Ann L. Maclean

Characterizing historical and modern fire regimes in Michigan (USA): A landscape ecosystem approach

We studied the relationships of landscape ecosystems to historical and contemporary fire regimes across 4.3 million hectares in northern lower Michigan (USA). Changes in fire regimes were documented by comparing historical fire rotations in different landscape ecosystems to those occurring between 1985 and 2000. Previously published data and a synthesis of the literature were used to identify six forest-replacement fire regime categories with fire rotations ranging from very short (<100 years) to very long (>1,000 years). We derived spatially-explicit estimates of the susceptibility of landscape ecosystems to fire disturbance using Landtype Association maps as initial units of investigation. Each Landtype Association polygon was assigned to a fire regime category based on associations of ecological factors known to influence fire regimes. Spatial statistics were used to interpolate fire points recorded by the General Land Office. Historical fire rotations were determined by calculating the area burned for each category of fire regime and dividing this area by fifteen (years) to estimate area burned per annum. Modern fire rotations were estimated using data on fire location and size obtained from federal and state agencies. Landtype Associations networked into fire regime categories exhibited differences in both historical and modern fire rotations. Historical rotations varied by 23-fold across all fire rotation categories, and modern forest fire rotations by 13-fold. Modern fire rotations were an order of magnitude longer than historical rotations. The magnitude of these changes has important implications for forest health and understanding of ecological processes in most of the fire rotation categories that we identified.

Mapping lava flows from Nyamuragira volcano (1967–2011) with satellite data and automated classification methods

The volume, location and extent of historical lava flows are important when assessing volcanic hazards, as well as the productivity or longevity of a volcanic system. We use a Landsat/Hyperion/ALI dataset and automated classification methods to map lava flows at Nyamuragira volcano (1967–2011) in the Democratic Republic of the Congo. The humid tropical climate of Nyamuragira is advantageous because its lava flows are emplaced onto heavily forested flanks, resulting in strong contrast between lava and vegetation, which contributes to efficient flow mapping. With increasing age, there is an increase in Landsat band-4 reflectance, suggesting lava flow revegetation with time. This results in a distinct spectral contrast to delineate overlapping flows emplaced ∼5 years apart. Areal extents of the flows are combined with published lava flow thicknesses to derive volumes. The Landsat/Hyperion/ALI dataset is advantageous for mapping future flows quickly and inexpensively, particularly for volcano observatories where resources are limited.

An accuracy assessment of tree detection algorithms in juniper woodlands

This research provides a comprehensive accuracy assessment of five methods for classifying western juniper (Juniperus occidentalis) canopy cover from 1 m, 4-band National Agriculture Imagery Program (NAIP) imagery. Two object-oriented classification approaches (image segmentation and spatial wavelet analysis, (SWA)) are compared to three pixel based classification approaches (random forests, Iterative Self-Organizing Data Analysis (ISODATA), and maximum likelihood). Methods are applied to approximately 250 km 2 in the intermountain western USA. A robust suite of statistical approaches, which offer an alternative to traditional kappa-based methods, are utilized to determine equivalence between methods and overall effectiveness. Object-oriented approaches have the highest overall accuracy among the assessed methods. Each of the methods varied considerably in cover class accuracy. SWA has the highest class accuracy when juniper canopy cover is low (0 to 40 percent cover), ISODATA performs best at moderate cover (60 to 80 percent) and maximum likelihood performs best at higher cover (60 to 100 percent cover).

Determination of the Influence of Wind on the Keweenaw Current in the Lake Superior Basin as Identified by Advanced Very High Resolution Radiometer (AVHRR) Imagery

Abstract The Keweenaw Current is a warm coastal current in Lake Superior that flows northeastward along the northern shore of Michigans Keweenaw Peninsula. This study focuses on the fate of the current at the tip of the Keweenaw Peninsula. Results of this study suggest that the path of the current beyond the peninsula is primarily controlled by wind. In this study, eleven surface temperature maps derived from Advanced Very High Resolution Radiometric (AVHRR) data using computer assisted image processing techniques were used to identify the Keweenaw Current. Wind data from two moored data buoys, a Coastal Marine Automated Network (CMAN) fixed buoy, and three airport weather stations, collected on the same day as each of the images and for the two days preceding the image date, are used to determine whether wind direction and speed influence the path of the Keweenaw Current past the tip of the peninsula. In nine images the currents path is similar to the surface Ekman transport direction predicted from wind data. All eleven images show a similarity between the currents actual path and a path calculated when net Ekman transport is assumed. Results of this study also show that there may be a possible lag time of one day between a change in wind direction and the currents adjustment to that change.

NiepoŁomice forest—a gis analysis of ecosystem response to industrial pollution

Abstract The Niepolomice Forest is located near the city of Krakow (Southern Poland). Since the erection of large iron works in the 1950’s, the forest has suffered from heavy pollution with SO2 and industrial dusts containing heavy metals. During the last 10 years this impact was significantly reduced. In the same period the Niepolomice Forest ecology has been intensively studied. With the advent of modern, computer intensive techniques, data gathered in the past are being reanalysed with respect to the spatial and temporal variation of the forest ecosystem response to the industrial pollution. To that end, the effects of natural conditions (soil, vegetation) and of industrial pollution (heavy metals, sulphur dioxide) upon the pine stands (tree volume increment, crown injuries) in the Niepolomice Forest were studied using a geographic information system. Procedures of statistical analysis involving bootstrapping were developed. Results suggest fertilization of forest stands due to industrial pollution, an effect not revealed in former studies.

Modeling Riparian Zones Utilizing DEMS and Flood Height Data

Riparian ecotones are unique, diverse networks of vegetation and soils in close proximity to streams, rivers, and lakes. Previous approaches to riparian boundary delineation utilized fixed width buffers, but using a fixed width riparian buffer only takes the watercourse into consideration; it does not consider the surrounding landscape. By hydrologically defining a riparian ecotone to occur at the 50-year flood height and incorporating digital elevation data, the spatial modeling capabilities of ArcMap ® GIS are utilized to map riparian zones accurately. This approach better characterizes the watercourse and its associated floodplain. Riparian zones delineated using 10 versus 30 meter DEMs and stream course information from the National Hydrography Dataset differ significantly. Within our study areas, 30 meter DEMs are not adequate to map elevation changes for accurate riparian area delineation. The result is a robust GIS based model in an ArcMap ® Toolbox format to delineate a variable-width riparian boundary.

Documenting Complex Surface Temperature Patterns from Advanced Very High Resolution Radiometer (AVHRR) Imagery of Saginaw Bay, Lake Huron

Interannual differences in nutrient concentrations, phytoplankton densities, and the dispersal of zooplankton and fish life history stages (e.g., planktonic larvae, resting eggs) in embayments often are contingent upon bay and coastal water exchange and movements. However, predicting water mass exchange is difficult in that many factors influence the circulation of waters within bays. The central theme of this contribution is that circulation phenomena derived from simple models can be identified and classified using satellite-obtained lake surface temperature maps, and the incidence of events related to gross temperature regime (season) and winds (shorter-term perturbations). To illustrate this potential, the high sampling frequency of AVHRR imagery was used to examine seasonal surface temperature patterns between Saginaw Bay and Lake Huron over a 3-year period. Linear regressions of CoastWatch IMGMAP and OCNMAP daytime sea surface temperature (SST) algorithms against shipboard bulk temperatures were highly significant, with r2 values of 0.98 and 0.94. Synoptic reconnaissance of lake surface temperatures from AVHRR verified many previously known general seasonal events, yet provided much better spatial coverage. The thermal bar persisted in the bay for approximately 6 weeks from late April until mid-June. The combination of shallow depths and impounded river discharges caused inner bay waters to warm more rapidly than outer bay and open lake waters. A thermal gradient of 6 to 10°C persisted between the inner bay and Lake Huron waters throughout the summer. The persistence of major spatial thermal gradients restricted mixing of inner bay waters with the outer bay and open lake, whereas inner and outer bay temperatures converged during fall months, increasing the likelihood of mixing. However, frequent wind-induced effects can cause circulation reversals and move surface waters in quite complex patterns across the bay. AVHRR image classification confirms the sensitivity of inner bay waters to wind stress-related circulation, aiding interpretations of historical data sets.

An Approach to Lineament Analysis for Groundwater Exploration in Nicaragua

Wells in bedrock aquifers tend to yield more water where they intersect fracture networks. Lineament analysis using satellite imagery was employed to identify surface expressions of subsurface fracturing for possible new well locations. An imagery integration approach was developed to evaluate satellite imagery for lineament analysis in terrain where the influences of human development and vegetation confound lineament interpretation. Four satellite sensors (ASTER, Landsat-7 ETM+, QuickBird, RADARSAT-1) and a DEM were used for lineament mapping a volcanic region of Nicaragua. Image processing and interpretations obtained 12 complementary products, which were synthesized into a raster image of lineament-zone coincidence for creating a lineament delineation map. Nine of the 11 previously mapped faults were identified from the coincidence-based map along with 26 new lineaments. The locations of ten new lineaments were confirmed by field observation. RADARSAT-1 products were best for minimizing anthropogenic features but not able to identify all the geological lineaments.