Methods for the visualization of digital elevation models for landform mapping

Digital elevation models (DEMs) are increasingly used for landform mapping, particularly with the growing availability of national and global datasets. In this paper we describe a variety of techniques that can visualize a DEM. We then compare five techniques to ascertain which performs the most complete and unbiased visualization. We assess the visualization techniques by comparing landforms mapped from them against a detailed morphological map (derived from mapping of multi‐azimuth relief‐shaded DEMs cross‐checked with stereo aerial photographs). Results show that no single visualization method provides complete and unbiased mapping. The relief‐shaded visualizations are particularly prone to azimuth biasing, although they can highlight subtle landforms. We recommend curvature visualization for initial mapping as this provides a non‐illuminated (and therefore unbiased) image. Initial mapping can then be supplemented with data from relief‐shaded visualizations. Copyright © 2005 John Wiley & Sons, Ltd.     

The Influence of the “Mixed Pixel” Problem on the Detection of Analogous Forest Communities Between Presettlement and Present in Western New York∗

We conducted a land change analysis to determine if the forest communities of presettlement and present contain areas that are analogous in composition, using surveys of the Holland Land Company (1797–1799) and U.S. Forest Service (1991–1993) from western New York. Gridded forest-type maps are produced from each survey using two models: a uniform model that assumes each data grid cell is occupied by a single forest type, and a mixture model in which grid cells are assumed to be occupied by multiple forest types in different proportions. The mixture model consistently detects a larger area of analogous communities in the two time periods at both global and local scales.     

Snow cover variability across central Canada (1978–2002) derived from satellite passive microwave data

Twenty-four winter seasons (1978–2002) of mean February snow water equivalent (SWE) values were analyzed in an exploration of the spatial pattern of temporal variability in snow cover across the non-mountainous interior of Canada. The SWE data were derived from space-borne passive microwave brightness temperatures processed with a land cover-sensitive suite of algorithms. Spatial patterns in the frequency and amount of variability were investigated on an annual basis through comparisons with average trends over all 24 years. Changes in temporal variability through time were also investigated by comparing three eight year time periods to general trends. Analyses were synthesized at the ecozone scale in order to link results both to potential land cover influences on algorithm performance and climatological variability in SWE. Prairie and northern ecozones were typically found to be the most variable in terms of SWE magnitude. Analyses indicate that non-treed land cover classes are generally more variable than treed classes. The results also indicate that extreme weather events appear to be occurring with increasing consistency in the Prairie and Arctic regions. Discerning climatologically significant variability in the time series, compared to algorithm-related issues can be a challenge, but in an era of eroding surface observing networks the passive microwave time series represents an important resource for monitoring and detecting trends and variability in terrestrial snow cover.     

How well do integrated assessment models simulate climate change?

Integrated assessment models (IAMs) are regularly used to evaluate different policies of future emissions reductions. Since the global costs associated with these policies are immense, it is vital that the uncertainties in IAMs are quantified and understood. We first demonstrate the significant spread in the climate system and carbon cycle components of several contemporary IAMs. We then examine these components in more detail to understand the causes of differences, comparing the results with more complex climate models and earth system models (ESMs), where available. Our results show that in most cases the outcomes of IAMs are within the range of the outcomes of complex models, but differences are large enough to matter for policy advice. There are areas where IAMs would benefit from improvements (e.g. climate sensitivity, inertia in climate response, carbon cycle feedbacks). In some cases, additional climate model experiments are needed to be able to tune some of these improvements. This will require better communication between the IAM and ESM development communities.     

The Indus-Tsangpo suture zone in Ladakh, northwest Himalaya: Further palaeomagnetic data and implications

A total of 81 samples (244 specimens) from Upper Cretaceous Indus Molasse and Middle to Upper Cretaceous Dras Flyschoids of the Indus-Tsangpo suture zone in Ladakh (northwest Himalaya) has been studied by thermal demagnetization methods.Both formations showed a characteristic magnetization component indicative for equatorial to low northern palaeolatitudes of acquisition. Similar palaeolatitudes have been obtained before from secondary magnetization components of Early Tertiary age in the Ladakh Intrusives and in the Tibetan Sedimentary Series of central Nepal. The present characteristic components are interpreted likewise as secondary magnetizations which stabilized between 50 and 60 m.y. ago, during Greater India's collision with Asia's southern margin.The Dras Flyschoids show another magnetic component which, in case of primary origin, indicates acquisition at a low southern palaeolatitude. If correct, this interpretation supports recent suggestions for Late Cretaceous obduction of an island arc on Greater India's northern margin.     

Community preparedness for lava flows from Mauna Loa and Hualālai volcanoes,Kona, Hawai‘i

Lava flows from Mauna Loa and Huallai volcanoes are a major volcanic hazard that could impact the western portion of the island of Hawaii (e.g., Kona). The most recent eruptions of these two volcanoes to affect Kona occurred in a.d. 1950 and ca. 1800, respectively. In contrast, in eastern Hawaii, eruptions of neighboring Klauea volcano have occurred frequently since 1955, and therefore have been the focus for hazard mitigation. Official preparedness and response measures are therefore modeled on typical eruptions of Klauea.The combinations of short-lived precursory activity (e.g., volcanic tremor) at Mauna Loa, the potential for fast-moving lava flows, and the proximity of Kona communities to potential vents represent significant emergency management concerns in Kona. Less is known about past eruptions of Huallai, but similar concerns exist. Future lava flows present an increased threat to personal safety because of the short times that may be available for responding.Mitigation must address not only the specific characteristics of volcanic hazards in Kona, but also the manner in which the hazards relate to the communities likely to be affected. This paper describes the first steps in developing effective mitigation plans: measuring the current state of peoples knowledge of eruption parameters and the implications for their safety. We present results of a questionnaire survey administered to 462 high school students and adults in Kona. The rationale for this study was the long lapsed time since the last Kona eruption, and the high population growth and expansion of infrastructure over this time interval. Anticipated future growth in social and economic infrastructure in this area provides additional justification for this work.The residents of Kona have received little or no specific information about how to react to future volcanic eruptions or warnings, and short-term preparedness levels are low. Respondents appear uncertain about how to respond to threatening lava flows and overestimate the minimum time available to react, suggesting that personal risk levels are unnecessarily high. A successful volcanic warning plan in Kona must be tailored to meet the unique situation there.     

Topographic changes of a supply‐limited inland parabolic sand dune during the incipient phase of stabilization

Topographic surveys on an inland parabolic sand dune over a six‐year period provide insight into the effects of diminishing local sand supply on dune stabilization. During the interval (2003–2009) sparse vegetation cover (Psoralea lanceolata) increased despite drier than normal moisture conditions and steady wind power during the growing season. Whereas these climatic conditions are typically ascribed to sustaining or increasing dune activity, here they coincide with stabilization. Through the use of geographic information system (GIS) analysis of volumetric changes it is shown that the increase of P. lanceolata can be attributed to the reduction of local sand supply from two blowouts along the arms of the parabolic dune during the six‐year period. These results show that climate is not the only control on dune activity in vegetated inland dunefields. Copyright © 2010 John Wiley & Sons, Ltd.     

The Creation of a National Agricultural Land Use Dataset: Combining Pycnophylactic Interpolation with Dasymetric Mapping Techniques

Agricultural Census data is summarised over spatially coarse reporting units for reasons of farm confidentiality. This is problematic for research at a local level. This article describes an approach combining dasymetric and volume preserving techniques to create a national land use dataset at 1 km² resolution. The results for an English county are compared with contemporaneous aggregated habitat data. The results show that the accurate estimates of local agricultural land use (Arable and Grass) patterns can be estimated when individual 1 km squares are combined into blocks of > 9 squares, thereby providing local estimates of agricultural land use. This in turn allows more detailed modelling of land uses related to specific livestock and cropping activities. The dataset created by this work has been subject to extensive external validation through its incorporation into a number of other national models: nitrate leaching (e.g. MAGPIE, NEAP‐N), waste, and pathogen modelling related to agricultural activity.