18,787 research outputs found
Breaking new ground in mapping human settlements from space -The Global Urban Footprint-
Today 7.2 billion people inhabit the Earth and by 2050 this number will have
risen to around nine billion, of which about 70 percent will be living in
cities. Hence, it is essential to understand drivers, dynamics, and impacts of
the human settlements development. A key component in this context is the
availability of an up-to-date and spatially consistent map of the location and
distribution of human settlements. It is here that the Global Urban Footprint
(GUF) raster map can make a valuable contribution. The new global GUF binary
settlement mask shows a so far unprecedented spatial resolution of 0.4 arcsec
() that provides - for the first time - a complete picture of the
entirety of urban and rural settlements. The GUF has been derived by means of a
fully automated processing framework - the Urban Footprint Processor (UFP) -
that was used to analyze a global coverage of more than 180,000 TanDEM-X and
TerraSAR-X radar images with 3m ground resolution collected in 2011-2012.
Various quality assessment studies to determine the absolute GUF accuracy based
on ground truth data on the one hand and the relative accuracies compared to
established settlements maps on the other hand, clearly indicate the added
value of the new global GUF layer, in particular with respect to the
representation of rural settlement patterns. Generally, the GUF layer achieves
an overall absolute accuracy of about 85\%, with observed minima around 65\%
and maxima around 98 \%. The GUF will be provided open and free for any
scientific use in the full resolution and for any non-profit (but also
non-scientific) use in a generalized version of 2.8 arcsec ().
Therewith, the new GUF layer can be expected to break new ground with respect
to the analysis of global urbanization and peri-urbanization patterns,
population estimation or vulnerability assessment
Harmonization of space-borne infra-red sensors measuring sea surface temperature
Sea surface temperature (SST) is observed by a constellation of sensors, and SST retrievals
are commonly combined into gridded SST analyses and climate data records (CDRs). Differential
biases between SSTs from different sensors cause errors in such products, including feature artefacts.
We introduce a new method for reducing differential biases across the SST constellation, by reconciling
the brightness temperature (BT) calibration and SST retrieval parameters between sensors. We use the
Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature
Radiometer (SLSTR) as reference sensors, and the Advanced Very High Resolution Radiometer
(AVHRR) of the MetOp-A mission to bridge the gap between these references. Observations across a
range of AVHRR zenith angles are matched with dual-view three-channel skin SST retrievals from
the AATSR and SLSTR. These skin SSTs act as the harmonization reference for AVHRR retrievals
by optimal estimation (OE). Parameters for the harmonized AVHRR OE are iteratively determined,
including BT bias corrections and observation error covariance matrices as functions of water-vapor
path. The OE SSTs obtained from AVHRR are shown to be closely consistent with the reference sensor
SSTs. Independent validation against drifting buoy SSTs shows that the AVHRR OE retrieval is stable
across the reference-sensor gap. We discuss that this method is suitable to improve consistency across
the whole constellation of SST sensors. The approach will help stabilize and reduce errors in future
SST CDRs, as well as having application to other domains of remote sensing
Views from the coalface: chemo-sensors, sensor networks and the semantic sensor web
Currently millions of sensors are being deployed in sensor networks across the world. These networks generate vast quantities of heterogeneous data across various levels of spatial and temporal granularity. Sensors range from single-point in situ sensors to remote satellite sensors which can cover the globe. The semantic sensor web in principle should allow for the unification of the web with the real-word. In this position paper, we discuss the major challenges to this unification from the perspective of sensor developers (especially chemo-sensors) and integrating sensors data in real-world deployments. These challenges include: (1) identifying the quality of the data; (2) heterogeneity of data sources and data transport methods; (3) integrating data streams from different sources and modalities (esp. contextual information), and (4) pushing intelligence to the sensor level
Evaluation of a global soil moisture product from finer spatial resolution sar data and ground measurements at Irish sites
In the framework of the European Space Agency Climate Change Initiative, a global, almost daily, soil moisture (SM) product is being developed from passive and active satellite microwave sensors, at a coarse spatial resolution. This study contributes to its validation by using finer spatial resolution ASAR Wide Swath and in situ soil moisture data taken over three sites in Ireland, from 2007 to 2009. This is the first time a comparison has been carried out between three sets of independent observations from different sensors at very different spatial resolutions for such a long time series. Furthermore, the SM spatial distribution has been investigated at the ASAR scale within each Essential Climate Variable (ECV) pixel, without adopting any particular model or using a densely distributed network of in situ stations. This approach facilitated an understanding of the extent to which geophysical factors, such as soil texture, terrain composition and altitude, affect the retrieved ECV SM product values in temperate grasslands. Temporal and spatial variability analysis provided high levels of correlation (p < 0.025) and low errors between the three datasets, leading to confidence in the new ECV SM global product, despite limitations in its ability to track the driest and wettest conditions
Unmanned Aerial Systems for Wildland and Forest Fires
Wildfires represent an important natural risk causing economic losses, human
death and important environmental damage. In recent years, we witness an
increase in fire intensity and frequency. Research has been conducted towards
the development of dedicated solutions for wildland and forest fire assistance
and fighting. Systems were proposed for the remote detection and tracking of
fires. These systems have shown improvements in the area of efficient data
collection and fire characterization within small scale environments. However,
wildfires cover large areas making some of the proposed ground-based systems
unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial
Systems (UAS) were proposed. UAS have proven to be useful due to their
maneuverability, allowing for the implementation of remote sensing, allocation
strategies and task planning. They can provide a low-cost alternative for the
prevention, detection and real-time support of firefighting. In this paper we
review previous work related to the use of UAS in wildfires. Onboard sensor
instruments, fire perception algorithms and coordination strategies are
considered. In addition, we present some of the recent frameworks proposing the
use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more
efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at:
https://doi.org/10.3390/drones501001
The function of remote sensing in support of environmental policy
Limited awareness of environmental remote sensing’s potential ability to support environmental policy development constrains the technology’s utilization. This paper reviews the potential of earth observation from the perspective of environmental policy. A literature review of “remote sensing and policy” revealed that while the number of publications in this field increased almost twice as rapidly as that of remote sensing literature as a whole (15.3 versus 8.8% yr−1), there is apparently little academic interest in the societal contribution of environmental remote sensing. This is because none of the more than 300 peer reviewed papers described actual policy support. This paper describes and discusses the potential, actual support, and limitations of earth observation with respect to supporting the various stages of environmental policy development. Examples are given of the use of remote sensing in problem identification and policy formulation, policy implementation, and policy control and evaluation. While initially, remote sensing contributed primarily to the identification of environmental problems and policy implementation, more recently, interest expanded to applications in policy control and evaluation. The paper concludes that the potential of earth observation to control and evaluate, and thus assess the efficiency and effectiveness of policy, offers the possibility of strengthening governance
HATSouth: a global network of fully automated identical wide-field telescopes
HATSouth is the world's first network of automated and homogeneous telescopes
that is capable of year-round 24-hour monitoring of positions over an entire
hemisphere of the sky. The primary scientific goal of the network is to
discover and characterize a large number of transiting extrasolar planets,
reaching out to long periods and down to small planetary radii. HATSouth
achieves this by monitoring extended areas on the sky, deriving high precision
light curves for a large number of stars, searching for the signature of
planetary transits, and confirming planetary candidates with larger telescopes.
HATSouth employs 6 telescope units spread over 3 locations with large longitude
separation in the southern hemisphere (Las Campanas Observatory, Chile; HESS
site, Namibia; Siding Spring Observatory, Australia). Each of the HATSouth
units holds four 0.18m diameter f/2.8 focal ratio telescope tubes on a common
mount producing an 8.2x8.2 arcdeg field, imaged using four 4Kx4K CCD cameras
and Sloan r filters, to give a pixel scale of 3.7 arcsec/pixel. The HATSouth
network is capable of continuously monitoring 128 square arc-degrees. We
present the technical details of the network, summarize operations, and present
weather statistics for the 3 sites. On average each of the 6 HATSouth units has
conducted observations on ~500 nights over a 2-year time period, yielding a
total of more than 1million science frames at 4 minute integration time, and
observing ~10.65 hours per day on average. We describe the scheme of our data
transfer and reduction from raw pixel images to trend-filtered light curves and
transiting planet candidates. Photometric precision reaches ~6 mmag at 4-minute
cadence for the brightest non-saturated stars at r~10.5. We present detailed
transit recovery simulations to determine the expected yield of transiting
planets from HATSouth. (abridged)Comment: 25 pages, 11 figures, 1 table, submitted to PAS
Development and Implementation - DSIF Development
Antenna system instrumentation, phase modulator designs, control systems for transmitter and motor generator, and related DSIF development
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