Label-free 3D visualization of cellular and tissue structures in intact muscle with second and third harmonic generation microscopy.

Second and Third Harmonic Generation (SHG and THG) microscopy is based on optical effects which are induced by specific inherent physical properties of a specimen. As a multi-photon laser scanning approach which is not based on fluorescence it combines the advantages of a label-free technique with restriction of signal generation to the focal plane, thus allowing high resolution 3D reconstruction of image volumes without out-of-focus background several hundred micrometers deep into the tissue. While in mammalian soft tissues SHG is mostly restricted to collagen fibers and striated muscle myosin, THG is induced at a large variety of structures, since it is generated at interfaces such as refraction index changes within the focal volume of the excitation laser. Besides, colorants such as hemoglobin can cause resonance enhancement, leading to intense THG signals. We applied SHG and THG microscopy to murine (Mus musculus) muscles, an established model system for physiological research, to investigate their potential for label-free tissue imaging. In addition to collagen fibers and muscle fiber substructure, THG allowed us to visualize blood vessel walls and erythrocytes as well as white blood cells adhering to vessel walls, residing in or moving through the extravascular tissue. Moreover peripheral nerve fibers could be clearly identified. Structure down to the nuclear chromatin distribution was visualized in 3D and with more detail than obtainable by bright field microscopy. To our knowledge, most of these objects have not been visualized previously by THG or any label-free 3D approach. THG allows label-free microscopy with inherent optical sectioning and therefore may offer similar improvements compared to bright field microscopy as does confocal laser scanning microscopy compared to conventional fluorescence microscopy

What do we know about poverty in North Korea?

Reliable quantitative information on the North Korean economy is extremely scarce. In particular, reliable income per capita and poverty figures for the country are not available. In this contribution, we provide for the first time estimates of absolute poverty rates in North Korean subnational regions based on the combination of innovative remote-sensednight-time light intensity data (monthly information for built areas) with estimated income distributions. Our results, which are robust to the use of different methods to approximatethe income distribution in the country, indicate that the share of persons living in extreme poverty in North Korea may be larger than previously thought. We estimate a poverty rate for the country of around 60% in 2018 and a high volatility in the dynamics of income at the national level in North Korea for the period 2012–2018. Income per capita estimates tend to decline significantly from 2012 to 2015 and present a recovery since 2016. The subnational estimates of income and poverty reveal a change in relative dynamics since the second half of the 2012–2018 period. The first part of the period is dominated by divergent dynamics inincome across regions, while the second half reveals convergence in regional income

Late Pleistocene fans and terraces in the Majes valley, southern Peru, and their relation to climatic variations

This study investigates the connection between sediment aggradation, erosion and climate in a desert environment of the Majes valley, southern Peru. Luminescence dating of terraces and fans shows that sediment aggradation correlates with wet time intervals on the Altiplano, suggesting a climatic influence on the aggradation-degradation cycles. Major periods of aggradation occurred between ~110-100, ~60-50 and 12-8ka. More precipitation in the Majes catchment resulted in increased erosion and transportation of sediment from the hillslopes into the trunk river. As a result, the sediment loads exceeded the transport capacity of the Majes River and aggradation started in the lower reaches where the river gradient is less. Depletion of the hillslope sediment reservoirs caused a relative increase in the capacity of the trunk river to entrain and transport sediment, resulting in erosion of the previously deposited sediment. Consequently, although climate change may initiate a phase of sediment accumulation, degradation can be triggered by an autocyclic negative feedback and does not have to be driven by climatic chang

A comparison and evaluation of performances among crop yield forecasting models based on remote sensing: Results from the GEOLAND Observatory of Food Monitoring

In the context of the GEOLAND EC FP6 project the comparison of different remote sensing based approaches for yield forecasting over large areas in Europe are tested and results inter-compared. In particular the methods tested include the ones in use within the MARS-Crop Yield Forecasting System as the results from a Crop Growth Monitoring model (Alterra) and vegetation indicators derived from Low Resolution VGT and NOAA Images (VITO, IGiK), METEOSAT based yield forecasting (EARS) and ERS-Scatterometer Crop Performance Index (TPF and NEO). Performances of the different models were tested in Spain, Belgium and Poland. The inter-comparison of the crop yield forecasts were mainly based on the forecasting error obtained from the different approaches based on the Root Mean Square Forecast Error (RMSFE). This error was derived by comparing the predicted yields of the different models with the official yield from EUROSTAT. The comparison of the RMSFE was used to verify the convergence of results from the different models, the reliability of the information, i.e. precision and bias, and its precocity compared to the crop cycle. The results showed that the indicators are able to give reliable information with some differences: remote sensing indicators are more precise and accurate in southern areas (less cloud cover) while in northern areas good results are obtained under the use of better local calibrations of traditional crop yield forecasting systems, the use of additional information or the additional use of remote sensing data as inputs into advanced crop modelling systems. Furthermore, in order to take care of the different time series length available, a qualitative indicator called Performance Score (Ps) was introduced. The analysis of the Ps showed that when a long time series of observation is available greater advantages are obtained from RS rather than from more advanced crop models.JRC.DG.G.3-Monitoring agricultural resource

Best practices for crop area estimation with Remote Sensing

This document gives recommendations on different ways to use Earth Observation as a tool for crop area estimation highlighting strengths and limitations. The document was discussed in a workshop hosted by the Joint Research Centre (JRC) of the European Commission in June 2008 and attended by 40 remote sensing practitioners and users.JRC.DG.G.3-Monitoring agricultural resource

Harmonizing and combining existing land cover/land use datasets for cropland area monitoring at the African continental scale

Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this study were to (i) consolidate the best existing land cover/land use datasets, (ii) adapt the Land Cover Classification System (LCCS) for harmonization, (iii) assess the final product, and (iv) compare the final product with two existing datasets. Ten datasets were compared and combined through an expert-based approach to create the derived map of cropland areas at 250m covering the whole of Africa. The resulting cropland mask was compared with two recent cropland extent maps at 1km: one derived from MODIS and one derived from five existing products. The accuracy of the three products was assessed against a validation sample of 3591 pixels of 1km regularly distributed over Africa and interpreted using high resolution images, which were collected using the Geo-Wiki tool. The comparison of the resulting crop mask with existing products shows that it has a greater agreement with the expert validation dataset, in particular for places where the cropland represents more than 30% of the area of the validation pixel.JRC.H.4-Monitoring Agricultural Resource

Harmonizing and combining existing land cover and land use datasets for cropland area monitoring at the African continental scale

Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this study were to (i) consolidate the best existing land cover/land use datasets, (ii) adopt the Land Cover Classification System (LCCS) for harmonization and (iii) assess the final product. Ten datasets were compared and combined through an expert-based approach to create the derived map of cropland areas at 250m covering the whole of Africa. The resulting cropland mask was compared with two recent cropland extent maps at 1km: one derived from MODIS and one derived from five existing products. The accuracy of the three products was assessed against a validation sample of 3591 pixels of 1km² regularly distributed over Africa and interpreted using high resolution images, which were collected using the agriculture.geo.wiki.org tool. The comparison of the resulting crop mask with existing products shows that it has a greater agreement with the expert validation dataset, in particular for cropland above 30%.JRC.H.4 - Monitoring Agricultural Resource

D7.4 Strategic view for the sustainability of ENEON after the end of the project

EU Framework Program for Research and Innovation (SC5-18a-2014 - H2020)Project title: Coordinating an Observation Network of Networks EnCompassing saTellite and IN situ to fill the Gaps in European ObservationsTheme: SC5-18a-2014. Coordinating European Observation Networks to reinforce the knowledge base for climate, natural resources and raw materials.Report with options for the continuation and sustainability of ENEON after the end of the project

Enhancing the role of citizen sensors in mapping: COST Action TD1202

This article introduces a strategic initiative, COST Action TD1202, focused on the role of citizen sensors in mapping. It outlines the Action's scope, aims and current status. In particular, the article outlines the potential of citizen science in mapping activities and indicates the scope of current work undertaken by the Action's four working groups. It is stressed that the Action is at an early stage and that it is open to new members

Economic Development and Forest Cover: Evidence from Satellite Data

We use satellite data on forest cover along national borders in order to study the determinants of deforestation differences across countries. We combine the forest cover information with data on homogeneous response units, which allow us to control for cross-country geoclimatic differences when assessing the drivers of deforestation. Income per capita appears to be the most robust determinant of differences in cross-border forest cover and our results present evidence of the existence of decreasing effects of income on forest cover as economic development progresses.(authors' abstract)Series: Department of Economics Working Paper Serie