Application of uncertainty and variability in LCA

As yet, the application of an uncertainty and variability analysis is not common practice in LCAs. A proper analysis will be facilitated when it is clear which types of uncertainties and variabilities exist in LCAs and which tools are available to deal with them. Therefore, a framework is developed to classify types of uncertainty and variability in LCAs. Uncertainty is divided in (1) parameter uncertainty, (2) model uncertainty, and (3) uncertainty due to choices, while variability covers (4) spatial variability, (5) temporal variability, and (6) variability between objects and sources. A tool to deal with parameter uncertainty and variability between objects and sources in both the inventory and the impact assessment is probabilistic simulation. Uncertainty due to choices can be dealt with in a scenario analysis or reduced by standardisation and peer review. The feasibility of dealing with temporal and spatial variability is limited, implying model uncertainty in LCAs. Other model uncertainties can be reduced partly by more sophisticated modelling, such as the use of non-linear inventory models in the inventory and multi media models in the characterisation phase.     

Groundwater nitrate removal in riparian buffer zones: a review of research progress in the past 20 years

This review evaluates research in the past 20 years focusing on groundwater nitrate removal in the riparian zones of agricultural watersheds. Studies have reported a large range in the magnitude of groundwater and nitrate fluxes to buffers in different hydrogeologic settings. An earlier focus on buffers with shallow subsurface flow has expanded to include sites with deep flow paths and groundwater-fed overland flow. Nitrate removal efficiency and the width required for removal have been linked to riparian sediment texture and depth to an impervious layer. Denitrification has been identified as the dominant mechanism of nitrate removal based on evidence that this process occurs at depth in many buffers which contain buried organic-rich deposits. Several studies have assessed the cumulative effect of riparian buffers on nitrate removal at the watershed scale. Despite considerable research progress areas of uncertainty still remain. Buffers with coarse-textured sediments located in landscapes with upslope sand aquifers have received most attention. In contrast, few sites have been analysed in weathered bedrock and glacial till landscapes. Many studies have reported nitrate removal efficiency based on nitrate concentrations rather than measuring groundwater fluxes which assess the magnitude of nitrate removal. More information is needed on interactions between riparian hydrological flow paths and biogeochemical processes. Further research is recommended on the effect of riparian zone nitrate removal at the watershed scale and long-term monitoring with respect to buffer restoration, the ability to sustain nitrate removal and responses to land use and climate change.

     

Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction.     

冬小麦生育期农田尺度下土壤硝态氮淋失动态的数值模拟

在北京通州区永乐店田间试验的基础上 ,假设土壤由一系列不发生相互作用的一维土柱组成 ,根据实测的土壤有机质含量 ,假定土壤有机氮的矿化作用速率常数 (零级动力学 )和有机质含量成正比 ,运用 HYDRUS- 1D软件 ,分别就考虑和不考虑土壤有机氮的矿化速率的空间变异性这两种方案 ,对 2 0 0 0～ 2 0 0 1年冬小麦生长条件下农田尺度土壤氮素转化和硝态氮淋失规律进行了数值分析。两种方案的模拟结果表明 :考虑和不考虑土壤有机氮矿化速率的空间变异性对剖面 2 5 0 cm埋深处硝态氮淋失量的影响很小 ,其差异主要在于前者对土壤氮素的矿化量、固持及反硝化量、作物吸氮量的影响更大 ,其空间变异性高于不考虑矿化速率时的结果。剖面 2 5 0 cm埋深处平均的土壤水渗透量和累积硝态氮淋失量分别为 2 .2 5 mm、0 .0 0 984 m g/cm2 ,变异系数大于 1.4 6 ,属于强变异性。对模拟结果进行地统计学分析 ,结果表明 :剖面 2 5 0 cm埋深处的土壤水渗透量和硝态氮淋失量的半方差函数为纯块金形式 ,在空间上表现为相互独立。考虑有机氮矿化速率空间变异性时的土壤氮素净转化量、吸氮量均可用球状模型描述 ,其变程与土壤有机质含量的变程接近 ,约为 4 .7m;而不考虑有机氮矿化速率空间变异性时的土壤氮素净转化量用线性无基台值     

Field Scale Variations in Soil Properties for Spatially Variable Control: A Review

This article reviews the widely scattered information on spatial variability of field-scale properties. It mainly addresses the variations in properties that influence nitrate accumulation and movement resulting from the agricultural activities in the root zone. The drive for this research comes from the perception and evidence of widespread contamination arising from production agriculture. The information is useful in the spatial management of soil for prevention of non-point source groundwater contamination from production practices. The review includes most of the static soil properties, one water transport property, some soil fertility variables, and crop yield. It examines various investigations and parameters identifying the magnitude of variability, and spatial correlation values for a given property are provided in a tabular form. Various sources of spatial variability, as well as methods of evaluating soil variability, are also discussed. For static soil properties, the range of coefficient of variation (CV) value was found to be small given the diversity of soils and field sizes on which the observations were conducted. The selected soil fertility variables and crop yield exhibited intermediate variations. However, CVs were considerably higher for the investigated transport property than those of static soil properties. The static soil properties and fertility variables were found to be correlated over a much larger distance than the transport property. If there was no variability, production through traditional practice with proper adjustment for field conditions would be the most appropriate choice. However, variations in soil and crop growth properties have led to attempts to understand these variations and application of spatially variable control in production agriculture.     

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information.     

Nutrient retention and release in a floodplain's aquifer and in the hyporheic zone of a lowland river

Fertilizer applications and other non-point sources result in an increasing diffuse N and P pollution of receiving waters degrading water quality by eutrophication with several adverse impacts. Floodplains are regarded as reactive interfaces between uplands and receiving waters. In the present study groundwater quality on its subsurface flow from an upland area through a lowland floodplain towards the receiving water body of the Spree River was monitored biweekly over 2 years with two transects of 18 groundwater observation wells. Within the floodplain reaction rates of the nutrients are unevenly distributed. On a scale smaller than the floodplain, the hyporheic zone is regarded as reactive interface with unproportional high reaction rates. Therefore, phosphate and dissolved iron were measured with high spatial resolution in the pore water of the riverbed and the oxbow bed to investigate turnover processes and their small-scale spatial variability at the immediate surface–subsurface interface. The biogeochemical composition of subsurface water is characterized by little temporal variability while spatial heterogeneity is high on the hectametre scale of the study site as well as on the centimetre scale of the bed sediments. Nitrate is eliminated very efficiently by denitrification in the anoxic aquifer of the floodplain while ammonium and phosphate concentrations increase under anoxic conditions. Phosphate and ammonium originate from the mineralization of organic matter and phosphate is additionally released by reductive dissolution of iron-bound phosphorus and weathering of bedrock. Sorption–desorption processes equalize temporal fluctuations of phosphate concentrations. Phosphate uptake by plants is assumed as an important process at only one of the groundwater observation wells. Redox conditions required for a phosphate sink are opposite to those involved in nitrate removal by denitrification. Thus, redox patchiness of floodplain aquifers favours nitrate and phosphate removal, i.e. a temporal and spatial sequence of anoxic and oxic conditions eliminates nitrogen and causes phosphate storage. On the groundwater's path from the upland to the river further phosphate is released in the bed sediments. It originates from previously settled particulate compounds containing phosphorus. While the release of iron-bound phosphorus clearly predominates in the riverbed sediments the mineralization of organic matter is an important additional phosphorus release process in the oxbow bed sediments.     

How nitrate leaching from agricultural lands provokes phosphate eutrophication in groundwater fed wetlands: the sulphur bridge

Increased phosphorus availability may provoke serious eutrophication problems in wetlands. Strong evidence indicates that sulphate induced mobilization of phosphate (internal eutrophication) has been responsible for a strong decline of the biodiversity in wetlands during the last decades. It is currently underestimated, however, that the wide spread leaching of nitrate from agricultural lands can indirectly provoke strong internal phosphate eutrophication in wetlands, via its interference with sulphur and iron biogeochemistry in the subsoil. Nitrate can mobilize sulphate from geological pyrite deposits by the oxidation of FeS_x in the aquifer, leading to a decrease of nitrate and an increase of groundwater sulphate concentrations. Furthermore nitrate immobilizes iron in the subsoil by oxidizing reduced (dissolved) iron. Increased sulphate concentrations may provoke strong phosphate eutrophication in wetlands fed directly or indirectly (via surface water) with groundwater as sulphate strongly interferes with iron phosphorus chemistry and stimulates anaerobic decomposition of organic matter. Management of wetlands should therefore be approached at a broader scale which includes the landscape-scale management of groundwater systems. Leaching of nitrate to the groundwater, for instance, should not only receive attention for its potential effects on drinking water quality but above all because of the resulting large scale mobilization of sulphate from geological pyrite deposits and the immobilization of ferrous iron.     

Partial validation of the Dutch model for emission and transport of nutrients (STONE)

The Netherlands has to cope with large losses of N and P to groundwater and surface water. Agriculture is the dominant source of these nutrients, particularly with reference to nutrient excretion due to intensive animal husbandry in combination with fertilizer use. The Dutch government has recently launched a stricter eutrophication abatement policy to comply with the EC nitrate directive. The Dutch consensus model for N and P emission to groundwater and surface water (STONE) has been developed to evaluate the environmental benefits of abatement plans. Due to the possibly severe socioeconomic consequences of eutrophication abatement plans, it is of utmost importance that the model is thoroughly validated. Because STONE is applied on a nationwide scale, the model validation has also been carried out on this scale. For this purpose the model outputs were compared with lumped results from monitoring networks in the upper groundwater and in surface waters. About 13,000 recent point source observations of nitrate in the upper groundwater were available, along with several hundreds of observations showing N and P in local surface water systems. Comparison of observations from the different spatial scales available showed the issue of scale to be important. Scale issues will be addressed in the next stages of the validation study.     

盐渍化灌区土壤盐分的时空变异特征及其与地下水埋深的关系

土壤盐分空间变异特征和地下水埋深状况是指导灌区合理用水和防治土壤盐碱化的重要依据。运用经典统计学和地质统计学方法,结合GIS技术,分析了河套灌区沙壕渠灌域0-20 cm、20-40 cm、40-60 cm土壤EC值的空间变异特征及地下水埋深对土壤盐分分布的影响。结果表明:沙壕渠灌域土壤盐分Cv值在不同灌溉时期和不同土壤深度均大于36%,表现为强变异特征;各灌水时期和不同土壤深度土壤EC值均表现为中等强度的空间自相关性,表层0-20 cm土壤空间自相关程度最高;秋浇前不同层次土壤EC值的空间分布在灌域内从南到北呈增大趋势,秋浇后土壤含盐量的高值区在西北部或东北部;土壤盐分受地下水埋深影响显著,灌域内地下水埋深南深北浅,土壤盐分随地下水埋深的增大而减小,二者之间满足指数关系。因此,应采取合理措施控制地下水埋深,防止区域土壤盐渍化加剧。     

Denitrification in a Sand and Gravel Aquifer

Denitrification was assayed by the acetylene blockage technique in slurried core material obtained from a freshwater sand and gravel aquifer. The aquifer, which has been contaminated with treated sewage for more than 50 years, had a contaminant plume greater than 3.5-km long. Near the contaminant source, groundwater nitrate concentrations were greater than 1 mM, whereas 0.25 km downgradient the central portion of the contaminant plume was anoxic and contained no detectable nitrate. Samples were obtained along the longitudinal axis of the plume (0 to 0.25 km) at several depths from four sites. Denitrification was evident at in situ nitrate concentrations at all sites tested; rates ranged from 2.3 to 260 pmol of N₂O produced (g of wet sediment)⁻¹ h⁻¹. Rates were highest nearest the contaminant source and decreased with increasing distance downgradient. Denitrification was the predominant nitrate-reducing activity; no evidence was found for nitrate reduction to ammonium at any site. Denitrifying activity was carbon limited and not nitrate limited, except when the ambient nitrate level was less than the detection limit, in which case, even when amended with high concentrations of glucose and nitrate, the capacity to denitrify on a short-term basis was lacking. These results demonstrate that denitrification can occur in groundwater systems and, thereby, serve as a mechanism for nitrate removal from groundwater.     

基于主成分回归的河南省地下水硝酸盐脆弱性评价

根据水文与地貌特征将河南省分为山区和平原区,选取富水程度、降水入渗、单位面积施肥量、蔬菜种植面积比例和土壤质地作为共性指标,坡度和地下水埋深作为个性指标,利用主成分回归分析确定指标权重,在ArcGIS 9.2的支持下对河南省地下水硝酸盐脆弱性进行评价. 结果表明,河南省地下水硝酸盐脆弱性程度以中低水平为主,中等脆弱性以下地区占总面积的68.4%,高脆弱性地区占19.8%,极高脆弱性地区占11.8%.影响河南省平原地区地下水脆弱性的主要因素依次为土壤质地、施肥水平和降水入渗,而影响山区地下水脆弱性的主要因素依次为施肥水平、土壤质地和坡度.研究结果为合理施肥和农业环境管理提供了理论依据.     

Estimating the uncertainty in annual net ecosystem carbon exchange: spatial variation in turbulent fluxes and sampling errors in eddy-covariance measurements

Above forest canopies, eddy covariance (EC) measurements of mass (CO₂, H₂O vapor) and energy exchange, assumed to represent ecosystem fluxes, are commonly made at one point in the roughness sublayer (RSL). A spatial variability experiment, in which EC measurements were made from six towers within the RSL in a uniform pine plantation, quantified large and dynamic spatial variation in fluxes. The spatial coefficient of variation (CV) of the scalar fluxes decreased with increasing integration time, stabilizing at a minimum that was independent of further lengthening the averaging period (hereafter a ‘stable minimum’). For all three fluxes, the stable minimum (CV=9–11%) was reached at averaging times (τ_p) of 6–7 h during daytime, but higher stable minima (CV=46–158%) were reached at longer τ_p (>12 h) during nighttime. To the extent that decreasing CV of EC fluxes reflects reduction in micrometeorological sampling errors, half of the observed variability at τ_p=30 min is attributed to sampling errors. The remaining half (indicated by the stable minimum CV) is attributed to underlying variability in ecosystem structural properties, as determined by leaf area index, and perhaps associated ecosystem activity attributes. We further assessed the spatial variability estimates in the context of uncertainty in annual net ecosystem exchange (NEE). First, we adjusted annual NEE values obtained at our long‐term observation tower to account for the difference between this tower and the mean of all towers from this experiment; this increased NEE by up to 55 g C m^?2 yr^?1. Second, we combined uncertainty from gap filling and instrument error with uncertainty because of spatial variability, producing an estimate of variability in annual NEE ranging from 79 to 127 g C m^?2 yr^?1. This analysis demonstrated that even in such a uniform pine plantation, in some years spatial variability can contribute ～50% of the uncertainty in annual NEE estimates.     

Relationship between DOC concentration and vadose zone thickness and depth below water table in groundwater of Cape Cod, U.S.A.

Changes in concentration ofdissolved organic carbon (DOC) reflectbiogeochemical processes that determinechemical composition of groundwater and othernatural waters. We found that the deeper thevadose zone, the lower the concentration of DOCin groundwater near the water table, indicatingthat considerable attenuation ofsurface-derived DOC occurred in the vadosezone. Under vadose zones <1.25 m, DOCconcentrations at the surface of the watertable ranged to >20 mg C l^–1, while forvadose zones >5.0 m, DOC never exceeded2.0 mg C l^–1. DOC concentrations alsodecreased exponentially with increasing depthbelow the water table, most notably in theupper two meters, implying continuedattenuation in the upper layer of the saturatedzone. Ninety-nine percent of the DOC wasattenuated by the time the water reached adepth of 19 m below the water table. A stronginverse relationship between DOC and nitrateconcentrations suggests that nitrate isdepleted where DOC supplies are high, providingevidence that some portion of the DOC losses ingroundwater are due to microbialtransformations, including denitrification. DOC concentrations in shallow groundwater showconsiderable spatial variability, butconcentration of DOC at any one site issurprisingly stable over time. The largestsource of variation in DOC concentration ingroundwater therefore is spatial rather thantemporal, suggesting that local heterogeneitiesplay an important role in DOC delivery toshallow groundwater. Our results highlightboth the importance of shallow vadose areas inDOC delivery to groundwater and the need todistinguish where samples are collected inrelation to flow paths before conclusions aremade about mean groundwater DOC concentrations. The substantial losses of DOC in the vadosezone and in shallow depths within the aquifersuggest quite active biogeochemical processesin these boundary environments.     

Interpreting spatial patterns in redox and coupled water–nitrogen fluxes in the streambed of a gaining river reach

Water pathways through permeable riverbeds are multi-dimensional, including lateral hyporheic exchange flows as well as vertical (upwelling and downwelling) fluxes. The influence of different pathways of water on solute patterns and the supply of nitrate and other redox-sensitive chemical species in the riverbed is poorly understood but could be environmentally significant. For example, nitrate-rich upwelling water in the gaining reaches of groundwater-fed rivers has the potential to supply significant quantities of nitrate through the riverbed to surface waters, constraining opportunities to deliver the goals of the EU Water Framework Directive to achieve ‘good ecological status’. We show that patterns in porewater chemistry in the armoured river bed of a gaining reach (River Leith, Cumbria) reflect the spatial variability in different sources of water; oxic conditions being associated with preferential discharge from groundwater and reducing conditions with longitudinal and lateral fluxes of water due to water movement from riparian zones and/or hyporheic exchange flows. Our findings demonstrate the important control of both vertical and lateral water fluxes on patterns of redox-sensitive chemical species in the river bed. Furthermore, under stable, baseflow conditions (<Q₉₀) a zone of preferential discharge, comprising 20 % of the reach by area contributes 4–9 % of the total nitrate being transported through the reach in surface water, highlighting the need to understand the spatial distribution of such preferential discharge locations at the catchment scale to establish their importance for nitrate delivery to the stream channel.     

Prioritizing regionalization to enhance interpretation in consequential life cycle assessment: application to alternative transportation scenarios using partial equilibrium economic modeling

Purpose

Consequential life cycle assessment (C-LCA) aims to assess the environmental consequences of a decision. It differs from traditional LCA because its inventory includes all the processes affected by the decision which are identified by accounting for causal links (physical, economic, etc.). However, C-LCA results could be quite uncertain which makes the interpretation phase harder. Therefore, strategies to assess and reduce uncertainty in C-LCA are needed. Part of uncertainty in C-LCA is due to spatial variability that can be reduced using regionalization. However, regionalization can be complex and time-consuming if straightforwardly applied to an entire LCA model.

Methods

The main purpose of this article is to prioritize regionalization efforts to enhance interpretation in C-LCA by assessing the spatial uncertainty of a case study building on a partial equilibrium economic model. Three specific objectives are derived: (1) perform a C-LCA case study of alternative transportation scenarios to investigate the benefits of implementing a public policy for energy transition in France by 2050 with an uncertainty analysis to explore the strength of our conclusions, (2) perform global sensitivity analyses to identify and quantify the main sources of spatial uncertainty between foreground inventory model from partial equilibrium economic modeling, background inventory model and characterization factors, (3) propose a strategy to reduce the spatial uncertainty for our C-LCA case study by prioritizing regionalization.

Results and discussion

Results show that the implementation of alternative transport scenarios in compliance with public policy for the energy transition in France is beneficial for some impact categories (ICs) (global warming, marine acidification, marine eutrophication, terrestrial acidification, thermally polluted water, photochemical oxidant formation, and particulate matter formation), with a confidence level of 95%. For other ICs, uncertainty reduction is required to determine conclusions with a similar level of confidence. Input variables with spatial variability from the partial equilibrium economic model are significant contributors to the C-LCA spatial uncertainty and should be prioritized for spatial uncertainty reduction. In addition, characterization factors are significant contributors to the spatial uncertainty results for all regionalized ICs (except land occupation IC).

Conclusions

Ways to reduce the spatial uncertainty from economic modeling should be explored. Uncertainty reduction to enhance the interpretation phase and the decision-making should be prioritized depending on the goal and scope of the LCA study. In addition, using regionalized CFs in C-LCA seems to be relevant, and C-LCA calculation tools should be adapted accordingly.

     

Removal of nitrate from groundwater by cyanobacteria: quantitative assessment of factors influencing nitrate uptake

The feasibility of biologically removing nitrate from groundwater was tested by using cyanobacterial cultures in batch mode under laboratory conditions. Results demonstrated that nitrate-contaminated groundwater, when supplemented with phosphate and some trace elements, can be used as growth medium supporting vigorous growth of several strains of cyanobacteria. As cyanobacteria grew, nitrate was removed from the water. Of three species tested, Synechococcus sp. strain PCC 7942 displayed the highest nitrate uptake rate, but all species showed rapid removal of nitrate from groundwater. The nitrate uptake rate increased proportionally with increasing light intensity up to 100 micromol of photons m(-2) s(-1), which parallels photosynthetic activity. The nitrate uptake rate was affected by inoculum size (i.e., cell density), fixed-nitrogen level in the cells in the inoculum, and aeration rate, with vigorously aerated, nitrate-sufficient cells in mid-logarithmic phase having the highest long-term nitrate uptake rate. Average nitrate uptake rates up to 0.05 mM NO(3-) h(-1) could be achieved at a culture optical density at 730 nm of 0.5 to 1. 0 over a 2-day culture period. This result compares favorably with those reported for nitrate removal by other cyanobacteria and algae, and therefore effective nitrate removal from groundwater using this organism could be anticipated on large-scale operations.     

The Use of Probabilistic Risk Assessment in Establishing Drinking Water Quality Objectives

There has been a trend in recent years toward the use of probabilistic methods for the analysis of uncertainty and variability in risk assessment. By developing a plausible distribution of risk, it is possible to obtain a more complete characterization of risk than is provided by either best estimates or upper limits. We describe in this paper a general framework for evaluating uncertainty and variability in risk estimation and outline how this framework can be used in the establishment of drinking water quality objectives. In addition to characterizing uncertainty and variability in risk, this framework also facilitates the identification of specific factors that contribute most to uncertainty and variability. The application of these probabilistic risk assessment methods is illustrated using tetrachloroethylene and trihalomethanes as examples.     

Interactions between landcover pattern and geospatial processing methods: Effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric “number of patches” than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty.