SENSECO: Optical synergies for spatiotemporal sensing of scalable ecophysiological traits. (COST Action CA17134)

2020 ◽  
Author(s):  
Javier Pacheco-Labrador ◽  
Helge Aasen ◽  
Agnieszka Bialek ◽  
Marco Celesti ◽  
Maria Pilar Cendrero-Mateo ◽  
...  
Keyword(s):  
Optical Sensors ◽  
Spatial Information ◽  
Environmental Changes ◽  
European Space Agency ◽  
Analytical Techniques ◽  
Terrestrial Ecosystems ◽  
Sensor Data ◽  
Cost Action ◽  
Ecophysiological Traits ◽  
Recent Advances

<p>Vegetation in terrestrial ecosystems controls a significant part of the gas and energy exchanges at the atmosphere-biosphere-pedosphere interface. Continuous spatial information about vegetation status (biophysical properties) and photosynthetic rates are needed to understand and model the responses of terrestrial ecosystems to environmental changes induced by human activity. This information is therefore critical to climate change monitoring, adaptation and mitigation. </p><p>Earth Observation (EO) allows the collection spatially continuous Earths surface reflectance at ecologically relevant scales. Recent advances in EO are bringing the chance to retrieve from space a subtle emission from vegetation originated at the core of the photosynthetic machinery of the plants: the chlorophyll sun-induced fluorescence (F). The upcoming Fluorescence Explorer (FLEX) mission from the European Space Agency (ESA) will be the first EO mission dedicated to the exploitation of this signal for the study of vegetation photosynthetic activity. FLEX will fly in tandem with Sentinel-3 (S3). This multi-sensor approach brings new opportunities to test the potential of synergistic use of multi-source data to capture scalable ecophysiological traits. The information provided by FLEX-S3 tandem together with observations from other Copernicus missions will boost the development of novel data analytical techniques, still to be realized. The development of these techniques will requires the combination of EO data with drone-based proximal sensing and tower-based eddy covariance (EC) observations. Together with modeling, this approach will allow solving critical and still open spatiotemporal scaling questions. Recent advances allow nowadays the synergistic use, processing and interpretation of data provided by multiple optical sensors featuring different spatial, spectral and temporal resolutions. The implementation of these techniques requires of the collaboration of the remote sensing, EC, and modeling communities; this need has motivated the development of a network within recently approved COST Action SENSECO. </p><p>SENSECO aims to ensure the multi-scale compatibility of EO measurements and protocols dedicated to the study of ecophysiological properties. This is needed to enable the synergistic use of multi-sensor data, as well as to ensure the transfer and exchange of knowledge on scaling approaches within the European communities. SENSECO achieves his objectives via dedicated expert workshops, training schools and short term scientific missions.</p>

scholarly journals Combined use of SAR and optical data for environmental assessments around refugee camps in semiarid landscapes

2015 ◽  
Vol XL-7/W3 ◽  
pp. 777-782 ◽  
Author(s):  
A. Braun ◽  
V. Hochschild
Keyword(s):  
Land Cover ◽  
Optical Sensors ◽  
Land Degradation ◽  
Spatial Information ◽  
Environmental Changes ◽  
Optical Data ◽  
Landsat 8 ◽  
Refugee Camps ◽  
Internally Displaced ◽  
Regional Conflicts

Over 15 million people were officially considered as refugees in the year 2012 and another 28 million as internally displaced people (IDPs). Natural disasters, climatic and environmental changes, violent regional conflicts and population growth force people to migrate in all parts of this world. This trend is likely to continue in the near future, as political instabilities increase and land degradation progresses. <br><br> EO4HumEn aims at developing operational services to support humanitarian operations during crisis situations by means of dedicated geo-spatial information products derived from Earth observation and GIS data. The goal is to develop robust, automated methods of image analysis routines for population estimation, identification of potential groundwater extraction sites and monitoring the environmental impact of refugee/IDP camps. <br><br> This study investigates the combination of satellite SAR data with optical sensors and elevation information for the assessment of the environmental conditions around refugee camps. In order to estimate their impact on land degradation, land cover classifications are required which target dynamic landscapes. We performed a land use / land cover classification based on a random forest algorithm and 39 input prediction rasters based on Landsat 8 data and additional layers generated from radar texture and elevation information. The overall accuracy was 92.9 %, while optical data had the highest impact on the final classification. By analysing all combinations of the three input datasets we additionally estimated their impact on single classification outcomes and land cover classes.

scholarly journals Shining light on recent advances in microbial mercury cycling

FACETS ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 858-879 ◽  
Author(s):  
Daniel S. Grégoire ◽  
Alexandre J. Poulain
Keyword(s):  
Conceptual Framework ◽  
Environmental Changes ◽  
Terrestrial Ecosystems ◽  
Mercury Cycling ◽  
Recent Advances ◽  
Oxidation Reduction ◽  
New Findings ◽  
The Face ◽  
Global Pollutant ◽  
Analytical Tools

Mercury (Hg) is a global pollutant emitted primarily as gaseous Hg0 that is deposited in aquatic and terrestrial ecosystems following its oxidation to HgII. From that point, microbes play a key role in determining Hg’s fate in the environment by participating in sequestration, oxidation, reduction, and methylation reactions. A wide diversity of chemotrophic and phototrophic microbes occupying oxic and anoxic habitats are known to participate directly in Hg cycling. Over the last few years, new findings have come to light that have greatly improved our mechanistic understanding of microbe-mediated Hg cycling pathways in the environment. In this review, we summarize recent advances in microbially mediated Hg cycling and take the opportunity to compare the relatively well-studied chemotrophic pathways to poorly understood phototrophic pathways. We present how the use of genomic and analytical tools can be used to understand Hg transformations and the physiological context of recently discovered cometabolic Hg transformations supported in anaerobes and phototrophs. Finally, we propose a conceptual framework that emphasizes the role that phototrophs play in environmental Hg redox cycling and the importance of better characterizing such pathways in the face of the environmental changes currently underway.

scholarly journals Deep Belief Network for Spectral–Spatial Classification of Hyperspectral Remote Sensor Data

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 204 ◽  
Author(s):  
Chenming Li ◽  
Yongchang Wang ◽  
Xiaoke Zhang ◽  
Hongmin Gao ◽  
Yao Yang ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Optical Sensors ◽  
Spatial Information ◽  
Hyperspectral Image ◽  
Deep Belief Network ◽  
Fine Tuning ◽  
Sensor Data ◽  
Belief Network

With the development of high-resolution optical sensors, the classification of ground objects combined with multivariate optical sensors is a hot topic at present. Deep learning methods, such as convolutional neural networks, are applied to feature extraction and classification. In this work, a novel deep belief network (DBN) hyperspectral image classification method based on multivariate optical sensors and stacked by restricted Boltzmann machines is proposed. We introduced the DBN framework to classify spatial hyperspectral sensor data on the basis of DBN. Then, the improved method (combination of spectral and spatial information) was verified. After unsupervised pretraining and supervised fine-tuning, the DBN model could successfully learn features. Additionally, we added a logistic regression layer that could classify the hyperspectral images. Moreover, the proposed training method, which fuses spectral and spatial information, was tested over the Indian Pines and Pavia University datasets. The advantages of this method over traditional methods are as follows: (1) the network has deep structure and the ability of feature extraction is stronger than traditional classifiers; (2) experimental results indicate that our method outperforms traditional classification and other deep learning approaches.

scholarly journals Demographic history and genomic response to environmental changes in a rapid radiation of wild rats

2021 ◽  
Author(s):  
Deyan Ge ◽  
Anderson Feijó ◽  
Zhixin Wen ◽  
Alexei V Abramov ◽  
Liang Lu ◽  
...  
Keyword(s):  
Environmental Changes ◽  
Demographic History ◽  
Terrestrial Ecosystems ◽  
Tibet Plateau ◽  
Global Changes ◽  
Rapid Radiation ◽  
Protein Functions ◽  
Wild Rats ◽  
Qinghai Tibet Plateau ◽  
Genomic Response

Abstract For organisms to survive and prosper in a harsh environment, particularly under rapid climate change, poses tremendous challenges. Recent studies have highlighted the continued loss of megafauna in terrestrial ecosystems and the subsequent surge of small mammals, such as rodents, bats, lagomorphs, and insectivores. However, the ecological partitioning of these animals will likely lead to large variation in their responses to environmental change. In the present study, we investigated the evolutionary history and genetic adaptations of white-bellied rats (Niviventer Marshall, 1976), which are widespread in the natural terrestrial ecosystems in Asia but also known as important zoonotic pathogen vectors and transmitters. The southeastern Qinghai-Tibet Plateau (QHTP) was inferred as the origin center of this genus, with parallel diversification in temperate and tropical niches. Demographic history analyses from mitochondrial and nuclear sequences of Niviventer demonstrated population size increases and range expansion for species in Southeast Asia, and habitat generalists elsewhere. Unexpectedly, population increases were seen in N. eha, which inhabits the highest elevation among Niviventer species. Genome scans of nuclear exons revealed that among the congeneric species, N. eha has the largest number of positively selected genes. Protein functions of these genes are mainly related to olfaction, taste and tumor suppression. Extensive genetic modification presents a major strategy in response to global changes in these alpine species.

scholarly journals Overview of Popular Techniques of Raman Spectroscopy and Their Potential in the Study of Plant Tissues

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1537
Author(s):  
Aneta Saletnik ◽  
Bogdan Saletnik ◽  
Czesław Puchalski
Keyword(s):  
Raman Spectroscopy ◽  
Cell Walls ◽  
Structural Changes ◽  
Spatial Information ◽  
Technological Development ◽  
Analytical Techniques ◽  
High Sensitivity ◽  
Plant Tissues ◽  
Wide Range ◽  
Identification Technique

Raman spectroscopy is one of the main analytical techniques used in optical metrology. It is a vibration, marker-free technique that provides insight into the structure and composition of tissues and cells at the molecular level. Raman spectroscopy is an outstanding material identification technique. It provides spatial information of vibrations from complex biological samples which renders it a very accurate tool for the analysis of highly complex plant tissues. Raman spectra can be used as a fingerprint tool for a very wide range of compounds. Raman spectroscopy enables all the polymers that build the cell walls of plants to be tracked simultaneously; it facilitates the analysis of both the molecular composition and the molecular structure of cell walls. Due to its high sensitivity to even minute structural changes, this method is used for comparative tests. The introduction of new and improved Raman techniques by scientists as well as the constant technological development of the apparatus has resulted in an increased importance of Raman spectroscopy in the discovery and defining of tissues and the processes taking place in them.

scholarly journals Volunteered Geographic Information: Interpretation, Visualisation and Social Computing (VGIscience)

2018 ◽  
Vol 1 ◽  
pp. 1-5 ◽  
Author(s):  
Dirk Burghardt ◽  
Wolfgang Nejdl ◽  
Jochen Schiewe ◽  
Monika Sester
Keyword(s):  
Visual Analysis ◽  
Spatial Information ◽  
Volunteered Geographic Information ◽  
Scientific Basis ◽  
Geographic Information ◽  
Sensor Data ◽  
Short Paper ◽  
German Research Foundation ◽  
Knowledge Presentation ◽  
Large Heterogeneity

In the past years Volunteered Geographic Information (VGI) has emerged as a novel form of user-generated content, which involves active generation of geo-data for example in citizen science projects or during crisis mapping as well as the passive collection of data via the user’s location-enabled mobile devices. In addition there are more and more sensors available that detect our environment with ever greater detail and dynamics. These data can be used for a variety of applications, not only for the solution of societal tasks such as in environment, health or transport fields, but also for the development of commercial products and services. The interpretation, visualisation and usage of such multi-source data is challenging because of the large heterogeneity, the differences in quality, the high update frequencies, the varying spatial-temporal resolution, subjective characteristics and low semantic structuring.<br> Therefore the German Research Foundation has launched a priority programme for the next 3&amp;ndash;6 years which will support interdisciplinary research projects. This priority programme aims to provide a scientific basis for raising the potential of VGI- and sensor data. Research questions described more in detail in this short paper span from the extraction of spatial information, to the visual analysis and knowledge presentation, taking into account the social context while collecting and using VGI.

Classification of Landscape Sensitivity in the Territory of Cremona

2013 ◽  
Vol 4 (3) ◽  
pp. 63-79 ◽  
Author(s):  
Pier Luigi Paolillo ◽  
Umberto Baresi ◽  
Roberto Bisceglie
Keyword(s):  
Spatial Information ◽  
Analytical Techniques ◽  
Urban System ◽  
Multidimensional Analysis ◽  
Environmental Constraints ◽  
Synthetic Indicators ◽  
Territorial Planning ◽  
Landscape Sensitivity ◽  
The Right

Centrality of landscape, in territorial planning, has been influencing for years, the testing of innovative analytical techniques aimed to gather peculiarities of urban and suburban context. The advent of Spatial Information System created the possibility to produce more detailed studies analyzing a lot of information dealing with territorial phenomena of crucial importance in spatial planning. The development of analytical systems based on multidimensional analysis may represent the right way to synthesize different phenomena that interact locally, in order to obtain the intrinsic sensitivity of a specific landscape as a result. In the case of Cremona Urban Variant, the production of thematic maps has allowed the construction of six synthetic indicators, dealing with specific aspects of Cremona landscape. The indicators are: i) insularisation of non – built spaces, ii) morphological / structural values, iii) perceptual landscape aspects, iv) permanence of urban system, v) degree of imperativeness of environmental constraints, vi) integrity of land use.

scholarly journals The Infrared Space Observatory

1990 ◽  
Vol 123 ◽  
pp. 205-214 ◽  
Author(s):  
C.J. Cesarsky ◽  
M.F. Kessler
Keyword(s):  
Optical Sensors ◽  
European Space Agency ◽  
Space Observatory ◽  
Infrared Space Observatory ◽  
Long Wavelength ◽  
Space Agency ◽  
Pointing Accuracy ◽  
Funded Project ◽  
Astronomical Satellite ◽  
The Universe

AbstractThe Infrared Space Observatory (ISO), a fully approved and funded project of the European Space Agency (ESA), is an astronomical satellite, which will operate at wavelengths from 3–200 μm. ISO will provide astronomers with a unique facility of unprecedented sensitivity for a detailed exploration of the universe ranging from objects in the solar system right out to distant extragalactic sources. The satellite essentially consists of a large cryostat containing at launch about 2300 litres of superfluid helium to maintain the Ritchey-Chrétien telescope, the scientific instruments and the optical baffles at temperatures between 2K and 8K. The telescope has a 60-cm diameter primary mirror and is diffraction-limited at a wavelength of 5μm. A pointing accuracy of a few arc seconds is provided by a three-axis-stabilisation system consisting of reaction wheels, gyros and optical sensors. ISO’s instrument complement consists of four instruments, namely: a photo-polarimeter (3–200μm), a camera (3–17μm), a short wavelength spectrometer (3–45μm) and a long wavelength spectrometer (45–180μm). These instruments are being built by international consortia of scientific institutes and will be delivered to ESA for in-orbit operations. ISO will be launched in 1993 by an Ariane 4 into an elliptical orbit (apogee 70000km and perigee 1000km) and will be operational for at least 18 months. In keeping with ISO’s role as an observatory, two-thirds of its observing time will be made available to the european and american astronomical community.

scholarly journals Coastal Dune Vegetation Mapping Using a Multispectral Sensor Mounted on an UAS

2019 ◽  
Vol 11 (15) ◽  
pp. 1814 ◽  
Author(s):  
Suo ◽  
McGovern ◽  
Gilmer
Keyword(s):  
High Resolution ◽  
Data Processing ◽  
Spatial Patterns ◽  
Near Infrared ◽  
Environmental Changes ◽  
Vegetation Mapping ◽  
Coastal Dune ◽  
Sensor Data ◽  
Surface Model ◽  
Dune Vegetation

Vegetation mapping, identifying the type and distribution of plant species, is important for analysing vegetation dynamics, quantifying spatial patterns of vegetation evolution, analysing the effects of environmental changes and predicting spatial patterns of species diversity. Such analysis can contribute to the development of targeted land management actions that maintain biodiversity and ecological functions. This paper presents a methodology for 3D vegetation mapping of a coastal dune complex using a multispectral camera mounted on an unmanned aerial system with particular reference to the Buckroney dune complex in Co. Wicklow, Ireland. Unmanned aerial systems (UAS), also known as unmanned aerial vehicles (UAV) or drones, have enabled high-resolution and high-accuracy ground-based data to be gathered quickly and easily on-site. The Sequoia multispectral sensor used in this study has green, red, red edge and near-infrared wavebands, and a regular camer with red, green and blue wavebands (RGB camera), to capture both visible and near-infrared (NIR) imagery of the land surface. The workflow of 3D vegetation mapping of the study site included establishing coordinated ground control points, planning the flight mission and camera parameters, acquiring the imagery, processing the image data and performing features classification. The data processing outcomes included an orthomosaic model, a 3D surface model and multispectral imagery of the study site, in the Irish Transverse Mercator (ITM) coordinate system. The planimetric resolution of the RGB sensor-based outcomes was 0.024 m while multispectral sensor-based outcomes had a planimetric resolution of 0.096 m. High-resolution vegetation mapping was successfully generated from these data processing outcomes. There were 235 sample areas (1 m × 1 m) used for the accuracy assessment of the classification of the vegetation mapping. Feature classification was conducted using nine different classification strategies to examine the efficiency of multispectral sensor data for vegetation and contiguous land cover mapping. The nine classification strategies included combinations of spectral bands and vegetation indices. Results show classification accuracies, based on the nine different classification strategies, ranging from 52% to 75%.

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