From land cover change to land function dynamics: a major challenge to improve land characterization

Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and linkages between these. Consideration of land functions that provide a wide range of goods and services makes more integrated assessments of land change possible. The increasing attention to multifunctional land use is another incentive to develop methods to assess changes in land functions. A number of methods to quantify and map the spatial extent of land use and land functions are discussed and the implications for modeling are identified based on recent model approaches in land change science. The mixed use of land cover, land use and land function in maps and models leads to inconsistencies in land change assessments. Explicit attention to the non-linear relations between land cover, land use and land function is essential to consistently address land change. New methods to map and quantify land function dynamics will enhance our ability to understand and model land system change and adequately inform policies and planning.     

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.     

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

The conversion of natural habitat to urban settlements is a primary driver of biodiversity loss, and species' persistence is threatened by the extent, location, and spatial pattern of development. Urban growth models are widely used to anticipate future development and to inform conservation management, but the source of spatial input to these models may contribute to uncertainty in their predictions. We compared two sources of historic urban maps, used as input for model calibration, to determine how differences in definition and scale of urban extent affect the resulting spatial predictions from a widely used urban growth model for San Diego County, CA under three conservation scenarios. The results showed that rate, extent, and spatial pattern of predicted urban development, and associated habitat loss, may vary substantially depending on the source of input data, regardless of how much land is excluded from development. Although the datasets we compared both represented urban land, different types of land use/land cover included in the definition of urban land and different minimum mapping units contributed to the discrepancies. Varying temporal resolution of the input datasets also contributed to differences in projected rates of development. Differential predicted impacts to vegetation types illustrate how the choice of spatial input data may lead to different conclusions relative to conservation. Although the study cannot reveal whether one dataset is better than another, modelers should carefully consider that geographical reality can be represented differently, and should carefully choose the definition and scale of their data to fit their research objectives.     

Assessing the impact of urbanization on regional net primary productivity in Jiangyin County, China

Urbanization is one of the most important aspects of global change. The process of urbanization has a significant impact on the terrestrial ecosystem carbon cycle. The Yangtze Delta region has one of the highest rates of urbanization in China. In this study, carried out in Jiangyin County as a representative region within the Yangtze Delta, land use and land cover changes were estimated using Landsat TM and ETM+ imagery. With these satellite data and the BEPS process model (Boreal Ecosystem Productivity Simulator), the impacts of urbanization on regional net primary productivity (NPP) and annual net primary production were assessed for 1991 and 2002. Landsat-based land cover maps in 1991 and 2002 showed that urban development encroached large areas of cropland and forest. Expansion of residential areas and reduction of vegetated areas were the major forms of land transformation in Jiangyin County during this period. Mean NPP of the total area decreased from 818 to 699 gCm(-2)yr(-1) during the period of 1991 to 2002. NPP of cropland was only reduced by 2.7% while forest NPP was reduced by 9.3%. Regional annual primary production decreased from 808 GgC in 1991 to 691 GgC in 2002, a reduction of 14.5%. Land cover changes reduced regional NPP directly, and the increasing intensity and frequency of human-induced disturbance in the urbanized areas could be the main reason for the decrease in forest NPP.     

Modelling the conversion of Colombian lowland ecosystems since 1940: drivers, patterns and rates

In biologically mega-diverse countries that are undergoing rapid human landscape transformation, it is important to understand and model the patterns of land cover change. This problem is particularly acute in Colombia, where lowland forests are being rapidly cleared for cropping and ranching. We apply a conceptual model with a nested set of a priori predictions to analyse the spatial and temporal patterns of land cover change for six 50-100 km(2) case study areas in lowland ecosystems of Colombia. Our analysis included soil fertility, a cost-distance function, and neighbourhood of forest and secondary vegetation cover as independent variables. Deforestation and forest regrowth are tested using logistic regression analysis and an information criterion approach to rank the models and predictor variables. The results show that: (a) overall the process of deforestation is better predicted by the full model containing all variables, while for regrowth the model containing only the auto-correlated neighbourhood terms is a better predictor; (b) overall consistent patterns emerge, although there are variations across regions and time; and (c) during the transformation process, both the order of importance and significance of the drivers change. Forest cover follows a consistent logistic decline pattern across regions, with introduced pastures being the major replacement land cover type. Forest stabilizes at 2-10% of the original cover, with an average patch size of 15.4 (+/-9.2)ha. We discuss the implications of the observed patterns and rates of land cover change for conservation planning in countries with high rates of deforestation.     

Comparing Environmental Conditions Using Indicators of Pollution Hazard

/ Land use/land cover classifications for 1973 and 1991, derived from the interpretation of satellite imagery, are quantified on the basis of biophysical land units in a study area in southeastern Australia. Nutrient export potentials are estimated for each land unit based on their composition of land use/land cover classes. Spatial and temporal comparisons are made of the land units based on the calculated pollution hazard indicators to provide an insight into changes in the state of the environment and the regional significance of land use changes. For example, one ecosystem, unique to the study, showed a large increase in pollution hazard over the study period as a manifestation of an 11-fold rise in cleared area and an expansion of cropping activities. The benefits to environmental management in general are discussed.KEY WORDS: Land cover change; Nutrient export; Environmental condition; Pollution hazard; Agricultural pollution; Nonpoint source pollution; Diffuse pollution; Environmental degradation     

Classifying environmentally significant urban land uses with satellite imagery

We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.     

Detecting Temporal Change in Watershed Nutrient Yields

Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.     

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.     

Predicting the distribution of ground beetle species (Coleoptera, Carabidae) in Britain using land cover variables

Predictions of plant and animal species distributions are important for conservation and for the assessment of large-scale ecosystem change. Land cover data are becoming more widely available for use in land management and conservation. We use a logistic regression modelling approach to investigate the utility of these data for modelling. The relationship between the distribution of 137 British ground beetles species and land cover was investigated using data from 1,687 10 km national grid squares. Land cover data were simplified using ordination and the axes used as predictors in logistic regression with presence absence data for individual beetle species as response variables. Significant regression models were generated for all species with first and second axis scores. The amounts of variation explained by models were generally low, but predictions derived from models generally matched the known distributions of the species in Britain. Species with coastal preferences were poorly modelled and predicted to occur throughout lowland Britain whilst a number of species occurring in southern Britain were predicted to occur into Scotland. A validation exercise comparing model predictions with new data from a survey of 59 10 km(2) produced mixed results with the distribution of grassland species being better predicted than riverine species. Jack-knifing was used to assess the robustness of models for four species which differed in their apparent responses to the land cover variables. Methods for improving the predictive power of these models and their potential for use in assessing the impact of global climate change are discussed.     

Land Use/Cover Changes, the Environment and Water Resources in Northeast China

Land use/cover in Northeast China went through extensive changes during the 1990s. This report explores the interaction between these changes and the environment, and the implication of these changes for rational allocation of water resources. Two maps of land use/cover produced from 1990 and 2000 Landsat TM satellite images were overlaid in ArcInfo to reveal changes in land cover. Results indicate that farmland and grassland decreased by 386,195 and 140,075 ha, respectively, while water, built-up areas, and woodland increased by 238,596, 194,231, and 192,682 ha, respectively. These changes bore a mutual relationship with the environmental change. On the one hand, climate warming made some of these changes (e.g., conversion of woodland and grassland to farmland) possible. On the other hand, the changed surface cover modified the local climate. These changes, in turn, caused severe environmental degradation and increased flooding. The change between dry field and rice paddy, in particular, raised severe implications for the proper allocation of limited water resources in the Northeast. Efforts are needed to coordinate their rational allocation to reap maximum and sustainable return over the entire area, not just in some localities. Results obtained in this study should be of interest to the international audience of Environmental Management in that they highlight the interactive nature of human activities and the environment and the off-site impact of these activities on the environment.     

Multi-scale analysis of oxygen demand trends in an urbanizing Oregon watershed, USA

Human alteration of the landscape has an extensive influence on the biogeochemical processes that drive oxygen cycling in streams. We estimated trends from the mid-1990s to 2003, using the seasonal Mann-Kendall's test, for percent saturation dissolved oxygen (DO), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), and ammonia-nitrogen (NH(3)-N) for 12 sites in the Rock Creek watershed, northwest Oregon, USA. In order to understand the influence of landscape change, scale, and stormwater runoff management on dissolved oxygen trends, we calculated land cover change through aerial photo interpretation at full-basin, local (near sample point) basin, and 100m stream buffer scales, for the years 1994 and 2000. Significant (p < or = 0.05) trends occurred in DO (increasing at five sites), COD (decreasing at seven sites), TKN (decreasing at five sites, increasing at one site), and NH(3)-N (decreasing at one site, increasing at one site). Significant land cover change occurred in agricultural land cover (-8% for the entire basin area) and residential land cover (+10% for the entire basin area) (p < or = 0.05). Correlation results indicated that: (1) forest cover negatively influenced COD at the full basin scale and positively influences NH(3)-N at local scales, (2) residential land cover influenced oxygen demand variables at local scales, (3) agricultural land cover did not influence oxygen demand, (4) local topography negatively influenced TKN and NH(3)-N, and (5) stormwater runoff management infrastructure correlated positively with COD at the local scale. This study indicates that landscape factors influencing DO conditions for the study streams act at multiple scales, suggesting that better knowledge of scale-process interactions can guide watershed managers' decision making in order to maintain improving water quality conditions.     

Understanding land cover change in a Special Protection Area in Central Spain through the enhanced land cover transition matrix and a related new approach

This work analyses land cover changes occurring between 1990 and 2000 within a Natural Protected Area, southwest of Madrid (Spain). We develop a new methodology that considers the net change in different land cover categories in each municipality of the study area. Our methodology, which uses Factorial Correspondence Analysis, allows identification of the most important changes at the municipality level and groups the municipalities where land use dynamics are similar. This method is a powerful tool for synthesis and can potentially be applied to non-spatial geographical data sources (e.g. agrarian census statistics). Our results show that the land cover around SW Madrid is highly dynamic. The shrub vegetation, arable land, heterogeneous agricultural and human-created area categories show the highest total change. The dynamics of the changes detected are dominated by decreases in the area of different types of crops and increases in forest areas. These changes may have indirect effects on the conservation of natural resources and wildlife if not managed appropriately.     

Land Use and Land Cover Change Analysis and Prediction in the Upper Reaches of the Minjiang River,China

Scientists have aimed at exploring land use and land cover change (LUCC) and modeling future landscape pattern in order to improve our understanding of the causes and consequences of these phenomena. This study addresses LUCC in the upper reaches of Minjiang River, China, from 1974 to 2000. Based on remotely sensed images, LUCC and landscape pattern change were assessed using cross-tabulation and landscape metrics. Then, using the CLUE-S model, changes in area of four types of land cover were predicted for two scenarios considering forest polices over the next 20 years. Results showed that forestland decreased from 1974 to 2000 due to continuous deforestation, while grassland and shrubland increased correspondingly. At the same time, the farmland and settlement land increased dramatically. Landscape fragmentation in the study area accompanied these changes. Forestland, grassland, and farmland take opposite trajectories in the two scenarios, as does landscape fragmentation. LUCC has led to ecological consequences, such as biodiversity loss and lowering of ecological carrying capacity.     

Impact of Changing Climate and Land Cover on Flood Magnitudes in the Delaware River Basin,USA

Changing climate and land cover are expected to impact flood hydrology in the Delaware River Basin over the 21st Century. HEC‐HMS models (U.S. Army Corps of Engineers Hydrologic Engineering Center‐Hydrologic Modeling System) were developed for five case study watersheds selected to represent a range of scale, soil types, climate, and land cover. Model results indicate that climate change alone could affect peak flood discharges by ?6% to +58% a wide range that reflects regional variation in projected rainfall and snowmelt and local watershed conditions. Land cover changes could increase peak flood discharges up to 10% in four of the five watersheds. In those watersheds, the combination of climate and land cover change increase modeled peak flood discharges by up to 66% and runoff volumes by up to 44%. Precipitation projections are a key source of uncertainty, but there is a high likelihood of greater precipitation falling on a more urbanized landscape that produces larger floods. The influence of climate and land cover changes on flood hydrology for the modeled watersheds varies according to future time period, climate scenario, watershed land cover and soil conditions, and flood frequency. The impacts of climate change alone are typically greater than land cover change but there is substantial geographic variation, with urbanization the greater influence on some small, developing watersheds.     

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.     

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.     

The Ecological Modelling System of NELUP

Within the NERC/ESRC Land Use Programme ecological change is assumed to be driven principally by agronomic activity. Land use change is defined as being of two types depending on whether there is a complete change of cover or a modification of an existing cover. Some agronomic activities lead to quantitative changes between land cover types and others to more subtle qualitative changes within land cover types. A modelling system based on three distinct models is described for predicting the effects of the two types of change in land cover on the distribution of plants, invertebrates and birds. The potential use of the system in analysing problems of land use change is illustrated using a simple scenario based on changing nitrogenous fertilizer regimes in lowland agriculture.     

STREAM HEALTH RANKINGS PREDICTED BY SATELLITE DERIVED LAND COVER METRICS1

ABSTRACT: Land cover and land use change have long been known to influence the chemical, physical, and biological characteristics of streams. This study makes use of land cover maps derived from fine resolution satellite imagery and an extensive stream quality dataset to determine the relationship between small watershed health rankings and land cover composition and configuration. Landscape metrics were derived from digital impervious surface area (ISA), tree cover (percent), and agricultural crop maps within Montgomery County, Maryland. Watershed rankings were developed by state and county collaborators (MD‐DNR and MCDEP) using extensive biological and chemical measurements. In stepwise logistic regression models the factors accounting for the most variation in stream health ranking were the percent ISA, followed by the percent of tree cover. Riparian buffer zone tree cover was also a significant predictor. Of the metrics that considered the spatial configuration of the landscape, a contagion index and the percent of ISA in the flow path from the ISA to the stream were also found to be significant predictors of stream health. Despite limited ability to characterize landscape configuration or narrow riparian buffer zone vegetation with coarser resolution imagery (from Landsat), model results were not significantly different from those based on the use of fine‐resolution ISA information, suggesting that broader area applications of the approach are possible. The results indicate that management practices designed to improve stream water quality should focus on the amount of ISA and tree cover in both the watershed and within the buffer zone.     

Changes in Land Cover and Subsequent Effects on Lower Fraser Basin Ecosystems from 1827 to 1990

/ European settlement began in the Lower Fraser Basin (LFB) inwestern British Columbia in 1827 and has impacted the basin ecosystem in anumber of ways, especially affecting the vegetation. Using previouslypublished data, air photos, and other historical material for the area,estimates of land cover were made for the years prior to 1827 and for 1930and 1990. The area of coniferous forest changed from 71% prior to 1827to 50% in 1930 to 54% in 1990. However, prior to 1827, only27% of the forest would have been immature (<120 years old), while40% would have been immature in 1930 and 73% of the forest wasimmature in 1990. The amount of wetland area decreased from 10% to1% of the study area while urban and agricultural area increased to26% of the study area by 1990. The changes in land cover have hadadverse effects on soil, water, and air quality; aquatic life; and plant andanimal populations. Estimates of changes in net primary production andorganic soil carbon suggest a decline over the past 170 years, although thelatter rate of decrease has slowed since 1930. As human populations in theLower Fraser Basin continue to increase, the quality of air, water, and soilwill continue to decline unless measures are taken.KEY WORDS: Human impact; Land cover; Net primary productivity; Organiccarbon in soil