Jan Verbesselt

Jan Verbesselt
Wageningen University & Research | WUR · Laboratory of Geo-Information Science and Remote Sensing

PhD

About

137
Publications
81,336
Reads
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Introduction
Dr. Jan Verbesselt is associate professor in remote sensing at Wageningen University, Laboratory of Geo-information Science and Remote Sensing. He focusses at measuring and understanding ecosystem dynamics by developing novel spatio-temporal approaches to detect, monitor and forecast changes using remotely sensed data from in-situ, terrestrial- and airborne LiDAR, and satellite sensors. The application of remotely sensed images for ecological modelling, and collaborative earth science for assessing vegetation, climate, and human impacts takes a central place.
Additional affiliations
February 2013 - February 2016
Wageningen University & Research
Position
  • Tenure track Professor
December 2012 - present
Wageningen University & Research
Position
  • Professor (Assistant)
February 2007 - July 2010
The Commonwealth Scientific and Industrial Research Organisation
Position
  • PostDoc Position

Publications

Publications (137)
Article
Recent work suggests that episodes of drought and heat can bring forests across climate zones to a threshold for massive tree mortality. As complex systems approach a threshold for collapse they tend to exhibit a loss of resilience, as reflected in declining recovery rates from perturbations. Trees may be no exception, as at the verge of drought-in...
Article
Combining observations from multiple optical and synthetic aperture radar (SAR) satellites can provide temporally dense and regular information at medium resolution scale, independently of weather, season, and location. This has the potential to improve near real-time deforestation monitoring in dry tropical regions, where traditional optical only...
Article
Implementation of policies to reduce forest loss challenges the Earth observation community to improve forest monitoring. An important avenue for progress is the use of new satellite missions and the combining of optical and synthetic aperture radar sensor data.
Article
Full-text available
Current research on forest change monitoring using medium spatial resolution Landsat satellite data aims for accurate and timely detection of forest disturbances. However, producing forest disturbance maps that have both high spatial and temporal accuracy is still challenging because of the trade-off between spatial and temporal accuracy. Timely de...
Article
Full-text available
Current methods for monitoring deforestation from satellite data at sub-annual scales require pixel time series to have many historical observations in the reference period to model normal forest dynamics before detecting deforestation. However, in some areas, pixel time series often do not have many historical observations. Detecting deforestation...
Article
Full-text available
National-scale assessments of post-deforestation land-use are crucial for decreasing deforestation and forest degradation-related emissions. In this research, we assess the potential of different satellite data modalities (single-date, multi-date, multi-resolution, and an ensemble of multi-sensor images) for classifying land-use following deforesta...
Article
Full-text available
An increase in the frequency and severity of disturbances (such as forest fires) is putting pressure on the resilience of the Amazon tropical forest; potentially leading to reduced ability to recover and to maintain a functioning forest ecosystem. Dense and long-term satellite time series approaches provide a largely untapped data source for charac...
Article
Full-text available
Two novel satellite LiDAR missions —GEDI and ICESat-2— are currently operational and combined provide near-global measurements of forest height and structure. Such data underpin a new era of large-area approaches for measuring forest height in regrowing forests of different ages and assessing associated regrowth rates. Two LiDAR missions further al...
Article
Full-text available
About half of the anthropogenic CO2 emissions remain in the atmosphere and half are taken up by the land and ocean¹. If the carbon uptake by land and ocean sinks becomes less efficient, for example, owing to warming oceans² or thawing permafrost³, a larger fraction of anthropogenic emissions will remain in the atmosphere, accelerating climate chang...
Article
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Comparing the performance of different satellite sensors in global land cover change (LCC) monitoring is necessary to assess their potential and limitations for more accurate and operational LCC estimations. This paper aims to examine and compare the performance in LCC monitoring using three satellite sensors: PROBA-V, Landsat 8 OLI, and Sentinel-2...
Article
Monitoring spatio-temporal changes of aerosols is necessary to better understand atmospheric processes. Here, the vertical distribution of aerosols and how it has changed from 2006 to 2017 is studied using time series data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on board the Cloud-Aerosol Lidar and Infrared Pat...
Article
Full-text available
BFAST Lite is a newly proposed unsupervised time series change detection algorithm that is derived from the original BFAST (Breaks for Additive Season and Trend) algorithm, focusing on improvements to speed and flexibility. The goal of the BFAST Lite algorithm is to aid the upscaling of BFAST for global land cover change detection. In this paper, w...
Article
Full-text available
The paper evaluates Deep neural network architectures that account for either (a) spatial-temporal information, i.e., Hybrid Recurrent convolutional neural network, 3D-convolutions, ConvLSTM, and the novel CNN + Multi Head Self-Attention model, or (b) only spatial information, i.e., 2D-convolutions, (c) only temporal information, i.e.,Long short te...
Article
Currently most global land cover maps are produced with discrete classes, which express the dominant land cover class in each pixel, or a combination of several classes at a predetermined ratio. In contrast, land cover fraction mapping enables expressing the proportion of each pure class in each pixel, which increases precision and reduces legend c...
Article
Full-text available
Accurate sub-annual detection of forest disturbance provides timely baseline information for understanding forest change and dynamics to support the development of sustainable forest management strategies. Traditionally , Landsat imagery was widely used to monitor forest disturbance, but the low temporal density of Landsat observations limits the t...
Article
Full-text available
Tropical forest disturbances linked to fire usage cause large amounts of greenhouse gas (GHG) emissions and environmental damages. Supporting precise GHG estimations and counteracting illegal fire usages in the tropics require timely and thematically detailed large-scale information on fire-related forest disturbances. Multi-sensor optical and rada...
Article
Full-text available
At present, accessing and processing Earth Observation (EO) data on different cloud platforms requires users to exercise distinct communication strategies as each backend platform is designed differently. The openEO API (Application Programming Interface) standardises EO-related contracts between local clients (R, Python, and JavaScript) and cloud...
Article
Full-text available
Construction of transportation infrastructure is a vital step in boosting economic and societal opportunities and often results in land use changes. In this study, we focus on the land use dynamics of the urban agglomeration around Hangzhou Bay, where the Qiantang River flows into the East China Sea. The Hangzhou Bay Bridge crosses the bay since 20...
Article
Full-text available
Historical land cover maps are of high importance for scientists and policy makers studying the dynamic character of land cover change in the Sudano-Sahel, including anthropogenic and climatological drivers. Despite its relevance, an accurate high resolution record of historical land cover maps is currently lacking over the Sudano-Sahel. In this st...
Article
Full-text available
Monitoring of abnormal changes on the earth's surface (e.g., forest disturbance) has improved greatly in recent years because of satellite remote sensing. However, high computational costs inherently associated with processing and analysis of satellite data often inhibit large-area and sub-annual monitoring. Normal seasonal variations also complica...
Article
Full-text available
Dryland ecosystems are frequently struck by droughts. Yet, woody vegetation is often able to recover from mortality events once precipitation returns to pre-drought conditions. Climate change, however, may impact woody vegetation resilience due to more extreme and frequent droughts. Thus, better understanding how woody vegetation responds to drough...
Poster
Full-text available
Ecosystems in drylands are highly susceptible to changes in their way of functioning due to extreme and prolonged droughts or anthropogenic perturbation. Long-standing pressure, from climate or human action, may result in severe alterations in their dynamics. Moreover, changes in dryland ecosystems functioning can take place abruptly (Horion et al....
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
Aim Changes in dryland ecosystem functioning are threatening the well‐being of human populations worldwide, and land degradation, exacerbated by climate change, contributes to biodiversity loss and puts pressures on sustainable livelihoods. Here, abrupt changes in ecosystem functioning [so‐called turning points (TPs)] were detected using time serie...
Article
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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...
Presentation
Full-text available
Presentation on bit data challenges in the Copernicus Global Land Services Land Cover project.
Presentation
Full-text available
The open-access paper with the results presented here can be found at https://doi.org/10.1111/geb.13099
Article
Full-text available
Increasing demand for food and the shortage of arable land call for sustainable intensification of farming, especially in Sub-Saharan Africa where food insecurity is still a major concern. Kenya needs to intensify its dairy production to meet the increasing demand for milk. At the same time, the country has set national climate mitigation targets a...
Article
Full-text available
Tree crops such as cocoa and oil palm are important to smallholders’ livelihoods and national economies of tropical producer countries. Governments seek to expand tree-crop acreages and improve yields. Existing literature has analyzed socioeconomic and environmental effects of tree-crop expansion, but its spatial effects on the landscape are yet to...
Conference Paper
The field of remote sensing is nowadays faced with huge amounts of data. While this offers a variety of exciting research opportunities, it also yields significant challenges regarding both computation time and space requirements. In practice, the sheer data volumes render existing approaches too slow for processing and analyzing all the available...
Preprint
The field of remote sensing is nowadays faced with huge amounts of data. While this offers a variety of exciting research opportunities, it also yields significant challenges regarding both computation time and space requirements. In practice, the sheer data volumes render existing approaches too slow for processing and analyzing all the available...
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...
Poster
Full-text available
The current standard of land cover classification is to assign each pixel to one land cover class, which at coarse resolution causes loss of information about mixed land cover. Fuzzy land cover classification, which assigns fractions of each land cover class to each pixel, can deal with mixed pixels. However, so far its application has been limited...
Article
Full-text available
Fire use for land management is widespread in natural tropical and plantation forests, causing major environmental and economic damage. Recent studies combining active fire alerts with annual forest-cover loss information identified fire-related forest-cover loss areas well, but do not provide detailed understanding on how fires and forest-cover lo...
Article
Full-text available
In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI), which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not be...
Thesis
Full-text available
Global land cover (GLC) classification is well established, and GLC products are used as input to a variety of scientific models. However, traditional GLC classification assumes that each pixel in a map can be classified into one of the predefined land cover classes. This is rarely the case in reality due to heterogeneity in land cover that results...
Article
Full-text available
Satellite based land cover classification for Africa’s semi-arid ecosystems is hampered commonly by heterogeneous landscapes with mixed vegetation and small scale land use. Higher spatial resolution remote sensing time series data can improve classification results under these difficult conditions. While most large scale land cover mapping attempts...
Article
The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Tr...
Article
Full-text available
Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time series change detection is affected by diverse forest types found in tropical dry regions. In this paper...
Article
Full-text available
Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satell...
Article
Full-text available
In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat time series data. We analysed a representative State...
Article
Full-text available
In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat time series data. We analysed a representative State...
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...