Reflectance spectra of RAMI forest stands in Estonia: Simulations and measurements

Simulated reflectance spectra of three mature hemiboreal forests are compared to top-of-canopy reflectance factor from helicopter measurements in the spectral range of 400-1050 nm. Most of the input parameters of the forest reflectance model FRT used in the simulations have been measured in situ. The same data were used in the fourth phase of the Radiation Transfer Model Intercomparison (RAMI). The reasons of the discrepancies between simulated and measured spectra are analyzed.     

On the reproducibility of field-measured reflectance factors in the context of vegetation studies

This paper describes a study aimed at quantifying uncertainty in field measurements of vegetation canopy hemispherical conical reflectance factors (HCRF). The use of field spectroradiometers is common for this purpose, but the reliability of such measurements is still in question. In this paper we demonstrate the impact of various measurement uncertainties on vegetation canopy HCRF, using a combined laboratory and field experiment employing three spectroradiometers of the same broad specification (GER 1500). The results show that all three instruments performed similarly in the laboratory when a stable radiance source was measured (NEΔL < 1 mW m⁻² sr⁻¹ nm⁻¹ in the range of 400-1000 nm). In contrast, field-derived standard uncertainties (u = SD of 10 consecutive measurements of the same surface measured in ideal atmospheric conditions) significantly differed from the lab-based uncertainty characterisation for two targets: a control (75% Spectralon panel) and a cropped grassland surface. Results indicated that field measurements made by a single instrument of the vegetation surface were reproducible to within ± 0.015 HCRF and of the control surface to within ± 0.006 HCRF (400-1000 nm (± 1σ)). Field measurements made by all instruments of the vegetation surface were reproducible to within ± 0.019 HCRF and of the control surface to within ± 0.008 HCRF (400-1000 nm (± 1σ)). Statistical analysis revealed that even though the field conditions were carefully controlled and the absolute values of u were small, different instruments yielded significantly different reflectance values for the same target. The results also show that laboratory-derived uncertainty quantities do not present a useful means of quantifying all uncertainties in the field. The paper demonstrates a simple method for u characterisation, using internationally accepted terms, in field scenarios. This provides an experiment-specific measure of u that helps to put measurements in context and forms the basis for comparison with other studies.     

Subsurface microwave remote sensing of soil-water content: Field studies in the Negev Desert and optical modelling

The population increase in the Middle East and the respective decrease of water resources necessitate innovative methods for utilization and monitoring of water resources. Development of remote sensing tools can pave the way for remote, rapid mapping of soil-water content, control of excessive irrigation, and prevention of water waste. This paper describes a series of experiments conducted in the Negev Desert that were aimed at developing such tools for monitoring soil-water content. The use of visible near infrared and microwave techniques seems suitable. All provide good correlation with soil-water content measured on the ground. However, the microwave techniques presented here using a P-band scatterometer and ERS-2 SAR seem the most promising. Finally the possibility of optical simulation of the microwave processes is presented in an effort to improve the physical basis for empirical studies. A method of fabrication of optical samples that model soils with different water content and different surface roughness is developed, and a system for measuring backscattered signals is designed. It is shown that the reflectivity of a layered medium is a non-monotonic function of the water content. The effect of the surface roughness on the reflection from a strong buried reflector is being studied.     

Assessment of physical work load in epidemiologic studies: concepts,issues and operational considerations

Ergonomic epidemiology is a rapidly increasing field of research providing data on the occurrence of musculoskeletal disorders and possible risk factors. The present paper states, on the basis of a literature overview, that physical work load (mechanical exposure) is poorly denned and measured in most studies on ergonomic epidemiology. On this background the paper: (1) suggests adjustments of mechanical exposure concepts and terminology; (2) concludes that invalid exposure assessment may, to a large extent, explain the lack of quantitative data on relationships between mechanical exposures and musculoskeletal disorders; and (3) suggests some guidelines for future quantitative assessments of mechanical exposure in large populations.     

In-situ measured spectral directional emissivity of snow and ice in the 8–14 μm atmospheric window

The directional emissivity of snow and ice surfaces in the 8–14 μm thermal infrared (TIR) atmospheric window was determined from spectral radiances obtained by field measurements using a portable Fourier transform infrared spectrometer in conjunction with snow pit work. The dependence of the directional emissivity on the surface snow type (grain size and shape) was examined. We obtained emissivity spectra for five different surface types, i.e., fine dendrite snow, medium granular snow, coarse grain snow, welded sun crust snow, and smooth bare ice. The derived emissivities show a distinct spectral contrast at wavelengths λ = 10.5–12.5 μm which is enhanced with increasing the snow grain size. For example, emissivities at both 10.5 μm and 12.5 μm for the nadir angle were 0.997 and 0.984 for the fine dendrite snow, 0.996 and 0.974 for the medium granular snow, 0.995 and 0.971 for the coarse grain snow, 0.992 and 0.968 for the sun crust, and 0.993 and 0.949 for the bare ice, respectively. In addition, the spectral contrast exhibits a strong angular dependence, particularly for the coarser snow and bare ice, e.g., the emissivity at λ = 12.5 μm for the off-nadir angle of 75° reaches down to 0.927, 0.896, and 0.709 for the coarse grain snow, sun crust, and bare ice cases, respectively. The angular dependent emissivity spectra of the bare ice were quite consistent with the spectra predicted by the Fresnel reflectance theory. The observed results firmly demonstrate that the directional emissivity of snow in the TIR can vary depending upon the surface snow type. The high variability of the spectral emissivity of snow also suggests the possibility to discriminate between snow and ice types from space using the brightness temperature difference in the atmospheric window.     

Reflectance seasonality and its relation to the canopy leaf area index in an eastern Siberian larch forest: Multi-satellite data and radiative transfer analyses

Reliable monitoring of seasonality in the forest canopy leaf area index (LAI) in Siberian forests is required to advance the understanding of climate-forest interactions under global environmental change and to develop a forest phenology model within ecosystem modeling. Here, we compare multi-satellite (AVHRR, MODIS, and SPOT/VEGETATION) reflectance, normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and LAI with aircraft-based spectral reflectance data and field-measured forest data acquired from April to June in 2000 in a larch forest near Yakutsk, Russia. Field data in a 30 × 30-m study site and aircraft data observed around the field site were used. Larch is a dominant forest type in eastern Siberia, but comparison studies that consider multi-satellite data, aircraft-based reflectance, and field-based measurement data are rarely conducted. Three-dimensional canopy radiative transfer calculations, which are based on Antyufeev and Marshak's [Antyufeev, V.S., & Marshak, A.L. (1990). Monte Carlo method and transport equation in plant canopies, Remote Sensing of Environment, 31, 183-191] Monte Carlo photon transport method combined with North's [North, P.R. (1996). Three-dimensional forest light interaction model using a Monte Carlo method, IEEE Transactions on Geoscience and Remote Sensing, 34(4), 946-956] geometric-optical hybrid forest canopy scene, helped elucidate the relationship between canopy reflectance and forest structural parameters, including several forest floor conditions. Aircraft-based spectral measurements and the spectral response functions of all satellite sensors confirmed that biases in reflectance seasonality caused by differences in spectral response functions among sensors were small. However, some reflectance biases occur among the near infrared (NIR) reflectance data from satellite products; these biases were potentially caused by absolute calibration errors or cloud/cloud shadow contamination. In addition, reflectance seasonality in AVHRR-based NIR data was very small compared to other datasets, which was partially due to the spring-to-summer increase in the amount of atmospheric water vapor. Radiative transfer simulations suggest that bi-directional reflectance effects were small for the study site and observation period; however, changes in tree density and forest floor conditions affect the absolute value of NIR reflectance, even if the canopy leaf area condition does not change. Reliable monitoring of canopy LAI is achieved by minimizing these effects through the use of NIR reflectance difference, i.e., the difference in reflectance on the observation day from the reflectance on a snow-free/pre-foliation day. This may yield useful and robust parameters for multi-satellite monitoring of the larch canopy LAI with less error from intersensor biases and forest structure/floor differences. Further validation with field data and combined use of other index (e.g. normalized difference water index, NDWI) data will enable an extension of these findings to all Siberian deciduous forests.     

Variation and directional anisotropy of reflectance at the crown scale — Implications for tree species classification in digital aerial images

Tree species classification is still solved at insufficient reliability in airborne optical data. The variation caused by directional reflectance anisotropy hampers image-based solutions. In addition, trees show considerable within-species variation in reflectance properties. We examined these phenomena at the single-tree level, using the Leica ADS40 line sensor and XPro software, which constitute the first photogrammetric large-format multispectral system to provide target reflectance images. To analyze the influence of illumination conditions in the canopy, we developed a method in which the crown shape as well as between-tree occlusions and shading were modeled, using dense LiDAR data. The precision of the ADS40 reflectance images in well-defined surfaces was 5% as coefficient of variation when 1−4-km image data were fused. The range of reflectance anisotropy was ± 30% for trees near the solar principal plane, with differences between bands and species. Because of the anisotropy differences observed, the spectral separability of the tree species in different bands is dependent on the view-illumination geometry. The within-species variation was high; the coefficient of variation was 13−31%. The contribution of tree and stand variables to anisotropy-normalized reflectance variation was examined. The effects of the species composition of adjacent trees were substantial in NIR and this variation hampers spectral classification in mixed stands. We also studied species- and band-specific intracrown brightness patterns, and we suggest their use as high-order image features in species classification. A species classification accuracy of up to 80% was obtained using 4-km data, which showed the high potential of the ADS40.     

Settlement detection and impervious surface estimation in the Mekong Delta using optical and SAR remote sensing data

Information about the extent of impervious surface and its rate of development is a valuable indicator of urban growth and environmental quality and thus relevant for a wide range of research related to urban ecosystems. Using SPOT-5 data from 2005 to 2009, impervious surface was estimated at a subpixel level for the area of Can Tho province in the Mekong Delta, based on a Support Vector Regression model. Training data comprised a set of SPOT-5 reflectance values each associated with an individual value of subpixel imperviousness as their respective labels. The latter were obtained on the basis of a land cover map, which in turn was derived from a pansharpened QB subset by means of an object-oriented image classification approach. In addition, by varying different sets of training data in the model building process the spectral interrelationships between the urban land cover classes (water, bare soil, vegetation, and impervious surface) and their effect on the estimation of subpixel imperviousness could be examined. In order to exclude irrelevant areas (natural/undeveloped land) from the impervious surface estimation process, single-polarised TerraSAR-X data were used to delineate settlement areas by an object-oriented image classification approach. Furthermore, a change detection method was applied for the respective time period in order to test the suitability of the approach for the automated detection of structural developments within the urban topography. Settlement areas were correctly identified with overall accuracies between 81% and 94%, whilst the comparison of the modelled impervious estimates to the training values gave an absolute mean error below 15%. The results prove the suitability of the approach for an area-wide but selective mapping and monitoring of impervious surface cover within settlement areas only.     

3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains

A detailed 3D structural model of a conifer forest canopy was developed in order to simulate the reflectance (optical) and backscatter (microwave) signals measured remotely. We show it is feasible to model forest canopy scattering using detailed 3D models of tree structure including the location and orientation of individual needles. An existing structural growth model of Scots pine (Pinus sylvestris L.), Treegrow, was modified to simulate observed growth stages of a Scots pine canopy from age 5 to 50 years. The 3D tree models showed close structural agreement with in situ measurements. Needles were added to the structural models according to observed phyllotaxy (distribution). Individual trees were used to generate model canopies, which in turn were used to drive optical and microwave models of canopy scattering. Simulated canopy radiometric response was compared with airborne hyperspectral reflectance data (HyMAP) and airborne synthetic aperture RADAR (ASAR) backscatter data. Model simulations agreed well in general with observations, particularly at optical wavelengths where model simulations of low and high density canopy stands were shown to bracket observations. Relatively small sensitivity of observed reflectance to canopy age was captured reasonably well by the simulations. The choice of needle shape and phyllotaxy was shown to have a significant impact on multiple scattering behaviour at the branch scale. In the microwave domain, simulated backscatter values agreed reasonably well with observations at L-band, less so at X-band. L-band simulated backscatter significantly underestimated observed backscatter at younger canopy ages, probably as a result of inappropriate modelling of soil/understory. It is demonstrated that a combined structural and radiometric modelling approach provides a flexible and powerful method for simulating the remotely sensed signal of a forest canopy in the optical and microwave domains. This is particularly useful for exploring the impact of canopy structure on the resulting signal and also for combined retrievals of forest structural parameters from optical and microwave data.     

Vocabulary learning by mobile‐assisted authentic content creation and social meaning‐making: two case studies

In recent years, we have witnessed the concomitant rise of communicative and contextualized approaches as well as the paradigmatic development of the mobile‐assisted language learning (MALL) framework in analysing language learning. The focus of MALL research has gradually shifted from content‐based (delivery of learning content through mobile devices) to design‐oriented (authentic and/or social mobile learning activities) study. In this paper, we present two novel case studies of MALL that emphasize learner‐created content. In learning English prepositions and Chinese idioms, respectively, the primary school students used the mobile devices assigned to them on a one‐to‐one basis to take photos in real‐life contexts so as to construct sentences with the newly acquired prepositions or idioms. Subsequently, the learners were voraciously engaged in classroom or online discussion of their semantic constructions, thereby enhancing their understanding of the proper usage of the prepositions or idioms. This work shows the potential of transforming language learning into an authentic seamless learning experience.     

Evaluating micas in petrologic and metallogenic aspect: I–definitions and structure of the computer program MICA

Micas are significant ferromagnesian minerals in felsic to mafic igneous, metamorphic, and hydrothermal rocks. Because of their considerable potential to reveal the physicochemical conditions of magmas in terms of petrologic and metallogenic aspects, mica chemistry is used extensively in the earth sciences. For example, the composition of phlogopite and biotite can be used to evaluate the intensive thermodynamic parameters of temperature (T, °C), oxygen fugacity (fO₂), and water fugacity (fH₂O) of magmatic rocks. The halogen contents of micas permit the estimation of the fluorine and chlorine fugacities that may be used in understanding the metal transportation and deposition processes in hydrothermal ore deposits. The Mica⁺ computer program has been written to edit and store electron-microprobe or wet-chemical mica analyses. This software calculates structural formulae and shares out the calculated anions into the I, M, T, and A sites. Mica⁺ classifies micas in terms of composition and octahedral site-occupancy. It also calculates the intensive parameters such as fO₂, T, and fH₂O from the composition of biotite in equilibrium with K-feldspar and magnetite. Using the calculated F–OH and Cl–OH exchange systematics and various log ratios (fH₂O/fHF, fH₂O/fHCl, fHCl/fHF, X_Cl/X_OH, X_F/X_OH, X_F/X_Cl) of mica analyses. Mica⁺ gives valuable determinations about the characteristics of hydrothermal fluids associated with alteration and mineralization processes. The program output is generally in the form of screen outputs. However, by using the “Grf” files that come up with this program they can be visualized under the Grapher software both as binary and ternary diagrams. Mica analyses subjected to the Mica⁺ program were calculated on the basis of 22+z positive charges taking into account the procedure by the Commission on New Mineral Names Mica Subcommittee of 1998.     

Assessment of multispectral, -temporal and -angular MODIS data for tree cover mapping in the tundra–taiga transition zone

The latitudinal tree cover gradient is an important characteristic of the tundra–taiga transition zone stretching around the northern hemisphere. Accurately mapped continuous tree cover fields would enable the depiction of forest extent over this ecotone, which is sensitive to climate change, natural disturbances and human activities. The objective of this study was to assess the explanatory power of multispectral, -temporal and -angular MODIS data to estimate tree cover at the regional scale in northernmost Finland. The standard MODIS BRDF/Albedo (MOD43B) data products at approximately 1 km resolution were used. The tree cover was estimated using generalized linear models (GLM), which were calibrated and evaluated by high resolution biotope inventory data. The benefit of coupling the multispectral, -temporal and -angular variables was assessed by variation partitioning. The predicted tree cover fields were also used for the forest–non-forest classification over a larger region and compared with the forest extent of Finnish CORINE land cover 2000 data set. The results show that multitemporal and -angular variables can increase the accuracy of the tree cover estimates and mapping of the forest extent in comparison to the peak of the growing season nadir-view multispectral data. The season of the data acquisition also affect the model performance, the late-spring and early-summer data being superior to mid- and late-summer data. Although the pure effect of the multiangular variables i.e. the parameters of the MODIS BRDF model and selected multiangular indices were relatively small in the models, the inclusion of these data increased the accuracy of the tree cover estimates in the mires in comparison to the peak of the growing season nadir-view multispectral data and multitemporal variables.     

Computational intelligence approaches and linear models in case studies of forecasting exchange rates

Artificial neural networks and fuzzy systems, have gradually established themselves as a popular tool in approximating complicated nonlinear systems and time series forecasting. This paper investigates the hypothesis that the nonlinear mathematical models of multilayer perceptron and radial basis function neural networks and the Takagi–Sugeno (TS) fuzzy system are able to provide a more accurate out-of-sample forecast than the traditional auto regressive moving average (ARMA) and ARMA generalized auto regressive conditional heteroskedasticity (ARMA-GARCH) linear models. Using series of Brazilian exchange rate (R$/US$) returns with 15 min, 60 min and 120 min, daily and weekly basis, the one-step-ahead forecast performance is compared. Results indicate that forecast performance is strongly related to the series’ frequency and the forecasting evaluation shows that nonlinear models perform better than their linear counterparts. In the trade strategy based on forecasts, nonlinear models achieve higher returns when compared to a buy-and-hold strategy and to the linear models.     

Participatory design in OSS development: interpretive case studies in company and community OSS development contexts

This article examines distributed participatory design in open source software (OSS) development. User participation is becoming a relevant topic of research in the OSS development context. Though it has not been examined much to date, the OSS development context has been argued to advocate a particular type of participatory design, which can now be scrutinised in its natural setting as it evolves. Two interpretive case studies on user participation in OSS development are included in this article. The first examines a traditional community OSS development project; the second concentrates on the company OSS development context, the case being a software development unit of a global corporation involved in OSS development. Through analysis of the cases, different forms of participatory design (PD), especially of distributed PD, are identified. Distributed PD is interpreted to include gaining an understanding of users' current practices, redesigning them together with users and gathering feedback from users related to the solutions. Different kinds of roles are available to users, as well as to for intermediaries ‘representing users’. Especially, the importance of online forum-based and intermediary-driven PD is emphasised in this article. Implications for PD and OSS research and practice are considered.     

Ecosystem functioning of protected and altered Mediterranean environments: A remote sensing classification in Doñana, Spain

Spatial heterogeneity in ecosystem functioning is a key component of ecological variability requiring special attention in the context of global change. A large history of human use has produced high physiognomic heterogeneity in Mediterranean ecosystems. However, the consequences for ecosystem functioning remain insufficiently understood. We analyzed spectral indicators of matter and energy fluxes in the land surface to classify the functional ecosystem heterogeneity in a Mediterranean region covering different management histories and protection types. We specifically analyzed the spatial variability in seasonal and annual patterns in the Normalized Difference Vegetation Index (NDVI), surface temperature (T_s) and albedo from five Landsat ETM images. Then we classified numerically this variability into ecosystem functional types (EFTs) and explored their seasonal dynamics in terms of photosynthetic radiation absorption and evapotranspiration. We identified eight main EFTs with ecologically relevant differences including contrasting dynamics in fPAR seasonality, great variation in incoming radiation reflection and differing evapotranspiration rates, particularly during the water-limitation period. Functional variability in natural vegetation mostly consisted in dissimilar annual rates of NDVI and albedo, whereas differences in seasonality were more evident in transformed areas. Similarly, the spatial distribution of EFTs was partly associated to protection, with two EFTs exclusive of protected areas and comparatively higher functional diversity in humanized areas. Landform effects on water availability in protected areas and human activities under different ecological settings were seemingly responsible for the large functional diversity of the region. We advocate for the explicit incorporation of multifunctional ecosystem heterogeneity in ecosystem management and monitoring designs.     

Online political marketing in Greece: An evaluation of the 2007 national elections and two case studies

This paper presents findings on the use of Web sites as a political marketing tool in the context of the 2007 Greek national elections. The questions guiding this research are how popular were online campaigns in terms of candidate use of Web sites and which trust and credibility-building Web site design cues were leveraged by candidates. This study also explored differences in online campaign practices both between Greek political parties and between the 2007 national Greek elections and the 2002 federal US elections.     

A step-by-step performance assessment and improvement method for ERP implementation: Action case studies in Chinese companies

The implementation of enterprise resource planning (ERP) is a complex process, and the failure rate remains very high. The literature has reported over 80 critical success factors for ERP implementation, but companies typically do not know to exploit them. In this article, a step-by-step assessment and improvement method for ERP implementation is proposed and applied in three companies. First, a five-stage ERP implementation model is proposed. Second, about 80 critical success factors (CSFs) from the literature are elaborated into key performance indices (KPIs), which are associated with each stage of ERP implementation by ten local ERP experts. Third, the weights of the KPIs are calculated using the Dumpster–Shafer method and the evaluation of ten experts. During the implementation process, performance is measured at each stage and remedial actions are identified if the performance is below expectation. An implementation flowchart is developed based on a five-stage model and the philosophy of continuous improvement. Three action cases in Chinese manufacturing companies are conducted to illustrate the effects of the assessment model, which is also currently being used by a consulting company specialising in ERP implementation. With further evaluation by local experts, the model has the potential to serve as a guideline for ERP implementation in other countries.     

Variability in surface BRDF at different spatial scales (30 m-500 m) over a mixed agricultural landscape as retrieved from airborne and satellite spectral measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities impacted by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained ~ 1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75° off-nadir, and at spatial resolutions ranging from 3 m to 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a land cover type-specific a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.     

Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain

The aim of this study is to derive parameters from spectral variations associated with heavy metals in soil and to explore the possibility of extending the use of these parameters to hyperspectral images and to map the distribution of areas affected by heavy metals on HyMAP data. Variations in the spectral absorption features of lattice OH and oxygen on the mineral surface due to the combination of different heavy metals were linked to actual concentrations of heavy metals. The ratio of 610 to 500 nm (R_610,500 nm) in the visible and near-infrared (VNIR) range, absorption area at 2200 nm (Area_2200 nm), and asymmetry of the absorption feature at 2200 nm (Asym_2200 nm) showed significant correlations with concentrations of Pb, Zn, and As, respectively. The resulting spectral gradient maps showed similar spatial patterns to geochemical gradient maps. The ground-derived spectral parameters showed a reliable quantitative relationship with heavy metal levels based on multiple linear regression. To examine the feasibility to applying these parameters to a HyMAP image, image-derived spectral parameters were compared with ground-derived parameters in terms of R², one-way ANOVA, and spatial patterns in the gradient map. The R_1344,778 nm and Area_2200 nm parameters showed a weak relationship between the two datasets (R² > 0.5), and populations of spectral parameter values, Depth_500 nm, R_1344,778 nm, and Area_2200 nm derived from the image pixels were comparable with those of ground-derived spectral parameters along a section of the stream channel. The pixels classified in the rule image of Depth_500 nm, R_1344,778 nm, and Area_2200 nm derived from a HyMAP image showed similar spatial patterns to the gradient maps of ground-derived spectral parameters. The results indicate the potential applicability of the parameters derived from spectral absorption features in screening and mapping the distribution of heavy metals. Correcting for differences in spectral and spatial resolution between ground and image spectra should be considered for quantitative mapping and the retrieval of heavy metal concentrations from HyMAP images.