scholarly journals Remote sensing: generation of long‐term kelp bed data sets for evaluation of impacts of climatic variation

Ecology ◽  
2020 ◽  
Vol 101 (7) ◽  
Author(s):  
Sara L. Hamilton ◽  
Tom W. Bell ◽  
James R. Watson ◽  
Kirsten A. Grorud‐Colvert ◽  
Bruce A. Menge
Keyword(s):  
Remote Sensing ◽  
Climatic Variation ◽  
Data Sets ◽  
Kelp Bed

scholarly journals The Swiss snow climatology as seen by reanalyses and further gridded datasets

2021 ◽  
Author(s):  
Monika Goeldi ◽  
Stefanie Gubler ◽  
Christian Steger ◽  
Simon C. Scherrer ◽  
Sven Kotlarski
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Spatiotemporal Variability ◽  
Data Sets ◽  
Data Set ◽  
Climate Services ◽  
Snow Cover Extent ◽  
Snow Water

<p>Snow cover is a key component of alpine environments and knowledge of its spatiotemporal variability, including long-term trends, is vital for a range of dependent systems like winter tourism, hydropower production, etc. Snow cover retreat during the past decades is considered as an important and illustrative indicator of ongoing climate change. As such, the monitoring of surface snow cover and the projection of its future changes play a key role for climate services in alpine regions.</p><p>In Switzerland, a spatially and temporally consistent snow cover climatology that can serve as a reference for both climate monitoring and for future snow cover projections is currently missing. To assess the value and the potential of currently available long term spatial snow data we compare a range of different gridded snow water equivalent (SWE) datasets for the area of Switzerland, including three reanalysis-based products (COSMO-REA6, ERA5, ERA5-Land). The gridded data sets have a horizontal resolution between 1 and 30 km. The performance of the data sets is assessed by comparing them against three reference data sets with different characteristics (station data, a high-resolution 1km snow model that assimilates snow observations, and an optical remote sensing data set). Four different snow indicators are considered (mean SWE, number of snow days, date of maximum SWE, and snow cover extent) in nine different regions of Switzerland and six elevation classes.</p><p>The results reveal high temporal correlations between the individual datasets and, in general, a good performance regarding both countrywide and regional estimates of mean SWE. In individual regions, however, larger biases appear. All data sets qualitatively agree on a decreasing trend of mean SWE during the previous decades particularly at low elevations, but substantial differences can exist. Furthermore, all data sets overestimate the snow cover fraction as provided by the remote sensing reference. In general, reanalysis products capture the general characteristics of the Swiss snow climatology but indicate some distinctive deviations – e.g. like a systematic under- respectively overestimation of the mean snow water equivalent.</p>

Applications of Remotely Sensed Data from the Jornada Basin

2006 ◽  
Author(s):  
Albert Rango ◽  
Jerry Ritchie
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Data Sets ◽  
Remotely Sensed Data ◽  
Sensing Data ◽  
Laser Altimeters ◽  
Jornada Basin ◽  
Multitemporal Remote Sensing

Like other rangelands, little application of remote sensing data for measurement and monitoring has taken place within the Jornada Basin. Although remote sensing data in the form of aerial photographs were acquired as far back as 1935 over portions of the Jornada Basin, little reliance was placed on these data. With the launch of Earth resources satellites in 1972, a variety of sensors have been available to collect remote sensing data. These sensors are typically satellite-based but can be used from other platforms including ground-based towers and hand-held apparatus, low-altitude aircraft, and high-altitude aircraft with various resolutions (now as good as 0.61 m) and spectral capabilities. A multispectral, multispatial, and multitemporal remote sensing approach would be ideal for extrapolating ground-based point and plot knowledge to large areas or landscape units viewed from satellite-based platforms. This chapter details development and applications of long-term remotely sensed data sets that are used in concert with other long-term data to provide more comprehensive knowledge for management of rangeland across this basin and as a template for their use for rangeland management in other regions. In concert with the ongoing Jornada Basin research program of ground measurements, in 1995 we began to collect remotely sensed data from ground, airborne, and satellite platforms to provide spatial and temporal data on the physical and biological state of basin rangeland. Data on distribution and reflectance of vegetation were measured on the ground along preestablished transects with detailed vegetation surveys (cover, composition, and height); with hand-held and yoke-mounted spectral and thermal radiometers; from aircraft flown at different elevations with spectral and thermal radiometers, infrared thermal radiometers, multispectral video, digital imagers, and laser altimeters; and from space with Landsat Thematic Mapper (TM), IKONOS, QuickBird, Terra/Aqua, and other satellite-based sensors. These different platforms (ground, aircraft, and satellite) allow evaluation of landscape patterns and states at different scales. One general use of these measurements will be to quantify the hydrologic budget and plant response to changes in components in the water and energy balance at different scales and to evaluate techniques of scaling data.

scholarly journals Evaluation of Global Surface Water Temperature Data Sets for Use in Passive Remote Sensing of Soil Moisture

2021 ◽  
Vol 13 (10) ◽  
pp. 1872
Author(s):  
Runze Zhang ◽  
Steven Chan ◽  
Rajat Bindlish ◽  
Venkataraman Lakshmi
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Temperature ◽  
Temperature Data ◽  
Data Sets ◽  
Surface Water Temperature ◽  
Passive Remote Sensing ◽  
Water Temperature Data

Inland open water bodies often pose a systematic error source in the passive remote sensing retrievals of soil moisture. Water temperature is a necessary variable used to compute water emissions that is required to be subtracted from satellite observation to yield actual emissions from the land portion, which in turn generates accurate soil moisture retrievals. Therefore, overestimation of soil moisture can often be corrected using concurrent water temperature data in the overall mitigation procedure. In recent years, several data sets of lake water temperature have become available, but their specifications and accuracy have rarely been investigated in the context of passive soil moisture remote sensing on a global scale. For this reason, three lake temperature products were evaluated against in-situ measurements from 2007 to 2011. The data sets include the lake surface water temperature (LSWT) from Global Observatory of Lake Responses to Environmental Change (GloboLakes), the Copernicus Global Land Operations Cryosphere and Water (C-GLOPS), as well as the lake mix-layer temperature (LMLT) from the European Centers for Medium-Range Weather Forecast (ECMWF) ERA5 Land Reanalysis. GloboLakes, C-GLOPS, and ERA5 Land have overall comparable performance with Pearson correlations (R) of 0.87, 0.92 and 0.88 in comparison with in-situ measurements. LSWT products exhibit negative median biases of −0.27 K (GloboLakes) and −0.31 K (C-GLOPS), whereas the median bias of LMLT is 1.56 K. When mapped from their respective native resolutions to a common 9 km Equal-Area Scalable Earth (EASE) Grid 2.0 projection, similar relative performance was observed. LMLT and LSWT data are closer in performance over the 9 km grid cells that exhibit a small range of lake cover fractions (0.05–0.5). Despite comparable relative performance, ERA5 Land shows great advantages in spatial coverage and temporal resolution. In summary, an integrated evaluation on data accuracy, long-term availability, global coverage, temporal resolution, and regular forward processing with modest data latency led us to conclude that LMLT from the ERA5 Land Reanalysis product represents the most optimal path for use in the development of a long-term soil moisture product.

Asian Americans and Pacific Islanders: Employment Issues in the United States

2011 ◽  
Vol 9 (1-2) ◽  
pp. 58-69
Author(s):  
Marlene Kim
Keyword(s):  
United States ◽  
Asian Americans ◽  
The United States ◽  
Current Data ◽  
Pacific Islanders ◽  
Native Hawaiians ◽  
Data Sets ◽  
High Poverty ◽  
Unemployment Rates

Asian Americans and Pacific Islanders (AAPIs) in the United States face problems of discrimination, the glass ceiling, and very high long-term unemployment rates. As a diverse population, although some Asian Americans are more successful than average, others, like those from Southeast Asia and Native Hawaiians and Pacific Islanders (NHPIs), work in low-paying jobs and suffer from high poverty rates, high unemployment rates, and low earnings. Collecting more detailed and additional data from employers, oversampling AAPIs in current data sets, making administrative data available to researchers, providing more resources for research on AAPIs, and enforcing nondiscrimination laws and affirmative action mandates would assist this population.

The problem of ballistic design of the space system Earth remote sensing in stable near-circular sun-synchronous orbits with long-term spacecraft lifetime

2018 ◽  
pp. 3-9
Author(s):  
V. M. Artyushenko ◽  
D. Y. Vinogradov
Keyword(s):  
Remote Sensing ◽  
Target Function ◽  
Normal Operation ◽  
Space Systems ◽  
Light Conditions ◽  
Space System ◽  
Earth Remote Sensing ◽  
Synchronous Orbit ◽  
Favorable Conditions

The article deals with the issues related to the problem of ballistic design of the space system of remote sensing of the Earth on stable near-circular solar-synchronous orbits with long-term existence of spacecraft. We propose a rational method of maintaining a solar-synchronous orbit in given light conditions with prolonged active lifetime of space systems. In solving this problem, the total time of normal operation of the system for a given period of operation, during which the most favorable conditions for the use of spacecraft are provided on the main parts of orbits, is taken as a target function.

Epidemiological Evidence that Maternal Influenza Contributes to the Aetiology of Schizophrenia

1993 ◽  
Vol 163 (4) ◽  
pp. 522-534 ◽  
Author(s):  
W. Adams ◽  
R. E. Kendell ◽  
E. H. Hare ◽  
P. Munk-Jørgensen
Keyword(s):  
Data Sets ◽  
Time Lags ◽  
Epidemiological Evidence ◽  
Intrauterine Development ◽  
Increased Risk ◽  
Schizophrenic Patients ◽  
The Relationship ◽  
Monthly Incidence ◽  
Maternal Influenza

The epidemiological evidence that the offspring of women exposed to influenza in pregnancy are at increased risk of schizophrenia is conflicting. In an attempt to clarify the issue we explored the relationship between the monthly incidence of influenza (and measles) in the general population and the distribution of birth dates of three large series of schizophrenic patients - 16 960 Scottish patients born in 1932–60; 22 021 English patients born in 1921–60; and 18 723 Danish patients born in 1911–65. Exposure to the 1957 epidemic of A2 influenza in midpregnancy was associated with an increased incidence of schizophrenia, at least in females, in all three data sets. We also confirmed the previous report of a statistically significant long-term relationship between patients' birth dates and outbreaks of influenza in the English series, with time lags of - 2 and - 3 months (the sixth and seventh months of pregnancy). Despite several other negative studies by ourselves and others we conclude that these relationships are probably both genuine and causal; and that maternal influenza during the middle third of intrauterine development, or something closely associated with it, is implicated in the aetiology of some cases of schizophrenia.

Budapest airport air quality long-term studies by remote sensing with DOAS and FTIR with focus upon runway emissions

2007 ◽  
Author(s):  
Klaus Schäfer ◽  
Gregor Schürmann ◽  
Carsten Jahn ◽  
Candy Matuse ◽  
Herbert Hoffmann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Quality ◽  
Long Term Studies

scholarly journals Shedding New Light on Mountainous Forest Growth: A Cross-Scale Evaluation of the Effects of Topographic Illumination Correction on 25 Years of Forest Cover Change across Nepal

2021 ◽  
Vol 13 (11) ◽  
pp. 2131
Author(s):  
Jamon Van Den Hoek ◽  
Alexander C. Smith ◽  
Kaspar Hurni ◽  
Sumeet Saksena ◽  
Jefferson Fox
Keyword(s):  
Remote Sensing ◽  
Geographic Distribution ◽  
Classification Accuracy ◽  
Forest Cover ◽  
Forest Growth ◽  
Forest Cover Change ◽  
Scale Evaluation ◽  
Beneficial Effects ◽  
Affect Detection

Accurate remote sensing of mountainous forest cover change is important for myriad social and ecological reasons, but is challenged by topographic and illumination conditions that can affect detection of forests. Several topographic illumination correction (TIC) approaches have been developed to mitigate these effects, but existing research has focused mostly on whether TIC improves forest cover classification accuracy and has usually found only marginal gains. However, the beneficial effects of TIC may go well beyond accuracy since TIC promises to improve detection of low illuminated forest cover and thereby normalize measurements of the amount, geographic distribution, and rate of forest cover change regardless of illumination. To assess the effects of TIC on the extent and geographic distribution of forest cover change, in addition to classification accuracy, we mapped forest cover across mountainous Nepal using a 25-year (1992–2016) gap-filled Landsat time series in two ways—with and without TIC (i.e., nonTIC)—and classified annual forest cover using a Random Forest classifier. We found that TIC modestly increased classifier accuracy and produced more conservative estimates of net forest cover change across Nepal (−5.2% from 1992–2016) TIC. TIC also resulted in a more even distribution of forest cover gain across Nepal with 3–5% more net gain and 4–6% more regenerated forest in the least illuminated regions. These results show that TIC helped to normalize forest cover change across varying illumination conditions with particular benefits for detecting mountainous forest cover gain. We encourage the use of TIC for satellite remote sensing detection of long-term mountainous forest cover change.

Sign in / Sign up

Export Citation Format

Share Document