos Laser Scanning campaign. The data covers ca 2 ha of forest of which are ca 1 ha mature beech and oak and 1 ha of mix between Douglas fir, Norway spruce, giant fir and young beech. Data was acquired while ca half of the deciduous trees still had no leaves.
Conference Paper
Full-text available
The actual photosynthesis is important for studying crop dynamics. Remote sensing of vegetation has the potential to greatly improve our understanding in this respect. Recently, sun-induced chlorophyll fluorescence (SIF) was proven to be an indicator for the functional status of instantaneous plant photosynthesis. However, the relationships between...
Data
Data connected to this study can be found at the 4TU Centre for Research Data: https://doi.org/10.4121/uuid:c12affd8-779c-47e4-a93c-ea0afb939237
Article
Full-text available
The European Space Agency (ESA)’s Sentinel-2A (S2A) mission is providing time series that allow the characterisation of dynamic vegetation, especially when combined with the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS) Landsat 7 (L7) and Landsat 8 (L8) missions. Hybrid retrieval workflows combining non...
Article
Full-text available
Above-Ground Biomass (AGB) product calibration and validation require ground reference plots at hectometric scales to match space-borne missions' resolution. Traditional forest inventory methods that use allometric equations for single tree AGB estimation suffer from biases and low accuracy, especially when dealing with large trees. Terrestrial Las...
Article
Full-text available
Obtaining information on vertical forest structure requires detailed data acquisition and analysis which is often performed at a plot level. With the growing availability of multi-modal satellite remote sensing (SRS) datasets, their usability towards forest structure estimation is increasing. We assessed the relationship of PlanetScope-, Sentinel-2...
Article
Full-text available
Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation activity, there are significant regional variations in carbon dioxide (CO2) fluxes between the biosphere and atmosphere in forests that are affecting the gl...
Data
MAE of the LSTM setup per PFT and climate region from the ensemble mean mean ±sd estimate of the 50 runs. Statistics for the anomalies were not calculated in the arid and tropical climate (i.e. NA) because there was no site with at least 2 years of complete data after data quality control. (PDF)
Data
RMSE of the proposed approach against the other model set-ups from the ensemble mean mean ±sd estimate of the 50 runs. LSTM = LSTM model using the full depth of the Landsat time series and climate data; LSTMperm = LSTM model but the temporal patterns of both the predictive and the target variables were randomly permuted while instantaneous relation...
Data
MAE of the proposed approach against the other model set-ups from the ensemble mean mean ±sd estimate of the 50 runs. LSTM = LSTM model using the full depth of the Landsat time series and climate data; LSTMperm = LSTM model but the temporal patterns of both the predictive and the target variables were randomly permuted while instantaneous relations...
Data
Performance of the gap-filling procedure for the differtent climate variables. Assessment of the gap-filling procedure was done for Tair, Precip, Rg, and VPD. For Tair, Rg, and VPD, the Nash-Sutcliffe efficiency (NSE) is reported, while the root mean squared error (RMSE) is reported for Precip. (PDF)
Data
List of sites used in this study. DBF = Deciduous broadleaf forest, DNF = deciduous needleleaf forest, EBF = evergreen broadleaf forest, ENF = evergreen needleleaf forest, MF = mixed forest, WSA = woody savanna, and SAV = savanna. (PDF)
Data
RMSE of the LSTM setup per PFT and climate region from the ensemble mean mean ±sd estimate of the 50 runs. Statistics for the anomalies were not calculated in the arid and tropical climate (i.e. NA) because there was no site with at least 2 years of complete data after data quality control. (PDF)
Data
Scatterplots of the coefficient of determination of the proposed approach against the other model set-ups at site level. The coefficient of determination was computed using monthly observed and predicted NEE estimates for each site. Each point represents one site and only the sites with at least one complete year of good quality data (n site = 81)...
Data
Coefficient of determination of the proposed approach against the other model set-ups from the ensemble mean mean ±sd estimate of the 50 runs. LSTM = LSTM model using the full depth of the Landsat time series and climate data; LSTMperm = LSTM model but the temporal patterns of both the predictive and the target variables were randomly permuted whil...
Data
Performance of the gap-filling procedure of each Landsat band using a Random Forest model and climate variables (i.e. Tair, Precip, Rg, VPD, rpot), PFT, month of the year, and latitude as predictive variables. The model was trained on 70% of the data and evaluated on 30% of the left out data. nir = near-infrared, swir1 = shortwave infrared 1, swir2...
Data
Performance of the gap-filling procedure of each Landsat band using a Random Forest model and the MODIS bands as predictive variables. The model was trained on 70% of the data and evaluated on 30% of the left out data. nir = near-infrared, swir1 = shortwave infrared 1, swir2 = shortwave infrared 2, and tir = thermal infrared. (PDF)
Article
Full-text available
Land Surface Phenology (LSP) and Leaf Area Index (LAI) are important variables that describe the photosynthetically active phase and capacity of vegetation. Both are derived on the global scale from optical satellite sensors and require robust validation based on in situ sensors at high temporal resolution. This study assesses the PAI Autonomous Sy...
Article
Full-text available
In addition to single-angle reflectance data, multi-angular observations can be used as an additional information source for the retrieval of properties of an observed target surface. In this paper, we studied the potential of multi-angular reflectance data for the improvement of leaf area index (LAI) and leaf chlorophyll content (LCC) estimation b...
Article
Full-text available
In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is...
Article
Full-text available
The high spatiotemporal variability of clouds requires automated monitoring systems. This study presents a retrieval algorithm that evaluates observations of a hemispherically scanning thermal infrared radiometer, the NubiScope, to produce georeferenced, spatially explicit cloud maps. The algorithm uses atmospheric temperature and moisture profiles...
Article
Full-text available
The poor constraint of forest Above Ground Biomass (AGB) is responsible, in part, for large uncertainties in modelling future climate scenarios. Terrestrial Laser Scanning (TLS) can be used to derive unbiased and non-destructive estimates of tree structure and volume and can, therefore, be used to address key uncertainties in forest AGB estimates....
Article
Full-text available
Terrestrial laser scanning (TLS) data provide 3-D measurements of vegetation structure and have the potential to support the calibration and validation of satellite and airborne sensors. The increasing range of different commercial and scientific TLS instruments holds challenges for data and instrument interoperability. Using data from various TLS...
Conference Paper
Full-text available
This contribution describes the Speulderbos fiducial reference site for biophysical variables with a focus on foliage variables and Leaf Area Index (LAI). The site implements Unmanned Aerial Vehicle (UAV)-and ground-based sensing systems that aim at high temporal resolution observations to capture fast canopy changes like spring leaf flush. It aims...
Article
Full-text available
The seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and...
Article
Full-text available
The seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and...
Article
Full-text available
In this study, the effect of solar zenith angle () on enhanced vegetation index (EVI) of a Guyanese tropical rainforest was studied. For this sub-crown resolution, hyperspectral data have been collected with an unmanned aerial vehicle (UAV) at five different solar zenith angles in a 1-day period. The hyperspectral data were used to simulate Moderat...
Conference Paper
Full-text available
The Amazon rainforests represent the largest connected forested area in the tropics and play an integral role in the global carbon cycle. In the last years the discussion about their phenology and response to drought has intensified. A recent study argued that seasonality in greenness expressed as Enhanced Vegetation Index (EVI) is an artifact of v...

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Projects

Projects (2)
Project
The QA4EO project is the evolution of IDEAS+ with the main objective to ensure the best quality of ESA EO missions currently in operations to meet and possibly exceed original mission requirements. It is the place where innovative R&D ideas are developed and tested to foster Cal/Val protocols, instrument design, and retrieval algorithms in the various EO disciplines, e.g., Land, Atmosphere, Water, and Cryosphere. The project adopts a holistic approach and implements methods adhering to metrological best practices in Cal/Val and products definition
Project
The site implements a multi-sensor approach to (i) monitor leaf phenology and chemistry, and LAI, (ii) test new autonomous sensors, e.g. for LAI monitoring, (iii) test new UAV-based sensors, e.g. UAV-borne Lidar for biomass estimation.