bluuebunny/crossref_metadata_2025 huggingface dataset:
Orange Snow—A Saharan Dust Intrusion over Romania During Winter Conditions
Authors: Mărmureanu Luminiţa , Marin Cristina Antonia , Andrei Simona , Antonescu Bogdan , Ene Dragoş , Boldeanu Mihai , Vasilescu Jeni , Viţelaru Cătălin , Cadar Oana , Levei Erika
Published: October 2019

On the morning of 23 March 2018, an unusual phenomenon was observed over Romania where the southeastern part of the country was covered in a fresh-layer of orange snow. The event was extensively reported in mass-media and social-media and raised questions about the origin and the possible impact of the orange snow. Even if this type of events, intrusions of Saharan dust, have been reported before in Romania, and in Europe in general, their occurrence during negative temperature conditions is very rare. Saharan dust intrusion occurs over Europe mainly during spring and, in general, is not accompanied by snow at low altitudes. In this article, for the first time, the synoptic-scale conditions leading to the Saharan dust intrusion over Romania and the chemical and physical properties of the deposited dust particles in a snow layer were analyzed. The Saharan dust event affected a permanent atmospheric measurement research infrastructure located southwest of Bucharest, the capital city of Romania. In-situ and remote sensing measurements conducted at this research infrastructure allowed the identification of the dust source as the north Sahara. The source was confirmed by the elemental ratios of the main components (e.g., Al, Ca, Mg, Fe, K). For example, the (Ca+Mg)/Fe ratio of 1.39 was characteristic for the north Sahara. The dust morphology and the minerals were analyzed by scanning electron microscopy with energy disperse X-ray spectrometry (SEM/EDX). The size distribution of the particle geometric diameter showed that they are centred on 1 μ m, but larger particles up to 40 μ m are also present. To visualize the minerals, an approach was developed which emphasized the presence of the calcite, quartz or clay minerals. The optical parameters of dust were measured by re-suspending the particles. Values of the optical parameters (i.e., asymmetry parameter at 550 nm was 0.604, single scattering albedo was 0.84–0.89) were similar to those measured for Saharan dust intrusions over the Iberian Peninsula. Also, the non-refractory particles found in the dust-contaminated snow layer were analyzed, indicating the presence of HULIS-like compounds, most probably advected from the Mediterranean sea.
Assessment of IMERG Precipitation Estimates over Europe
Authors: Navarro Andrés , García-Ortega Eduardo , Merino Andrés , Sánchez José , Kummerow Christian , Tapiador Francisco
Published: October 2019

This paper evaluates Integrated Multi-Satellite Retrievals from GPM (IMERG-F) over Europe for the period 2014–2018 in order to evaluate application of the retrievals to hydrology. IMERG-F is compared with a large pan-European precipitation dataset built on rain gauge stations, i.e., the ENSEMBLES OBServation (E-OBS) gridded dataset. Although there is overall agreement in the spatial distribution of mean precipitation (R2 = 0.8), important discrepancies are revealed in mountainous regions, specifically the Alps, Pyrenees, west coast of the British Isles, Scandinavia, the Iberian and Italian peninsulas, and the Adriatic coastline. The results show that the strongest contributors to poor performance are pixels where IMERG-F has no gauges available for adjustment. If rain gauges are available, IMERG-F yields results similar to those of the surface observations, although the performance varies by region. However, even accounting for gauge adjustment, IMERG-F systematically underestimates precipitation in the Alps and Scandinavian mountains. Conversely, IMERG-F overestimates precipitation in the British Isles, Italian Peninsula, Adriatic coastline, and eastern European plains. Additionally, the research shows that gauge adjustment worsens the spatial gradient of precipitation because of the coarse resolution of Global Precipitation Climatology Centre data.
Retrieval of the Fraction of Radiation Absorbed by Photosynthetic Components (FAPARgreen) for Forest Using a Triple-Source Leaf-Wood-Soil Layer Approach
Authors: Chen Siyuan , Liu Liangyun , Zhang Xiao , Liu Xinjie , Chen Xidong , Qian Xiaojin , Xu Yue , Xie Donghui
Published: October 2019

The fraction of absorbed photosynthetically active radiation (FAPAR) is generally divided into the fraction of radiation absorbed by the photosynthetic components ( F A P A R g r e e n ) and the fraction of radiation absorbed by the non-photosynthetic components ( F A P A R w o o d y ) of the vegetation. However, most global FAPAR datasets do not take account of the woody components when considering the canopy radiation transfer. The objective of this study was to develop a generic algorithm for partitioning F A P A R c a n o p y into F A P A R g r e e n and F A P A R w o o d y based on a triple-source leaf-wood-soil layer (TriLay) approach. The LargE-Scale remote sensing data and image simulation framework (LESS) model was used to validate the TriLay approach. The results showed that the TriLay F A P A R g r e e n had higher retrieval accuracy, as well as a significantly lower bias (R2 = 0.937, Root Mean Square Error (RMSE) = 0.064, and bias = −6.02% for black-sky conditions; R2 = 0.997, RMSE = 0.025 and bias = −4.04% for white-sky conditions) compared to the traditional linear method (R2 = 0.979, RMSE = 0.114, and bias = −18.04% for black-sky conditions; R2 = 0.996, RMSE = 0.106 and bias = −16.93% for white-sky conditions). For FAPAR that did not take account of woody components ( F A P A R n o W A I ), the corresponding results were R2 = 0.920, RMSE = 0.071, and bias = −7.14% for black-sky conditions, and R2 = 0.999, RMSE = 0.043, and bias = −6.41% for white-sky conditions. Finally, the dynamic F A P A R g r e e n , F A P A R w o o d y , F A P A R c a n o p y and F A P A R n o W A I products for a North America region were generated at a resolution of 500 m for every eight days in 2017. A comparison of the results for F A P A R g r e e n against those for F A P A R n o W A I and F A P A R c a n o p y showed that the discrepancy between F A P A R g r e e n and other FAPAR products for forest vegetation types could not be ignored. For deciduous needleleaf forest, in particular, the black-sky F A P A R g r e e n was found to contribute only about 23.86% and 35.75% of F A P A R c a n o p y at the beginning and end of the year (from January to March and October to December, JFM and OND), and 75.02% at the peak growth stage (from July to September, JAS); the black-sky F A P A R n o W A I was found to be overestimated by 38.30% and 28.46% during the early (JFM) and late (OND) part of the year, respectively. Therefore, the TriLay approach performed well in separating F A P A R g r e e n from F A P A R c a n o p y , which is of great importance for a better understanding of the energy exchange within the canopy.
Increasing the Number of Sea Surface Reflected Signals Received by GNSS-Reflectometry Altimetry Satellite Using the Nadir Antenna Observation Capability Optimization Method
Authors: Liu Zongqiang , Zheng Wei , Wu Fan , Kang Guohua , Li Zhaowei , Wang Qingqing , Cui Zhen
Published: October 2019

High spatial resolution Global Navigation Satellite System-Reflectometry (GNSS-R) sea surface altimetry is of great significance for extracting precise information from sea surface topography. The nadir antenna is one of the key payloads for the GNSS-R altimetry satellite to capture and track the sea surface GNSS reflected signal. The observation capability of the nadir antenna directly determines the number of received reflected signals, which, in turn, affects the spatial resolution of the GNSS-R altimetry. The parameters affecting the ability of the nadir antenna to receive the reflected signal mainly include antenna gain, half-power beam width (HPBW), and pointing angle. Thus far, there are rarely studies on the observation capability of GNSS-R satellite nadir antenna. The design of operational satellite antenna does not fully combine the above three parameters to optimize the design of GNSS-R nadir antenna. Therefore, it is necessary to establish a GNSS-R spaceborne nadir antenna observation capability optimization method. This is the key to improving the number of sea surface reflected signals received by the GNSS-R altimeter satellites, thereby increasing the spatial resolution of the altimetry. This paper has carried out the following research on this. Firstly, based on the GNSS-R geometric relationship and signal processing theory, the nadir antenna signal-to-noise ratio model (NASNRM) with the gain and the elevation angle at the specular point (SP) as the main parameters is established. The accuracy of the model was verified using TechDemoSat-1 (TDS-1) observations. Secondly, based on the theory of electromagnetic scattering, considering the influence of HPBW and pointing angle on the antenna footprint size, a specular point filtering algorithm (SPFA) is proposed. Combined with the results obtained by NASNRM, the number of available specular points (SPs) is counted. The results show that as the antenna gain and the nadir-pointing angle increase, the number of SPs can reach a peak and then gradually decrease. Thirdly, combined with NASNRM and SPSA, a nadir antenna observation capability optimization method (NAOCOM) is proposed. The nadir antenna observation capability is characterized through the reflected signal utilization, and the results obtained by the method are used to optimize the combination of nadir antenna parameters. The research shows that when the orbital height of the GNSS-R satellite is 635 km, the optimal combination of nadir antenna parameters is 20.94 dBi for the gain and 32.82 degrees for the nadir-pointing angle, which can increase the observation capability of the TDS-1 satellite nadir antenna by up to 5.38 times.
Remote Sensing the Archaeological Traces of Boat Movement in the Marshes of Southern Mesopotamia
Authors: Jotheri Jaafar , de Gruchy Michelle , Almaliki Rola , Feadha Malath
Published: October 2019

This study presents the results of the first remote sensing survey of hollow ways in Southern Mesopotamia between Baghdad and the Persian Gulf, primarily using the imagery in Google Earth. For archaeologists, hollow ways are important trace fossils of past human movement that inform about how people travelled in the past and what considerations were important to them as they moved through the landscape. In this study, remotely sensed hollow ways were ground-truthed and dated by association with both palaeochannels and known archaeological sites. Contextual and morphological evidence of the hollow ways indicate that they are likely the archaeological manifestation of ethnographically attested “water channels” formed through the dense reeds of marshlands in southern Iraq, not formed by traction overland like other known hollow ways. The map itself documents the first known hollow ways preserved underwater and one of the best-preserved landscapes of past human movement in the Near East.
Remotely-Observed Early Spring Warming in the Southwestern Yellow Sea Due to Weakened Winter Monsoon
Authors: Wu Xiangbai , Xu Qing , Li Gen , Liou Yuei-An , Wang Bin , Mei Huan , Tong Kai
Published: October 2019

The seasonal warming over the southwestern Yellow Sea (YS) in the spring is of vital importance to the local ecologic environment, especially to the massive green algae blooms of the YS in late spring and early summer. Based on daily optimum interpolation sea surface temperature (SST) data consisting of satellite derived SST from Advanced Very High Resolution Radiometer (AVHRR) and in situ measurements, this study analyzed the spring SST variation over the southwestern YS (SWYS) from 1982 to 2018. The results show that the recent warming trend of spring SST over the SWYS is four-to-six times that of the global average, and as a result, sea water over the Subei Shoal (SBS) shifts about 10–13 days earlier to reach 10 °C in early April. This implies that, accordingly, the micro-propagules of green algae over the SBS may have the chance to germinate earlier. SST variability in early April significantly correlates with northerly wind and exhibits a general warming over the SWYS with an intensified warming anchored along the axis of the submarine canyon off the Yangtze estuary. The Moderate Resolution Imaging Spectroradiometer (MODIS) red–green–blue composite images captured the intrusion of the Taiwan Warm Current (TWC) into the SWYS through the submarine canyon during northerly wind relaxation in early April. Ocean remote sensing provides important clues for understanding the regional SST variability in the SWYS. Following this clue, this study finds that the weakening of winter monsoon in the spring leads to northward migration of the TWC and results in enhanced spring warming over the SWYS. The attendant advanced warming in spring, resulting in a favorable temperature condition for early development of green alga, may have contributed to the green tide blooms in the Yellow Sea in the recent decade.
Incorporating the Plant Phenological Trajectory into Mangrove Species Mapping with Dense Time Series Sentinel-2 Imagery and the Google Earth Engine Platform
Authors: Li Huiying , Jia Mingming , Zhang Rong , Ren Yongxing , Wen Xin
Published: October 2019

Information on mangrove species composition and distribution is key to studying functions of mangrove ecosystems and securing sustainable mangrove conservation. Even though remote sensing technology is developing rapidly currently, mapping mangrove forests at the species level based on freely accessible images is still a great challenge. This study built a Sentinel-2 normalized difference vegetation index (NDVI) time series (from 2017-01-01 to 2018-12-31) to represent phenological trajectories of mangrove species and then demonstrated the feasibility of phenology-based mangrove species classification using the random forest algorithm in the Google Earth Engine platform. It was found that (i) in Zhangjiang estuary, the phenological trajectories (NDVI time series) of different mangrove species have great differences; (ii) the overall accuracy and Kappa confidence of the classification map is 84% and 0.84, respectively; and (iii) Months in late winter and early spring play critical roles in mangrove species mapping. This is the first study to use phonological signatures in discriminating mangrove species. The methodology presented can be used as a practical guideline for the mapping of mangrove or other vegetation species in other regions. However, future work should pay attention to various phenological trajectories of mangrove species in different locations.
Comparison of Arctic Sea Ice Concentrations from the NASA Team, ASI, and VASIA2 Algorithms with Summer and Winter Ship Data
Authors: Alekseeva Tatiana , Tikhonov Vasiliy , Frolov Sergei , Repina Irina , Raev Mikhael , Sokolova Julia , Sharkov Evgeniy , Afanasieva Ekaterina , Serovetnikov Sergei
Published: October 2019

The paper presents a comparison of sea ice concentration (SIC) derived from satellite microwave radiometry data and dedicated ship observations. For the purpose, the NASA Team (NT), Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI), and Variation Arctic/Antarctic Sea Ice Algorithm 2 (VASIA2) algorithms were used as well as the database of visual ice observations accumulated in the course of 15 Arctic expeditions. The comparison was performed in line with the SIC gradation (in tenths) into very open (1–3), open (4–6), close (7–8), very close and compact (9–10,10) ice, separately for summer and winter seasons. On average, in summer NT underestimates SIC by 0.4 tenth as compared to ship observations, while ASI and VASIA2 by 0.3 tenth. All three algorithms overestimate total SIC in regions of very open ice and underestimate it in regions of close, very close, and compact ice. The maximum average errors are typical of open ice regions that are most common in marginal ice zones. In winter, NT and ASI also underestimate SIC on average by 0.4 and 0.8 tenths, respectively, while VASIA2, on the contrary, overestimates by 0.2 tenth against the ship data, however, for open and close ice the average errors are significantly higher than in summer. In the paper, we also estimate the impact of ice melt stage and presence of new ice and nilas on SIC derived from NT, ASI, and VASIA2.
Archaeological Prospection with Motorised Multichannel Ground-Penetrating Radar Arrays on Snow-Covered Areas in Norway
Authors: Gabler Manuel , Trinks Immo , Nau Erich , Hinterleitner Alois , Paasche Knut , Gustavsen Lars , Kristiansen Monica , Tonning Christer , Schneidhofer Petra , Kucera Matthias , Neubauer Wolfgang
Published: October 2019

The technical advancements of the past decade have rendered motorised, high-resolution ground-penetrating radar (GPR) investigations increasingly popular for archaeological research and cultural heritage management in Norway. However, the agricultural use of most survey areas limits the time available for fieldwork in spring and autumn and thus reduces the method’s potential. An extension of the fieldwork period into the winter season would be desirable. The project “Arkeologi i veien?” aimed to develop practical solutions for efficient motorised GPR surveys on snow and to evaluate to what extent the thickness of the snow cover affects data quality. Four sites with known archaeological remains in the ground have been investigated under snowless conditions and with snow cover. The comparative data analysis showed that GPR surveys can result in useful data even on areas covered with one metre of snow. This study shows that different temperatures and resulting variable snow conditions can have a strong effect on the quality of the generated GPR data. The possibility for GPR measurements on snow offers the opportunity to extend fieldwork into the winter period without conflicting with the growing season; however, local weather and snow conditions have to be closely observed in order to obtain useful prospection data.
Assessment and Improvement of Sea Surface Microwave Emission Models for Salinity Retrieval in the East China Sea
Authors: Jin Xuchen , He Xianqiang , Bai Yan , Shanmugam Palanisamy , Ying Jianyun , Gong Fang , Zhu Qiankun
Published: October 2019

Accurate prediction of sea surface emission is the key for sea surface salinity retrieval from satellite microwave radiometer. In order to retrieve salinity from satellite observation, several sea surface microwave emission models have been developed based on theoretical or empirical methods and validated by in-situ measurements in different regions. However, their performances are still unclear in the Chinese coastal waters. In this study, based on two cruises measurements in the East China Sea (ECS), including the brightness temperature measured by a shipborne microwave radiometer and other auxiliary data (sea surface salinity, sea surface temperature and wind speed), the performances of different sea surface emission models are tested. The results showed that the developed models provide fairly good accuracy in predicting brightness temperature; for example, the accuracy of small perturbance/small scale approximation model (SPM/SSA), two-scale model (TSM) and empirical model is in the range from 0.6 K to 3 K. Moreover, the TSM and empirical models are further improved by optimizing the model parameters in the ECS. Finally, the sea surface salinity were retrieved from shipborne measured data based on the improved models, and the results show that the root mean square (rms) differences between retrieved and in-situ sea surface salinity is about 0.4 psu, indicating the significant improvement by the regional model parameters.
Seasonal Evaluation of SMAP Soil Moisture in the U.S. Corn Belt
Authors: Walker Victoria A. , Hornbuckle Brian K. , Cosh Michael H. , Prueger John H.
Published: October 2019

NASA’s Soil Moisture Active Passive (SMAP) Level 2 soil moisture products are not meeting mission goals in the U.S. Corn Belt according to our seasonal evaluation conducted at a SMAP Core Validation Site in central Iowa. The single-channel algorithm (SCA) soil moisture products are too dry in early spring and late fall before and after crops are present, and too noisy in late spring and early summer when crops begin to grow. We investigated likely contributing factors. The climatology of vegetation’s effect on soil moisture retrieval in the SCA can differ by more than 14 days from what is retrieved by SMAP’s dual-channel algorithm (DCA). Soil and vegetation temperatures, assumed to be equal by all retrieval algorithms, are not: vegetation is about 2 K colder at 6:00 a.m. and about 2 K warmer at 6:00 p.m.. The effective temperature in version 2 products is too warm as compared to in situ soil temperatures. We propose a new effective temperature model that is consistent with observations, decreases the unbiased root-mean-square-error (ubRMSE) overall, and increases the coefficient of determination (R2) of the DCA in every month. However, some monthly dry biases increase to more than 0.10 m3 m−3. The single-scattering albedo, ω , has a significant impact on soil moisture retrieval. While the DCA has its lowest ubRMSE and highest R2 when ω is non-zero, the SCA have their lowest ubRMSE and highest R2 when ω = 0 , and the dry bias of all algorithms increases as ω increases. Errors in soil texture are not significant, but soil surface roughness should not be static and have a higher overall value. Our findings make it clear that a new retrieval algorithm that can account for changing soil roughness and vegetation conditions is needed.
Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories
Authors: Wang Fenjuan , Maksyutov Shamil , Tsuruta Aki , Janardanan Rajesh , Ito Akihiko , Sasakawa Motoki , Machida Toshinobu , Morino Isamu , Yoshida Yukio , Kaiser Johannes , Janssens-Maenhout Greet , Dlugokencky Edward , Mammarella Ivan , Lavric Jost , Matsunaga Tsuneo
Published: October 2019

We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 yr−1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.
Patch Similarity Convolutional Neural Network for Urban Flood Extent Mapping Using Bi-Temporal Satellite Multispectral Imagery
Authors: Peng Bo , Meng Zonglin , Huang Qunying , Wang Caixia
Published: October 2019

Urban flooding is a major natural disaster that poses a serious threat to the urban environment. It is highly demanded that the flood extent can be mapped in near real-time for disaster rescue and relief missions, reconstruction efforts, and financial loss evaluation. Many efforts have been taken to identify the flooding zones with remote sensing data and image processing techniques. Unfortunately, the near real-time production of accurate flood maps over impacted urban areas has not been well investigated due to three major issues. (1) Satellite imagery with high spatial resolution over urban areas usually has nonhomogeneous background due to different types of objects such as buildings, moving vehicles, and road networks. As such, classical machine learning approaches hardly can model the spatial relationship between sample pixels in the flooding area. (2) Handcrafted features associated with the data are usually required as input for conventional flood mapping models, which may not be able to fully utilize the underlying patterns of a large number of available data. (3) High-resolution optical imagery often has varied pixel digital numbers (DNs) for the same ground objects as a result of highly inconsistent illumination conditions during a flood. Accordingly, traditional methods of flood mapping have major limitations in generalization based on testing data. To address the aforementioned issues in urban flood mapping, we developed a patch similarity convolutional neural network (PSNet) using satellite multispectral surface reflectance imagery before and after flooding with a spatial resolution of 3 meters. We used spectral reflectance instead of raw pixel DNs so that the influence of inconsistent illumination caused by varied weather conditions at the time of data collection can be greatly reduced. Such consistent spectral reflectance data also enhance the generalization capability of the proposed model. Experiments on the high resolution imagery before and after the urban flooding events (i.e., the 2017 Hurricane Harvey and the 2018 Hurricane Florence) showed that the developed PSNet can produce urban flood maps with consistently high precision, recall, F1 score, and overall accuracy compared with baseline classification models including support vector machine, decision tree, random forest, and AdaBoost, which were often poor in either precision or recall. The study paves the way to fuse bi-temporal remote sensing images for near real-time precision damage mapping associated with other types of natural hazards (e.g., wildfires and earthquakes).
Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program
Authors: Gebremedhin Alem , Badenhorst Pieter , Wang Junping , Giri Khageswor , Spangenberg German , Smith Kevin
Published: October 2019

Sensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate HY of single plants in a large perennial ryegrass breeding program. For sensor calibration, fresh HY (FHY) and dry HY (DHY) were acquired destructively, and plant height was measured at four dates each in 2017 and 2018 from a selected subset of 480 plants. Global multiple linear regression models based on K-fold and random split cross-validation methods were used to evaluate the relationship between observed vs. predicted HY. The coefficient of determination (R2) = 0.67–0.68 and a root mean square error (RMSE) between 5.43–7.60 g was obtained for the validation of predicted vs. observed DHY. The mean absolute error (MAE) and mean percentage error (MPE) ranged between 3.59–5.44 g and 22–28%, respectively. For the FHY, R2 values ranged from 0.63 to 0.70, with an RMSE between 23.50 and 33 g, MAE between 15.11 and 24.34 g and MPE between ~22% and 31%. Combining NDVI and plant height is a robust method to enable high-throughput phenotyping of herbage yield in perennial ryegrass breeding programs.
Monitoring Harvesting by Time Series of Sentinel-1 SAR Data
Authors: Kavats Olena , Khramov Dmitriy , Sergieieva Kateryna , Vasyliev Volodymyr
Published: October 2019

Algorithm for determining crop harvesting dates based on time series of coherence and backscattering coefficient ( σ 0 ) derived from Sentinel-1 single look complex (SLC) synthetic-aperture radar (SAR) images is proposed. The algorithm allows the ability to monitor harvesting over large areas without having to install additional sensors on agricultural machinery. Coherence between SAR images allows the ability to track changes in field-scatterers configuration resulting from agricultural work. The proposed algorithm finds a step-like increase in coherence that occurs after the harvesting and is related to the conversion of a field into a bare soil area. An additional check of potential harvest dates is carried out by threshold values of σ 0 depending on vegetation height. The algorithm is adapted for the monitoring of non-homogeneous fields with traces of erosion and insertions of fallow land. The algorithm was tested on agricultural fields located in the north of Kazakhstan. The obtained accuracy (mean absolute error = 6.5 days) of determining the dates of harvesting can be deemed satisfactory. This accuracy can be increased by shortening the interval between observations from 12 to 6 days when using data from both Sentinel-1 satellites.
Road Extraction of High-Resolution Remote Sensing Images Derived from DenseUNet
Authors: Xin Jiang , Zhang Xinchang , Zhang Zhiqiang , Fang Wu
Published: October 2019

Road network extraction is one of the significant assignments for disaster emergency response, intelligent transportation systems, and real-time updating road network. Road extraction base on high-resolution remote sensing images has become a hot topic. Presently, most of the researches are based on traditional machine learning algorithms, which are complex and computational because of impervious surfaces such as roads and buildings that are discernible in the images. Given the above problems, we propose a new method to extract the road network from remote sensing images using a DenseUNet model with few parameters and robust characteristics. DenseUNet consists of dense connection units and skips connections, which strengthens the fusion of different scales by connections at various network layers. The performance of the advanced method is validated on two datasets of high-resolution images by comparison with three classical semantic segmentation methods. The experimental results show that the method can be used for road extraction in complex scenes.
Forest Degradation Assessment Based on Trend Analysis of MODIS-Leaf Area Index: A Case Study in Mexico
Authors: Reygadas Yunuen , Jensen Jennifer L. R. , Moisen Gretchen G.
Published: October 2019

: Assessing forest degradation has been a challenging task due to the generally slow-changing nature of the process, which demands long periods of observation and high frequency of records. This research contributes to efforts aimed at detecting forest degradation by analyzing the trend component of the time series of Leaf Area Index (LAI) collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Central Mexico from 2002 to 2017. The analysis of the trend component is proposed to overcome the challenge of identifying very subtle and gradual changes that can be undetected if only the raw time series is examined. Additionally, the use of LAI as an alternative to other widely used indexes (e.g., Normalize Difference Vegetation Index and Enhanced Vegetation Index) facilitates consideration of the structural changes evident from degradation though not necessarily observable with spectral indices. Overall, results indicate that 52% of the study area has experienced positive trends of vegetation change (i.e., increasing LAI), 37% has remained unchanged, and 11% exhibits some level of forest degradation. Particularly, the algorithm estimated that 0.6% (385 km2) is highly degraded, 5.3% (3406 km2) moderately degraded, and 5.1% (3245 km2) slightly degraded. Most of the moderate and highly degraded areas are distributed over the east side of the study area and evergreen broadleaf appears to be the most affected forest type. Model validation resulted an accuracy of 63%. Some actions to improve this accuracy are suggested, but also a different approach to validate this type of study is suggested as an area of opportunity for future research.
Integration of Safety in IFMIF-DONES Design
Authors: Martín-Fuertes Francisco , García Miguel E. , Fernández Pedro , Cortés Ángela , D’Ovidio Gianluca , Fernández Elena , Pinna Tonio , Porfiri Maria Teresa , Fischer Ulrich , Ogando Francisco , Mota Fernando , Qiu Yuefeng , Helminen Atte , Potempski Slawomir , Gallego Eduardo , Ibarra Ángel
Published: October 2019

The IFMIF-DONES (International Fusion Material Irradiation Facility-DEMO Oriented NEutron Source) facility is being designed with the general objective of providing irradiation of representative samples of power fusion machine materials under prototypical conditions. A linear accelerator will deliver deuterons at high intensity to circulating lithium in a loop, which will produce neutrons capable of obtaining the required damage conditions. As a result of this process, radionuclides will be produced as a by-product, which is characterized by several degrees of mobility. Shielding and radiation protection measures will be required in the facility. IFMIF-DONES will be classified as a first class radioactive facility according to national regulations, with Spain being the European candidate to site the facility. Several aspects of the main safety instructions affecting the facility’s design are explained and discussed in this paper.
The Development of Generalized Trust among Young People in England
Authors: Janmaat Jan Germen
Published: October 2019

This paper explores how generalized trust develops over the life course among young people in England and whether trust is influenced more by family background factors or by conditions in late adolescence and early adulthood. If the latter are important, there may be reason for concern about falling levels of trust as material conditions, particularly regarding housing, have deteriorated for the present generation of young people. The first set of influences are highlighted by a perspective arguing that trust is primarily shaped by conditions in early childhood, while the latter are suggested by the so-called social learning perspective, which claims that people continuously adjust their social trust through interactions with people in different contexts. Analyzing data of the Citizenship Education Longitudinal Survey, the study finds that trust remains quite volatile until the early twenties. It declines between ages 16 and 23 and groups differing in educational attainment, civic participation and housing situation start to drift apart in their levels of trust between these ages. Educational attainment, civic participation and housing, as conditions pertaining to late adolescence and early adulthood, also turn out to have a significant impact on trust at age 23 controlling for trust at age 16. However, while the first two conditions are influenced by trust at age 16, housing (tenure) is not, indicating it is a more exogenous factor. Family background factors are not influential. Not only do these findings support the social learning perspective, they also suggest that poor living conditions depress trust among a significant minority of young people and exacerbate disparities of trust.
Pairwise Voting to Rank Touristic Destinations Based on Preference Valuation
Authors: Cabrera Francisco E. , Amaya Manuel , Vaccaro Witt Gustavo Fabián , Peláez José Ignacio
Published: October 2019

This paper presents a novel approach for ranking tourist destinations based on the eigenvector method for pairwise voting (EMPV). The proposed approach relies solely on pairwise comparisons instead of direct-vote polling. The EMPV method was tested over a real-world case application to rank various tourist destinations in the Costa del Sol region, Spain, and its outcome was compared against a polling approach using a Likert-type scale. Results show that the EMPV and the Likert-based approach provided different rankings of preferred tourist destinations. Furthermore, both the EMPV and the Likert-based approaches shared the same preference patterns per ranking position, thus confirming that the reported predilection of the tourist is independent of the measurement approach. Finally, results show that the ranking produced by the EMPV methodology was highly related to the real number of visitors of the Costa del Sol tourist destinations, surpassing the Likert-based approach in both ordering and value similarities.
The Politics of Agricultural Development in Iraq and the Kurdistan Region in Iraq (KRI)
Authors: Jongerden Joost , Wolters Wouter , Dijkxhoorn Youri , Gür Faik , Öztürk Murat
Published: October 2019

From being a smallholder-based, food-producing country covering its basic needs, Iraq and the Kurdistan Region in Iraq (KRI) have become major importers of food. The sustainability of the agricultural sector has been systematically undermined by conflict, neglect, and mismanagement, as a result of which the capacity of its farmers to feed the population declined. Even though local policymakers, the international community, and the international organisations emphasise the potential of agriculture for food production, job creation, and income generation, they also tend to consider the current food system problematic because of an alleged low productivity that they relate to the existing smallholder system. For them, such system poses a lack of competences and skills of farmers, and a subsistence production orientation. This approach culminated in a policy-making process that offered land and water for capital investments, and thus neglecting the potentials and competencies of (small-scale) farmers. The concomitant neglect of the human dimension of agriculture, namely the family farm, is essentially the continuation of an economically and ecologically high-risk approach that may lead to a further decline of the sector’s ability to produce food for the local market.
Relevance of Life-Cycle Assessment in Context-Based Science Education: A Case Study in Lower Secondary School
Authors: Tolppanen Sakari , Jäppinen Ilpo , Kärkkäinen Sirpa , Salonen Anssi , Keinonen Tuula
Published: October 2019

The article introduces a science education intervention using life-cycle analysis of consumer products. The intervention aims to promote lower secondary school students’ science career awareness and interest toward science studies. In this study, two lower secondary school teachers planned an intervention on life-cycle analysis, which aimed to be relevant for the students from an individual, societal, and vocational perspective. The study then examined how students perceived the relevance of the intervention, based on classroom observations, students’ life-cycle presentations, questionnaire responses, as well as interviews. The findings indicate that students found life-cycle assessment to be a relevant topic both from an individual and societal perspective. However, findings on vocational relevance were two-fold, as students gained knowledge on different occupations, but this did not seem to directly affect their future career aspirations.
Daylight and Architectural Simulation of the Egebjerg School (Denmark): Sustainable Features of a New Type of Skylight
Authors: Cabeza-Lainez Joseph , Almodovar-Melendo Jose-Manuel , Dominguez Ismael
Published: October 2019

This article discusses the performance of a new skylight for standard classrooms at the Egebjerg School (Denmark), which was built ca. 1970. This building underwent important reforms under a European project to which the authors contributed. This research aimed to create a new skylight prototype that is useful for several schools in the vicinity, since there is a lack of educational facilities. The former skylights consisted of plastic pyramids that presented serious disadvantages in terms of sustainability matters. During the design process, the priority changed to studying the factors that correlate daylighting with energy and other environmental aspects in a holistic and evocative approach. Accordingly, the new skylight features promote the admittance and diffusion of solar energy through adroit guidance systems. In order to simulate different scenarios, we employed our own simulation tool, Diana X. This research-oriented software works with the effects of direct solar energy that are mostly avoided in conventional programs. By virtue of Lambert’s reciprocity theorem, our procedure, which was based on innovative equations of radiative transfer, converts the energy received by diffusive surfaces into luminous exitance for all types of architectural elements. Upon completion of the skylights, we recorded onsite measurements, which roughly coincided with the simulation data. Thus, conditions throughout the year improved.
Does ISO 9000 Certification Benefit Service Firms?
Authors: Chen Yan-ying , Wu Long , Zhai Qing-guo
Published: October 2019

This paper examines whether ISO 9000 certification benefits service firms in terms of their financial performance and promotes sustainable improvement. We argue that in a developing country setting such as China, the massive benefits brought by the signalling effect of the certification can discourage firms’ motivation to fully implement the standard of certification and lead to the decline of investment on productivity-improving activities. In other words, the certification may have negative effects on the productivity of certified firms. We investigate 89,024 firms in Chinese service industries to assess the impacts of the certification on sales, productivity and profitability of these firms. To address the potential selection bias of ISO 9000 certification, the Propensity Score Matching method and Coarsened Exact Matching method were used. Our key findings are that the ISO 9000 certification does help to increase the total amount of sales, but it decreases the productivity and profitability of these certified service firms. We also find that earlier certifiers seem to gain larger advantage in sales but more reduction in productivity, and firms with higher level of technology intensity seem to obtain a larger increase in sales and less productivity loss after receiving their ISO 9000 certification.
Environmental Life Cycle Assessment of Grid-Integrated Hybrid Renewable Energy Systems in Northern Nigeria
Authors: Abubakar Jumare Ismail , Bhandari Ramchandra , Zerga Abdellatif
Published: October 2019

Life cycle assessment is a crucial tool in evaluating systems performances for sustainability and decision-making. This paper provided environmental impact of integrating renewable energy systems to the utility-grid based on a baseline optimized energy production data from “HOMER” for renewable systems modelling of a site in northern Nigeria. The ultimate goal was to ascertain the best hybrid option(s) in sustaining the environment. Different assumptions and scenarios were modelled and simulated using Ganzleitlichen Bilanz (GaBi). Uncertainty analysis was ensured to the impact data based on pedigree-matrix and Excel-program, as well as overall policy relevance. The results of the impact categories revealed first scenario (i.e., conventional path-based) with the highest impacts on global warming potential (GWP), acidification potential (AP), human toxicity potential (HTP), and abiotic depletion potential (ADPfossils). The lowest impacts arise in the renewable-based scenarios for all the considered categories except the Ozone-layer depletion potential Category where the highest contribution falls in the third scenario (i.e., photovoltaic (PV)/biomass-biogas system) although all values being infinitesimal. In quantitative terms, the reduction in the GWP from the highest being the first scenario to the lowest being the fourth scenario (i.e., wind/biomass-biogas system) was 96.5%. Hence, with the outstanding contributions of the hybrid renewable systems, adopting them especially the lowest impact scenarios with expansions is relevant for environmental sustainability.
From Single-Use Community Facilities Support to Integrated Sustainable Development: The Aims of Inter-Municipal Cooperation in Poland, 1990–2018
Authors: Furmankiewicz Marek , Campbell Adrian
Published: October 2019

The paper explores and compares the aims of the three most common legal forms of inter-municipal cooperation in Poland (engaging rural, urban-rural and urban municipalities) during the years 1990–2018: Mono-sectoral Special Purpose Unions, Municipal Associations and cross-sectoral Local Action Groups. Content analysis was applied and development priorities from the statutes and strategies were studied. The main form of territorial association evolved from, initially, mono-functional bodies concerned mainly with local infrastructural investment and managed solely by a group of local authorities, to a devolved type, consisting of multi-purpose associations managed with the participation of economic and third sector representatives. This was the result of the European Union policy of promoting territorial governance and integrated development in functional regions, this being considered as part of the process of Europeanisation. However, these successive forms of municipal cooperation do not appear to have replaced the pre-existing forms, but they have introduced additional modes of governance of local resources. The findings show that the most “integrated” and “sustainable” management of local resources is observed mainly in cross-sectoral partnerships, like Local Action Groups, but not so often in mono-sectoral municipal unions and associations led solely by local government and focused more on hard infrastructure and municipal facilities. However, given the specialisation shown by each of the three types of association, it is likely that the full range of development possibilities in the areas concerned can only be realised if all three forms of cooperation are present. The analysis confirms the positive role of local economic and social sector participation in shaping sustainable development. The findings also indicate the utility of the concept of cross-sectoral territorial partnerships in post-socialist and post-authoritarian countries lacking traditions of grassroots or participative development.
A Joint Control Model Based on Emission Rights Futures Trading for Regional Air Pollution That Accounts for the Impacts on Employment
Authors: Wang Shijie , Zhao Laijun , Yang Yong , Wang Chenchen , Xue Jian , Bo Xin , Li Deqiang , Liu Dengguo
Published: October 2019

To reduce air pollutant control costs and solve the problem of decreased employment caused by air pollution control, we established a double-objective optimization Joint Control Model (JCM) based on emission rights futures trading. The JCM calculates the spot price of emission rights, classifies regions in the trading market for emission rights into buyers and sellers, and calculates the optimal cooperative pollution abatement quantity. Compared with a non-cooperative control mode, the JCM generated benefits of US$2485.19 × 106. We then used a Game Quadratic Programming (GQP) method to distribute the benefits, and applied the JCM to a case study of the abatement of sulfur dioxide in China’s Shanxi, Henan, and Shaanxi provinces. We found that: (i) Compared with a JCM that does not account for employment, employment under the JCM increased by 3.20 × 103 people, and the pollution control cost decreased by US$11.20 × 106 under the JCM that considered employment. The effect of the latter model is better than that of the former. (ii) Employment under the JCM increased by 18.80 × 104 people compared with that under a territorial control mode, reducing the cost by US$99.73 × 106. The JCM is helpful for all participating regions to balance environmental and livelihood issues in the process of air pollution control to achieve sustainable development.