Statistical and Spatial Analysis of Land Cover Impact on Selected Metro Vancouver, British Columbia Watersheds

The Greater Vancouver area has undergone significant land use and land cover (LULC) change over the past several decades, often adversely affecting stream health and water quality, particularly in those areas that have undergone the most urbanization. In this study 30 years of historical LULC and water quality data were examined using GIS and statistical analysis to better understand these impacts and to help build a broader understanding of cause and effect relationships of changing LULC, especially since urbanization is increasingly occurring within sensitive watersheds at greater distances from the City of Vancouver. Urban, agriculture, and disturbed LULC data from 1976, 1986, and 2000 were examined within a number of watersheds and related to historical water quality data sampled from streams during similar time frames. Additional higher resolution 2006 LULC data from a smaller number of watersheds were then examined and compared to stream health data to investigate the sensitivity of LULC data resolution on monitoring watershed impact. While LULC impact can be clearly seen at both high and lower resolutions, issues of ambiguous land cover and land use designations can potentially affect the magnitude of the relationship.     

Land Use Change and Land Degradation in Southeastern Mediterranean Spain

The magnitude of the environmental and social consequences of soil erosion and land degradation in semiarid areas of the Mediterranean region has long been recognized and studied. This paper investigates the interrelationship between land use/cover (LULC) changes and land degradation using remotely sensed and ancillary data for southeastern Spain. The area of study, the Xaló River catchment situated in the north of the Alicante Province, has been subjected to a number of LULC changes during the second half of the 20th century such as agricultural abandonment, forest fires, and tourist development. Aerial photographs dating back to 1956 were used for the delineation of historic LULC types; Landsat ETM+ data were used for the analysis and mapping of current conditions. Two important indicators of land degradation, namely, susceptibility to surface runoff and soil erosion, were estimated for the two dates using easily parametrizable models. The comparison of 1956 to 2000 conditions shows an overall “recuperating” trend over the catchment and increased susceptibility to soil erosion only in 3% of the catchment area. The results also identify potential degradation hot-spots where mitigation measures should be taken to prevent further degradation. The readily implemented methodology, based on modest data requirements demonstrated by this study, is a useful tool for catchment to regional scale land use change and land degradation studies and strategic planning for environmental management.     

Estimation of biogenic emissions with satellite-derived land use and land cover data for air quality modeling of Houston-Galveston ozone nonattainment area

The Houston-Galveston Area (HGA) is one of the most severe ozone non-attainment regions in the US. To study the effectiveness of controlling anthropogenic emissions to mitigate regional ozone nonattainment problems, it is necessary to utilize adequate datasets describing the environmental conditions that influence the photochemical reactivity of the ambient atmosphere. Compared to the anthropogenic emissions from point and mobile sources, there are large uncertainties in the locations and amounts of biogenic emissions. For regional air quality modeling applications, biogenic emissions are not directly measured but are usually estimated with meteorological data such as photo-synthetically active solar radiation, surface temperature, land type, and vegetation database. In this paper, we characterize these meteorological input parameters and two different land use land cover datasets available for HGA: the conventional biogenic vegetation/land use data and satellite-derived high-resolution land cover data. We describe the procedures used for the estimation of biogenic emissions with the satellite derived land cover data and leaf mass density information. Air quality model simulations were performed using both the original and the new biogenic emissions estimates. The results showed that there were considerable uncertainties in biogenic emissions inputs. Subsequently, ozone predictions were affected up to 10 ppb, but the magnitudes and locations of peak ozone varied each day depending on the upwind or downwind positions of the biogenic emission sources relative to the anthropogenic NOx and VOC sources. Although the assessment had limitations such as heterogeneity in the spatial resolutions, the study highlighted the significance of biogenic emissions uncertainty on air quality predictions. However, the study did not allow extrapolation of the directional changes in air quality corresponding to the changes in LULC because the two datasets were based on vastly different LULC category definitions and uncertainties in the vegetation distributions.     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

Implications of Land Use/Land Cover Change in the Buffer Zone of a National Park in the Tropical Andes

The impacts of land use and land cover (LULC) change in buffer zones surrounding protected ecological reserves have important implications for the management and conservation of these protected areas. This study examines the spatial and temporal patterns of LULC change along the boundary of Rio Abiseo National Park in the Northern Peruvian Andes. Landscape change within four ecological zones was evaluated based on trends expected to occur between 1987 and 2001. Landsat TM and ETM imagery were used to produce LULC classification maps for both years using a hybrid supervised/unsupervised approach. LULC changes were measured using landscape metrics and from-to change maps created by post-classification change detection. Contrary to expectations, tropical upper wet montane forest increased despite being threatened by human-induced fires and cattle grazing of the highland grasslands inside the park. Within the park’s buffer zone, tropical moist forest remnants were fragmented into more numerous and smaller patches between 1987 and 2001; this was in part due to conversion into agricultural land. The methods used in this study provide an effective way to monitor LULC change detection and support the management of protected areas and their surrounding environments.     

Spatial Relations Between Floodplain Environments and Land Use – Land Cover of a Large Lowland Tropical River Valley: Pánuco Basin, México

Large lowland river valleys include a variety of floodplain environments that represent opportunities and constraints for human activities. This study integrates extensive field observations and geomorphic data with analysis of satellite remote sensing data to examine spatial relations between land use/land cover (LULC) and floodplain environments in the lower Pánuco basin of eastern Mexico. The floodplain of the lower Pánuco basin was delineated by combining a digital elevation model with a satellite image of a large flood event. The LULC was classified by combining a hybrid classification strategy with image stratification, applied to 15-m-resolution ASTER data. A geomorphic classification of floodplain environments was performed using a dry-stage image (ASTER data) and a 1993 Landsat image acquired during a large flood event. Accuracy assessment was based on aerial photographs (1:38,000), global positioning satellite ground-truthing, and a Landsat 7ETM⁺ image from 2000, which resulted in an overall accuracy of 82.9% and a KHAT of 79.8% for the LULC classification. The geomorphic classification yielded 83.5% overall accuracy, whereas the KHAT was 81.5%. LULC analysis was performed for the entire floodplain and individually within four valley segments. The analysis indicates that the study area is primarily utilized for grazing and farming. Agriculture is primarily associated with coarse-grained (sandy/silty) natural levee and point bar units close to the river channel, whereas cattle grazing occurs in distal and lower-lying reaches dominated by cohesive fine-grained (clayey) deposits, such as backswamps. In the Pánuco valley, wetlands and lakes occur within backswamp environments, whereas in the Moctezuma segments, wetlands and lakes are associated with relict channels. This study reveals considerable variation in LULC related to spatial differences in floodplain environments and illustrates the importance of considering older anthropogenic influences on the landscape. The research design should be applicable for other large lowland coastal plain river valleys where agriculture is a major component of the floodplain landscape.     

Flood Risk Reduction from Agricultural Best Management Practices

Best management practices (BMPs) play an important role in improving impaired water quality from conventional row crop agriculture. In addition to reducing nutrient and sediment loads, BMPs such as fertilizer management, reduced tillage, and cover crops could alter the hydrology of agricultural systems and reduce surface water runoff. While attention is devoted to the water quality benefits of BMPs, the potential co‐benefits of flood loss reduction are often overlooked. This study quantifies the effects of selected commonly applied BMPs on expected flood loss to agricultural and urban areas in four Iowa watersheds. The analysis combines a watershed hydrologic model, hydraulic model outputs, and a loss estimation model to determine relationships between hydrologic changes from BMP implementations and annual economic flood loss. The results indicate a modest reduction in peak discharge and economic loss, although loss reduction is substantial when urban centers or other high‐value assets are located downstream in the watershed. Among the BMPs, wetlands, and cover crops reduce losses the most. The research demonstrates that watershed‐scale implementation of agricultural BMPs could provide benefits of flood loss reduction in addition to water quality improvements.     

A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.     

Estimating the effects of urban residential development on water quality using microdata

In this study, we examine the impact on water quality of urbanization using disaggregate data from Wake County, North Carolina. We use a unique panel data set tracing the conversion of individual residentially zoned land parcels to relate the density of residential development and the change in residential land use to three measures of water quality. Using a spatial econometrics model, we relate spatially and temporally referenced monitoring station readings to our measures of residential land use while controlling for other factors affecting water quality. We find that both the density of residential land use and the rate of land conversion have a negative impact on water quality. The impacts of these non-point sources are found to be larger in magnitude than those from urban point sources.     

SUBWATERSHED SPATIAL ANALYSIS TOOL: DISCRETIZATION OF A DISTRIBUTED HYDROLOGIC MODEL BY STATISTICAL CRITERIA1

ABSTRACT: Complex hydrologic models, designed for simulating larger watersheds, require a huge amount of input data. Most of these models use spatially distributed data as inputs. Spatial data can be aggregated or disaggregated for use as input to a model, which can impact model outputs. Although, it is efficient to minimize data redundancy by aggregating the spatial data, upscaling reduces the detail/resolution of input information and increases model uncertainty. On the other hand, a large number of model inputs with high degrees of disaggregation take more computer time and space to process. Hence, a balance between striving for a maximum level of aggregation and a minimum level of information loss has to be achieved. This study presents a definition of an appropriate level of discretization, derived by establishing a relationship between a model's efficiency and the number of subwater‐sheds modeled. An entropy based statistical approach/tool called Subwatershed Spatial Analysis Tool (SUSAT) was developed to find an objective choice of an appropriate level of discretization. The new approach/tool was applied to three watersheds, each representing different hydrologic conditions, using a hydrologic model. Coefficients of efficiency and entropy estimated at different levels of discretization were used to validate the success of the new approach.     

An Analysis of the Effects of Land Use and Land Cover on Flood Losses along the Gulf of Mexico Coast from 1999 to 2009

Major coastal flooding events over the last decade have led decision makers in the United States to favor structural engineering solutions as a means to protect vulnerable coastal communities from the adverse impacts of future storms. While a resistance‐based approach to flood mitigation involving large‐scale construction works may be a central component of a regional flood risk reduction strategy, it is equally important to consider the role of land use and land cover (LULC) patterns in protecting communities from floods. To date, little observational research has been conducted to quantify the effects of various LULC configurations on the amount of property damage occurring across coastal regions over time. In response, we statistically examine the impacts of LULC on observed flood damage across 2,692 watersheds bordering the Gulf of Mexico. Specifically, we analyze statistical linear regression models to isolate the influence of multiple LULC categories on over 372,000 insured flood losses claimed under the National Flood Insurance Program per year from 2001 to 2008. Results indicate that percent increase in palustrine wetlands is the equivalent to, on average, a $13,975 reduction in insured flood losses per year, per watershed. These and other results provide important insights to policy makers on how protecting specific types of LULC can help reduce adverse impacts to local communities.     

A Multi‐Scale Analysis of Single‐Family Residential Water Use in the Phoenix Metropolitan Area

Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management.     

Estuarine Shoreline Changes in Jamaica Bay, New York City: Implications for Management of an Urban National Park

The Jamaica Bay portion of Gateway National Recreation Area, located next to highly urbanized New York City, faces many challenges to preserve and protect its natural, cultural, and recreational resources. To aid in the management of the park resources, detailed estuarine shoreline analyses of Jamaica Bay were undertaken using imagery taken in 1951, 1974, and 2006. A 15-class land use/land cover (LULC) classification scheme was created after doing an initial examination of the types of LULC in the 2006 orthoimagery and then applied in the analyses of the previous years. By quantifying how and where the shoreline has changed over the past 60 years, park managers can better assess the impact of management practices by comparing LULC of the shoreline within the park boundary to the LULC of the shoreline outside the park boundary before and after the park was created in 1972. Despite the heavy development of New York City and the trend for shoreline modification, the overall shoreline of Jamaica Bay has maintained large percentages of undeveloped vegetation and sandy beaches. Much of the LULC change has occurred in the creeks as a result of dredging and shape modification for residential and commercial uses. Park management has been effective in limiting the alteration of undeveloped shoreline although there have been significant changes in the relative percentages of sand and vegetated beaches between 1974 and 2006.     

An Ecology of Prestige in New York City: Examining the Relationships Among Population Density,Socio-economic Status,Group Identity,and Residential Canopy Cover

Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City’s property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont’s Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas’ Potential Rating Index for Zipcode Markets (PRIZM?) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.     

Landscape Trends in Mid-Atlantic and Southeastern United States Ecoregions

Landscape pattern and composition metrics are potential indicators for broad-scale monitoring of change and for relating change to human and ecological processes. We used a probability sample of 20-km × 20-km sampling blocks to characterize landscape composition and pattern in five US ecoregions: the Middle Atlantic Coastal Plain, Southeastern Plains, Northern Piedmont, Piedmont, and Blue Ridge Mountains. Land use/land cover (LULC) data for five dates between 1972 and 2000 were obtained for each sample block. Analyses focused on quantifying trends in selected landscape pattern metrics by ecoregion and comparing trends in land cover proportions and pattern metrics among ecoregions. Repeated measures analysis of the landscape pattern documented a statistically significant trend in all five ecoregions towards a more fine-grained landscape from the early 1970s through 2000. The ecologically important forest cover class also became more fine-grained with time (i.e., more numerous and smaller forest patches). Trends in LULC, forest edge, and forest percent like adjacencies differed among ecoregions. These results suggest that ecoregions provide a geographically coherent way to regionalize the story of national land use and land cover change in the United States. This study provides new information on LULC change in the southeast United States. Previous studies of the region from the 1930s to the 1980s showed a decrease in landscape fragmentation and an increase in percent forest, while this study showed an increase in forest fragmentation and a loss of forest cover.     

Estimating the Extent of Impervious Surfaces and Turf Grass across Large Regions

The ability of researchers to accurately assess the extent of impervious and pervious developed surfaces, e.g., turf grass, using land‐cover data derived from Landsat satellite imagery in the Chesapeake Bay watershed is limited due to the resolution of the data and systematic discrepancies between developed land‐cover classes, surface mines, forests, and farmlands. Estimates of impervious surface and turf grass area in the Mid‐Atlantic, United States that were based on 2006 Landsat‐derived land‐cover data were substantially lower than estimates based on more authoritative and independent sources. New estimates of impervious surfaces and turf grass area derived using land‐cover data combined with ancillary information on roads, housing units, surface mines, and sampled estimates of road width and residential impervious area were up to 57 and 45% higher than estimates based strictly on land‐cover data. These new estimates closely approximate estimates derived from authoritative and independent sources in developed counties.     

区域环境污染造成的经济损失估算——以银川市为例

通过研究银川市的环境监测资料、国民经济统计资料等,借鉴与银川市实际情况比较符合的参数,运用人力资本法、市场价值法、土地价值损失法、收益还原法、机会成本法等环境经济学方法,以2009年为例估算了大气污染、水污染、固体废弃物污染、噪声污染对银川市造成的经济损失。初步估算出银川市2009年因环境污染造成的直接经济损失为45.279亿元,环境污染状况严峻,城市环境保护成为银川市经济可持续发展的基础。     

The impact of land use and land cover changes on land surface temperature in a karst area of China

Satellite images have been used extensively to study temporal changes in land use and land cover (LULC) in China. However, few studies have been conducted in the karst areas despite the large area and population involved and the fragile ecosystem. In this study, LULC changes were examined in part of Guizhou Province of southern China from 1991 to 2001 based on Landsat Thematic Mapper (TM) images of November 7, 1991, December 5, 1994, and December 19, 2001. Land surface temperature (LST) and normalized difference vegetation index (NDVI) were computed based on LULC types. The results show that agricultural land decreased, while urban areas expanded dramatically, and forest land increased slightly. Barren land increased from 1991 to 1994, and then decreased from 1994 to 2001. These changes in LULC widened the temperature difference between the urban and the rural areas. The change in LST was mainly associated with changes in construction materials in the urban area and in vegetation abundance both in the urban and rural areas. Vegetation had a dual function in the temperatures of different LULC types. While it could ease the warming trend in the urban or built-up areas, it helped to keep other lands warmer in the cold weather. The study also reveals that due to the government's efforts on reforestation, rural ecosystems in some of the study area were being restored. The time required for the karst ecosystem to recover was shorter than previously thought.     

Temporal and Spatial Trends in Nutrient and Sediment Loading to Lake Tahoe,California‐Nevada,USA

Since 1980, the Lake Tahoe Interagency Monitoring Program (LTIMP) has provided stream‐discharge and water quality data—nitrogen (N), phosphorus (P), and suspended sediment—at more than 20 stations in Lake Tahoe Basin streams. To characterize the temporal and spatial patterns in nutrient and sediment loading to the lake, and improve the usefulness of the program and the existing database, we have (1) identified and corrected for sources of bias in the water quality database; (2) generated synthetic datasets for sediments and nutrients, and resampled to compare the accuracy and precision of different load calculation models; (3) using the best models, recalculated total annual loads over the period of record; (4) regressed total loads against total annual and annual maximum daily discharge, and tested for time trends in the residuals; (5) compared loads for different forms of N and P; and (6) tested constituent loads against land use‐land cover (LULC) variables using multiple regression. The results show (1) N and P loads are dominated by organic N and particulate P; (2) there are significant long‐term downward trends in some constituent loads of some streams; and (3) anthropogenic impervious surface is the most important LULC variable influencing water quality in basin streams. Many of our recommendations for changes in water quality monitoring and load calculation methods have been adopted by the LTIMP.     

PROBLEMS AND METHODS INVOLVED IN RELATING LAND USE TO GROUND-WATER QUALITY1

ABSTRACT: Efforts to relate shallow ground-water quality to the land use near a well lead to several statistical difficulties. These include potential uncertainty in land-use categorical data due to misclassification, data closure, distributional skewing, and spatial autocorrelation. Methods of addressing these problems are, respectively, the establishment of limits on minimum buffer radius, the estimation of contrasts, rank-based tests of association, and sub-sampling to prevent buffer overlap. Relations between the presence of purgeable organic compounds in ground water and land use are used to illustrate these problems and methods.