A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules

Cellular automata (CA) have emerged as a primary tool for urban growth modeling due to its simplicity, transparency, and ease of implementation. Sensitivity analysis is an important component in CA modeling for a better understanding of errors or uncertainties and their propagation. Most studies on sensitivity analyses in urban CA modeling focus on specific component such as neighborhood configuration or stochastic perturbation. However, sensitivity analysis of transition rules, which is one of the core components in CA models, has not been systematically done. This article proposes a systematic sensitivity analysis of major operational components in urban CA modeling using a stepwise comparison approach. After obtaining transition rules, three stages (i.e. static calibration of transition rules, dynamic evolution with varied time steps, and incorporation with stochastic perturbation) are designed to facilitate a comprehensive analysis. This scheme implemented with a case study in Guangzhou City (China) reveals that gaps in performance from static calibration with different transition rules can be reduced when dynamic evolution is considered. Moreover, the degree of stochastic perturbation is closely related to obtain urban morphology. However, a more realistic (i.e. fragmented) urban landscape is achieved at the cost of decreasing pixel-based accuracy in this study. Thus, a trade-off between pixel-based and pattern-based comparisons should be balanced in practical urban modeling. Finally, experimental results illustrate that models for transition rules extraction with good quality can do an assistance for urban modeling through reducing errors and uncertainty range. Additionally, ensemble methods can feasibly improve the performance of CA models when coupled with nonparametric models (i.e. classification and regression tree).     

基于案例推理的元胞自动机及大区域城市演变模拟

元胞自动机(CA) 被越来越多地用于复杂系统的模拟中。许多地理现象的演变与其影响要素之间存在着复杂的关系, 并往往具有时空动态性。在研究区域较大和模拟时间较长时, 定义具体的规则来反映这种复杂关系有较大的困难。为了解决CA 转换规则获取的瓶颈问题, 提出了基于案例推理(CBR) 的CA 模型, 并对CBR 的k 近邻算法进行了改进, 使其能反映转换规则的时空动态性。将该模型应用于大区域的珠江三角洲城市演变中。实验结果显示, 其模拟的空间格局与实际情况吻合较好。与常规的基于Logistic 的CA 模型进行了对比, 所获得的模拟结果有更高的精度和更接近实际的空间格局, 特别在模拟较为复杂的区域时有更好的模拟效果。     

A partitioned and asynchronous cellular automata model for urban growth simulation

Cellular automata (CA) models are used to analyze and simulate the global phenomenon of urban growth. However, these models are characterized by ignoring spatially heterogeneous transition rules and asynchronous evolving rates, which make it difficult to improve urban growth simulations. In this paper, a partitioned and asynchronous cellular automata (PACA) model was developed by implementing the spatial heterogeneity of both transition rules and evolving rates in urban growth simulations. After dividing the study area into several subregions by k-means and knn-cluster algorithms, a C5.0 decision tree algorithm was employed to identify the transition rules in each subregion. The evolving rates for cells in each regularly divided grid were calculated by the rate of changed cells. The proposed PACA model was implemented to simulate urban growth in Wuhan, a large city in central China. The results showed that PACA performed better than traditional CA models in both a cell-to-cell accuracy assessment and a shape dimension accuracy assessment. Figure of merit of PACA is 0.368 in this research, which is significantly higher than that of partitioned CA (0.327) and traditional CA (0.247). As for the shape dimension accuracy, PACA has a fractal dimension of 1.542, which is the closest to that of the actual land use (1.535). However, fractal dimension of traditional CA (1.548) is closer to that of the actual land use than that of partitioned CA (1.285). It indicates that partitioned transition rules play an important role in the cell-to-cell accuracy of CA models, whereas the combination of partitioned transition rules and asynchronous evolving rates results in improved cell-to-cell accuracy and shape dimension accuracy. Thus, implementing partitioned transition rules and asynchronous evolving rates yields better CA model performance in urban growth simulations due to its accordance with actual urban growth processes.     

The value of teaching about geomorphology in non-traditional settings

Academics usually teach about geomorphology in the classroom, where the audience is enthusiastic, but generally small. Less traditional settings offer opportunities to reach a wider audience, one that is equally enthusiastic, given its love of geomorphic features in the National Parks, but one which has little knowledge of the science behind what they are seeing. I have “taught” geomorphology in four non-traditional settings: at a summer camp, a state wildlife refuge, on community field trips, and at meetings for clubs and government boards. This paper discusses my experiences and offers suggestions to others who may wish to follow this less-traveled educational path.As Head of Nature Programs at Camp Pemigewassett in New Hampshire, I have worked, over the last 33 years, with thousands of campers ranging from 8 to 15 years old. Our setting, in a glaciated valley on a small lake, exhibits a wide range of geomorphic features and offers many opportunities for direct learning through field investigations. I have found that even 8-year olds can do real science, if we avoid the jargon. Once “taught” they carry their knowledge about landforms and processes with them and eagerly share it with their friends and family on outings and trips, thus reaching an even wider public.Parks, wildlife refuges, nature preserves, and other similar areas generally have nature trails, often with educational information about the environment. Generally, interpretive signs are prepared by biologists and the content ignores the site's physical features, as well as the connections between ecological communities and the underlying geology and geomorphology. My students and I have addressed this situation at two places in Connecticut, one a state wildlife management area, also used for training teachers to teach Environmental Education, and the other, a town recreation area. We catalogued the geomorphic features, looked at relationships of the community level ecology to those features, and prepared interpretive signs that added this perspective to the trails. The public response has been extremely favorable.Geomorphology can also be taught by leading field trips for community organizations. I have done this twice, once for the Manchester (NH) Historical Society and once for a small watershed association. The attendance and interest surprised me. We finally had to limit the Manchester trip to one full busload (45) and the watershed trip, which was part of a “trails day,” drew over 90 people.Finally, I have found that organizations such as Sierra Club chapters and town conservation boards are frequently looking for speakers for their periodic meetings. Why not a geomorphologist? After all, much of what conservationists do is related to what geomorphologists do. I have given several of these presentations and the receptions have always been enthusiastic.While the work involved in preparing to teach in one of these non-traditional settings is frequently substantial, the rewards are equally large. It is a way to reach masses of people who know little about the science of geomorphology and to demonstrate its importance to them. Taking our message directly to the public in these settings is an effective way to put geomorphology in the public eye.     

基于神经网络的元胞自动机及模拟复杂土地利用系统

本文提出了基于神经网络的元胞自动机(CellularAutomata),并将其用来模拟复杂的土地利用系统及其演变。国际上已经有许多利用元胞自动机进行城市模拟的研究,但这些模型往往局限于模拟从非城市用地到城市用地的转变。模拟多种土地利用的动态系统比一般模拟城市演化要复杂得多,需要使用许多空间变量和参数,而确定模型的参数值和模型结构有很大困难。本文通过神经网络、元胞自动机和GIS相结合来进行土地利用的动态模拟,并利用多时相的遥感分类图像来训练神经网络,能十分方便地确定模型参数和模型结构,消除常规模拟方法所带来的弊端。     

Modeling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China

Spatially explicit urban expansion models that can trace urban development in the past and predict the expansion scenarios in the future are indispensable for examining urban planning policies. This paper demonstrates a new urban expansion scenario (UES) model by coupling one “bottom-up” cellular automata (CA)-based model and one “top-down” system dynamics (SD)-based model. By implementing the UES model in Beijing, the urban evolution from 1991 to 2004 was simulated and the UESs from 2004 to 2020 were predicted. The results suggest that a dilemma of urban expansion versus limited water resource and environment deterioration exists. Dealing with such a dilemma remains a challenge for the local government.     

Prediction of Aquifer Vulnerability to Pesticides Using Fuzzy Rule-Based Models at the Regional Scale

Contamination of ground water has been a major environmental concern in recent years. The potential for ground-water contamination by pesticides depends on porous media, solute, and hydrologic parameters. Although sophisticated deterministic computer models are available for assessing aquifer-contamination potential on a site-by-site basis, most deterministic models are too complex for vulnerability assessment on a regional scale because they require input data that are spatially and temporally variable, and which may not be available at this scale. Therefore, development of an affordable model that is robust under conditions of uncertainty at the watershed scale with minimum input of field data becomes a useful ground-water management tool. The purpose of this study was to examine the usefulness of fuzzy rule-based techniques in predicting aquifer vulnerability to pesticides at the regional scale. The objectives were to (1) develop fuzzy rule-based models using the same input parameters contained in an index-based model (i.e., the modified DRASTIC model), (2) determine the sensitivity of fuzzy rule model predictions, (3) compare the outputs of the fuzzy rule-based models with those of the modified DRASTIC model and with the results of aquifer water-quality analyses, and (4) examine the spatial variability of field parameters around contaminated wells of the Alluvial aquifer in Woodruff County Arkansas. The fuzzy rule-based model for objective (1) was developed using similar parameter weights and ratings as the modified DRASTIC model. For objective (2), fuzzy rule-based models were created using fewer parameters than the modified DRASTIC model. Sensitivity of the fuzzy rule-based models was determined using different combinations of weights of the four input parameters in DRASTIC. It was found that variations in the weights of the input parameters and number of fuzzy sets influenced the location of the aquifer-vulnerability categories as well as the area within each fuzzy category. The fuzzy rule models tended to predict somewhat higher vulnerabilities of the Alluvial aquifer than the modified DRASTIC model. The fuzzy rule base that had the soil-leaching index (S) as the highest weight was chosen as the best fuzzy rule model in predicting potential contamination by pesticides of the aquifer. In general, the fuzzy rule models tended to overestimate the vulnerability of the aquifer in the study area.     

Robust Rule-Based Aggradational Lobe Reservoir Models

Stratigraphic rule-based reservoir models approximate sedimentary dynamics to generate numerical models of reservoir architecture with realistic spatial distributions of petrophysical properties for reservoir forecasting and to support development decision making. A few intuitive rules for the sequential placement of surfaces bounding reservoir units render realistic reservoir heterogeneity, continuity, and spatial organization of petrophysical property distributions that are difficult to obtain using conventional geostatistical pixel- and object-based subsurface methods. While these methods are emerging in applications specifically for deepwater and fluvial clastic reservoirs, there are some remaining obstacles to broad application, such as selection of rule parameters and addressing emergent non-stationarities over the sequence of the placed surfaces. Firstly, there is a need to tune rule parameters to ensure the models honor natural heterogeneities. We demonstrate this for the compensational rule. Secondly, invariants over model sequence (from the base to the top of the model) may occur with respect to shape, volume, undulation, and gradients of surfaces. For example, for a stack of compensational lobes, the volume of individual lobes may decrease due to the onlapping of previous bathymetry and also increasing undulation over model sequence may occur. In addition, for stacking of compensational lobes, the interfacial width and average gradient of the composite surface may initially increase, but then saturate and stabilize. Such non-stationarities represent numerical artifacts that may bias the results from these rule-based models. It is essential that these features are quantified and mitigated as a prerequisite for robust application of rule-based aggradational lobe methods for reservoir modeling.

     

Simple spatially-distributed models for predicting flood inundation: A review

In this paper we review recent progress in the use of reduced complexity models for predicting floodplain inundation. We review the theoretical basis for modelling floodplain flow with simplified hydraulic treatments based on a dimensional analysis of the one-dimensional shallow water equations. We then review how such schemes can be applied in practice and consider issues of space discretization, time discretization and model parameterisation, before going on to consider model assessment procedures. We show that a key advantage of reduced complexity codes is that they force modellers to think about the minimum process representation necessary to predict particular quantities and act as a check on any tendency to reductionism. At the same time, however, the use (compared to standard hydraulic codes) of strong simplifying assumptions requires us to also address the question “how simple can a model be and still be physically realistic?” We show that by making explicit this debate about acceptable levels of abstraction, reduced complexity codes allow progress to be made in addressing a number of long-standing debates in hydraulics.     

Geomorphology as science: the role of theory

Because geomorphology is a science, it is permeated by theory. Overt recognition of this actuality is frequently resisted by geomorphologists. Earth history does not represent an alternative to earth science, it is an essential component of earth science. In its broadest sense science seeks to discover new knowledge through a two-stage activity involving the creation and justification of ideas (theory). Deduction is generally regarded as the only logically-consistent method of justifying ideas. The creation of ideas is a much more controversial topic. Some methodologists deem it beyond logic; certainly deductive arguments, which are nothing more than formal, logical expressions of theory, play no role in the conception of new ideas. Many earth scientists generate possible explanations of observed phenomena based on abductive reasoning. Others advocate reliance on purported forms of “pure” induction, such as serendipity and intuition, in which observations assume primacy over theory. Besides lacking consistency and educability, the latter posture is flawed because it mistakenly implies that becoming well-versed in theory is irrelevant to or impedes scientific discovery. Irrational or subjective factors play a role in the creation of ideas, but it is erroneous to claim that these factors are divorced from theory. Science is first and foremost a cognitive activity; thus, the primacy of observations in science is a myth. All observations are theory-laden in the sense that the act of observation inherently involves interpretation and classification, both of which can only occur within the context of theoretical preconceptions. Even discoveries based on unexpected observations require the fortunate investigator to recognize the theoretical importance of what is seen or measured.The most useful view of geomorphology as a science is one in which theory is seen as central, but fragile, and in which theory and observation are viewed symbiotically with theory providing the generative force and observation providing a vital policing role. Much of the current debate in geomorphology centers around differences in characteristics of theory, type of scientific arguments, and metaphysical perspectives among investigators working at different temporal scales. Full recognition and understanding of these differences are essential for developing a unified approach to the science of geomorphology.     

粤港澳区域联动发展的关键科学问题与重点议题

在新时期新背景下,实现粤港澳区域联动发展具有紧迫性、必要性和重大现实意义。本文认为研究粤港澳区域联动发展需要以区域一体化理论体系、“全球—地方”尺度理论、区域空间相互作用理论体系为主要的理论基础。其关键科学问题是研究“一国两制”下粤港澳尺度的区域联动理论,探索粤港澳区域联动的机制、关键因素、模式与路径;提出了粤港澳区域联动发展关注的4个重点议题：①粤港澳区域一体化/协同理论的研究与探索;②粤港澳地位与作用研究;③粤港澳联动的多尺度、多主体影响机制与模式研究;④粤港澳联动发展的实施路径研究。     

Development of Voronoi-based cellular automata -an integrated dynamic model for Geographical Information Systems

This paper presents a development of the extended Cellular Automata (CA), a Voronoi-based CA, to model dynamic interactions among spatial objects. Cellular automata are efficient models for representing dynamic spatial interactions. A complex global spatial pattern is generated by a set of simple local transition rules. However, its original definition for a two-dimensional array limits its application to raster spatial data only. This paper presents a newly developed Voronoi-based CA in which the CA is extended by using the Voronoi spatial model as its spatial framework. The Voronoi spatial model offers a ready solution to handling neighbourhood relations among spatial objects dynamically. By implementing this model, we have demonstrated that the Voronoi-based CA can model local interactions among spatial objects to generate complex global patterns. The Voronoi-based CA can further model interactions among point, line and polygon objects with irregular shapes and sizes in a dynamic system. Each of these objects possesses its own set of attributes, transition rules and neighbourhood relationships. The Voronoi-based CA models spatial interactions among real entities, such as shops, residential areas, industries and cities. Compared to the original CA, the Voronoi-based CA is a more natural and efficient representation of human knowledge over space.     

Lithologic, structural, and geomorphic controls on ribbon forest patterns in a glaciated mountain environment

So-called “ribbon forests” have been attributed to snowdrift patterns and fire history without reference to geomorphology [Vegetatio 19 (1969) 192.]. This paper illustrates how site conditions of geomorphology and geology explain the origin of ribbon forests. In Glacier National Park, MT (USA), regional tectonic uplift associated with the Laramide Orogeny produced structural features that amplify lithologic differences. Pleistocene glaciation scoured deeply along the strike of bedding planes, highlighting this pattern and in some cases producing fine-scale parallel finger lakes between forested ribbon strips.Twelve ribbon forest sites on both sides of the Continental Divide were closely studied on stereoscopic aerial photographs, and several of these sites were examined in the field or from helicopter overflights. In all cases, geologic and geomorphic conditions explain the location and distribution of the ribbon forests. Change-detection of the distribution of trees versus nontree-covered surfaces in an area of ribbon forest on Flattop Mountain, a complex uplifted synclinal structure, was undertaken using panchromatic, low-altitude aerial photographs from 1966 to 1991. Areas changed from forest to meadow and from meadow to forest in roughly equal amounts in a generally random spatial pattern. No evidence was seen to suggest that the creation of one ribbon eventually created another downwind, as suggested by Billings. Aerial photograph interpretation, field examination and soils analyses of forest ribbons and adjacent unforested meadows clearly illustrated that trees occupy higher, parallel to subparallel, well-drained sites where the spatial pattern is in turn a distinct reflection of the spatial pattern of structure and stratigraphy. Meadows occupy topographically lower positions between ridges where erosion along bedding plane strike was concentrated. Topography sets conditions that allow tree growth in certain locations while precluding it in immediately adjacent areas. Ribbon forests there are thus a spatial manifestation of the interaction between structure, lithology, and topography.     

Fractal behavior in space and time in a simplified model of fluvial landform evolution

Two general approaches have been applied to understanding the fractal structure of fluvial topography: (1) deterministic, process-based models, and (2) stochastic partial differential equations (PDE). Deterministic models reproduce the fractal behavior of fluvial topography but have two limitations: they often underestimate the amount of lateral valley and ridge migration that occurs in nature, and the complexity has made it difficult to identify the precise origin of fractal behavior in fluvial landscapes. The simplicity of stochastic PDE models has made them useful for investigating fractal behavior, but they incorrectly suggest that fractal behavior is only possible with stochastic forcing. In this paper I investigate whether simplified, deterministic PDE models of landform evolution also exhibit fractal behavior and other features of complexity (i.e. deterministic chaos). These models are based on the KPZ equation, well known in the physics literature. This equation combines diffusion (i.e. hillslope processes) and nonlinear advection (i.e. bedrock or alluvial channel incision). Two models are considered: (1) a deterministic model with uniform erodibility and random initial topography, and (2) a deterministic model with random erodibility and uniform initial topography. Results illustrate that both of these deterministic models exhibit fractal behavior and deterministic chaos. In this context, chaotic behavior means that valley and ridge migration and nonlinear amplification of small perturbations in these models prevent an ideal steady state landscape from ever developing in the large-system limit. These results suggest that fractal structure and deterministic chaos are intrinsic features of the evolution of fluvial landforms, and that these features result from an inverse cascade of energy from small to large wavelengths in drainage basins. This inverse cascade differs from the direct cascade of three-dimensional turbulence in which energy flows from large to small wavelengths.     

从高维特征空间中获取元胞自动机的非线性转换规则

元胞自动机 (CA) 具有强大的空间模拟能力,能够模拟和预测复杂的地理现象演变过程。CA 的核心是如何定义转换规则,但目前CA转换规则获取往往是基于线性方法来进行,例如采用多准则判断 (MCE) 技术。这些方法较难反映地理现象所涉及的非线性等复杂特征。为此提出了利用新近发展的核学习机来获取地理元胞自动机非线性转换规则的新方法。该方法是通过核函数产生隐含的高维特征空间,把复杂的非线性问题转化成简单的线性问题,为解决复杂非线性问题提供了一种非常有效的途径。利用所提出的方法自动获取地理元胞自动机的转换规则,不仅大大减少了建模所需的时间,也较好地反映地理现象复杂的特性,从而改善了CA模拟的效果。     

A heuristic model for potential geomorphic influences on trophic interactions in streams

Whereas certain linkages between stream channel morphology and stream ecology are fairly well-understood, how geomorphology influences trophic interactions remains largely unknown. As a first step, a simple, heuristic model is developed that couples reach-scale geomorphic morphology with trophic dynamics between vegetation, detritus, herbivores, and predators. Predation is assumed to increase with depth beyond a threshold depth, and herbivory is assumed to decrease with velocity beyond a threshold velocity. Results show that the modeled food chain is sensitive to channel geometry, particularly around the threshold conditions for predators and herbivores. Importantly, geomorphic influences are not isolated to a particular trophic level, but rather are transferred through the food chain via top-down and bottom-up effects. The modeled system is particularly sensitive to changes in the end-members of the food chain: vegetation and predators. Results illustrate that geomorphic disturbances, known to affect a single trophic level (e.g., fish), likely impact multiple trophic levels in the stream ecosystem via trophic interactions. Such impacts at the multiple trophic level are poorly understood. While limited by the lack of empirical long-term data for testing and calibration, this simple model provides a structure for generating hypotheses, collecting targeted data, and assessing the potential impacts of stream disturbance or restoration on entire stream ecosystems. Further, the model illustrates the potential for future coupled stream models to explore spatial and temporal linkages.     

Crossing the divide: Representation of channels and processes in reduced-complexity river models at reach and landscape scales

Reduced-complexity models have considerable potential as tools for elucidating river behaviour over periods of 10⁰–10⁴ years and, consequently, for addressing fundamental questions concerning the scale-dependent nature of explanation in geomorphology. This paper proposes a simple subdivision of reduced-complexity models of river behaviour into two categories that mirror methodological developments in fluvial geomorphology over the past 50 years. First, high-resolution cellular approaches that are implemented within a framework that resolves process-form feedbacks at small time and space scales. Second, models that incorporate section-averaged representations of channel geometry and processes, and that are typically underpinned by regime theory and equilibrium concepts. Examples of both model types are presented here, in the form of a cellular representation of stream braiding and a combined lattice-network model of alluvial fan evolution. Simulations conducted using these models demonstrate how small-scale process-form interactions determine the emergence of larger-scale channel and fan morphology and, in so doing, regulate system response to external forcing. In this sense, both models demonstrate that internal feedbacks play a critical role in controlling river responses to environmental change over historic and Holocene timescales. However, both classes of model are characterised by uncertainty in their parameterisation of geomorphic processes, such that internal feedbacks and thresholds for channel response to external forcing may vary substantially between competing models. Methods of refining both approaches are considered, and hybrid models based on lattice-network structures and mechanistic representations of channel process-form interactions are identified as a means of addressing the shortcomings of existing strategies.     

Using neural networks and cellular automata for modelling intra‐urban land‐use dynamics

Empirical models designed to simulate and predict urban land‐use change in real situations are generally based on the utilization of statistical techniques to compute the land‐use change probabilities. In contrast to these methods, artificial neural networks arise as an alternative to assess such probabilities by means of non‐parametric approaches. This work introduces a simulation experiment on intra‐urban land‐use change in which a supervised back‐propagation neural network has been employed in the parameterization of several biophysical and infrastructure variables considered in the simulation model. The spatial land‐use transition probabilities estimated thereof feed a cellular automaton (CA) simulation model, based on stochastic transition rules. The model has been tested in a medium‐sized town in the Midwest of São Paulo State, Piracicaba. A series of simulation outputs for the case study town in the period 1985–1999 were generated, and statistical validation tests were then conducted for the best results, based on fuzzy similarity measures.     

分析学习智能元胞自动机及优化的城市模拟

元胞自动机被广泛应用于城市及其他地理现象的模拟,模拟过程中的最大问题是如何确定模型的结构和参数。该文提出一种基于分析学习的智能优化元胞自动机,该模型在逻辑回归模型的基础上,基于分析学习的智能方法,寻找元胞自动机模型的最佳参数。该方法允许用户控制空间变量影响权重,进而模拟出不同的城市发展模式,可为城市规划提供重要参考。     

The human role in changing fluvial systems: Retrospect, inventory and prospect

Historical and modern scientific contexts are provided for the 2006 Binghamton Geomorphology Symposium on the Human Role in Changing Fluvial Systems. The 2006 symposium provides a synthesis of research concerned with human impacts on fluvial systems — including hydrologic and geomorphic changes to watersheds — while also commemorating the 50th anniversary of the 1955 Man's Role in Changing the Face of the Earth Symposium [Thomas, Jr., W. L. (Ed.), 1956a. Man's Role in Changing the Face of the Earth. Univ. Chicago Press, Chicago. 1193 pp]. This paper examines the 1955 symposium from the perspective of human impacts on rivers, reviews current inquiry on anthropogenic interactions in fluvial systems, and anticipates future directions in this field.Although the 1955 symposium did not have an explicit geomorphic focus, it set the stage for many subsequent anthropogeomorphic studies. The 1955 conference provided guidance to geomorphologists by recommending and practicing interdisciplinary scholarship, through the use of diverse methodologies applied at extensive temporal and geographical scales, and through its insistence on an integrated understanding of human interactions with nature. Since 1956, research on human impacts to fluvial systems has been influenced by fundamental changes in why the research is done, what is studied, how river studies are conducted, and who does the research. Rationales for river research are now driven to a greater degree by institutional needs, environmental regulations, and aquatic restoration. New techniques include a host of dating, spatial imaging, and ground measurement methods that can be coupled with analytical functions and digital models. These new methods have led to a greater understanding of channel change, variations across multiple temporal and spatial scales, and integrated watershed perspectives; all changes that are reflected by the papers in this volume. These new methods also bring a set of technical demands for the training of geomorphologists. The 2006 Binghamton Geomorphology Symposium complements the 1956 symposium by providing a more specific and updated view of river systems coupled with human interactions. The symposium focuses on linkages between human land use, structures, and channel modification with geomorphology, hydrology, and ecology. The emergence of sustainability as a central policy guideline in environmental management should generate greater interest in geomorphic perspectives, especially as they pertain to human activities. The lack of theories of anthropogeomorphic change, however, presents a challenge for the next generation of geomorphologists in this rapidly growing subfield.