Assessing Surface Water Quality and Its Relation with Urban Land Cover Changes in the Lake Calumet Area, Greater Chicago

Urban land use and land cover change significantly affect spatial and temporal patterns of runoff, which in turn impacts surface water quality. With the exponential growth in urban areas over the past three decades, changes in land use and land cover to cater for the growth of cities has been a conspicuous spectacle in urban spaces. The main goal of this study was to assess the impacts of land cover change on runoff and surface water quality using a partial area hydrology framework. The study employed ArcHydro GIS extension and a modified version of Long-Term Hydrologic and Nonpoint Source Pollution model (L-THIA-NPS) in estimating runoff and nonpoint source pollutant concentration around Lake Calumet between 1992 and 2001. Data employed include National Land Cover Data set, rainfall data, digital elevation model (DEM), Soil Survey Geographic (SSURGO) data, and The United States Environmental Protection Agency’s STORET (storage and retrieval) water quality data. The model was able to predict surface water quality reasonably well over the study period. Sensitivity analysis facilitated a manual calibration of the model. Model validation was executed by comparing simulated results following calibration and observed water quality data for the study area. The study demonstrates that the level of concentration of nonpoint source pollutants in surface water within an urban watershed heavily depends on the spatiotemporal variations in areas that contribute towards runoff compared to the spatial extent of change in major land use/land cover.     

Remotely Sensed Data for Ecosystem Analyses: Combining Hierarchy Theory and Scene Models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost–benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.     

Assessment of National Parks affected by naturbanization processes in Southern Europe

This paper assesses land-use changes related to naturbanization processes on three biosphere reserves in Southern Europe. A comparative analysis has been done on the National Parks in Peneda-Gerês in North Portugal, Cévennes in South France and Sierra Nevada in South Spain, using Corine Land Cover data from 1990 until 2006. Results indicate that the process of land-use intensification is taking place in the frame of naturbanization dynamics that could jeopardize the role of Protected Areas. Focusing on the trends faced by National Parks and their surrounding territories, the analysis demonstrates, both in quantitative and spatial terms, the intensification processes of land-use changes and how it is important to know them for coping with increasing threats. The article concludes that in the current context of increasing stresses, a broader focus on nature protection, encompassing the wider countryside, is needed if the initiatives for biodiversity protection are to be effective.     

Land Use Planning: A Decision Support System

The NERC/ESRC Land Use Programme has led to the development of a decision support system (DSS) for land use planning. A conceptual framework for DSS development has been modified to encompass the unique needs of a system which aims to deal with a wide range of land use issues. Large volumes of diverse, land use related data have been brought together into a central database using geographical information system and relational database management system technology. The data, as well as economic, ecological and hydrological modelling capabilities, are made available to the decision maker via a user-friendly graphical interface specifically designed for this project.     

Assessing Land-Use Impacts on Natural Resources

/ Much information is available on changes that occur in natural resources from both spatially-explicit data on environmental conditions and models of the interactions of these conditions and resources with human activities. The strategy for assessing land-use impacts on natural resources developed in this paper provides a framework for using relevant data and models to address questions of how management practices can promote both use and protection of resources. This assessment strategy integrates spatially explicit environmental data using geographic information systems (GIS) with computer models that simulate changes in land cover in response to land-use impacts. The computer models also simulate susceptibility of species to changes in habitat suitability and landscape patterns. The approach is applied to management of limestone barrens on the Oak Ridge Reservation in East Tennessee. Potential limestone barrens habitats are identified by overlaying appropriate soils, geology, slope, and land-use/land-cover conditions. Their validity is tested against known sites containing rare species that occur in these habitats. The location of habitats at risk in the aftermath of human activities is determined by using an available area model that identifies the size and proximity of sites that particular types of species can no longer use as habitat. The resulting risk map can be used in land management planning. The approach uses readily available in situ and remotely sensed data and is applicable to a wide range of locations and land-use scenarios. This approach can be refined based on needs identified by land managers and on the sensitivity of the results to the resolution of available resource information.KEY WORDS: Land management; Assessment; Habitat characterization; Limestone barrens; Ecological modeling; Geographic information systems     

Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore,Maryland1

Smith, Monica Lipscomb, Weiqi Zhou, Mary Cadenasso, Morgan Grove, and Lawrence E. Band, 2010. Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore, Maryland. Journal of the American Water Resources Association (JAWRA) 46(2):429-442. DOI: 10.1111/j.1752-1688.2009.00412.x Abstract: We compared the National Land Cover Database (NLCD) 2001 land cover, impervious, and canopy data products to land cover data derived from 0.6-m resolution three-band digital imagery and ancillary data. We conducted this comparison at the 1 km², 9 km², and gauged watershed scales within the Baltimore Ecosystem Study to determine the usefulness and limitations of the NLCD in heterogeneous urban to exurban environments for the determination of land-cover information for hydrological applications. Although the NLCD canopy and impervious data are significantly correlated with the high-resolution land-cover dataset, both layers exhibit bias at <10 and >70% cover. The ratio of total impervious area and connected impervious area differs along the range of percent imperviousness – at low percent imperviousness, the NLCD is a better predictor of pavement alone, whereas at higher percent imperviousness, buildings and pavement together more resemble NLCD impervious estimates. The land-cover composition and range for each NLCD urban land category (developed open space, low-intensity, medium-intensity, and high-intensity developed) is more variable in areas of low-intensity development. Fine-vegetation land-cover/lawn area is incorporated in a large number of land use categories with no ability to extract this land cover from the NLCD. These findings reveal that the NLCD may yield important biases in urban, suburban, and exurban hydrologic analyses where land cover is characterized by fine-scale spatial heterogeneity.     

A Knowledge-Based Systems Approach to Design of Spatial Decision Support Systems for Environmental Management

/ This paper describes a framework for designing spatial decision support systems for environmental management using a knowledge-based systems approach. An architecture for knowledge-based spatial decision supportsystems (KBSDSS) is presented that integrates knowledge-based systems with geographical information systems (GIS) and other problem-solving techniques. A method based on spatial influence diagrams is developed for representation of environmental problems. The spatial influence diagram provides an interface through which knowledge-based systems techniques can be applied to build capabilities for problem formulation, automated design, and execution of a solution process. In addition to the flexibility and developmental advantages of knowledge-based systems, the KBSDSS incorporates expert knowledge to provide assistance for structuring spatial influence diagrams and executing a solution process that automatically integrates the GIS, data base, knowledge base, and different types of models. The framework is illustrated with a system, known as the Islay Land Use Decision Support System (ILUDSS), designed to assist planners in strategic planning of land use for the development of the island of Islay, off the west coast of Scotland.KEY WORDS: Geographical information systems; Spatial decision support systems; Knowledge-based systems; Spatial influence diagrams; Environmental management     

Valuing New Jersey’s Ecosystem Services and Natural Capital: A Spatially Explicit Benefit Transfer Approach

We intend to estimate the value of ecosystem services in the U.S. State of New Jersey using spatially explicit benefit transfer. The aggregated net rent, a conservative underestimate for the total economic value of the state’s natural environment, ranged from 11.6 to11.6 to 19.6 billion/year, conditional on how inclusive we were in selecting the primary studies used to calculate the central tendency values to transfer. In addition to calculating the range, mean, and standard deviation for each of 12 ecosystem services for 11 Land Use/Land Cover (LULC) types, we also conduct a gap analysis of how well ecosystem service values are represented in the literature. We then map these values by assuming a mean value for each LULC and apply this to spatial data. As to sensitivity analysis, we calculate the net present value of New Jersey’s natural environment utilizing three different methods of discounting. These research results provide a useful, albeit imperfect, basis for assessing the value of ecosystem services and natural capital, and their comparison with the value of conventional human and built capitals.     

Community Capacity for Implementing Clean Development Mechanism Projects Within Community Forests in Cameroon

There is a growing assumption that payments for environmental services including carbon sequestration and greenhouse gas emission reduction provide an opportunity for poverty reduction and the enhancement of sustainable development within integrated natural resource management approaches. Yet in experiential terms, community-based natural resource management implementation falls short of expectations in many cases. In this paper, we investigate the asymmetry between community capacity and the Land Use Land Use Change Forestry (LULUCF) provisions of the Clean Development Mechanism within community forests in Cameroon. We use relevant aspects of the Clean Development Mechanism criteria and notions of “community capacity” to elucidate determinants of community capacity needed for CDM implementation within community forests. The main requirements are for community capacity to handle issues of additionality, acceptability, externalities, certification, and community organisation. These community capacity requirements are further used to interpret empirically derived insights on two community forestry cases in Cameroon. While local variations were observed for capacity requirements in each case, community capacity was generally found to be insufficient for meaningful uptake and implementation of Clean Development Mechanism projects. Implications for understanding factors that could inhibit or enhance community capacity for project development are discussed. We also include recommendations for the wider Clean Development Mechanism/Kyoto capacity building framework.     

Spatial planning and changing landscapes: a failure of policy in peri-urban Victoria,Australia

Building on the scientific literature, this article first summarises the socio-environmental impacts of land-use change expected to occur in high amenity Australian peri-urban areas, involving in particular, the effects of land development on agriculture, biodiversity, landscape character, bushfire risk and social factors. Second, the current spatial planning framework and its distribution in seven municipalities in Victoria, Australia, is critically analysed, and records of approved planning permits are related to this framework to assess the challenges posed by peri-urban growth. We argue that the current planning framework supports a static approach which does not address foreseen challenges and lacks strategic power. Both the strategic framework and the development approval process lead to unanticipated, cumulative impacts and contestation. A more coordinated, less urban-centric approach to planning and the introduction of rural land-use plans would substantially address some of the issues encountered.     

The Impact of Land Use/Land Cover Changes on Land Degradation Dynamics: A Mediterranean Case Study

In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.     

The relevance of physical forces on land-use change and planning process

This study analysed the importance of physical forces on land-use change, on the planning framework in a Portuguese periurban area. A temporal matrix showing the trajectories of land transformation was obtained. A multivariate redundancy analysis explored the importance of physical parameters on temporal and spatial land-use change. A content analysis on urban or municipal master plans was made framing the importance of physical parameters on the planning process. The results highlighted a consistent trajectory of profound land-use changes with distinctive trajectories, with increasingly complex patterns with a limited dependence on physical variables. The trajectories were more related to the planning framework, where political actors and planning managers seemed to be most important. A theoretical model balancing three main components – physical forces, actors, and land transformation (DFA-C model) is proposed, reflecting the informal relationships between physical parameters and actors during the planning process.     

Relationships Between Major Ownerships, Forest Aboveground Biomass Distributions, and Landscape Dynamics in the New England Region of USA

This study utilizes remote sensing derived forest aboveground biomass (AGB) estimates and ownership information obtained from the Protected Areas Database (PAD), combining landscape analyses and GIS techniques to demonstrate how different ownerships (public, regulated private, and other private) relate to the spatial distribution of AGB in New England states of the USA. “Regulated private” lands were dominated by lands in Maine covered by a Land Use Regulatory Commission. The AGB means between all pairs of the identified ownership categories were significantly different (P < 0.05). Mean AGB observed in public lands (156 Mg/ha) was 43% higher than that in regulated private lands (109 Mg/ha), or 30% higher than that of private lands as a whole. Seventy-seven percent of the regional forests (or about 9,300 km²) with AGB >200 Mg/ha were located outside the area designated in the PAD and concentrated in western MA, southern VT, southwestern NH, and northwestern CT. While relatively unfragmented and high-AGB forests (>200 Mg/ha) accounted for about 8% of total forested land, they were unevenly proportioned among the three major ownership groups across the region: 19.6% of the public land, 0.8% of the regulated private land, and 11.0% of the other private land. Mean disturbance rates (in absolute value) between 1992 and 2001 were 16, 66, and 19 percent, respectively, on public, regulated private, and other private land. This indicates that management practices from different ownerships have a strong impact on dynamic changes of landscape structures and AGB distributions. Our results may provide insight information for policy makers on issues regarding forest carbon management, conservation biology, and biodiversity studies at regional level.     

Towards Sustainable Integrated Watershed Ecosystem Management: A Case Study in Dingxi on the Loess Plateau, China

The Chinese government initiated a massive conservation program called “Grain-for-Green” in 1999 to reduce soil erosion and improve ecosystem function. Implementing practical sustainable development in the loess plateau still remains problematic, particularly in its eco-fragile areas. Here we discussed an approach for sustainable development at the watershed scale by integrating land use suitability, ecosystem services and public participation in the loess hilly area. We linked land use scenario analysis and economic modeling to compare the outcomes of three scenarios, CLU (Current Land Use), GOLU (Grain-production Oriented Land Use) and PSLU (Potential Sustainable Land Use). The results indicated that compared to PSLU, GOLU may provide a higher economic productivity in the short-term, but not in the long-term. CLU ranked lowest in terms of economic benefits and did not meet the daily needs of the local farmers. To reconcile the land use adjustments with farmers’ basic needs, a labor-saving land use strategy is necessary. Since the PSLU scenario assumes that slope cropland should be converted to pastures or orchards, more time may be available for off-farm work and for more public participation in integrated ecosystem management. Financial support to the local farmers for environmental conservation should be modulated in function of their positive contribution to ecosystem management.     

Estimating Root Zone Soil Moisture at Continental Scale Using Neural Networks

This study investigates the feasibility of artificial neural networks (ANNs) to retrieve root zone soil moisture (RZSM) at the depths of 20 cm (SM20) and 50 cm (SM50) at a continental scale, using surface information. To train the ANNs to capture interactions between land surface and various climatic patterns, data of 557 stations over the continental United States were collected. A sensitivity analysis revealed that the ANNs were able to identify input variables that directly affect the water and energy balance in root zone. The data important for RZSM retrieval in a large area included soil texture, surface soil moisture, and the cumulative values of air temperature, surface soil temperature, rainfall, and snowfall. The results showed that the ANNs had high skill in retrieving SM20 with a correlation coefficient above 0.7 in most cases, but were less effective at estimating SM50. The comparison of the ANNs showed that using soil texture data improved the model performance, especially for the estimation of SM50. It was demonstrated that the ANNs had high flexibility for applications in different climatic regions. The method was used to generate RZSM in North America using Soil Moisture and Ocean Salinity (SMOS) soil moisture data, and achieved a spatial soil moisture pattern comparable to that of Global Land Data Assimilation System Noah model with comparable performance to the SMOS surface soil moisture retrievals. The models can be efficient alternatives to assimilate remote sensing soil moisture data for shallow RZSM retrieval.     

Stuck between the historic and modern China: A case study of children’s space in a hutong community

Physically and psychologically, children demand special-purpose space for activities. With the fast urbanization and population growth in modern China, the conflict between the needs for economic development and human-friendly environment becomes increasingly prominent. The study adopts an in-depth ethnographic research method and applies the research framework of Sudeshna Chatterjee (2005) to investigate children’s environmental friendliness of a hutong community in Beijing. The study investigated spatial preferences of those children and the characteristics and affordance of their space. This study suggests that different emotional dimensions demand different spatial attributes, which are lacking in the hutong community. The results show that in China’s historical residential areas, children’s environmental and spatial needs remain unfulfilled. The researchers suggest that improving specific environmental affordance could help enhance the overall child-friendliness.     

Estimation of Evapotranspiration Across the Conterminous United States Using a Regression With Climate and Land‐Cover Data1

Sanford, Ward E. and David L. Selnick, 2012. Estimation of Evapotranspiration Across the Conterminous United States Using a Regression with Climate and Land‐Cover Data. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12010 Abstract: Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water‐balance method was combined with a climate and land‐cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971‐2000 across the U.S. to obtain long‐term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land‐cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land‐cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land‐cover data can also improve those predictions. Using the climate and land‐cover data at an 800‐m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land‐cover data are plentiful.     

A Conceptual Framework for Selecting and Analyzing Stressor Data to Study Species Richness at Large Spatial Scales

/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy     

Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location

Use of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act.     

Coupling a settlement growth model with an agro-economic land allocation model for securing ecosystem services provision

Mountain landscapes are undergoing rapid land-use changes. Settlement expansion, the intensification of agricultural land-use practices, and farmland abandonment result in a decline of natural and semi-natural habitats and the related ecosystem services (ES). In this context, spatial planning has emerged as a key instrument for the management of ES provision. To better understand trade-offs and interactions between settlement growth and ES provision in a spatially explicit manner, we present a new modeling framework coupling an agent-based, agro-economic optimization model and a cellular-automata-based settlement growth model. The framework is applied in an inner alpine valley in the Valais, Switzerland, which experienced rapid settlement growth in recent years. Results demonstrate how the model framework allows support of local planning processes. Particularly cooperation among municipalities and an explicit consideration of ES can inform spatially explicit ES trade-off decisions under increasing demand for land. We conclude that better informed spatial planning processes support ES provision.