Spatial Patterns Of Land Cover Research Articles

Assessment of Land Cover Status and Change in the World and "the Belt and Road" Region from 2016 to 2020.

The assessment of land cover and changes will help to understand the temporal and spatial pattern of land cover in the world and the Belt and Road (B&R) region, and provide reference information for global sustainable development and the Belt and Road construction. In this paper, the 1 km global land cover classification maps of 2016 and 2020 with a high accuracy of 88% are mapped using the Moderate Resolution Imaging Spectroradiometer (MODIS) time series surface reflectance products. Based on the maps, the land cover status of the world and the Belt and Road region, the land cover change from 2016 to 2020, and the mutual transformation characteristics between various types, are analyzed. The research results indicate that from 2016 to 2020, the global change rates of cropland, forest, grassland, and impervious surface are 0.25%, 0.22%, 0.08% and 3.41%, respectively. In the Belt and Road region, the change rates of cropland, forest, grassland, and impervious surface are 0.42%, 0.60%, -0.55% and 2.98% respectively. The assessment results will help to clarify the spatial pattern of land cover change in the five years from 2016 to 2020, so as to provide valuable scientific information for the global realization of sustainable development goals and the construction of the B&R.

Toward a High Spatial Resolution Aerial Monitoring Network for Nature Conservation—How Can Remote Sensing Help Protect Natural Areas?

Aerial surveys have always significantly contributed to the accurate mapping of certain geographical phenomena. Remote sensing opened up new perspectives in nature monitoring with state-of-the-art technical solutions using modern onboard recording equipment. We developed the technical background and the methodology that supports detailed and cost-effective monitoring of a network of natural areas, thereby detecting temporal changes in the spatial pattern of land cover, species, biodiversity, and other natural features. In this article, we share our experiences of the technical background, geometric accuracy and results of comparisons with selected Copernicus Land Monitoring products and an Ecosystem Map based on the testing of our methodology at 25 sites in Hungary. We combined a high-spatial-resolution aerial remote sensing service with field studies to support an efficient nature conservation monitoring network at 25 permanent sites. By analyzing annually (or more frequently) orthophotos taken with a range of 0.5–5 cm spatial resolution and 3D surface models of aerial surveys, it is possible to map the upper canopy of vegetation species. Furthermore, it allows us to accurately follow the changes in the dynamics at the forest edge and upper canopy, or the changes in species’ dominance in meadows. Additionally, spatial data obtained from aerial surveys and field studies can expand the knowledge base of the High-Resolution Aerial Monitoring Network (HRAMN) and support conservation and restoration management. A well-conducted high-resolution survey can reveal the impacts of land interventions and habitat regeneration. By building the HRAMN network, nature conservation could have an up-to-date database that could prompt legal processes, establish protection designation procedures and make environmental habitat management more cost-effective. Landscape protection could also utilize the services of HRAMN in planning and risk reduction interventions through more reliable inputs to environmental models.

The Flows of Nature to People, and of People to Nature: Applying Movement Concepts to Ecosystem Services

To date, the provision of ecosystem services has largely been estimated based on spatial patterns of land cover alone, using benefit transfer analysis. Although it is increasingly being recognised that the distribution of the human population affects whether a potential service translates into a realised service, this misses key steps in the process and assumes that everyone accesses ecosystem services in the same way. Here we describe a conceptual approach to ecosystem services in terms of movement and flows. We highlight that ecosystem service flows can be broken down into ‘nature to people’ (the movement of nature towards beneficiaries) and ‘people to nature’ (the movement of beneficiaries towards nature). The former has been relatively well described. Here, we explore the latter by reviewing research on human migration, animal foraging and landscape connectivity. We assess if and how existing theories might be useful in describing how people seek out ecosystem services. We consider some of the ways in which flows of people to nature can be measured. Such measurements may reveal which movement theories best represent how people seek out and access ecosystem services. Overall, our review aims to improve the future modelling of ecosystem services by more explicitly considering how people access potential services and therefore realise them.

Progressive fragmentation and loss of natural forest habitat in one of the world’s biodiversity hotspots

Knowledge of the state of fragmentation and transformation of a forested landscape is crucial for proper planning and biodiversity conservation. Chile is one of the world’s biodiversity hotspots; within it is the Nahuelbuta mountain range, which is considered an area of high biodiversity value and intense anthropic pressure. Despite this, there is no precise information on the degree of transformation of its landscape and its conservation status. The objective of this work was to evaluate the state of the landscape and the spatio-temporal changes of the native forests in this mountain range. Using Landsat images from 1986 and 2011, thematic maps of land use were generated. A 33% loss of native forest in 25 years was observed, mainly associated to the substitution by forest plantations. Changes in the spatial patterns of land cover and land use reveal a profound transformation of the landscape and advanced fragmentation of forests. We discuss how these patterns of change threaten the persistence of several endemic species at high risk of extinction. If these anthropogenic processes continue, these species could face an increased risk of extinction.

Market Structure and the Local Effects of Ethanol Expansion on Land Allocation: A Spatially Explicit Analysis

We investigate how the structures of local corn procurement markets shape the effect of expansion in ethanol production on corn planting decisions in surrounding areas. We first characterize competition intensity as a function of the spatial structure of plant capacities and then econometrically estimate the response in corn acreage to competition intensity at the grid‐cell level. We use the estimated parameters to conduct factual and counterfactual experiments quantifying the effect of different sources of capacity expansion on competition intensity and, ultimately, spatial patterns of land cover. We find that an expansion of ethanol capacity of a given magnitude can have disparate effects on total land conversion to corn depending on its source, that is, whether it is due to plant entry, expansion of an incumbent plant, or the location where the expansion occurs. Expansions that increase competition intensity the most also trigger the most land conversion. This is because, as spatial competition for corn intensifies, plants are forced to procure more from the intensive margin, where additional corn can only be obtained from land conversion. We also find that competitive spillovers trigger land conversion in grid cells that are not within the procurement area of a new plant or of a plant that expands capacity. Our results underscore the importance of considering market structure when quantifying local land use changes associated with ethanol capacity expansion.

Super-resolution land cover mapping by deep learning

ABSTRACTSuper-resolution mapping (SRM) is a technique to estimate a fine spatial resolution land cover map from coarse spatial resolution fractional proportion images. SRM is often based explicitly on the use of a spatial pattern model that represents the land cover mosaic at the fine spatial resolution. Recently developed deep learning methods have considerable potential as an alternative approach for SRM, based on learning the spatial pattern of land cover from existing fine resolution data such as land cover maps. This letter proposes a deep learning-based SRM algorithm (DeepSRM). A deep convolutional neural network was first trained to estimate a fine resolution indicator image for each class from the coarse resolution fractional image, and all indicator maps were then combined to create the final fine resolution land cover map based on the maximal value strategy. The results of an experiment undertaken with simulated images show that DeepSRM was superior to conventional hard classification and a suite of popular SRM algorithms, yielding the most accurate land cover representation. Consequently, methods such as DeepSRM may help exploit the potential of remote sensing as a source of accurate land cover information.

Fragmentación progresiva y pérdida de hábitat de bosques naturales en uno de los hotspot mundiales de biodiversidad

The understanding of the degree of forest fragmentation and landscape transformation is crucial for landscape sustainability and biodiversity conservation. Within the Chilean hotspot the Nahuelbuta Mountain can be found, which is considered as a high biodiversity value area under an intense human pressure. However, there is no information on the degree of transformation of the landscape and the conservation status of its natural forest ecosystems. The aim of this study was to evaluate the state of the landscape and the spatiotemporal changes in native forests in Nahuelbuta. Through the use of Landsat imagery acquired for 1986 and 2011, land-cover and use maps were generated. Results revealed a loss of 33% of native forest in 25 years, mainly associated with the conversion to forest plantations. Changes in spatial patterns of land-cover and uses revealed a profound transformation of the study landscape and an advanced fragmentation of native forests. We discuss how these changes threaten the persistence of different endemic species at high risk of extinction. If the current trend of spatial pattern changes continues, it is probable that these species might face an increase in their extinction risk.

Modelling the impact of rural land use scenarios on water management: a FREEWAT approach to the Bakumivka catchment case study, Ukraine

The Bakumivka River’s catchment, Ukraine serves as a case study to the application of FREEWAT to the ground and surface water management. The main objective of the study is to find out the optimal spatial distribution of the water supplied to the farms by modifying the land cover pattern of the catchment. An integrated numerical model was developed to provide quantitative estimates of the water budget components. The model includes four model layers, representing the main hydrostratigraphic units, different types of boundary conditions assigned along the area’s boundaries, major components of the water balance introduced through source and sink layers. It was implemented through the FREEWAT software. Three water management scenarios were developed in order to compare different spatial patterns of land cover and distribution of water within the Bakumivka River’s basin. The scenarios represent continuum from market oriented pattern to environmentally sounding pattern of land cover. The objective of the modeling exercise is to obtain mass balances and maps representing three scenarios of water management. Each map shows distribution of the areas where the water balance is optimal, insufficient (dry) or excessive (wet) for vegetation (land cover) of particular type.The simulation shows that changing spatial land cover pattern is an effective measure to reduce water supply to the farms, however it does not prevent water logging in the areas adjacent to the flood plains and drying on summer stress periods in lands of sandyloam soils. Irrigation should be excluded in the areas with sandy and sandyloam soils. The flood plain with peat bogs despite the high water head in spring and late summer stress periods should be irrigated to prevent peat fires. The intrusion of eco-corridors to the land cover pattern in the catchment is positive from ecological perspective, but could prevent drainage causing water logging in the arable lands.

Fertility and urban context: A case study from Ghana, West Africa, using remotely sensed imagery and GIS

AbstractSub‐Saharan Africa has the highest levels of fertility in the world, despite rapid urban growth in most nations of the region. While there are many reasons for the fact that fertility decline is slow in Africa, we hypothesize that the relationship between fertility and urbanization is obscured by the fact that urbanization takes place along a gradient. In the most urban places (e.g., neighborhoods of the largest cities), fertility is apt to be very low, but most urban residents are residing in places that are somewhere along a continuum from completely rural to the most urban possible. All previous attempts to define that urban gradient and relate it to fertility levels rely in one form or another on census data. Because sub‐Saharan‐African countries are among the least prolific in terms of census gathering, a measure that relies solely on satellite imagery to gage a place's position along the urban gradient could be extremely useful. This paper describes a methodology for doing this and then uses data from the West African country of Ghana to examine how spatial patterns of land cover are associated with fertility. Satellite imagery and landscape metrics are used to create an urban context definition based on landscape patterns using a gradient approach. Census data are used to model the association between urban context and fertility through ordinary least square regression and spatial autoregressive models. Results indicate that there are significant differences in fertility between different urban contexts.

Landscape structure affects the provision of multiple ecosystem services

Understanding how landscape structure, the composition and configuration of land use/land cover (LULC) types, affects the relative supply of ecosystem services (ES), is critical to improving landscape management. While there is a long history of studies on landscape composition, the importance of landscape configuration has only recently become apparent. To understand the role of landscape structure in the provision of multiple ES, we must understand how ES respond to different measures of both composition and configuration of LULC. We used a multivariate framework to quantify the role of landscape configuration and composition in the provision of ten ES in 130 municipalities in an agricultural region in Southern Québec. We identified the relative influence of composition and configuration in the provision of these ES using multiple regression, and on bundles of ES using canonical redundancy analysis. We found that both configuration and composition play a role in explaining variation in the supply of ES, but the relative contribution of composition and configuration varies significantly among ES. We also identified three distinct ES bundles (sets of ES that regularly appear together on the landscape) and found that each bundle was associated with a unique area in the landscape, that mapped to a gradient in the composition and configuration of forest and agricultural LULC. These results show that the distribution of ES on the landscape depends upon both the overall composition of LULC types and their configuration on the landscape. As ES become more widely used to steer land use decision-making, quantifying the roles of configuration and composition in the provision of ES bundles can improve landscape management by helping us understand when and where the spatial pattern of land cover is important for multiple services.

Inter-regional pattern of urbanization in southern Ghana in the first decade of the new millennium

We analyze amounts and spatial patterns of land cover and land use change (LCLUC) and particularly change to Built for four contiguous regions of southern Ghana between 2000 and 2010. Our objective is to understand the degree of urban expansion relative to urban densification during this time frame, to understand the relationship between population growth and LCLUC at the census district level, and to explain the patterns of New Built LCLUC throughout this study area. During the study period 1.5% of the study area transitioned to Built, an increase of 56% Built area since 2000, while population increased by 33%. Most (84% of total study area) of this change to Built involved conversion from Agriculture al land use and occurred predominantly in suburban and periurban areas zones of the Accra and Kumasi metropolitan areas. While total population and amount of Built LCLU variables co-vary strongly at the census district level at the beginning and end of the study period, change in population and Built are less strongly correlated. In fact, we observe that new Built development increased at a greater rate than population growth within peri-urban areas of Accra and Kumasi, frequently occurring as spaced residential land use composed of large houses with minimal urban infrastructure.

Simulation of runoff and nutrient export from a typical small watershed in China using the Hydrological Simulation Program-Fortran.

The Hydrological Simulation Program-Fortran (HSPF), which is a hydrological and water-quality computer model that was developed by the United States Environmental Protection Agency, was employed to simulate runoff and nutrient export from a typical small watershed in a hilly eastern monsoon region of China. First, a parameter sensitivity analysis was performed to assess how changes in the model parameters affect runoff and nutrient export. Next, the model was calibrated and validated using measured runoff and nutrient concentration data. The Nash-Sutcliffe efficiency (E NS ) values of the yearly runoff were 0.87 and 0.69 for the calibration and validation periods, respectively. For storms runoff events, the E NS values were 0.93 for the calibration period and 0.47 for the validation period. Antecedent precipitation and soil moisture conditions can affect the simulation accuracy of storm event flow. The E NS values for the total nitrogen (TN) export were 0.58 for the calibration period and 0.51 for the validation period. In addition, the correlation coefficients between the observed and simulated TN concentrations were 0.84 for the calibration period and 0.74 for the validation period. For phosphorus export, the E NS values were 0.89 for the calibration period and 0.88 for the validation period. In addition, the correlation coefficients between the observed and simulated orthophosphate concentrations were 0.96 and 0.94 for the calibration and validation periods, respectively. The nutrient simulation results are generally satisfactory even though the parameter-lumped HSPF model cannot represent the effects of the spatial pattern of land cover on nutrient export. The model parameters obtained in this study could serve as reference values for applying the model to similar regions. In addition, HSPF can properly describe the characteristics of water quantity and quality processes in this area. After adjustment, calibration, and validation of the parameters, the HSPF model is suitable for hydrological and water-quality simulations in watershed planning and management and for designing best management practices.

Partial least-squares regression for linking land-cover patterns to soil erosion and sediment yield in watersheds

Summary There are strong ties between land cover patterns and soil erosion and sediment yield in watersheds. The spatial configuration of land cover has recently become an important aspect of the study of geomorphological processes related to erosion within watersheds. Many studies have used multivariate regression techniques to explore the response of soil erosion and sediment yield to land cover patterns in watersheds. However, many landscape metrics are highly correlated and may result in redundancy, which violates the assumptions of a traditional least-squares approach, thus leading to singular solutions or otherwise biased parameter estimates and confidence intervals. Here, we investigated the landscape patterns within watersheds in the Upper Du River watershed (8973 km 2 ) in China and examined how the spatial patterns of land cover are related to the soil erosion and sediment yield of watersheds using hydrological modeling and partial least-squares regression (PLSR). The results indicate that the watershed soil erosion and sediment yield are closely associated with the land cover patterns. At the landscape level, landscape characteristics, such as Shannon’s diversity index (SHDI), aggregation index (AI), largest patch index (LPI), contagion (CONTAG), and patch cohesion index (COHESION), were identified as the primary metrics controlling the watershed soil erosion and sediment yield. The landscape characteristics in watersheds could account for as much as 65% and 74% of the variation in soil erosion and sediment yield, respectively. Greater interspersion and an increased number of patch land cover types may significantly accelerate soil erosion and increase sediment export. PLSR can be used to simply determine the relationships between land-cover patterns and watershed soil erosion and sediment yield, providing quantitative information to allow decision makers to make better choices regarding landscape planning. With readily available remote sensing data and rapid developments in geographic information system (GIS) technology, this practical and simple PLSR approach could be applied to a variety of other watersheds.

Projection of the Spatially Explicit Land Use/Cover Changes in China, 2010–2100

Land use/cover change (LUCC) is an important part of the global environmental change. This study predicted the future structure of land use/cover on the basis of the Global Change Assessment Model (GCAM) and an econometric model with the socioeconomic factors as the driving forces. The future spatial pattern of land use/cover in China was simulated with the Dynamics of Land System (DLS) under the Business as Usual scenario, Rapid Economic Growth scenario and Cooperate Environmental Sustainability scenario. The simulation results showed that the land use/land cover in China will change continually due to the human activities and climate change, and the spatial pattern of land use/cover will also change as time goes by. Besides, the spatial pattern of land cover in China under the three scenarios is consistent on the whole, but with some regional differences. Built-up area will increase rapidly under the three scenarios, while most land cover types will show a decreasing trend to different degrees under different scenarios. The simulation results can provide an underlying land surface data and reference to the methodology research on the prediction of LUCC.

The Spatial Pattern of Landcover in the Drawdown Area of Danjiangkou Reservoir

In this paper,the location of the submerging area at different water levels(150 m,160 m,170 m and 172 m) in Danjiangkou reservoir basin was detected based on the DEM data,and the landcover below 172 m level was obtained by using object-oriented classification approach based on RapidEye and Landsat-5 TM data.The authors analyzed not only the spatial patterns of the landcover in the drawdown areas but also the impact factors.The results show that the acreage of the drawdown area at 150-160 m,160-170 m and 170-172 m level is 232.0 km2,242.6 km2 and 43.1 km2 respectively.The acreage of the cultivated land is the largest,accounting for about 50% in every drawdown area.In addition,the acreage of the bare land is larger at the low water level,while that of the forest is larger at the high water level.Dynamic scheduling and slope constitute the impact factors on the spatial pattern of landcover.Both have a significant impact on the distribution of landcover in the low elevation region,while the slope has a significant impact on the distribution of landcover in the high elevation region.

How landscapes change: Integration of spatial patterns and human processes in temperate landscapes of southern Chile

A comprehensive understanding of the patterns that occur as human processes transform landscapes is necessary for sustainable development. We provide new evidence on how landscapes change by analysing the spatial patterns of human processes in three forest landscapes in southern Chile at different states of alteration (40%–90% of old-growth forest loss). Three phases of landscape alteration are distinguished. In Phase I (40%–65% of old-growth forest loss), deforestation rates are < 1% yr −1, forests are increasingly degraded, and clearance for pastureland is concentrated on deeper soils. In Phase II (65%–80%), deforestation reaches its maximum rate of 1–1.5% yr −1, with clearance for pastureland being the main human process, creating a landscape dominated by disturbed forest and shrubland. In this phase, clearance for pastureland is the primary driver of change, with pastures expanding onto poorer soils in more spatially aggregated patterns. In Phase III (80%–90%), deforestation rates are again relatively low (<1% yr −1) and forest regrowth is observed on marginal lands. During this phase, clearance is the dominant process and pastureland is the main land cover. As a forest landscape is transformed, the extent and intensity of human processes vary according to the existing state of landscape alteration, resulting in distinctive landscape patterns in each phase. A relationship between spatial patterns of land cover and human-related processes has been identified along the gradient of landscape alteration. This integrative framework can potentially provide insights into the patterns and processes of dynamic landscapes in other areas subjected to intensifying human use.

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division,Kenya

Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change. Alterations in its status can have significant ramifications at local, regional and global levels. Hence, it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization, prediction and management of the potential environmental impacts. This paper presents the results of an effort to map land cover patterns in Kinangop division, Kenya, using geospatial tools. This is a geographic locality that has ex-perienced rapid land use transformations since Kenya’s independence culminating in uncontrolled land cover changes and loss of biodiversity. The changes in land use/ cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management. As such, the study had two objectives viz. (i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and; (ii) evaluating the quality of the resultant land cover map. ASTER satellite imagery acquired in January 23, 2007 was procured and field data gathered between September 10 and October 16, 2007. The latter were used for training the maximum likelihood classifier and validating the resultant land cover map. The land cover classification yielded 5 classes, overall accuracy of 83.5 % and kappa statistic of 0.79, which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.

Spatiotemporal analysis of an acoustic environment: interactions between landscape features and sounds

So far landscape analysis meant analysis of the spatial pattern of land cover or land use. However, biological organisms do not perceive the landscape only as land cover or land use, but they use all their senses, in order to become familiar with and react to their surroundings. We analyzed the acoustic environment as an additional layer of spatial information in landscape analysis, shortening the monopoly of visual patterns as landscape descriptors. We recorded sounds from a rural protected area into seven categories based on their origin, and examined their spatiotemporal variability and their correlation with landscape characteristics. The sounds were distinguished as Foreground or Background sounds. Foreground sounds correspond to sharp sounds originating near the observer and usually are understood as signals of urgent information, triggering reactions; while background sounds carry information over longer distances and may be used as landmarks to help individuals find their bearing even in the absence of visual signs. We found that the acoustic environment varies both temporally and spatially reflecting anthropogenic, geophysical and biological activities. The spatial pattern of the background sounds correlates, to an extent, with the visually perceived landscape features, but it does not correlate with the spatial pattern of the foreground sounds, which do not correlate strongly with the landscape pattern. This spatial pattern mismatch between acoustic environment and landscape, along with the highly dynamic nature of the acoustic environment compared to the relatively static nature of the land cover and land use spatial pattern highlight a limitation of the classical landscape analysis, and expands our understanding of the cognitive landscape.

Stream ecosystem responses to spatially variable land cover: an empirically based model for developing riparian restoration strategies

Summary1. The restoration of native, forested riparian habitats is a widely accepted method for improving degraded streams. Little is known, however, about how the width, extent and continuity of forested vegetation along stream networks affect stream ecosystems.2. To increase the likelihood of achieving restoration goals, restoration practitioners require quantitative tools to guide the development of restoration strategies in different catchment settings. We present an empirically based model that establishes a relationship between a ‘stress’ imposed at different locations along a stream by the spatial pattern of land cover within catchments, and the response of biologically determined ecosystem characteristics to this stress. The model provides a spatially explicit, quantitative framework for predicting the effects of changes in catchment land cover composition and spatial configuration on specific characteristics of stream ecosystems.3. We used geospatial datasets and biological data for attached algae and benthic macroinvertebrates in streams to estimate model parameters for 40 sites in 33 distinct catchments within the mid‐Atlantic Piedmont region of the eastern U.S. Model parameters were estimated using a genetic optimisation algorithm. R2 values for the resulting relationships between catchment land cover and biological characteristics of streams were substantially improved over R2 values for spatially aggregated regression models based on whole‐catchment land cover.4. Using model parameters estimated for the mid‐Atlantic Piedmont, we show how the model can be used to guide restoration planning in a case study of a small catchment. The model predicts the quantitative change in biological characteristics of the stream, such as indices of species diversity and species composition, that would occur with the implementation of a hypothetical restoration project.

HISTORICAL TRENDS IN SEDIMENTATION RATES AND SEDIMENT PROVENANCE, FAIRFIELD LAKE, WESTERN NORTH CAROLINA

: Sedimentation rates and sediment provenance were examined for lacustrine sediments deposited in Fairfield Lake, western North Carolina, during the past 111 years. Stratigraphic, radionuclide, and cartographic data indicate that sedimentation rates have increased several fold during the past three decades in response to localized development. The magnitude of increased sedimentation was surprising given limited development within the basin: 0.12 to 0.68 buildings/ha in 2000 in those parts directly delivering sediment to the dated cores. Thus, the analysis illustrates the potential sensitivity of watersheds in the southern Appalachians to changes in land cover. An approach that combined geochemical fingerprinting with sediment mixing models was subsequently evaluated to determine its ability to accurately estimate the contribution of sediment from (1) major bedrock formations that underlie the watershed and (2) potential sources associated with four land cover categories. Sediment sources in both analyses proved difficult to geochemically fingerprint to greater than 90 percent accuracy using data on acid-soluble metals and selected isotopes of lead (Pb). The relative contributions of sediment from delineated sources, estimated by the mixing models, generally corresponded with known temporal and spatial patterns of land cover. However, the models were plagued by two significant problems — the chemical alteration of sediments as they were transported through upland streams to depositional sites within the lake and the loss of elemental mass. Thus, future investigations using the fingerprinting approach in this area of intense weathering, and presumably others, will need to modify the existing methods to more accurately elucidate changes in sediment provenance related to development.