24 research outputs found
A satellite-based snow cover climatology (1985–2011) for the European Alps derived from AVHRR data
Seasonal snow cover is of great environmental and socio-economic importance
for the European Alps. Therefore a high priority has been assigned to
quantifying its temporal and spatial variability. Complementary to land-based
monitoring networks, optical satellite observations can be used to derive
spatially comprehensive information on snow cover extent. For understanding
long-term changes in alpine snow cover extent, the data acquired by the
Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the
National Oceanic and Atmospheric Association (NOAA) and Meteorological
Operational satellite (MetOp) platforms offer a unique source of information.
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In this paper, we present the first space-borne 1 km snow extent climatology
for the Alpine region derived from AVHRR data over the period 1985–2011. The
objective of this study is twofold: first, to generate a new set of
cloud-free satellite snow products using a specific cloud gap-filling
technique and second, to examine the spatiotemporal distribution of snow
cover in the European Alps over the last 27 yr from the satellite
perspective. For this purpose, snow parameters such as snow onset day, snow
cover duration (SCD), melt-out date and the snow cover area percentage (SCA)
were employed to analyze spatiotemporal variability of snow cover over the
course of three decades. On the regional scale, significant trends were found
toward a shorter SCD at lower elevations in the south-east and south-west.
However, our results do not show any significant trends in the monthly mean
SCA over the last 27 yr. This is in agreement with other research findings
and may indicate a deceleration of the decreasing snow trend in the Alpine
region. Furthermore, such data may provide spatially and temporally
homogeneous snow information for comprehensive use in related research fields
(i.e., hydrologic and economic applications) or can serve as a reference for
climate models
Use of automated change detection and VGI sources for identifying and validating urban land use change
© 2020, by the authors. Land use and land cover (LULC) mapping is often undertaken by national mapping agencies, where these LULC products are used for different types of monitoring and reporting applications. Updating of LULC databases is often done on a multi-year cycle due to the high costs involved, so changes are only detected when mapping exercises are repeated. Consequently, the information on LULC can quickly become outdated and hence may be incorrect in some areas. In the current era of big data and Earth observation, change detection algorithms can be used to identify changes in urban areas, which can then be used to automatically update LULC databases on a more continuous basis. However, the change detection algorithm must be validated before the changes can be committed to authoritative databases such as those produced by national mapping agencies. This paper outlines a change detection algorithm for identifying construction sites, which represent ongoing changes in LU, developed in the framework of the LandSense project. We then use volunteered geographic information (VGI) captured through the use of mapathons from a range of different groups of contributors to validate these changes. In total, 105 contributors were involved in the mapathons, producing a total of 2778 observations. The 105 contributors were grouped according to six different user-profiles and were analyzed to understand the impact of the experience of the users on the accuracy assessment. Overall, the results show that the change detection algorithm is able to identify changes in residential land use to an adequate level of accuracy (85%) but changes in infrastructure and industrial sites had lower accuracies (57% and 75 %, respectively), requiring further improvements. In terms of user profiles, the experts in LULC from local authorities, researchers in LULC at the French national mapping agency (IGN), and first-year students with a basic knowledge of geographic information systems had the highest overall accuracies (86.2%, 93.2%, and 85.2%, respectively). Differences in how the users approach the task also emerged, e.g., local authorities used knowledge and context to try to identify types of change while those with no knowledge of LULC (i.e., normal citizens) were quicker to choose 'Unknown' when the visual interpretation of a class was more difficult
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Amplified surface temperature response of cold, deep lakes to inter-annual air temperature variability
Summer lake surface water temperatures (LSWTs) have previously been shown to respond more rapidly to climatic warming compared to local summer surface air temperatures (SATs). In a global- scale analysis, we explore the factors underpinning the observation of an amplified response of summer LSWT to SAT variability using 20 years of satellite-derived temperatures from 144 lakes. We demonstrate that the degree of amplification in inter-annual summer LSWT is variable, and is greater for cold lakes (e.g. high latitude and high altitude), which are characterised by a short warming season, and deep lakes, that exhibit long correlation timescales of temperature anomalies due to increased thermal inertia. Such lakes are more likely to display responses in excess of local inter-annual summer SAT variability. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems, so quantifying this amplified response at a global scale is important
The state of the Martian climate
60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes
Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling
Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use
of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different
pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite
observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and
Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the
Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim
was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from
SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial
resolution.
CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx
output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols
(POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST_1 to CRST_4) to be used in AOD
quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column.
The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology
provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May
2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the
integration of these two different types of the data in order to improve air pollution assessment
Erprobung, Vergleich, Weiterentwicklung und Beurteilung von Genotoxizitaetstests fuer Oberflaechenwasser. Teilprojekt 9: Weiterentwicklung und Anwendung des Ames-Tests als Referenzverfahren Abschlussbericht
SIGLEAvailable from TIB Hannover: F00B264+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung und Forschung (BMBF), Bonn (Germany)DEGerman
Erprobung, Vergleich, Weiterentwicklung und Beurteilung von Genotoxizitaetstests fuer Oberflaechenwasser. Teilprojekt 9: Weiterentwicklung und Anwendung des Ames-Tests als Referenzverfahren Abschlussbericht
SIGLEAvailable from TIB Hannover: F00B264+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung und Forschung (BMBF), Bonn (Germany)DEGerman