Accuracy and congruency of three different digital land-use maps

For numerous model applications in the earth and environmental sciences, digital land-use data are indispensable as a source of information on the geographical distribution of the land-use/cover. Therefore, the land-use data sets ATKIS, CORINE Land Cover, and Landsat TM classifications are widely used in Germany. However, the users of these data mostly do not have information on their quality. In this study, the accuracy of the three above-mentioned digital land-use maps was evaluated a posteriori based on the results of a field inventory in two test areas with a total area of 17 km². The results show that the overall accuracy of the land-use maps varies from 0.692 to 0.876. For the individual land-use classes, the user accuracy ranged from less than 0.001 to 0.991. In this paper, the positional congruency of the land-use class polygons among the three maps was also evaluated for a larger study region of 670 km² in the state of Hessen (Germany). This region is a small structured landscape with a relatively high portion of fallow land. In the analysis, the following six land-use classes were considered: urban and traffic areas, forest, water, arable land, pastures and meadows, and fallow land (including other uses). The results showed that the congruency of the land-use classes forest and urban and traffic areas is higher than the congruency of the land-use classes of the open land (arable land, pastures and meadows, fallow).     

The dimensions of global urban expansion: Estimates and projections for all countries, 2000–2050

Our study of the expansion of a representative sample of 30 cities showed that 28 of them expanded more than 16-fold during the twentieth century. More generally, cities are now expanding at twice their population growth rates, on average, and now cover almost 0.5% of the planet's land area. We created a new dataset comprising the universe of all 3646 named metropolitan agglomerations and cities that had populations in excess of 100,000 in the year 2000, their populations in that year, and their built-up area identified in the Mod500 map, currently the best of eight satellite-based global maps of urban land cover. Using this dataset, we estimated urban land cover in smaller cities and towns in all countries and calculated total urban land cover in every country in the year 2000. We then employed multiple regression models that could explain more than 90% of the variations in our urban land cover estimates amongst countries. Then, using U.N. urban population projections in combination with three realistic density change scenarios based on our previous global and historical study of densities, we projected urban land cover in every country and world region from 2000 to 2050. According to our medium projection, urban land cover in developing countries will increase from 300,000 km² in 2000 to 770,000 km² in 2030 and to 1,200,000 km² in 2050. Containing this expansion is likely to fail. Minimal preparations for accommodating it – realistic projection of urban land needs, the extension of metropolitan boundaries, acquiring the rights-of-way for an arterial road grid that can carry infrastructure and public transport, and the selective protection of open space from incursion by formal and informal land development – are now in order.     

The wildland–urban interface dynamics in the southeastern U.S. from 1990 to 2000

Resolving environmental impacts caused by the wildland–urban interface (WUI) expansion such as wildlife habitat fragmentation, or increased fire risk entails an accurate delineating of WUI boundary and its dynamics prediction. This study identified WUIs throughout the 11 states of southeastern U.S. in 1990 and 2000 and observed their change during this period utilizing census surveyed housing density and remotely sensed land-cover data. In 1990 and 2000, states of North Carolina and Virginia had the highest, while the state of Arkansas had the lowest proportion of WUI coverage. From 1990 to 2000, states of South Carolina, Florida and Mississippi have seen a radical WUI expansion, while North Carolina has experienced no noticeable WUI transformation. Total WUI area increased from 241,983 km² in 1990 to 285,415 km² in 2000. Wildland–urban interface patch number decreased from 1362 to 1282 and mean WUI patch size enlarged from 178 km² to 233 km². Total WUI area in each single year and new added WUI from 1990 to 2000 have high sensitivity to threshold adjustment of low housing density, vegetation density, while subtle sensitivity to threshold modification of high housing density. Vegetation density is a more significant factor than housing density in determining WUI coverage in both 1990 and 2000 and WUI dynamics from 1990 to 2000 in each state. Urban aggregation index is a significant factor related with WUI coverage in each state as well.     

Monitoring and modelling spatio-temporal urban growth of Delhi using Cellular Automata and geoinformatics

The study encompasses spatio-temporal land use/ land cover (LULC) monitoring (1989–2014) and urban growth modelling (1994–2024) of Delhi, India to deduce the past and future urban growth paradigm and its influence on varied LULC classes integrating geospatial techniques and Cellular Automata (CA). The study focused on scrutinising the reliability of the CA algorithm to function independently for urban growth modelling, provided with strong model calibration. For this purpose, satellite data of six stages of time at equal intervals along with the population density, distance to CBD and roads, and terrain slope are used. The satellite-based LULC during 1989–2014 exhibited 457 km² of net urban growth (275% change), cloned by the simulated LULC with net increase 448 km² (270% change). The spatial variation analysis using the principal component analysis (PCA) technique exhibit high similarity in classification ranging from 72% to 88%. The statistical accuracy between the satellite-based and simulated built-up extent of 2014 resulted in the overall accuracy 95.62% of the confusion matrix, and the area under the receiver operating characteristic (ROC) curve as 0.928—indication high model accuracy. The projected LULC exhibit that the urban area will increase to 708 km² and 787 km², primarily in western and eastern parts during 2019 and 2014 respectively. The rapid urban growth will replace and transform others LULC (net loss 138 km²) followed by vegetation cover (net loss 26 km²) during 2014–24. This rapid urban growth is detrimental to the habitat and may trigger critical risks to urban geo-environment and ecosystem in Delhi. Therefore, the study necessitates towards decentralization of urban functions and restoration of varied LULC in order to regulate the future urban growth patterns for sustainable development. The GDAL and NumPy libraries in Python 3.4 were efficient in spatial modelling and statistical calculations.     

Expansion of the US wildland–urban interface

For at least two decades, expansion of low-density residential development at the wildland–urban interface has been widely recognized as a primary factor influencing the management of US national forests. We estimate the location, extent, and trends in expansion of the wildland–urban interface (WUI) in the continental United States. We mapped the WUI by determining the intersection of housing density classes computed from refined US Census data with a map of wildfire hazards based on broad forest types using definitions of WUI from the Federal Register. Our methods allowed us to provide a more spatially precise estimation of the WUI that better reflects development patterns of interest to forest land managers. We defined three wildfire hazard classes based on vegetation type. “High” severity applies to vegetation types in which stand-replacing fires dominate both historical and recent fire regimes, e.g., lodgepole pine forest. “Low” severity applies where fuels and climate foster mostly low-intensity fires, e.g., aspen-birch forest. “High (historically low or variable)” applies to vegetation types in which fires historically were of low or variable intensity, but recently have often burned at high intensity because of a century of fire exclusion, e.g., southwestern ponderosa pine forest. In 2000, the WUI that includes a 3.2 km community protection zone occupied 465,614 km², and contained over 12.5 million housing units. This is an expansion of over 52% from 1970, and by 2030 the WUI is likely to expand to at least 513,670 km² with the greatest expansion occurring in the intermountain west states. Roughly 89% of the WUI is privately owned land and about 65% of the WUI occurs in high or high (historically low or variable) severity fire regime classes.     

Developing a land-cover classification to select indicators of forest ecosystem health in a rapidly urbanizing landscape

As moderate-sized cities become more urbanized, ecosystems are altered by land-use change. Key ecological services, such as clean air and water, drought and flood protection, soil generation and preservation, and detoxification of wastes are disrupted, risking the health and welfare of society. An understanding of ecosystem responses to urbanization is necessary to evaluate and balance short-term needs with long-term sustainability goals. Our main objective was to develop a land management and planning tool using a land-cover classification to select landscape indicators of ecosystem health near Columbus, GA. Spearman's Rho correlations were calculated to compare landscape and field-based indicators. Results suggest there are significant inverse correlations between ‘percent forest land-cover’ and ‘population, housing, and road densities’; ‘tree species richness’ and ‘forest patch density’; ‘percent urban land-cover’ and ‘lichen species richness’; ‘lichen incidence’ and ‘forest perimeter-area fractal dimension’. Overall, there were 152 significant urban/biological correlations obtained from this assessment (Rho ≥ |0.50| and p ≤ 0.10). Such a tool could prove useful to land managers and environmental planners by providing a quick and simple method to assess broad areas of land in a single analysis.     

Land management as a factor controlling dissolved organic carbon release from upland peat soils 1: Spatial variation in DOC productivity

The importance of soil storage in global carbon cycling is well recognised and factors leading to increased losses from this pool may act as a positive feedback mechanism in global warming. Upland peat soils are usually assumed to serve as carbon sinks, there is however increasing evidence of carbon loss from upland peat soils, and DOC concentrations in UK rivers have increased markedly over the past three decades. A number of drivers for increasing DOC release from peat soils have been proposed although many of these would not explain fine-scale variations in DOC release observed in many catchments.We examined the effect of land use and management on DOC production in upland peat catchments at two spatial scales within the UK. DOC concentration was measured in streams draining 50 small-scale catchments (< 3 km²) in three discrete regions of the south Pennines and one area in the North Yorkshire Moors. Annual mean DOC concentration was also derived from water colour data recorded at water treatment works for seven larger scale catchments (1.5-20 km²) in the south Pennines. Soil type and land use/management in all catchments were characterised from NSRI digital soil data and ortho-corrected colour aerial imagery.Of the factors assessed, representing all combinations of soil type and land use together with catchment slope and area, the proportion of exposed peat surface resulting from new heather burning was consistently identified as the most significant predictor of variation in DOC concentration. This relationship held across all blanket peat catchments and scales.We propose that management activities are driving changes in edaphic conditions in upland peat to those more favourable for aerobic microbial activity and thus enhance peat decomposition leading to increased losses of carbon from these environments.     

Significance of urban and agricultural land use for biocide and pesticide dynamics in surface waters

Biocides and pesticides are designed to control the occurrence of unwanted organisms. From their point of application, these substances can be mobilized and transported to surface waters posing a threat to the aquatic environment. Historically, agricultural pesticides have received substantially more attention than biocidal compounds from urban use, despite being used in similar quantities.This study aims at improving our understanding of the influence of mixed urban and agricultural land use on the overall concentration dynamics of biocides and pesticides during rain events throughout the year. A comprehensive field study was conducted in a catchment within the Swiss plateau (25 km²). Four surface water sampling sites represented varying combinations of urban and agricultural sources. Additionally, the urban drainage system was studied by sampling the only wastewater treatment plant (WWTP) in the catchment, a combined sewer overflow (CSO), and a storm sewer (SS). High temporal resolution sampling was carried out during rain events from March to November 2007.The results, based on more than 600 samples analyzed for 23 substances, revealed distinct and complex concentration patterns for different compounds and sources. Five types of concentration patterns can be distinguished: a) compounds that showed elevated background concentrations throughout the year (e.g. diazinon >50 ng L⁻¹), indicating a constant household source; b) compounds that showed elevated concentrations driven by rain events throughout the year (e.g. diuron 100-300 ng L⁻¹), indicating a constant urban outdoor source such as facades; c) compounds with seasonal peak concentrations driven by rain events from urban and agricultural areas (e.g. mecoprop 1600 ng L⁻¹ and atrazine 2500 ng L⁻¹ respectively); d) compounds that showed unpredictably sharp peaks (e.g. atrazine 10,000 ng L⁻¹, diazinon 2500 ng L⁻¹), which were most probably due to improper handling or even disposal of products; and finally, e) compounds that were used in high amounts but were not detected in surface waters (e.g. isothiazolinones).It can be safely concluded that in catchments of mixed land use, the contributions of biocide and pesticide inputs into surface waters from urban areas are at least as important as those from agricultural areas.     

Population growth away from the coastal zone: Thirty years of land use change and nutrient export in the Altamaha River, GA

We used more than thirty years of water quality monitoring data collected by the United States Geological Survey at several stations in the Altamaha River and its tributaries to examine the relationship between population density, agricultural land use, and nutrient export from the watershed. Population densities in the Altamaha River watershed increased during the study period, most notably in the upper watershed near metropolitan Atlanta, while agricultural land use declined throughout the watershed. NO_x, TN and P in rivers were related to human population densities, while OC and NH₄⁺ concentrations in rivers were apparently related to agricultural land use. A general pattern of increasing NO_x and TN and decreasing NH₄⁺, P and OC over time throughout the watershed reflected changing population and land use. The overall average load from the Altamaha River to the coastal zone during the study period was 1.1, 5.6, 16.9, 0.9 and 262 kmol km^− 2 yr^− 1, delivering 40, 197, 596, 30, and 9213 · 10⁶ mol yr^− 1 of NH₄⁺, NO_x, TN, P and OC, respectively, to the coastal zone. The nutrient export patterns suggest that N and P loading to rivers in the Altamaha River watershed was greatest in the upper watershed where high population densities were found, and in-stream processing, dilution, and only moderate inputs during transit through the lower watershed resulted in relatively low export from the watershed to coastal waters.     

The multi-annual carbon budget of a peat-covered catchment

This study estimates the complete carbon budget of an 11.4 km² peat-covered catchment in Northern England. The budget considers both fluvial and gaseous carbon fluxes and includes estimates of particulate organic carbon (POC); dissolved organic carbon (DOC); excess dissolved CO₂; release of methane (CH₄); net ecosystem respiration of CO₂; and uptake of CO₂ by primary productivity. All components except CH₄ were measured directly in the catchment and annual carbon budgets were calculated for the catchment between 1993 and 2005 using both extrapolation and interpolation methods. The study shows that: Over the 13 year study period the total carbon balance varied between a net sink of − 20 to − 91 Mg C/km²/yr. The biggest component of this budget is the uptake of carbon by primary productivity (− 178 Mg C/km²/yr) and in most years the second largest component is the loss of DOC from the peat profile (+ 39 Mg C/km²/yr). Direct exchanges of C with the atmosphere average − 89 Mg C/km²/yr in the catchment. Extrapolating the general findings of the carbon budget across all UK peatlands results in an approximate carbon balance of − 1.2 Tg C/yr (± 0.4 Pg C/yr) which is larger than previously reported values. Carbon budgets should always be reported with a clear statement of the techniques used and errors involved as this is significant when comparing results across studies.