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Featured researches published by Jing M. Chen.


Journal of Geophysical Research | 1997

Leaf area index of boreal forests: Theory, techniques, and measurements

Jing M. Chen; Paul M. Rich; Stith T. Gower; John M. Norman; Steven Plummer

Leaf area index (LAI) is a key structural characteristic of forest ecosystems because of the role of green leaves in controlling many biological and physical processes in plant canopies. Accurate LAI estimates are required in studies of ecophysiology, atmosphere-ecosystem interactions, and global change. The objective of this paper is to evaluate LAI values obtained by several research teams using different methods for a broad spectrum of boreal forest types in support of the international Boreal Ecosystem-Atmosphere Study (BOREAS). These methods include destructive sampling and optical instruments: the tracing radiation and architecture of canopies (TRAC), the LAI-2000 plant canopy analyzer, hemispherical photography, and the Sunfleck Ceptometer. The latter three calculate LAI from measured radiation transmittance (gap fraction) using inversion models that assume a random spatial distribution of leaves. It is shown that these instruments underestimate LAI of boreal forest stands where the foliage is clumped. The TRAC quantifies the clumping effect by measuring the canopy gap size distribution. For deciduous stands the clumping index measured from TRAC includes the clumping effect at all scales, but for conifer stands it only resolves the clumping effect at scales larger than the shoot (the basic collection of needles). To determine foliage clumping within conifer shoots, a video camera and rotational light table system was used. The major difficulties in determining the surface area of small conifer needles have been largely overcome by the use of an accurate volume displacement method. Hemispherical photography has the advantage that it also provides a permanent image record of the canopies. Typically, LAI falls in the range from 1 to 4 for jack pine and aspen forests and from 1 to 6 for black spruce. Our comparative studies provide the most comprehensive set of LAI estimates available for boreal forests and demonstrate that optical techniques, combined with limited direct foliage sampling, can be used to obtain quick and accurate LAI measurements.


Remote Sensing of Environment | 1996

Retrieving leaf area index of boreal conifer forests using Landsat TM images

Jing M. Chen; Josef Cihlar

Abstract Vegetation indices, including the simple ratio (SR) and the normalized difference vegetation index (NDVI), from Landsat TM data were correlated to ground-based measurements of LAI, effective LAI, and the crown closure in boreal conifer forests located near Candle Lake and Prince Albert, Saskatchewan and near Thompson, Manitoba, as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). The measurements were made using two optical instruments: the Plant Canopy Analyzer (LAI-2000, LI-COR) and the TRAC (Tracing Radiation and Architecture of Canopies). The TRAC was recently developed to quantify the effect of canopy architecture on optical measurements of leaf area index. The stands were located on georeferenced Landsat TM images using global positioning system (GPS) measurements. It is found that late spring Landsat images are superior to summer images for determining overstory LAI in boreal conifer stands because the effect of the understory is minimized in the spring before the full growth of the understory and moss cover. The effective LAI, obtained from gap fraction measurements assuming a random distribution of foliage spatial positions, was found to be better correlated to SR and NDVI than LAI. The effective LAI is less variable and easier to measure than LAI, and is also an intrinsic attribute of plant canopies. It is therefore suggested to use effective LAI as the most important parameter for radiation interception considerations.


Agricultural and Forest Meteorology | 1996

Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands

Jing M. Chen

The feasibility of detecting the seasonal variation in leaf area index (LAI) in boreal conifer forests is investigated using optical instruments. The LAI of six stands was measured. They include young and old jack pine (Pinus banksiana) and old black spruce (Picea mariana) located near the southern border (near Prince Albert, Saskatchewan) and near the northern border (near Thompson, Manitoba) of the Canadian boreal ecotone. LAI values of the stands are obtained by making several corrections to the effective LAI measured from the LI-COR LAI-2000 Plant Canopy Analyzer (PCA). The corrections include a foliage element (shoot) clumping index (for clumping at scales larger than the shoot) measured using the optical instrument TRAC (Tracing Radiation and Architecture of Canopies) developed by Chen and Cihlar (Chen, J.M. and Cihlar, J., 1995a, Plant canopy gap size analysis theory for improving optical measurements of leaf area index of plant canopies, Appl. Opt., 34: 6211–6222), a needle-to-shoot area ratio (for clumping within the shoot) obtained from shoot samples, and a woody-to-total area ratio obtained through destructive sampling of trees. It is found that the effective LAI varied about 5% to 10% in the growing season and the element clumping index remained almost unchanged. The needle-to-shoot area ratio varied the most, about 15% to 25%, which is of the same order of magnitude as the expected seasonal variability in LAI. This demonstrates that most of the seasonal variation information is contained in the needle-to-shoot area ratio, which can not be measured indirectly using in situ optical instruments and has to be obtained from a large quantity of shoot sample analysis which is laborious and error-prone. Based on our experience, an improved and convenient shoot sampling strategy is suggested for future studies. The optically-based LAI values were compared with destructive sampling results for three of the stands. Based on error analysis, we believe that optical measurements combined with shoot sample analysis can produce LAI values for conifer stands which are more accurate than destructive sampling results.


Remote Sensing of Environment | 2002

Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements

Jing M. Chen; Goran Pavlic; Leonard Brown; Josef Cihlar; Sylvain G. Leblanc; H.P. White; Ronald J. Hall; Derek R. Peddle; Douglas J. King; J.A. Trofymow; E. Swift; J.J. van der Sanden; Petri Pellikka

Leaf area index (LAI) is one of the surface parameters that has importance in climate, weather, and ecological studies, and has been routinely estimated from remote sensing measurements. Canada-wide LAI maps are now being produced using cloud-free Advanced Very High-Resolution Radiometer (AVHRR) imagery every 10 days at 1-km resolution. The archive of these products began in 1993. LAI maps at the same resolution are also being produced with images from the SPOT VEGETATION sensor. To improve the LAI algorithms and validate these products, a group of Canadian scientists acquired LAI measurements during the summer of 1998 in deciduous, conifer, and mixed forests, and in cropland. Common measurement standards using the commercial Tracing Radiation and Architecture of Canopies (TRAC) and LAI-2000 instruments were followed. Eight Landsat Thematic Mapper (TM) scenes at 30-m resolution were used to locate ground sites and to facilitate spatial scaling to 1-km pixels. In this paper, examples of Canada-wide LAI maps are presented after an assessment of their accuracy using ground measurements and the eight Landsat scenes. Methodologies for scaling from high- to coarse-resolution images that consider surface heterogeneity in terms of mixed cover types are evaluated and discussed. Using Landsat LAI images as the standard, it is shown that the accuracy of LAI values of individual AVHRR and VEGETATION pixels was in the range of 50–75%. Random and bias errors were both considerable. Bias was mostly caused by uncertainties in atmospheric correction of the Landsat images, but surface heterogeneity in terms of mixed cover types were also found to cause bias in AVHRR and SPOT VEGETATION LAI calculations. Random errors come from many sources, but pixels with mixed cover types are the main cause of random errors. As radiative signals from different vegetation types were quite different at the same LAI, accurate information about subpixel mixture of the various cover types is identified as the key to improving the accuracy of LAI estimates. D 2002 Elsevier Science Inc. All rights reserved.


Ecological Modelling | 1999

Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications

Jing M. Chen; Jane Liu; Josef Cihlar; M.L Goulden

Because Farquhar’s photosynthesis model is only directly applicable to individual leaves instantaneously, considerable skill is needed to use this model for regional plant growth and carbon budget estimations. In many published models, Farquhar’s equations were applied directly to plant canopies by assuming a plant canopy to function like a big-leaf. This big-leaf approximation is found to be acceptable for estimating seasonal trends of canopy photosynthesis but inadequate for simulating its day-to-day variations, when compared with eddy-covariance and gas-exchange chamber measurements from two boreal forests. The daily variation is greatly dampened in big-leaf simulations because the original leaf-level model is partially modified through replacing stomatal conductance with canopy conductance. Alternative approaches such as separating the canopy into sunlit and shaded leaf groups or stratifying the canopy into multiple layers can avoid the problem. Because of non-linear response of leaf photosynthesis to meteorological variables (radiation, temperature and humidity), considerable errors exist in photosynthesis calculation at daily steps without considering the diurnal variability of the variables. To avoid these non-linear effects, we have developed an analytical solution to a simplified daily integral of Farquhar’s model by considering the general diurnal patterns of meteorological variables. This daily model not only captures the main effects of diurnal variations on photosynthesis but is also computationally efficient for large area applications. Its application is then not restricted by availability of sub-daily meteorological data. This scheme has been tested using measured CO2 data from the Boreal Ecosystem–Atmosphere Study (BOREAS), which took place in Manitoba and Saskatchewan in 1994 and 1996


Applied Optics | 1995

Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index

Jing M. Chen; Josef Cihlar

Optical instruments currently available for measuring the leaf-area index (LAI) of a plant canopy all utilize only the canopy gap-fraction information. These instruments include the Li-Cor LAI-2000 Plant Canopy Analyzer, Decagon, and Demon. The advantages of utilizing both the canopy gap-fraction and gap-size information are shown. For the purpose of measuring the canopy gap size, a prototype sunfleck-LAI instrument named Tracing Radiation and Architecture of Canopies (TRAC), has been developed and tested in two pure conifer plantations, red pine (Pinus resinosa Ait.) and jack pine (Pinus banksiana Lamb). A new gap-size-analysis theory is presented to quantify the effect of canopy architecture on optical measurements of LAI based on the gap-fraction principle. The theory is an improvement on that of Lang and Xiang [Agric. For. Meteorol. 37, 229 (1986)]. In principle, this theory can be used for any heterogeneous canopies.


Environmental Research Letters | 2012

An underestimated role of precipitation frequency in regulating summer soil moisture

Chaoyang Wu; Jing M. Chen; Jukka Pumpanen; Alessandro Cescatti; Barbara Marcolla; Peter D. Blanken; Jonas Ardö; Yanhong Tang; Vincenzo Magliulo; Teodoro Georgiadis; H. Soegaard; David R. Cook; Richard Harding

Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 and 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.


Remote Sensing of Environment | 1997

A process-based boreal ecosystem productivity simulator using remote sensing inputs

Jane Liu; Jing M. Chen; Josef Cihlar; W.M. Park

This paper describes a boreal ecosystems productivity simulator (BEPS) recently developed at the Canada Centre for Remote Sensing to assist in natural resources management and to estimate the carbon budget over Canadian landmass (106–107 km2). BEPS uses principles of FOREST biogeochemical cycles (FOREST-BGC) (Running and Coughlan, 1988) for quantifying the biophysical processes governing ecosystems productivity, but the original model is moth fled to better represent canopy radiation processes. A numerical scheme is developed to integrate different data types: remote sensing data at 1-km resolution in lambert conformal conic projection, daily meteorological data in Gaussian or longitude-latitude grided systems, and soil data grouped in polygons. The processed remote sensing data required in the model are leaf area index (LAI) and land-cover type. The daily meteorological data include air temperature, incoming shortwave radiation, precipitation, and humidity. The soil-data input is the available water-holding capacity. The major outputs of BEPS include spatial fields of net primary productivity (NPP) and evapotranspiration. The NPP calculated by BEPS has been tested against biomass data obtained in Quebec, Canada. A time series o f LAI over the growing season of 1993 in Quebec was derived by using 10-day composite normalized difference vegetation index images acquired by the advanced very high resolution radiometer at 1-km resolution (resampled). Soil polygon data were mosaicked, georeferenced, and rasterized in a geographic information system (ARC/INFO). With the use of the process-based model incorporating all major environmental variables affecting plant growth and development, detailed spatial distributions of NPP (annual and four seasons) in Quebec are shown in this paper. The accuracy of NPP calculation is estimated to be 60% for single pixels and 75% for 3×3 pixel areas (9 km9). The modeled NPP ranges from 0.6 kg C/m2/year at the southern border to 0.01 kg C/m2/year at the northern limit of the province. The total annual NPP in Quebec is estimated to be 0.24 Gt C in 1993, which is about 0.3–0.4% of the global NPP.


IEEE Transactions on Geoscience and Remote Sensing | 1997

A four-scale bidirectional reflectance model based on canopy architecture

Jing M. Chen; Sylvain G. Leblanc

Open boreal forests present a challenge in understanding remote sensing signals acquired with various solar and view geometries. Much research is needed to improve our ability to model the bidirectional reflectance distribution (BRD) for retrieving the surface information using measurements at a few angles. The geometric-optical bidirectional reflectance model presented in this paper considers four scales of canopy architecture: tree groups, tree crowns, branches and shoots. It differs from the Li-Strahlers model in the following respects: 1) the assumption of random spatial distribution of trees is replated by the Neyman distribution which is able to model the patchiness or clumpiness of a forest stand; 2) the multiple mutual shadowing effect between tree crowns is considered using a negative binomial and the Neyman distribution theory; 3) the effect of the sunlit background is modeled using a canopy gap size distribution function that affects the magnitude and width of the hotspot; 4) the branch architecture affecting the directional reflectance is simulated using a simple angular radiation penetration function; and 5) the tree crown surface is treated as a complex surface with microscale structures which themselves generate mutual shadows and a hotspot. All these scales of canopy architecture are shown to have effects on the directional distribution of the reflected radiance from conifer forests. The model results compare well with a data set from a boreal spruce forest.


Journal of Geophysical Research | 2011

Simulating the Impacts of Disturbances on Forest Carbon Cycling in North America: Processes, Data, Models, and Challenges

Shuguang Liu; Benjamin Bond-Lamberty; Jeffrey A. Hicke; Rodrigo Vargas; Shuqing Zhao; Jing M. Chen; Steven L. Edburg; Yueming Hu; Jinxun Liu; A. David McGuire; Jingfeng Xiao; Robert E. Keane; Wenping Yuan; Jianwu Tang; Yiqi Luo; Christopher Potter; Jennifer Oeding

[1] Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty.

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Josef Cihlar

Canada Centre for Remote Sensing

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Jane Liu

University of Toronto

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David T. Price

Natural Resources Canada

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Chaoyang Wu

Chinese Academy of Sciences

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T. Andrew Black

University of British Columbia

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Liming He

University of Toronto

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