Low frequency variability in the lower St. Lawrence Estuary

The lower St. Lawrence Estuary is a good example of wide estuaries with a second lateral boundary within several internal Rossby radii. We compare direct measurements from the 1979 lower St. Lawrence estuary mesoscale current meter array with satellite thermal images observed during the same period. The current field appears to show two quasi-steady states: one configuration is characterized by strong outflow along the north shore of the estuary with a transverse front at the mouth. The other current pattern is more typical of estuaries, with inflow along the north shore and outflow along the south shore. Transitions between these configurations are likely to be due to instability of the current field

Exploring the Thermal Microcosms at the Forest Floor : A Case Study of a Temperate Forest

With the expected changes in summer weather due to global warming, knowledge of the microclimatic variability at the forest floor dramatically increased in importance for silviculture, wildfire management and biodiversity issues. Thus, during the warm season in 2014, thermal aspects within a heterogeneous forest were recorded at nine sites and compared to data from a nearby weather station. It was found that soil (−5 cm) and near-surface (0–2 cm) temperatures under shaded conditions stayed remarkably cooler than temporarily or fully radiated spots inside and outside the forest; largest differences occurred in maxima (July: 22.5 °C to 53.5 °C). Solar radiation was found to be the main driver for the strong heating of near-surface microhabitats, which could be reinforced by the vegetation type (moss). The weather station widely reflected the average condition on forest floor, but lacks the biological meaningful temperature extremes. The measurement system (internal versus external sensor) resulted in differences of up to 6 K. The findings underline the importance of old or dense stands for maintaining cool microrefugia. However, also the need for careful selection and analysis of microclimatic measurements in forests, representative for specific microhabitats, under consideration of ground vegetation modifications

Informing Field Management Decisions to Enhance Alfalfa Seed Production Using Remote Sensing

The development rate of alfalfa seed crop depends on both environmental conditions and management decisions. Crop management decisions, such as determining when to release pollinators to optimize pollination, can be informed by the identification of plant development stages from remote sensing data. I first identify what electromagnetic wavelengths are sensitive to alfalfa plant development stages using hyperspectral data. A Random Forest regression is used to determine the best Vegetation Index (VI) to monitor how much of the plant is covered in flower. The results indicate that Blue, Green, and Near-Infrared are the important electromagnetic wavelengths for the VI. Imagery collected throughout this study are converted into a VI time-series for analysis. The analysis involves using a state-space model to estimate the percentage of flower cover from observations. We found that a simple state-space model can be used to estimate, as well as predict, the flower cover percentage

저렴한 근접 표면 센서를 이용한 식생지수, 엽면적 지수, 광합성유효복사량의 흡수률 관찰

학위논문 (석사)-- 서울대학교 대학원 농업생명과학대학 생태조경·지역시스템공학부, 2017. 8. 류영렬.Monitoring vegetation indices, fraction of absorbed photosynthetically active radiation (fPAR) and leaf area index (LAI) has advanced our understanding of biosphere-atmosphere interactions. Although there are continuous observations for each variable, monitoring vegetation indices, fPAR and LAI simultaneously is still lacking. Recent advances of technology provide unprecedented opportunities to integrate various low-cost sensors as an intelligent near surface observation system for monitoring ecosystem structure and functions. In this study, we developed a Smart Surface Sensing System (4S), which can automatically collect, transfer, process and analyze data, and then publish time series results on public-available website. The system is composed of micro-computers, micro-controllers, multi-spectral spectrometers made from Light Emitting Diode (LED), micro cameras, and Internet module. We did intensive tests and calibrations in the lab. Then, we conducted in-situ observations of normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), fraction of absorbed photosynthetically active radiation (fPAR), and leaf area index (LAI) continuously at a rice paddy field during the growing season. NDVI and EVI obtained by 4S showed linear relationships with those from a reference hyperspectrometer (R2 = 0.98NDVI, R2 = 0.96EVI). 4S derived fPAR and LAI were comparable to LAI-2200 and destructive measurements in both magnitude and seasonal trajectory. We retrieved vegetation indices, fPAR and LAI independently and continuously and show that after the reproductive stage, fPAR remained constant, whereas LAI and NDVI decreased continuously after their peak because of non-photosynthetic materials such as grain and yellow leaf. In addition, using vegetation index to estimate fPAR has limitation because the spectral reflectance could not capture the diurnal pattern. On the other hand, fPAR changes abruptly depending on the sky conditions and the amount of light transmitted. We believe that 4S will be useful in the expansion of ecological sensing networks across multiple spatial and temporal scales.1 Introduction 1 2 Method and materials 4 2.1 Development and calibration of 4S 4 2.2 Testing the 4S LED spectrometer 6 2.2.1 Site description 10 2.2.2 4S in-situ 12 2.2.3 Reference data collection 15 2.2.4 Satellite remote sensing data 16 3 Results 17 3.1 Seasonal variation in 4S LED sensor 17 3.2 Seasonal variation in 4S camera sensor 20 3.3 Comparison of NDVI obtained from 4S and satellite with different resolutions 22 4 Discussion 23 4.1 What are the advantages of 4S development 23 4.2 What are the advantages of observing vegetation indices, fPAR and LAI independently 25 4.3 What are the advantages of continuous observation compared to different sensors 29 5 Conclusion 32 6 References 33 7 Abstract (Korean) 38Maste

Toward the detection of permafrost using land-surface temperature mapping

Permafrost is degrading under current warming conditions, disrupting infrastructure, releasing carbon from soils, and altering seasonal water availability. Therefore, it is important to quantitatively map the change in the extent and depth of permafrost. We used satellite images of land-surface temperature to recognize and map the zero curtain, i.e., the isothermal period of ground temperature during seasonal freeze and thaw, as a precursor for delineating permafrost boundaries from remotely sensed thermal-infrared data. The phase transition of moisture in the ground allows the zero curtain to occur when near-surface soil moisture thaws or freezes, and also when ice-rich permafrost thaws or freezes. We propose that mapping the zero curtain is a precursor to mapping permafrost at shallow depths. We used ASTER and a MODIS-Aqua daily afternoon land-surface temperature (LST) timeseries to recognize the zero curtain at the 1-km scale as a "proof of concept. " Our regional mapping of the zero curtain over an area around the 7000 m high volcano Ojos del Salado in Chile suggests that the zero curtain can be mapped over arid regions of the world. It also indicates that surface heterogeneity, snow cover, and cloud cover can hinder the effectiveness of our approach. To be of practical use in many areas, it may be helpful to reduce the topographic and compositional heterogeneity in order to increase the LST accuracy. The necessary finer spatial resolution to reduce these problems is provided by ASTER (90 m).Fil: Batbaatar, Jigjidsurengiin. University of Washington; Estados UnidosFil: Gillespie , Alan R.. University of Washington; Estados UnidosFil: Sletten, Ronald S.. University of Washington; Estados UnidosFil: Mushkin , Amit. University of Washington; Estados UnidosFil: Amit, Rivka. Geological Survey Of Israel; IsraelFil: Trombotto, Dario Tomas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Liu , Lu. University of Washington; Estados UnidosFil: Petrie, Gregg. University of Washington; Estados Unido

A Near-Surface Microstructure Sensor System Used During TOGA COARE. Part II: Turbulence Measurements

New techniques developed for near-surface turbulence measurements during the Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE) employ a difference in spatial scales of turbulence and surface waves. According to this approach, high relative speed of the measurements provides separation of the turbulence and surface wave signals. During the TOGA COARE field studies, highresolution probes of pressure, temperature, conductivity, fluctuation velocity, and acceleration were mounted on the bow of the vessel at a 1.7-m depth in an undisturbed region ahead of the moving vessel. The localization in narrow frequency bands of the vibrations of the bow sensors allows accurate calculation of the dissipation rate. A coherent noise reduction algorithm effectively removes vibration contamination of the velocity dataset. Due to the presence of surface waves and the associated pitching of the vessel, the bow probes ‘‘scanned’’ the near-surface layer of the ocean. Contour plots calculated using the bow signals provide a spatial context for the analysis of near-surface turbulence. A fast-moving free-rising profiler equipped by similar probes sampled the near-surface turbulence during stations. Theory of the three-component electromagnetic velocity sensor and examples of data obtained by bow sensors and free-rising profiler are also presented in this paper

Monitoring vegetation phenology using an infrared-enabled security camera

Sensor-based monitoring of vegetation phenology is being widely used to quantify phenological responses to climate variability and change. Digital repeat photography, in particular, can characterize the seasonality of canopy greenness. However, these data cannot be directly compared to satellite vegetation indices (e.g. NDVI, the normalized difference vegetation index) that require information about vegetation properties at near-infrared (NIR) wavelengths. Here, we develop a new method, using an inexpensive, NIR-enabled camera originally designed for security monitoring, to calculate a “camera NDVI” from sequential visible and visible + NIR photographs. We use a lab experiment for proof-of-concept, and then test the method using a year of data from an ongoing field campaign in a mixed temperate forest. Our analysis shows that the seasonal cycle of camera NDVI is almost identical to that of NDVI measured using narrow-band radiometric instruments, or as observed from space by the MODIS platform. This camera NDVI thus provides different information about the state of the canopy than can be obtained using only visible-wavelength imagery. In addition to phenological monitoring, our method should be useful for a variety of applications, including continuous monitoring of plant stress and quantifying vegetation responses to manipulative treatments in large field experiments.Organismic and Evolutionary Biolog

IMOS national reference stations: A continental-wide physical, chemical and biological coastal observing system

Sustained observations allow for the tracking of change in oceanography and ecosystems, however, these are rare, particularly for the Southern Hemisphere. To address this in part, the Australian Integrated Marine Observing System (IMOS) implemented a network of nine National Reference Stations (NRS). The network builds on one long-term location, where monthly water sampling has been sustained since the 1940s and two others that commenced in the 1950s. In-situ continuously moored sensors and an enhanced monthly water sampling regime now collect more than 50 data streams. Building on sampling for temperature, salinity and nutrients, the network now observes dissolved oxygen, carbon, turbidity, currents, chlorophyll a and both phytoplankton and zooplankton. Additional parameters for studies of ocean acidification and bio-optics are collected at a sub-set of sites and all data is made freely and publically available. Our preliminary results demonstrate increased utility to observe extreme events, such as marine heat waves and coastal flooding; rare events, such as plankton blooms; and have, for the first time, allowed for consistent continental scale sampling and analysis of coastal zooplankton and phytoplankton communities. Independent water sampling allows for cross validation of the deployed sensors for quality control of data that now continuously tracks daily, seasonal and annual variation. The NRS will provide multi-decadal time series, against which more spatially replicated short-term studies can be referenced, models and remote sensing products validated, and improvements made to our understanding of how large-scale, long-term change and variability in the global ocean are affecting Australia's coastal seas and ecosystems. The NRS network provides an example of how a continental scaled observing systems can be developed to collect observations that integrate across physics, chemistry and biology