Jan Pisek

Algorithm for global leaf area index retrieval using satellite imagery

Leaf area index (LAI) is one of the most important Earth surface parameters in modeling ecosystems and their interaction with climate. Based on a geometrical optical model (Four-Scale) and LAI algorithms previously derived for Canada-wide applications, this paper presents a new algorithm for the global retrieval of LAI where the bidirectional reflectance distribution function (BRDF) is considered explicitly in the algorithm and hence removing the need of doing BRDF corrections and normalizations to the input images. The core problem of integrating BRDF into the LAI algorithm is that nonlinear BRDF kernels that are used to relate spectral reflectances to LAI are also LAI dependent, and no analytical solution is found to derive directly LAI from reflectance data. This problem is solved through developing a simple iteration procedure. The relationships between LAI and reflectances of various spectral bands (red, near infrared, and shortwave infrared) are simulated with Four-Scale with a multiple scattering scheme. Based on the model simulations, the key coefficients in the BRDF kernels are fitted with Chebyshev polynomials of the second kind. Spectral indices - the simple ratio and the reduced simple ratio - are used to effectively combine the spectral bands for LAI retrieval. Example regional and global LAI maps are produced. Accuracy assessment on a Canada-wide LAI map is made in comparison with a previously validated 1998 LAI map and ground measurements made in seven Landsat scenes

Estimating leaf inclination and G-function from leveled digital camera photography in broadleaf canopies

The effectiveness of using leveled digital camera for measuring leaf inclination angles was investigated in this study as an inexpensive and convenient alternative to existing approaches. The new method is validated with manual leaf angle measurements for various broadleaf tree species common to hemi-boreal region of Estonia and the tropical forests of Hawai’i Islands. The acquired leaf angle distributions suggest that planophile case might be more appropriate than the commonly assumed spherical as the general approximation of leaf orientation while modeling the radiation transmission through the canopies of (hemi)-boreal broadleaf stands. However, direct leaf inclination measurements should be obtained whenever possible, as there will always exist a large variety of leaf orientation, both among different species and in the space–time domain within a single species. The camera method tested in this study provides a new robust and affordable tool to obtain this information.

Mapping Forest Background Reflectance in a Boreal Region Using Multiangle Compact Airborne Spectrographic Imager Data

Forest background, consisting of understory, moss, litter, and soil, contributes significantly to optical remote sensing signals from forests in the boreal region. In this paper, we present results of background reflectance retrieval from multiangle high-resolution Compact Airborne Spectrographic Imager sensor data over a boreal forest area near Sudbury, ON, Canada. Modifications of the background by white and black plastic sheets at two sites provide two extreme limits for the development and testing of an algorithm for retrieving the background information from multiangle data. Measured background reflectances in red and near-infrared bands at six sites in the vicinity of these modified sites are used to validate the algorithm. We also explore the effect of uncertainties in the input forest structural parameters on this retrieval. The results document: 1) capability of the algorithm to retrieve meaningful background reflectance values for various forest stand conditions, particularly in the low to intermediate canopy density range; 2) the effect of background bidirectional reflectance distribution function on retrieved values; 3) performance of the algorithm using data with different cross angle values; and 4) verification of the internal consistency of the geometric-optical 4-Scale model used. The results provide an important platform for the operational estimation of the vegetation background reflectance from the bidirectional reflections observed by the Multiangle Imaging Spectroradiometer instrument.

Estimation of vegetation clumping index using MODIS BRDF data

The foliage clumping index quantifies the degree of the deviation of leaf spatial distribution in the canopy from the random case. It is of comparable importance for ecological models as the leaf area index for quantifying radiation interception and distribution in plant canopies. Previously, an improved angular index named normalized difference between hotspot and darkspot was proposed for retrieving the clumping index using multi-angle remote sensing data. Global maps of clumping index have been derived successfully from multi-angular Polarization and Directionality of Earth Reflectance (POLDER) data at ∼6 km resolution. In this article, we investigate whether it is feasible to derive the clumping index at 500 m resolution with the 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function model parameters product. The results are compared with an assembled set of field measurements from 63 different sites, covering five continents and diverse biomes.

Improving Clumping and LAI Algorithms Based on Multiangle Airborne Imagery and Ground Measurements

Measurements at more than one angle capture the directional anisotropy of solar radiance reflected from vegetated surfaces. According to our recent research, we propose that the best two view angles for vegetation structural mapping are the following: 1) the hotspot, where the Sun and view directions coincide, and 2) the darkspot, where the sensor sees the maximum amount of vegetation structural shadows. The Normalized Difference between Hotspot and Darkspot (NDHD), an angular index generated from Compact Airborne Spectrographic Imager (CASI) data, is found to be highly correlated with the field-measured foliage clumping index. The foliage clumping index characterizes the nonrandomness in the spatial distribution pattern of leaves. It is of comparable importance as the leaf area index (LAI) for quantifying radiation interception and distribution in plant canopies, and it also affects estimated LAI mapping using remote sensing data. As the clumping index can vary considerably within a cover type, it is highly desirable to map its spatial distribution for various ecological applications. We have generated clumping index maps based on the previous algorithms and empirical relationships between field-measured ¿ and CASI-derived NDHD. Through intensive validation using field data, we demonstrate that the combination of the hotspot and darkspot reflectances has the strongest response to changes in vegetation structure. Two crown structural characteristics, namely, crown height and within-crown density, are major factors that impact the NDHD and clumping index difference between the mature and young (regrowth) coniferous forests. The study area is located near Sudbury in the northern Ontario, Canada.

Estimation of foliage clumping from the LAI-2000 Plant Canopy Analyzer: effect of view caps

Key messageFoliage clumping can be estimated from logarithm averaging method in LAI-2000. The spatial scaling of clumping effects considered by the instrument is dependent on the sensor’s azimuthal view.AbstractAccurate estimates of foliage clumping index (Ω) are required to improve the retrieval of leaf area index (L) from optical instruments like LAI-2000/2200 Plant Canopy Analyzer (PCA) and digital hemispherical photography (DHP). The logarithm averaging method is often used to approximate L because clumping effects are considered at scales larger than the sensor’s field of view. However, the spatial scaling considered for logarithm averaging typically differs between PCA and DHP, resulting in different estimates of foliage clumping. Based on simulation, we demonstrated that applying restricting azimuth view caps (e.g., 45° or 10°) allows reliable estimation of Ω and more accurate estimation of L from PCA. Simulated Ω and L values were comparable to those measured using the PCA, DHP and litter traps. Linear averaging of the gap fractions across readings at a plot or site yields a concurrent estimate of effective leaf area index (Le), thus enabling the calculation of Le, L, and Ω from a single instrument fitted with view caps. Users need to be aware that the method they use for averaging gap fractions determines whether they are measuring Le or L, and PCA users need to be aware that they are applying increasingly large corrections for foliage clumping as they use more restrictive view caps, a fact that they can use to their advantage to improve estimates of L.

Mapping global seasonal forest background reflectivity with Multi‐angle Imaging Spectroradiometer data

Forest background reflectivities with seasonal and spatial variations are critically important in the estimation of canopy biophysical parameters of the forest canopy. In this paper, seasonal background reflectivity for global forested areas was mapped at 1.1 km resolution using four-scale model and Multi-angle Imaging Spectroradiometer data of the nadir and 45 degrees forward directions. The largest seasonal variation of forest background reflectivities was observed in middle and high latitudes of Northern Hemisphere. The background reflectivity differs between deciduous broadleaf forest and coniferous forest in the near-infrared band and varies with increasing canopy leaf area index. The partial validation of forest background reflectivity with adjacent grassland in the Northern Hemisphere and the comparison of understory leaf area index on leaf appearance day for larch forest in North Asia both indicate the relative reliability of results. The nearly 70% spatial coverage of retrieval with high-quality flags makes it eligible for applications over global coniferous and deciduous broadleaf forest areas.

Spectral reflectance patterns and seasonal dynamics of common understory types in three mature hemi-boreal forests

Abstract Due to the growing demand on more accurate prediction of biophysical properties (e.g., leaf area index) or carbon balance models based on remotely sensed data, the understory effect needs to be separated from the overstory. Reflectance models can provide possibility to model and retrieve understory reflectance over large scales, but ground truth data is needed to validate such models and algorithms. In this study, we documented the seasonal variation (April–September) and spectral changes occurring in understory layers of a typical European hemi-boreal forest. The understory composition was recorded and its spectra measured with an ASD FieldSpec Hand-Held UV/VNIR Spectroradiometer eight times at four site types during the growing period (from May to September) in 2013. The collected dataset presented within this study would be of much use to improve and validate algorithms or models for extracting spectral properties of understory from remote sensing data. It can be also further used as a valuable input in radiative transfer simulations that are used to quantify the roles of forest tree layer and understory components in forming a seasonal reflectance course of a hemi-boreal forest, and the upcoming phases of the RAdiation Model Intercomparison (RAMI) experiment.

Satellite-based products for monitoring optically complex inland waters in support of EU Water Framework Directive

The need to restore and protect waterbodies from further degradation has resulted in formulation of the European Union Water Framework Directive 2000/60/EC (WFD). The directive aims to harmonize European legislation on water; and member states shall establish a programme for monitoring the status of all waterbodies larger than 0.5 km2, in order to ensure future quality and quantity of inland waters. The biological and physical–chemical status and ecological potential should be assessed and action plans for a sustainable management and protection of freshwater resources should be established. In practice, this means that extensive and expensive sampling programmes are needed. The ecological status of a waterbody can be described by various biological and physical–chemical quality elements, and several of these important ecological parameters can be monitored by space-based instruments: (1) phytoplankton biomass; (2) chlorophyll-a concentration; (3) water transparency; and (4) frequency and intensity of blooms. The objective of this article is to demonstrate how Environmental Satellite/Medium Resolution Imaging Spectrometer and future Sentinel-3/Ocean Land Colour Instrument data can be effectively used to complement traditional water monitoring programmes by adding information with significantly improved spatial coverage and temporal detail to support the WFD status assessment process. Examples are provided for five large European lakes (Peipsi, Võrtsjärv, Vänern, Vättern, Mälaren). Time series based on satellite data and data collected within national and regional monitoring programmes were compiled and compared, to demonstrate good agreement between the two techniques, but also to discuss natural differences and limitations. Furthermore, the ecological status class based on satellite and in situ data for each waterbody was calculated and analysed.

A note on the height variation of foliage clumping: comparison with remote sensing retrievals

Clumping index (CI), quantifying the level of foliage grouping within distinct canopy structures relative to a random distribution, is a key structural parameter of plant canopies and is very useful in ecological and meteorological models. In this letter, we report on validating the global foliage clumping map derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data at 500 m resolution using new information about vertical profiles of foliage clumping in a wide range of forest type stands. We report that in moderate to dense forest stands with developed undergrowth layer, in situ measurements near the ground surface may considerably underestimate the overall canopy-level clumping effect. This is because the large gaps between tree crowns at upper levels of the canopy may not be all measured near the ground due to obscurity by lower vegetation of branches. This information about height variation of CI is shown to be important for correct estimating and validating the foliage clumping from airborne/satellite remote sensing.