Frieke M.B. Van Coillie

• PhD
• Professor at Ghent University

Current evidence suggests that liana (woody vine) competition with trees could be threatening the carbon sink by reducing carbon uptake and storage in tropical forests. Previous studies investigating forest demography in liana removal experiments have, however, assumed similar allometries for trees, regardless of the amount of lianas they support....

Questions Increased soil phosphorus (P) availability in fertilized grasslands can drive both community degradation and delayed community recovery upon agricultural abandonment. Beyond describing grassland community patterns along gradients in P availability, it remains unclear how individual species with different strategies respond to increasing p...

The current state of the mangrove ecosystem on Bangka Island requires urgent attention from the local government to protect, restore, and conserve the remaining mangrove areas. Hence, this study endeavors to assess the species composition of mangroves on Bangka Island, examining their correlation with edaphic factors and shedding light on the zonat...

An accurate and detailed understanding of land-use change affected by anthropogenic actions is key to environmental policy decision-making and implementation. Although global land cover products have been widely used to monitor and analyse land use/land cover (LULC) change, the feasibility of using these products at the regional level needs to be a...

Questions Effective and successful restoration of species‐rich semi‐natural grasslands requires knowledge of the soil nutrient status, including soil phosphorus availability. Plants are solid indicators of soil nutrient status, because their growth reflects nutrient availability integrated over a certain period. The use of reflectance spectroscopy...

We present a SAR-based flood monitoring approach for Belgium. The approach was designed based on the requirements of the local water manager (VMM), exploits locally available ancillary data and is adjusted to the local scale of the landscape. A validation was performed based on UAV imagery obtained in 2018-2020. The algorithm is implemented on the...

Background and aim Excess soil phosphorus often constrains ecological restoration of degraded semi-natural grasslands in Western-Europe. Slow-growing species, often target of restoration (measures), are at a disadvantage because they are outcompeted by fast-growing species. Gaining insight into the responses of plant species and communities to soil...

Supported by the IEEE Geoscience and Remote Sensing Society (GRSS) High School and Undergrad Student Outreach Program (HSUSO), the educational chairs of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2021 developed a remote sensing school project targeting 16- and 17-year-old pupils in the third grade of secondary educat...

The degradation of forest areas in the Amazon region, where many indigenous commu-20 nities live, has shown a marked deterioration in recent years. The Yasuní Biosphere Reserve (YBR), 21 placed on the Ecuadorian Amazon and settled by several indigenous groups, is considered a hotspot 22 of natural and cultural diversity. In this study, we draw atte...

Cocoa agroforests sustain ecosystem services (ESs) to varying degrees. These services are otherwise mostly provided by other non-cocoa shade or companion trees. However, the density of shade trees is associated with services and/or disservices that drive farm-specific tree management successions. Considering the growing impacts of climate crisis on...

Field inventory data collection in 2016 and 2017. Mapping of cocoa trees and associated non-cocoa trees in cocoa agrofrests in the Forest-Savannah transition landscape of Bokito. A total of 4080 trees mapped on farms in cocoa agroforests that were created from previously Savannah and forests land cover. Aim of the study is to assess temporal dynami...

Background and aim Excess soil phosphorus often constrains ecological restoration of degraded semi-natural grasslands in Western-Europe. Slow-growing species, often target for restoration, are at a disadvantage because they are outcompeted by fast-growing species. Gaining insight into the responses of plant species and communities to soil phosphoru...

As floods pose an increasing threat to our society, insights into their occurrence and dynamics are of major importance for emergency relief, damage assessment, the optimization of predictive models, and spatial planning. Due to their capability of providing synoptic observations independent of cloud cover and daylight, synthetic-aperture radar (SA...

A reliable estimation and monitoring of tree canopy cover or shade distribution is essential for a sustainable cocoa production via agroforestry systems. Remote sensing (RS) data offer great potential in retrieving and monitoring vegetation status at landscape scales. However, parallel advancements in image processing and analysis are required to a...

The European Space Agency's Sentinel-1 constellation provides timely and freely available dual-polarized C-band Synthetic Aperture Radar (SAR) imagery. The launch of these and other SAR sensors has boosted the field of SAR-based flood mapping. However, flood mapping in vegetated areas remains a topic under investigation, as backscatter is the resul...

Insights into flood dynamics, rather than solely flood extent, are critical for effective flood disaster management, in particular in the context of emergency relief and damage assessment. Although flood dynamics provide insight in the spatio-temporal behaviour of a flood event, to date operational visualization tools are scarce or even non-existen...

Urban residents are exposed to higher levels of heat stress in comparison to the rural population. As this phenomenon could be enhanced by both global greenhouse gas emissions (GHG) and urban expansion, urban planners and policymakers should integrate both in their assessment. One way to consider these two concepts is by using urban climate models...

The amount of freely available satellite data is growing rapidly as a result of Earth observation programmes, such as Copernicus, an initiative of the European Space Agency. Analysing these huge amounts of geospatial data and extracting useful information is an ongoing pursuit. This paper presents an alternative method for flood detection based on...

Over the last decade, Kunming has been subject to a strong urbanisation driven by rapid economic growth and socio-economic, topographical and proximity factors. As this urbanisation is expected to continue in the future, it is important to understand its environmental impacts and the role that spatial planning strategies and urbanisation regulation...

Delineating the cropping area of cocoa agroforests is a major challenge in quantifying the contribution of land use expansion to tropical deforestation. Discriminating cocoa agroforests from tropical transition forests using multispectral optical images is difficult due to the similarity of the spectral characteristics of their canopies. Moreover,...

Since 2012, Local Climate Zones (LCZ) have been used for numerous studies related to urban environment. In 2015, this use amplified because a method to map urban areas in LCZs was introduced by the World Urban Database and Access Portal Tools (WUDAPT). However in 2017, the first HUMan INfluence EXperiment showed that these maps often have poor or l...

Delineating the cropping area of cocoa agroforests is a major challenge for quantifying the contribution of the land use expansion to tropical deforestation. Discriminating cocoa agroforests from tropical transition forests using multi-spectral optical images is difficult due to a similarity in the spectral characteristics of their canopy; moreover...

Deep learning has been widely used to fuse multi-sensor data for classification. However, current deep learning architecture for multi-sensor data fusion might not always perform better than single data source, especially for fusion of hyperspectral and LiDAR (Light Detection And Ranging) remote sensing data for tree species mapping in complex, clo...

This study evaluates the uncertainty of delineating perennial cocoa agroforest land use from multi-date Sentinel1 SAR images. SAR images are cloud and season independent, and thus have high potentials for mapping tropical land uses. We use the random forest machine learning algorithm to compare land use/cover classification uncertainty from a high-...

Synthetic Aperture Radar (SAR) provides consistent information on target land features; especially in tropical conditions that restrain penetration of optical imaging sensors. Because radar response signal is influenced by geometric and di-electrical properties of surface features’, the different land cover may appear similar in radar images. For d...

In our changing world, floods are a threat of increasing concern. Within this context, flood mapping is important for both damage assessment and forecast improvement. Due to the suitability of synthetic aperture radar (SAR) for flood mapping, a broad range of SAR-based flood mapping algorithms has been developed during the past years. However, most...

The paper is freely available on this link until August 11, 2018: https://authors.elsevier.com/a/1XG9zcUG5AnqN. High population densities in cities and rapid urban growth increase the vulnerability of the urban environment to extreme weather events. Urban planning should account for these extreme events as efficiently as possible. One way is to lo...

jats:p> Abstract. Synthetic Aperture Radar (SAR) provides consistent information on target land features; especially in tropical conditions that restrain penetration of optical imaging sensors. Because radar response signal is influenced by geometric and di-electrical properties of surface features’, the different land cover may appear similar in r...

Light is a key resource for plant growth and is of particular importance in forest ecosystems, because of the strong vertical structure leading to successive light interception from canopy to forest floor. Tree species differ in the quantity and heterogeneity of light they transmit. We expect decreases in both the quantity and spatial heterogeneity...

The World Urban Database and Access Portal Tools (WUDAPT) is a community initiative to collect worldwide data on urban form (i.e., morphology, materials) and function (i.e., use and metabolism). This is achieved through crowdsourcing, which we define here as the collection of data by a bounded crowd, composed of students. In this process, training...

Despite the great importance of cities, relatively little consistent information about their internal configuration (structure, cover and materials) is available. The World Urban Database and Access Portal Tools (WUDAPT) initiative aims at the acquisition, storage and dissemination of data on the form and function of cities indifferent levels. At t...

Despite the great importance of cities, relatively little consistent information about their internal configuration (structure, cover and materials) is available. The World Urban Database and Access Portal Tools (WUDAPT) initiative aims at the acquisition, storage and dissemination of data on the form and function of cities indifferent levels. At t...

Global warming and the increasing world population will only put more pressure on the living conditions in urban environments. From a thermal comfort point of view, it is clear that there is a need for sustainable urban planning in which the thermal behavior of new developments can be accounted for. Mapping the city into local climate zones (LCZs),...

This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing stu...

The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up...

Background The trematode parasite Fasciola hepatica causes important economic losses in ruminants worldwide. Current spatial distribution models do not provide sufficient detail to support farm-specific control strategies. A technology to reliably assess the spatial distribution of intermediate host snail habitats on farms would be a major step for...

To address the environmental impacts of tourism in protected areas, park managers need to understand the spatial distribution of tourist use. Standard monitoring measures (tourist surveys and counting and tracking techniques) are not sufficient to accomplish this task, in particular for off-road travel. This article predicts tourists′ spatial use p...

Development of appropriate tourism infrastructure is important for protected areas that allow public access for tourism use. This is meant to avoid or minimize unfavorable impacts on natural resources through guiding tourists for proper use. In this paper, a GIS-based method, the least-cost path (LCP) modelling, is explored for planning tourist tra...

The integration between vegetation data, human disturbance factors, and geo-spatial data (Digital Elevation Model (DEM) and image data) is a particular challenge for vegetation mapping in mountainous areas. The present study aimed to incorporate the relationships between species distribution (or vegetation spatial distribution pattern) and topograp...

a b s t r a c t The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article in...

This study tackles a common, yet underrated problem in remote-sensing image analysis: the fact that human interpretation is highly variable among different operators. Despite current technological advancements, human perception and interpretation are still vital components of the map-making process. Consequently, human errors can considerably bias...

The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these...

Hyperspectral imagery contains a wealth of spectral and spatial information that can improve target detection and recognition performance. Typically, spectral information is inferred pixel-based, while spatial information related to texture, context and geometry are deduced on a per-object basis. Existing feature extraction methods cannot fully uti...

In this paper, the impact of image denoising on feature selection and tree species mapping accuracy is assessed. We apply a novel algorithm for hyperspectral (HS) image denoising using principal component analysis (PCA) and total variation (TV). The method is embedded in an object‐based classification framework and tested for complex forests with c...

Nowadays, advanced technology in remote sensing allows us to acquire multi-sensor and multi-resolution data from the same geographic region. Fusion of these data sources for classification purposes however remains challenging. We propose a novel framework for fusion of low spatial resolution Thermal Infrared (TI) hyperspectral (HS) and high spatial...

Fasciolosis, caused by the trematode parasite Fasciola hepatica, causes serious production losses in dairy cattle worldwide. This vector-borne disease is spread by the snail Galba truncatula which thrives in small water bodies (SWB). Several spatial models have been created to identify high-risk areas, but they cover large regions and are not suita...

The trematode parasite F. hepatica causes serious production losses in cattle worldwide. Several spatial models have been created to identify high-risk areas, but they cover large regions and are not suitable for herd level decisions. More knowledge on farm-level factors affecting the disease are needed to develop applicable small-scale risk maps....

Fasciolosis, caused by the trematode parasite Fasciola hepatica, causes serious production losses in dairy cattle worldwide. This vector-borne disease is spread by the snail Galba truncatula which thrives in small water bodies (SWB). Developing up-to-date, small-scale risk maps requires more insights in environmental factors affecting the snail dyn...

In this letter, we present a novel object-based approach addressing individual tree crown (ITC) detection to assess stand density from remotely sensed imagery in closed forest canopies: directional local filtering (DLF). DLF is a variant of local maximum filtering (LMF). Within locally homogeneous areas, it uses a 1-D neighborhood and simultaneousl...

Tegenwoordig is het gebruik van luchtfoto’s en satellietbeelden overal aanwezig, denk maar aan het veelzijdig gebruik van Google Earth. Aardobservatie of remote sensing is dan ook niet meer weg te denken uit de hedendaagse maatschappij en wetenschap. De beelden die aardobservatie oplevert, spreken tot ieders verbeelding. Maar het belang van remote...

Fasciolosis, caused by the trematode parasite Fasciola hepatica, causes serious production losses in dairy cattle worldwide. In Flanders, the cost for liver fluke infections at dairy farms was estimated at € 8.2 million a year. The presence of the intermediate host Galba truncatula is a key-factor for disease transmission. As part of the SATHELI pr...

It is widely acknowledged that model inputs can cause considerable errors in the model output. Since land cover maps obtained from the classification of remote sensing data are frequently used as input to spatially explicit environmental models, it is important to provide information regarding the classification quality of the produced map. Map qua...

Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is represented by a planar map, which depicts the projection of a nonflat surface into a 2-dimensional Cartesian space. As a result, ecologically meaningful terrain structures like terrain shape or el...

Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received considerable attention over the past 15 years for analyzing a...

Stand density, expressed as the number of trees per unit area, is an important forest management parameter. It is used by foresters to evaluate regeneration, to assess the effect of forest management measures, or as an indicator variable for other stand parameters like age, basal area, and volume. In this work, a new density estimation procedure is...

An often undervalued but inevitable component in remote sensing image analysis is human perception and interpretation. Human intervention is a requisite for visual image interpretation, where the interpreter actually performs the analysis. Although image processing became more and more automated, human screening and interpretation remained indispen...

A neural network-based method for speckle removal in synthetic aperture radar (SAR) images is introduced. The method rests on the idea that a neural network learning machine, trained on artificially generated input-target couples, can be used to efficiently process real SAR data. The explicit plus-point of the method is that it is trained with arti...

This study investigates the potential of very high resolution (VHR) optical and radar data for olive grove landscape mapping. VHR data were fed into a four-step processing chain performing an object-based land-use classification. The four steps included (i) image segmentation, (ii) object feature calculation, (iii) object-based classification and (...

Mapping of vegetation using remote sensing in mountainous areas is considerably hampered by topographic effects on the spectral response pattern. A variety of topographic normalization techniques have been proposed to correct these illumination effects due to topography. The purpose of this study was to compare six different topographic normalizati...

High-resolution proximal soil sensor data are an important source of information for optimising the prediction of soil properties. On a 10.5 ha arable field, an intensive EM38DD survey with a resolution of 2 m × 2 m resulted in 19,694 measurements of ECa-H and ECa-V. A large textural variation was present in the subsoil due to the presence of forme...

Floodplains in the Sahel region of Africa are of exceptional socio-economical and ecological importance. Due to their large extent and highly dynamic nature, monitoring these ecosystems can only be performed by means of remote sensing. The capability of the Envisat Advanced Synthetic Aperture Radar (ASAR) sensor to capture radar backscattering at v...

Looking at a satellite image one sees squares (i.e. pixels) representing landscape, although the actual shapes of roads, rivers, lakes, forest and nature reserve might more accurately be represented by lines, circles or irregularly shaped polygons. Over recent years earth observation has become an important data source, while image interpretation h...

Object-based image analysis (OBIA) involves pixels first being grouped into objects based on either spectral similarity or an external variable such as ownership, soil or geological unit. Each object is also part of a 'super-object,' obtained by combining several neighboring objects into one larger, and each can be subdivided into smaller objects c...