Integration of Synthetic Aperture Radar Imagery and Derived Products into Severe Weather Disaster Response

No abstract availabl

Investigating the Use and Integration of Synthetic Aperture Radar Imagery in the Damage Survey Process within the NOAA/NWS Damage Assessment Toolkit (DAT)

No abstract availabl

Climate Divisions for Alaska Based on Objective Methods

Alaska encompasses several climate types because of its vast size, high-latitude location, proximity to oceans, and complex topography. There is a great need to understand how climate varies regionally for climatic research and forecasting applications. Although climate-type zones have been established for Alaska on the basis of seasonal climatological mean behavior, there has been little attempt to construct climate divisions that identify regions with consistently homogeneous climatic variability. In this study, cluster analysis was applied to monthly-average temperature data from 1977 to 2010 at a robust set of weather stations to develop climate divisions for the state. Mean-adjusted Advanced Very High Resolution Radiometer surface temperature estimates were employed to fill in missing temperature data when possible. Thirteen climate divisions were identified on the basis of the cluster analysis and were subsequently refined using local expert knowledge. Divisional boundary lines were drawn that encompass the grouped stations by following major surrounding topographic boundaries. Correlation analysis between station and gridded downscaled temperature and precipitation data supported the division placement and boundaries. The new divisions north of the Alaska Range were the North Slope, West Coast, Central Interior, Northeast Interior, and Northwest Interior. Divisions south of the Alaska Range were Cook Inlet, Bristol Bay, Aleutians, Northeast Gulf, Northwest Gulf, North Panhandle, Central Panhandle, and South Panhandle. Correlations with various Pacific Ocean and Arctic climatic teleconnection indices showed numerous significant relationships between seasonal division average temperature and the Arctic Oscillation, Pacific–North American pattern, North Pacific index, and Pacific decadal oscillation.Keywords: Statistical techniques, Climate variability, Climate classification/regimes, Regional effects, Climatolog

Quantification and analysis of icebergs in a tidewater glacier fjord using an object-based approach

Tidewater glaciers are glaciers that terminate in, and calve icebergs into, the ocean. In addition to the influence that tidewater glaciers have on physical and chemical oceanography, floating icebergs serve as habitat for marine animals such as harbor seals (Phoca vitulina richardii). The availability and spatial distribution of glacier ice in the fjords is likely a key environmental variable that influences the abundance and distribution of selected marine mammals; however, the amount of ice and the fine-scale characteristics of ice in fjords have not been systematically quantified. Given the predicted changes in glacier habitat, there is a need for the development of methods that could be broadly applied to quantify changes in available ice habitat in tidewater glacier fjords. We present a case study to describe a novel method that uses object-based image analysis (OBIA) to classify floating glacier ice in a tidewater glacier fjord from high-resolution aerial digital imagery. Our objectives were to (i) develop workflows and rule sets to classify high spatial resolution airborne imagery of floating glacier ice; (ii) quantify the amount and fine-scale characteristics of floating glacier ice; (iii) and develop processes for automating the object-based analysis of floating glacier ice for large number of images from a representative survey day during June 2007 in Johns Hopkins Inlet (JHI), a tidewater glacier fjord in Glacier Bay National Park, southeastern Alaska. On 18 June 2007, JHI was comprised of brash ice ([Formula: see text] = 45.2%, SD = 41.5%), water ([Formula: see text] = 52.7%, SD = 42.3%), and icebergs ([Formula: see text] = 2.1%, SD = 1.4%). Average iceberg size per scene was 5.7 m2 (SD = 2.6 m2). We estimate the total area (± uncertainty) of iceberg habitat in the fjord to be 455,400 ± 123,000 m2. The method works well for classifying icebergs across scenes (classification accuracy of 75.6%); the largest classification errors occur in areas with densely-packed ice, low contrast between neighboring ice cover, or dark or sediment-covered ice, where icebergs may be misclassified as brash ice about 20% of the time. OBIA is a powerful image classification tool, and the method we present could be adapted and applied to other ice habitats, such as sea ice, to assess changes in ice characteristics and availability

Documenting earthquake-induced liquefaction using satellite remote sensing image transformations

Documenting earthquake-induced liquefaction effects is important to validate empirical liquefaction susceptibility models and to enhance our understanding of the liquefaction process. Currently, after an earthquake, field-based mapping of liquefaction can be sporadic and limited due to inaccessibility and lack of resources. Alternatively, researchers have used change detection with remotely sensed pre- and postearthquake satellite images to map earthquake-induced effects. We hypothesize that as liquefaction occurs in saturated granular soils due to an increase in pore pressure, liquefaction-induced surface changes should be associated with increased moisture, and spectral bands/transformations that are sensitive to soil moisture can be used to identify these areas. We verify our hypothesis using change detection with pre- and postearthquake thermal and tasseled cap wetness images derived from available Landsat 7 Enhanced Thematic Mapper Plus (ETM+) for the 2001 Bhuj earthquake in India. The tasseled cap wetness image is directly related to the soil moisture content, whereas the thermal image is inversely related to it. The change detection of the tasseled cap transform wetness image helped to delineate earthquake-induced liquefaction areas that corroborated well with previous studies. The extent of liquefaction varied within and between geomorphological units, which we believe can be attributed to differences in the soil moisture retention capacity within and between the geomorphological units

Surface Energy Flux Estimation in Two Boreal Settings in Alaska Using a Thermal-Based Remote Sensing Model

Recent Arctic warming has led to changes in the hydrological cycle. Circum-Arctic and circumboreal ecosystems are showing evidence of “greening” and “browning” due to temperature warming leading to shrub encroachment, tree mortality and deciduousness. Increases in latent heat flux from increased evapotranspiration rates associated with deciduous-dominated ecosystems may be significant, because deciduous vegetation has extremely high-water use and water storage capacity compared to coniferous and herbaceous plant species. Thus, the impact of vegetation change in boreal ecosystems on regional surface energy balance is a significant knowledge gap that must be addressed to better understand observed trends in water use/availability and tree mortality. To this end, output from a two-source energy balance model (TSEB) with modifications for high latitude boreal ecosystems was evaluated using flux tower measurements and Terra/Aqua MODIS remote sensing data collected over the two largest boreal forest types in Alaska (birch and black spruce). Data under clear and overcast days and from leaf-out to senescence from 2012 to 2016 were used for validation. Using flux tower observations and local model inputs, modifications to the model formulation for soil heat flux, net radiation partitioning, and canopy transpiration were required for the boreal forest. These improvements resulted in a mean absolute percent difference of around 23% for turbulent daytime fluxes when surface temperature from the flux towers was used, similar to errors reported in other studies conducted in warmer climates. Results when surface temperature from Terra/Aqua MODIS estimates were used as model input suggested that these model improvements are pertinent for regional scale applications. Vegetation indices and LAI time-series from the Terra/Aqua MODIS products were confirmed to be appropriate for energy flux estimation in the boreal forest to describe vegetation properties (LAI and green fraction) when field observations are not available. Model improvements for boreal settings identified in this study will be implemented operationally over North America to map surface energy fluxes at regional scales using long time series of remote sensing estimates as part of NOAA’s GOES Evapotranspiration and Drought Information System

Summary of classification error analysis results.

<p>Summary of classification error analysis results.</p

Spatial and numerical distribution of brash ice within Johns Hopkins Inlet.

<p>(a)Distribution of brash ice in Johns Hopkins Inlet on 18 June 2007, as a percentage of each aerial image. Histogram (blue) and probability density functions (PDF) (red) for percent coverage of brash ice (b) and water (c).</p

Workflow from aerial image acquisition to generation of distribution maps and statistics for seals and icebergs.

<p>Workflow from aerial image acquisition to generation of distribution maps and statistics for seals and icebergs.</p