The Experts below are selected from a list of 28533 Experts worldwide ranked by ideXlab platform
Jing M Chen - One of the best experts on this subject based on the ideXlab platform.
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effects of lidar point density sampling size and height threshold on estimation accuracy of crop biophysical parameters
Optics Express, 2016Co-Authors: Jing M Chen, Cheng Wang, Xiaohuan Xi, Hongcheng Zeng, Dailiang Peng, Dong LiAbstract:Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and Ecosystem Modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.
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mapping forest background reflectivity over north america with multi angle imaging spectroradiometer misr data
Remote Sensing of Environment, 2009Co-Authors: Jan Pisek, Jing M ChenAbstract:The spatial and temporal patterns of the forest background optical properties are critically important in retrieving the biophysical parameters of the forest canopy (overstory) and in Ecosystem Modeling. In this paper we carry out background reflectivity mapping over conterminous United States, Canada, Mexico, and the Caribbean land mass using Multi-angle Imaging SpectroRadiometer (MISR) data at 1.1 km resolution. The refined methodology uses the nadir and 45° forward directions of the MISR camera images. The background reflectivity is shown to vary between coniferous and deciduous stands, particularly in the near-infrared band, and with the overall amount of overstory vegetation. The largest seasonal differences were observed over a boreal region. The main drawback is a high amount of missing MISR data due to the presence of clouds and other atmospheric effects. The paper also contains a demonstration of the effect on LAI estimates when the dynamic background reflectivity information is inserted into a global LAI algorithm. Multi-angular remote sensing is thus shown to enable us to effectively map yet another forest structure parameter over large areas, which was not possible using mono-angle data.
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retrieving forest background reflectance in a boreal region from multi angle imaging spectroradiometer misr data
Remote Sensing of Environment, 2007Co-Authors: Francis Canisius, Jing M ChenAbstract:Studies of the bidirectional behavior of forest canopy have shown that the total reflectance of a forest canopy is the combination of illuminated and shaded components of the tree crown as well as the background. In this study, we estimate the background portion from the bidirectional reflection observed by Multi-angle Imaging SpectroRadiometer (MISR) instrument which scans the earth in nine different view angles in an oblique plane relative to the sun. The nadir and 60° forward directions of the MISR images were used to derive the reflectivity of the forest background based on the probabilities of viewing the illuminated tree crown and background on those view angles. The probabilities were estimated using the Four-Scale model. In the study, background reflectivity mosaic images in red and NIR wavelengths covering the BOREAS region during winter and spring seasons were obtained. The mosaic images of winter show high background reflectivity in both wavelengths, and in most of the areas the reflectivity was more than 0.3. In mosaic images of spring the spatial variations in the background reflectivity were considerable. The seasonal changes in the background reflectivity were also studied with multi temporal MISR data, and a similarity in the temporal pattern was found between the retrieved forest background reflectivity and grass land reflectance. These spatial and temporal patterns of the background component retrieved from MISR would be critically important in retrieving the biophysical parameters of vegetation and in Ecosystem Modeling.
Jan Pisek - One of the best experts on this subject based on the ideXlab platform.
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mapping forest background reflectivity over north america with multi angle imaging spectroradiometer misr data
Remote Sensing of Environment, 2009Co-Authors: Jan Pisek, Jing M ChenAbstract:The spatial and temporal patterns of the forest background optical properties are critically important in retrieving the biophysical parameters of the forest canopy (overstory) and in Ecosystem Modeling. In this paper we carry out background reflectivity mapping over conterminous United States, Canada, Mexico, and the Caribbean land mass using Multi-angle Imaging SpectroRadiometer (MISR) data at 1.1 km resolution. The refined methodology uses the nadir and 45° forward directions of the MISR camera images. The background reflectivity is shown to vary between coniferous and deciduous stands, particularly in the near-infrared band, and with the overall amount of overstory vegetation. The largest seasonal differences were observed over a boreal region. The main drawback is a high amount of missing MISR data due to the presence of clouds and other atmospheric effects. The paper also contains a demonstration of the effect on LAI estimates when the dynamic background reflectivity information is inserted into a global LAI algorithm. Multi-angular remote sensing is thus shown to enable us to effectively map yet another forest structure parameter over large areas, which was not possible using mono-angle data.
Francis Canisius - One of the best experts on this subject based on the ideXlab platform.
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retrieving forest background reflectance in a boreal region from multi angle imaging spectroradiometer misr data
Remote Sensing of Environment, 2007Co-Authors: Francis Canisius, Jing M ChenAbstract:Studies of the bidirectional behavior of forest canopy have shown that the total reflectance of a forest canopy is the combination of illuminated and shaded components of the tree crown as well as the background. In this study, we estimate the background portion from the bidirectional reflection observed by Multi-angle Imaging SpectroRadiometer (MISR) instrument which scans the earth in nine different view angles in an oblique plane relative to the sun. The nadir and 60° forward directions of the MISR images were used to derive the reflectivity of the forest background based on the probabilities of viewing the illuminated tree crown and background on those view angles. The probabilities were estimated using the Four-Scale model. In the study, background reflectivity mosaic images in red and NIR wavelengths covering the BOREAS region during winter and spring seasons were obtained. The mosaic images of winter show high background reflectivity in both wavelengths, and in most of the areas the reflectivity was more than 0.3. In mosaic images of spring the spatial variations in the background reflectivity were considerable. The seasonal changes in the background reflectivity were also studied with multi temporal MISR data, and a similarity in the temporal pattern was found between the retrieved forest background reflectivity and grass land reflectance. These spatial and temporal patterns of the background component retrieved from MISR would be critically important in retrieving the biophysical parameters of vegetation and in Ecosystem Modeling.
Chen Yang - One of the best experts on this subject based on the ideXlab platform.
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hydrological regulation drives regime shifts evidence from paleolimnology and Ecosystem Modeling of a large shallow chinese lake
Global Change Biology, 2017Co-Authors: Xiangzhen Kong, Bin Yang, Annette B G Janssen, Jan J Kuiper, Luuk P A Van Gerven, Ning Qin, Yujiao Jiang, Wenxiu Liu, Chen Yang, Zelin BaiAbstract:Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such 'regime shifts' can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long-term dynamics of shallow lake Ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and Ecosystem Modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in Ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake Ecosystem dynamics, and it highlights the urgency of using multi-objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic Ecosystems around the globe.
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hydrological regulation drives regime shifts evidence from paleolimnology and Ecosystem Modeling of a large shallow chinese lake
Global Change Biology, 2017Co-Authors: Xiangzhen Kong, Bin Yang, Annette B G Janssen, Jan J Kuiper, Yujiao Jiang, Qishuang He, Wei He, Fuliu Xu, Luuk P A Van Gerven, Chen YangAbstract:Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such ‘regime shifts’ can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long-term dynamics of shallow lake Ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and Ecosystem Modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in Ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 years and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake Ecosystem dynamics, and it highlights the urgency of using multi-objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic Ecosystems around the globe.
Jeroen Steenbeek - One of the best experts on this subject based on the ideXlab platform.
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using gaming technology to explore and visualize management impacts on marine Ecosystems
Frontiers in Marine Science, 2021Co-Authors: Jeroen Steenbeek, Joe Buszowski, Dalai Felinto, Mike Pan, Villy ChristensenAbstract:We have developed an approach that connects a complex and widely used scientific Ecosystem Modeling approach with a game engine for real-time communication and visualization of scientific results. The approach, OceanViz, focuses on communicating scientific data to non-scientific audiences to foster dialogue, offering experimental, immersive approaches to visualizing complex Ecosystems whilst avoiding information overload. Within the context of Ecosystem-based fisheries management, OceanViz can engage decision makers into the implicit operation of scientific software as an aid during the decision process, and it can be of direct use for public communication through appealing and informative visualizations. Beside a server-client architecture to centralize decision making around an Ecosystem model, OceanViz includes an extensive visualization toolkit capable of accurately reflecting marine Ecosystem changes through a simulated three-dimensional (3D) underwater environment. Here we outline the ideas and concepts that went into OceanViz, its implementation and its related challenges. We reflect on challenges to scientific visualization and communication as food-for-thought for the marine Ecosystem modelling community and beyond.
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Using Ecosystem Modeling to evaluate trade-offs in coastal management: Effects of large-scale river diversions on fish and fisheries
Ecological Modelling, 2017Co-Authors: Kim De ,mutsert, Joe Buszowski, Kristy A. Lewis, Scott P. Milroy, Jeroen SteenbeekAbstract:Abstract A coupled Ecosystem Modeling approach was used to evaluate how select combinations of large-scale river diversions in the lower Mississippi River Deltaic Plain may affect the distribution, biomass, and landings of fish and shellfish over decades relative to a future without action. These river diversions are controlled openings in the riverbank of the Mississippi River designed to reintroduce sediment, water, and nutrients into hydrologically isolated coastal wetlands in order to mitigate wetland loss. We developed a spatial Ecosystem model using Ecopath with Ecosim (EwE) software, and prepared it to receive output from a Delft3D hydrodynamic model coupled to primary production models. The Delft3D model provided environmental drivers including salinity, temperature, Chl a , total suspended solids, and change in wetland cover as a result of simulated river diversions over decadal model runs. Driver output was averaged either daily, monthly, or annually depending on the parameter. A novel oyster-specific subroutine is introduced in this paper to incorporate information at daily intervals in Ecospace, while Ecospace runs on a monthly time step. The Ecosystem model simulates biomass and distribution of fish and shellfish species, and landings of targeted fisheries species, as a result of environmental changes projected for a preliminary set of management scenarios designed to evaluate and screen select combinations of river diversions. Abundant local field samples and landings data allowed for model calibration and validation. The results of simulations indicate that inflow of Mississippi River water in estuaries may cause local shifts in species assemblages. These changes were in some cases direct effects of decreased salinity, such as locally reduced Spotted Seatrout biomass. Changes in some other species in the affected areas resulted from indirect effects; for example, reduced Chl a (as a result of increased TSS) resulted in near-field reductions of Gulf Menhaden. The simulations also showed that local biomass reductions were mostly the result of redistribution, since the scenario with the proposed diversions open had minimal impact on the total biomass or landings of species simulated in the Mississippi River Delta as compared to a future without action. The model and its output were used as a decision support tool to help evaluate and compare alternative management actions. The results of this study played a role in the decision by the Coastal Protection and Restoration Authority to prioritize moving forward to conduct more detailed analyses through engineering and design of the two middle diversions but not the two lower diversions that were tested in this study.
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bridging the gap between Ecosystem Modeling tools and geographic information systems driving a food web model with external spatial temporal data
Ecological Modelling, 2013Co-Authors: Jeroen Steenbeek, Marta Coll, Leigh J Gurney, Frederic Melin, Nicolas Hoepffner, Joe Buszowski, Villy ChristensenAbstract:Research toward the impacts of climate change and human activities on marine Ecosystems is challenged by the limitations of present-day Ecosystem models to address the interrelated spatial dynamics between climate, ocean chemistry, marine food webs, and human systems. The work presented here, the spatial–temporal data framework, is part of a larger study, the NF-UBC Nereus Program, to develop a new approach to model interoperability for closing the gap between marine Ecosystem Modeling tools via geographic information systems (GIS) technology. The approach we present simplifies interdisciplinary model interoperability by separating technical and scientific challenges into a flexible and modular software approach. To illustrate capabilities of the new framework, we use a remote-sensing derived spatial and temporal time series to drive the primary production dynamics in an existing food web model of the North-Central Adriatic using the Ecospace module of the Ecopath with Ecosim approach. In general, the predictive capabilities of the food web model to hind-cast Ecosystem dynamics are enhanced when applying the new framework by better reflecting observed species population trends and distributions. Results show that changes at the phytoplankton level due to changes in primary production are realistically reproduced and cascade up the pelagic food web. The dynamics of zooplankton and small and large pelagic fish are impacted. Highly exploited demersal species such as European hake do, however, not show clear signs of cascading. This may be due to the high fishing pressure on this species and the resulting strong historical decline in the area. In general, the development of the new framework offers Ecosystem modelers with unprecedented capabilities to include spatial–temporal time series into food web analysis with a minimal set of required steps. It is a promising step toward integrating species distribution models and food web dynamics, and future implementations of interdisciplinary model interoperability.
