Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring

Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring projects. Herein, we summarize a project characterizing the change history of Canada’s forested ecosystems with a time series of data representing 1984–2012. Using the Composite2Change approach, we applied spectral trend analysis to annual best-available-pixel (BAP) surface reflectance image composites produced from Landsat TM and ETM+ imagery. A total of 73,544 images were used to produce 29 annual image composites, generating ～400 TB of interim data products and resulting in ～25 TB of annual gap-free reflectance composites and change products. On average, 10% of pixels in the annual BAP composites were missing data, with 86% of pixels having data gaps in two consecutive years or fewer. Change detection overall accuracy was 89%. Change attribution overall accuracy was 92%, with higher accuracy for stand-replacing wildfire and harvest. Changes were assigned to the correct year with an accuracy of 89%. Outcomes of this project provide baseline information and nationally consistent data source to quantify and characterize changes in forested ecosystems. The methods applied and lessons learned build confidence in the products generated and empower others to develop or refine similar satellite-based monitoring projects.     

Application of Aqua MODIS sensor data for estimating chlorophyll a in the turbid Case 2 waters of Lake Erie using bio-optical models

There is considerable interest in accurately estimating water quality parameters in turbid (Case 2) and eutrophic waters such as the Western Basin of Lake Erie (WBLE). Lake Erie is a large, open freshwater body that supports diverse ecosystem, and over 12 million people in the mid-western part of the United States depend on it for drinking water, fisheries, navigational, and recreational purposes. The increasing utilization of the freshwater has deteriorated the water severely and currently the lake is experiencing recurring harmful algal blooms (HABs). Improving the water quality of Lake Erie requires the use of robust monitoring tools that help water quality managers understand sources and pathways of influxes that trigger HABs. Satellite-based remote sensing sensor such as the moderate resolution imaging spectroradiometer (MODIS) may provide frequent and synoptic view of the water quality indices. In this study, data set from field measurements was used to evaluate the performance of 14 existing ocean color algorithms. Results indicated that MODIS data consistently underestimated the chlorophyll a concentrations in the WBLE, with the largest source of errors from dissolved organic matter and xanthophyll accessory pigments in this data set. Most of the global algorithms, including OC4v4 and the Baltic model, generated near-identical statistical parameters with an average R² of ~0.57 and RMSE ~2.9 μg/l. MODIS performed poorly (R² ~0.18) when its NIR/red bands were used. A slightly improved model was developed using similar band ratio approach generating R² of ~0.62 and RMSE ~1.8 μg/l.     

Dissolution rates of talc as a function of solution composition, pH and temperature

Steady-state talc dissolution rates, at far-from-equilibrium conditions, were measured as a function of aqueous silica and magnesium activity, pH from 1 to 10.6, and temperature from 25 to 150 °C. All rates were measured in mixed flow reactors and exhibited stoichiometric or close to stoichiometric dissolution. All measured rates at pH > 2 obtained at a fixed ionic strength of 0.02 M can be described to within experimental uncertainty using

     

Radio-continuum study of the nearby sculptor group galaxies. Part 3: NGC 7793 at λ=12.2, 6 and 3 cm

We re-examine a series of archived centimetre radio-continuum observations (λ=16, 6 and 3 cm) focusing on NGC?7793 using the Australia Telescope Compact Array. These new images are both very sensitive (σ=0.011 mJy/beam) and feature reasonably high angular resolution (down to <3″). Using these images, a total of 76 discrete radio sources are identified, of which 57 have been classified. We also studied the radio component of the micro-quasar NGC7793-S26 which shows two distinct regions of somewhat steep spectral index (α) between ?0.3 and ?0.7.     

Farm-scale adaptation and vulnerability to environmental stresses: Insights from winegrowing in Northern California

The wine industry is increasingly recognized as especially vulnerable to climate change due to the climate sensitivity of both winegrape yields and quality, making it an important model system for the agricultural impacts of global changes. However, agricultural production is strongly influenced by the management decisions of growers, including their practices to modify the microclimate experienced by the growing crop; these adaptations have not been studied at the vineyard level, where managers on the ground are on the front lines of responding to global change.We conducted 20 in-depth interviews with winegrowers to examine farm-scale adaptive responses to environmental stresses, to understand the views and motivations of agricultural managers, and to explore adaptive capacity in practice. We found that growers tend to respond to stresses individually rather than collectively, except when facing severe, unfamiliar pests and diseases. Responses may be reactive or anticipatory; most anticipatory strategies have been short-term, in response to imminent threats. Growers tend to rely on their own experience to guide their management decisions, which may offer poor guidance under novel climate regimes. From using a Vulnerability Scoping Diagram, we find that changing exposure (vineyard location) and sensitivity (planting choices such as vine variety) have the biggest impact on reducing vulnerability, but that adaptations in growing or processing the crop in the vineyard and winery are easier to implement, much more commonly undertaken, and may also offer substantial adaptive capacity. Understanding the context of adaptations, as well as the decision-making processes motivating them, is important for understanding responses to global change.These findings highlight some innovations in adapting to global change, as well as some of the barriers, and point to the need for strategic investments to enhance agricultural resilience to climate change. In particular, strategies to enhance both effective and easy to implement farming adaptations, as well as broader-scale anticipatory, collective responses, could reduce vulnerability in the context of climate change.     

Historical discharge measurements on the Middle Mississippi River,USA: no basis for ‘changing history’

This study tests the hypothesis that historical float‐based discharge measurements on the Mississippi River systematically over‐stated actual flood flows by 10% to > 30% relative to measurements using current meters. This assertion has been repeated over the past 25 years and recently has been used to adjust historical discharges used for flood‐frequency analysis. This study tests the hypothesis above using 2150 historical discharge measurements digitized from the three principal gauging stations on the Middle Mississippi River (MMR): data that include 626 float‐based discharges and 1516 meter‐based discharges, including 122 paired measurements. Multiple comparative tests show that the hypothesis above cannot be supported; if anything, the float‐based measurements slightly underestimate flows (not over‐estimate) over a broad range of discharges up to large floods. In response to the purported data bias above (‘changing history’; Dieckmann RJ, Dyhouse GR. 1998. Changing history at St. Louis—adjusting historic flows for frequency analysis. First Federal Inter‐Agency Hydrologic Modeling Conference, April 20–22, 1998. Las Vegas, NV; 4·31–4·36), historical flood discharges on the MMR have been modified, most by 10–20% and several by > 30%. These altered discharges are now being promulgated, in particular, through the Upper Mississippi River System Flow Frequency Study (UMRSFFS). New flow frequencies, flood profiles, and new flood maps from the UMRSFFS may significantly underestimate the actual flood hazard on the MMR if the original hydrologic data have been erroneously altered on the basis of an assumption of data bias. Copyright © 2010 John Wiley & Sons, Ltd.