bluuebunny/crossref_metadata_2025 huggingface dataset:
Pathogenomics and Management of Fusarium Diseases in Plants
Authors: Rampersad Sephra
Published: May 2020

There is an urgency to supplant the heavy reliance on chemical control of Fusarium diseases in different economically important, staple food crops due to development of resistance in the pathogen population, the high cost of production to the risk-averse grower, and the concomitant environmental impacts. Pathogenomics has enabled (i) the creation of genetic inventories which identify those putative genes, regulators, and effectors that are associated with virulence, pathogenicity, and primary and secondary metabolism; (ii) comparison of such genes among related pathogens; (iii) identification of potential genetic targets for chemical control; and (iv) better characterization of the complex dynamics of host–microbe interactions that lead to disease. This type of genomic data serves to inform host-induced gene silencing (HIGS) technology for targeted disruption of transcription of select genes for the control of Fusarium diseases. This review discusses the various repositories and browser access points for comparison of genomic data, the strategies for identification and selection of pathogenicity- and virulence-associated genes and effectors in different Fusarium species, HIGS and successful Fusarium disease control trials with a consideration of loss of RNAi, off-target effects, and future challenges in applying HIGS for management of Fusarium diseases.
Detection of Porcine Circovirus 3 in Wildlife Species in Spain
Authors: Czyżewska-Dors Ewelina , Núñez José I. , Saporiti Viviane , Huerta Eva , Riutord Carme , Cabezón Oscar , Segalés Joaquim , Sibila Marina
Published: May 2020

Porcine circovirus 3 (PCV-3) is the third member of the family Circoviridae, genus Circovirus, able to infect swine. A high prevalence of viral DNA has been recorded in wild boars. Recently, PCV-3 DNA was identified in Italian wild ruminants. Based on these previous results, this study assessed the frequency of PCV-3 DNA detection in free-ranging ruminants and Lagomorpha species in Spain. In addition, the genetic characterization of the PCV-3 PCR-positive samples was performed. A total of 801 serum samples, including red deer (Cervus elaphus, [CE]; n = 108), roe deer (Capreolus capreolus, [CC]; n = 87), Pyrenean chamois (Rupicapra pyrenaica, [RP]; n = 133), Iberian ibex (Capra pyrenaica, [CP]; n = 92), mouflon (Ovis aries, [OA]; n = 91), fallow deer (Dama dama, [DD]; n = 104), European rabbit (Oryctolagus cuniculus, [OC]; n = 101), and European hare (Lepus europaeus, [LE]; n = 85) from Catalonia (northeast Spain) were tested by conventional polymerase chain reaction (PCR) and, when positive, sequenced. Overall, PCV-3 DNA was found in three out of 801 analyzed sera (0.37%) corresponding to one red deer (1/108, 0.9%), one mouflon (1/91, 1.1%), and one fallow deer (1/104, 0.96%). None of the samples collected from Lagomorpha species resulted PCR positive. The partial genome sequences detected in positive samples displayed high identity with some PCV-3 sequences detected in wild boars and domestic pigs (99.7% and 100%, respectively). In conclusion, the present study indicated that free-ranging ruminant and Lagomorpha species are not relevant in the epidemiology of PCV-3 in Spain.
Innovative Alternatives for Continuous In Vitro Culture of Babesia bigemina in Medium Free of Components of Animal Origin
Authors: Álvarez Martínez Jesús A. , Figueroa Millán Julio V. , Ueti Massaro W. , Rojas-Martínez Carmen
Published: May 2020

In this study, we report Babesia bigemina proliferation in culture medium free of components of animal origin supplemented with a lipid mixture. Babesia bigemina continuously proliferated in VP-SFM with a higher percent parasitized erythrocyte as compare to using other animal component-free culture media. Compared with Advanced DMEM/F12 (ADMEM/F12), VP-SFM had a similar percent parasitized erythrocyte (PPE). Supplementation of VP-SF with a lipid acid mixture improved B. bigemina proliferation in vitro culture, with a maximum PPE of 11.3%. Growth of B. bigemina in a perfusion bioreactor using VP-SFM medium supplemented with lipid mixture resulted in a PPE above 28%. In conclusion, we demonstrated that B. bigemina proliferated in an animal component-free medium supplemented with the fatty acid mixture. This innovation to B. bigemina in vitro culture method presented herein is an important source of biological material for live vaccine production and understanding the mechanisms and molecules involved in parasite attachment and invasion of bovine erythrocytes.
Evaluation of Volatile Organic Compounds Obtained from Breath and Feces to Detect Mycobacterium tuberculosis Complex in Wild Boar (Sus scrofa) in Doñana National Park, Spain
Authors: Nol Pauline , Ionescu Radu , Geremariam Welearegay Tesfalem , Barasona Jose Angel , Vicente Joaquin , de Jesus Beleño-Sáenz Kelvin , Barrenetxea Irati , Jose Torres Maria , Ionescu Florina , Rhyan Jack
Published: May 2020

The presence of Mycobacterium tuberculosis complex (MTBC) in wild swine, such as in wild boar (Sus scrofa) in Eurasia, is cause for serious concern. Development of accurate, efficient, and noninvasive methods to detect MTBC in wild swine would be highly beneficial to surveillance and disease management efforts in affected populations. Here, we describe the first report of identification of volatile organic compounds (VOC) obtained from the breath and feces of wild boar to distinguish between MTBC-positive and MTBC-negative boar. We analyzed breath and fecal VOC collected from 15 MTBC-positive and 18 MTBC-negative wild boar in Donaña National Park in Southeast Spain. Analyses were divided into three age classes, namely, adults (>2 years), sub-adults (12–24 months), and juveniles (<12 months). We identified significant compounds by applying the two-tailed statistical t-test for two samples assuming unequal variance, with an α value of 0.05. One statistically significant VOC was identified in breath samples from adult wild boar and 14 were identified in breath samples from juvenile wild boar. One statistically significant VOC was identified in fecal samples collected from sub-adult wild boar and three were identified in fecal samples from juvenile wild boar. In addition, discriminant function analysis (DFA) was used to build classification models for MTBC prediction in juvenile animals. Using DFA, we were able to distinguish between MTBC-positive juvenile wild boar and MTBC-negative juvenile wild boar using breath VOC or fecal VOC. Based on our results, further research is warranted and should be performed using larger sample sizes, as well as wild boar from various geographic locations, to verify these compounds as biomarkers for MTBC infection in this species. This new approach to detect MTBC infection in free-ranging wild boar potentially comprises a reliable and efficient screening tool for surveillance in animal populations.
Vasorelaxant Effects Induced by Red Wine and Pomace Extracts of Magliocco Dolce cv.
Authors: Carullo Gabriele , Ahmed Amer , Fusi Fabio , Sciubba Fabio , Di Cocco Maria Enrica , Restuccia Donatella , Spizzirri Umile Gianfranco , Saponara Simona , Aiello Francesca
Published: May 2020

Several epidemiological studies demonstrate that moderate (red) wine consumption may afford protection against cardiovascular diseases. Protection is ascribed to the biological activity of wine components, many of which, however, are discarded during winemaking. In vitro rat thoracic aorta rings contracted with phenylephrine or KCl were used to assess the vasorelaxant activity of extracts from wine pomaces (seeds and skins) of the Calabrian autochthonous grape variety Magliocco dolce (Arvino). NMR spectroscopy was used to ascertain their chemical composition. Data demonstrate that seed and skin, but not must, extracts are capable of relaxing vascular preparations in an endothelium-dependent manner, similarly to the red wine extract, due to the presence of comparable amounts of bioactive constituents. In rings pre-contracted with 20–30 mM KCl, only seed extracts showed a moderate relaxation. The most efficacious vasodilating extract (wine) showed a good antioxidant profile in both [(2,2-diphenyl-1-picrylhydrazyl)acid] radical (DPPH) and [2,2’-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid)] radical (ABTS) assays. In conclusion, winemaking from Magliocco dolce grape can provide potentially health-promoting by-products useful in cardiovascular disease management.
Exploring the Availability of Emergency Contraception in New Brunswick Pharmacies: A Mystery-Client Telephone Study
Authors: Borsella Madison , Foster Angel M.
Published: May 2020

Although levonorgestrel-only emergency contraceptive pills (LNg-ECPs) have been available over the counter in Canada for more than a decade, barriers to access persist. We aimed to obtain information about the availability and cost of LNg-ECPs in New Brunswick. Using a mystery-client study design, we called all 207 non-specialty pharmacies in the province posing as a 17-year-old woman seeking something to prevent pregnancy after sex. We evaluated the information provided for accuracy and quality. The overwhelming majority of pharmacies (n = 180, 87%) had at least one brand of LNg-ECPs in stock; the price averaged CAD28.69 (USD21.65). Although the majority of pharmacy representatives provided accurate information about LNg-ECPs, a small number made incorrect statements about the timeframe for use, side effects, and mechanism of action. In nine interactions (4%) pharmacy representatives incorrectly indicated that a male partner could not obtain LNg-ECPs; none indicated that parental involvement was required to procure LNg-ECPs. None of the pharmacy representatives referenced any other modality of emergency contraception, including ulipristal acetate. Our findings suggest that LNg-ECPs are widely available and that most pharmacy representatives are providing accurate medical and regulatory information. However, supporting the continuing education of pharmacists and pharmacy staff, particularly around alternative modalities of emergency contraception, appears warranted.
Tracking Australian Hajj Pilgrims’ Health Behavior before, during and after Hajj, and the Effective Use of Preventive Measures in Reducing Hajj-Related Illness: A Cohort Study
Authors: Alqahtani Amani Salem , Tashani Mohamed , Heywood Anita Elizabeth , Almohammed Abdulrahman Bader S. , Booy Robert , Wiley Kerrie Elizabeth , Rashid Harunor
Published: May 2020

This study assessed Australian Hajj pilgrims’ knowledge, attitude and practices throughout their Hajj journey to understand their health behaviors, use of preventative measures and development of illness symptoms. A prospective cohort study with data collection at three phases (before, during and after Hajj) was conducted among Australian pilgrims between August and December 2015. Baseline data were collected from 421 pilgrims before Hajj, with 391 providing follow-up data during Hajj and 300 after their home return. Most participants (78% [329/421]) received one or more recommended vaccines; travel agents’ advice was the main factor affecting vaccination uptake. Most participants (69% [270/391]) practiced hand hygiene with soap and sanitizers frequently, followed by disposable handkerchief use (36% [139/391]) and washing hands with water only (28% [111/391]). During Hajj 74% (288/391) of participants reported one or more illness symptoms, 86% (248/288) of these symptoms were respiratory. Cough was less often reported among pilgrims who received vaccinations, cleaned their hands with soap or alcoholic hand rubs, while a runny nose was less common among those who frequently washed their hands with plain water but was more common among those who used facemasks. This study reveals that most Australian Hajj pilgrims complied with key preventative measures, and that tour group operators’ advice played an important role in compliance. Pilgrims who were vaccinated and practiced hand hygiene were less likely to report infection symptoms.
‘He Will Rescue Us Again’: Affliction and Hope in 2 Corinthians 1:8–11
Authors: Winter Sean F.
Published: May 2020

Dark times can generate crippling despair all too easily. Resources for resistance to despair and for the discovery and articulation of hope are not always readily apparent. This essay considers Paul’s account of his own immersion in such a situation: An ‘affliction’ that left him ‘unbearably crushed’, ‘despairing of life itself’ (2 Cor 1:9), and under a ‘sentence of death’ (2 Cor 1:10). Making a speculative proposal about the nature of Paul’s experience, the essay goes on to argue that Paul identified two fundamental resources for hope. The first is a conviction about an eschatological act that undoes the sentence of death and effects the possibility of rescue or deliverance. The second is a form of human solidarity that generates potential reorientation to the reality of ‘rescue’. While the essay explores these ideas within the terms and framework of Paul’s rhetoric in 2 Corinthians, it will do so with one clear eye on the potential resources that Pauline theology offers those who live in inexplicably dark times today, not least by considering the potential resources for political optimism.
Conversion to Orthodox Christianity in Uganda: A Hundred Years of Spiritual Encounter with Modernity, 1919–2019
Authors: Bondarenko Dmitri M. , Tutorskiy Andrey V.
Published: May 2020

In 1919, three Ugandan Anglicans converted to Orthodox Christianity, as they became sure that this was Christianity’s original and only true form. In 1946, Ugandan Orthodox Christians aligned with the Eastern Orthodox Church of Alexandria. Since the 1990s, new trends in conversion to Orthodox Christianity in Uganda can be observed: one is some growth in the number of new converts to the canonical Orthodox Church, while another is the appearance of new Orthodox Churches, including parishes of the Russian Orthodox Church Outside of Russia and the Russian Orthodox Old-Rite Church. The questions we raise in this article are: Why did some Ugandans switch from other religions to Orthodox Christianity in the first half of the 20th century and in more recent years? Were there common reasons for these two developments? We argue that both processes should be understood as attempts by some Ugandans to find their own way in the modern world. Trying to escape spiritually from the impact of colonialism, post-coloniality, and globalization, they viewed Catholicism, Anglicanism, and Islam as part of the legacy they rejected. These people did not turn to African traditional beliefs either. They already firmly saw their own tradition as Christian, but were (and are) seeking its “true”, “original” form. We emphasize that by rejecting post-colonial globalist modernity and embracing Orthodox Christianity as the basis of their own “alternative” modernity, these Ugandans themselves turn out to be modern products, and this speaks volumes about the nature of conversion in contemporary Africa. The article is based on field evidence collected in 2017–2019 as well as on print sources.
Shushtarī’s Treatise on the Limits of Theology and Sufism: Discursive Knowledge (ʿilm), Direct Recognition (maʿrifa), and Mystical Realization (taḥqīq) in al-Risāla al-Quṣāriyya
Authors: Casewit Yousef
Published: May 2020

Abū l-Ḥasan al-Shushtarī’s (d. 668/1269) heretofore unedited and unstudied treatise, “On the Limits [of Theology and Sufism]” (R. al-Quṣāriyya) is a succinct account of the celebrated Andalusī Sufi poet’s understanding of the relationship between discursive knowledge (ʿilm) of the rational Ashʿarite theologians, direct and unitive recognition (maʿrifa) of the Sufis, and verified knowledge (taḥqīq) of the monist Realizers. Following a broad discussion of the major trends in Sufism that form the background out of which Shushtarī emerges, this article analyzes the Quṣāriyya and presents a full English translation and Arabic edition of this text. The Quṣāriyya is a treatise on epistemology that was written in order to provide guidance to a disciple on how to respond to accusations of doctrinal heresy and deviation from the revealed Law. As such, it offers a window into Shushtarī’s thought as well as his understanding of his own place within the 7th/13th century Islamic intellectual tradition. The hierarchy of knowledge that he outlines represents an early response to the growing epistemological debates between what may be called “monotheist Ashʿarites,” “monist-inclined Sufis,” and fully fledged “monist Realizers.” The differences between these three perspectives lie in how each understands God’s bestowal of existence (ījād) and, consequently, the ontological status of the created realm. The Ashʿarites are “monotheists” because they inhabit an atomistic creation that actually exists by virtue of God’s existentiating command. For them, God transcends creation, and creation proves the existence of a transcendent Creator. The Sufis, for their part, incline toward the monists for whom God is the sole Reality, and for whom all else is nonexistent (ʿadam). However, they begin by affirming the logic of the Ashʿarite monotheist paradigm, and as they acquire direct recognition of God through spiritual purification, they assert that the Creator proves the existence of creation, because the latter is an “empty tent” sustained by the divine command. Finally, the “monist” Realizer maintains that nothing other than God exists. Having realized the truths that the theologians speculate about and that the Sufis begin to experience, the Realizers can engage, affirm, and refute both groups at their respective levels without committing to the cosmological doctrines of Ashʿarism, the ontological categories of Avicennan philosophy, or even the Sufi conception of the spiritual path to God.
Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review
Authors: Risbøl Ole , Langhammer Daniel , Schlosser Mauritsen Esben , Seitsonen Oula
Published: May 2020

This paper gives a presentation of how airborne laser scanning (ALS) has been adopted in archaeology in the North over the period 2005–2019. Almost two decades have passed since ALS first emerged as a potential tool to add to the archaeologist’s toolbox. Soon after, it attracted the attention of researchers within archaeological communities engaged with remote sensing in the Fenno-Scandinavian region. The first archaeological ALS projects gave immediate good results and led to further use, research, and development through new projects that followed various tracks. The bulk of the research and development focused on studying how well-suited ALS is for identifying, mapping, and documenting archaeological features in outfield land, mainly in forested areas. The poor situation in terms of lack of information on archaeological records in outfield areas has been challenging for research and especially for cultural heritage management for a long period of time. Consequently, an obvious direction was to study how ALS-based mapping of cultural features in forests could help to improve the survey situation. This led to various statistical analyses and studies covering research questions related to for instance effects on detection success of laser pulse density, and the size and shape of the targeted features. Substantial research has also been devoted to the development and assessment of semi-automatic detection of archaeological features based on the use of algorithms. This has been studied as an alternative approach to human desk-based visual analyses and interpretations of ALS data. This approach has considerable potential for detecting sites over large regions such as the vast roadless and unbuilt wilderness regions of northern Fennoscandia, and has proven highly successful. In addition, the current review presents how ALS has been employed for monitoring purposes and for landscape studies, including how it can influence landscape understanding. Finally, the most recent advance within ALS research and development has been discussed: testing of the use of drones for data acquisition. In conclusion, aspects related to the utilization of ALS in archaeological research and cultural heritage management are summarized and discussed, together with thoughts about future perspectives.
Spatial Downscaling of MODIS Chlorophyll-a with Genetic Programming in South Korea
Authors: Mohebzadeh Hamid , Yeom Junho , Lee Taesam
Published: May 2020

Chlorophyll-a (Chl-a) is one of the major indicators for water quality assessment and recent developments in ocean color remote sensing have greatly improved the ability to monitor Chl-a on a global scale. The coarse spatial resolution is one of the major limitations for most ocean color sensors including Moderate Resolution Imaging Spectroradiometer (MODIS), especially in monitoring the Chl-a concentrations in coastal regions. To improve its spatial resolution, downscaling techniques have been suggested with polynomial regression models. Nevertheless, polynomial regression has some restrictions, including sensitivity to outliers and fixed mathematical forms. Therefore, the current study applied genetic programming (GP) for downscaling Chl-a. The proposed GP model in the current study was compared with multiple polynomial regression (MPR) to different degrees (2nd-, 3rd-, and 4th-degree) to illustrate their performances for downscaling MODIS Chl-a. The obtained results indicate that GP with R2 = 0.927 and RMSE = 0.1642 on the winter day and R2 = 0.763 and RMSE = 0.5274 on the summer day provides higher accuracy on both winter and summer days than all the applied MPR models because the GP model can automatically produce appropriate mathematical equations without any restrictions. In addition, the GP model is the least sensitive model to the changes in the input parameters. The improved downscaling data provide better information to monitor the status of oceanic and coastal marine ecosystems that are also critical for fisheries and fishing farming.
Integrating National Ecological Observatory Network (NEON) Airborne Remote Sensing and In-Situ Data for Optimal Tree Species Classification
Authors: Scholl Victoria , Cattau Megan , Joseph Maxwell , Balch Jennifer
Published: May 2020

Accurately mapping tree species composition and diversity is a critical step towards spatially explicit and species-specific ecological understanding. The National Ecological Observatory Network (NEON) is a valuable source of open ecological data across the United States. Freely available NEON data include in-situ measurements of individual trees, including stem locations, species, and crown diameter, along with the NEON Airborne Observation Platform (AOP) airborne remote sensing imagery, including hyperspectral, multispectral, and light detection and ranging (LiDAR) data products. An important aspect of predicting species using remote sensing data is creating high-quality training sets for optimal classification purposes. Ultimately, manually creating training data is an expensive and time-consuming task that relies on human analyst decisions and may require external data sets or information. We combine in-situ and airborne remote sensing NEON data to evaluate the impact of automated training set preparation and a novel data preprocessing workflow on classifying the four dominant subalpine coniferous tree species at the Niwot Ridge Mountain Research Station forested NEON site in Colorado, USA. We trained pixel-based Random Forest (RF) machine learning models using a series of training data sets along with remote sensing raster data as descriptive features. The highest classification accuracies, 69% and 60% based on internal RF error assessment and an independent validation set, respectively, were obtained using circular tree crown polygons created with half the maximum crown diameter per tree. LiDAR-derived data products were the most important features for species classification, followed by vegetation indices. This work contributes to the open development of well-labeled training data sets for forest composition mapping using openly available NEON data without requiring external data collection, manual delineation steps, or site-specific parameters.
Precise Orbit and Clock Products of Galileo, BDS and QZSS from MGEX Since 2018: Comparison and PPP Validation
Authors: Li Xingxing , Zhu Yiting , Zheng Kai , Yuan Yongqiang , Liu Gege , Xiong Yun
Published: May 2020

In recent years, the development of new constellations including Galileo, BeiDou Navigation Satellite System (BDS) and Quasi-Zenith Satellite System (QZSS) have undergone dramatic changes. Since January 2018, about 30 satellites of the new constellations have been launched and most of the new satellites have been included in the precise orbit and clock products provided by the Multi Global Navigation Satellite System (Multi-GNSS) Experiment (MGEX). Meanwhile, critical issues including antenna parameters, yaw-attitude models and solar radiation pressure models have been continuously refined for these new constellations and updated into precise MGEX orbit determination and precise clock estimation solutions. In this context, MGEX products since 2018 are herein assessed by orbit and clock comparisons among individual analysis centers (ACs), satellite laser ranging (SLR) validation and precise point positioning (PPP) solutions. Orbit comparisons showed 3D agreements of 3–5 cm for Galileo, 8–9 cm for BDS-2 inclined geosynchronous orbit (IGSO), 12–18 cm for BDS-2 medium earth orbit (MEO) satellites, 24 cm for BDS-3 MEO and 11–16 cm for QZSS IGSO satellites. SLR validations demonstrated an orbit accuracy of about 3–4 cm for Galileo and BDS-2 MEO, 5–6 cm for BDS-2 IGSO, 4–6 cm for BDS-3 MEO and 5–10 cm for QZSS IGSO satellites. Clock products from different ACs generally had a consistency of 0.1–0.3 ns for Galileo, 0.2–0.5 ns for BDS IGSO/MEO and 0.2–0.4 ns for QZSS satellites. The positioning errors of kinematic PPP in Galileo-only mode were about 17–19 mm in the north, 13–16 mm in the east and 74–81 mm in the up direction, respectively. As for BDS-only PPP, positioning accuracies of about 14, 14 and 49 mm could be achieved in kinematic mode with products from Wuhan University applied.
Application of Luojia 1-01 Nighttime Images for Detecting the Light Changes for the 2019 Spring Festival in Western Cities, China
Authors: Zhang Chengye , Pei Yanqiu , Li Jun , Qin Qiming , Yue Jun
Published: May 2020

This study analyzed changes in nighttime light during the 2019 Spring Festival using Luojia 1-01 nighttime images in six western cities of China (Chengdu, Panzhihua, Kunming, Yuxi, Lhasa, and Jinchang). First, the radiance of the nighttime images was calculated. Second, the light area (LA) and average light intensity (ALI) were estimated for both Spring Festival and non-festival dates. Third, the differences in LA and ALI between the Spring Festival and non-festival were analyzed for all six cities. Migration population data from Baidu Inc. were used to examine the relationship between the changes of nighttime light and the population migration. The results show that, during the non-festival to Spring Festival period, the decrease in LA values coincided with negative net immigration. During the Spring Festival to non-festival period, the LA values increased, which coincided with positive net immigration. The F-test shows that the positive linear relationship between the normalized change in LA and the normalized net immigration is significant at the 0.05 level. This strongly indicates that population migration causes changes in LA. Moreover, while the population is considerably less in these cities during the Spring Festival, the ALI is noticeably higher, which suggests that urban activities are intensified during this period. This study demonstrates the applicability of using Luojia 1-01 nighttime images to detect the nighttime light changes for the Spring Festival in western cities, China, which can then be used to evaluate population migration and urban activities in the Spring Festival. Considering the higher spatial resolution of Luojia 1-01 than NPP (National Polar-orbiting Partnership) / VIIRS (Visible infrared Imaging Radiometer), this study may inspire more applications of Luojia 1-01 to track the activities in a variety of festival-cultures and cities.
Assessing Meteorological and Agricultural Drought in Chitral Kabul River Basin Using Multiple Drought Indices
Authors: Baig Muhammad Hasan Ali , Abid Muhammad , Khan Muhammad Roman , Jiao Wenzhe , Amin Muhammad , Adnan Shahzada
Published: May 2020

Drought is a complex and poorly understood natural hazard in complex terrain and plains lie in foothills of Hindukush-Himalaya-Karakoram region of Central and South Asia. Few research studied climate change scenarios in the transboundary Chitral Kabul River Basin (CKRB) despite its vulnerability to global warming and importance as a region inhabited with more than 10 million people where no treaty on use of water exists between Afghanistan and Pakistan. This study examines the meteorological and agricultural drought between 2000 and 2018 and their future trends from 2020 to 2030 in the CKRB. To study meteorological and agricultural drought comprehensively, various single drought indices such as Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI) and Vegetation Condition Index (VCI), and combined drought indices such as Scaled Drought Condition Index (SDCI) and Microwave Integrated Drought Index (MIDI) were utilized. As non-microwave data were used in MIDI, this index was given a new name as Non-Microwave Integrated Drought Index (NMIDI). Our research has found that 2000 was the driest year in the monsoon season followed by 2004 that experienced both meteorological and agricultural drought between 2000 and 2018. Results also indicate that though there exists spatial variation in the agricultural and meteorological drought, but temporally there has been a decreasing trend observed from 2000 to 2018 for both types of droughts. This trend is projected to continue in the future drought projections between 2020 and 2030. The overall study results indicate that drought can be properly assessed by integration of different data sources and therefore management plans can be developed to address the risk and signing new treaties.
Improving 3-m Resolution Land Cover Mapping through Efficient Learning from an Imperfect 10-m Resolution Map
Authors: Dong Runmin , Li Cong , Fu Haohuan , Wang Jie , Li Weijia , Yao Yi , Gan Lin , Yu Le , Gong Peng
Published: May 2020

Substantial progress has been made in the field of large-area land cover mapping as the spatial resolution of remotely sensed data increases. However, a significant amount of human power is still required to label images for training and testing purposes, especially in high-resolution (e.g., 3-m) land cover mapping. In this research, we propose a solution that can produce 3-m resolution land cover maps on a national scale without human efforts being involved. First, using the public 10-m resolution land cover maps as an imperfect training dataset, we propose a deep learning based approach that can effectively transfer the existing knowledge. Then, we improve the efficiency of our method through a network pruning process for national-scale land cover mapping. Our proposed method can take the state-of-the-art 10-m resolution land cover maps (with an accuracy of 81.24% for China) as the training data, enable a transferred learning process that can produce 3-m resolution land cover maps, and further improve the overall accuracy (OA) to 86.34% for China. We present detailed results obtained over three mega cities in China, to demonstrate the effectiveness of our proposed approach for 3-m resolution large-area land cover mapping.
Identification of Wheat Yellow Rust Using Spectral and Texture Features of Hyperspectral Images
Authors: Guo Anting , Huang Wenjiang , Ye Huichun , Dong Yingying , Ma Huiqin , Ren Yu , Ruan Chao
Published: May 2020

Wheat yellow rust is one of the most destructive diseases in wheat production and significantly affects wheat quality and yield. Accurate and non-destructive identification of yellow rust is critical to wheat production management. Hyperspectral imaging technology has proven to be effective in identifying plant diseases. We investigated the feasibility of identifying yellow rust on wheat leaves using spectral features and textural features (TFs) of hyperspectral images. First, the hyperspectral images were preprocessed, and healthy and yellow rust-infected samples were obtained by creating regions of interest. Second, the extraction of spectral reflectance characteristics and vegetation indices (VIs) were performed from the preprocessed hyperspectral images, and the TFs were extracted using the grey-level co-occurrence matrix from the images transformed by principal component analysis. Third, the successive projections algorithm was employed to choose the optimum wavebands (OWs), and correlation-based feature selection was employed to select the optimal VIs and TFs (those most sensitive to yellow rust and having minimal redundancy between features). Finally, identification models of wheat yellow rust were established using a support vector machine and different features. Six OWs (538, 598, 689, 702, 751, and 895 nm), four VIs (nitrogen reflectance index, photochemical reflectance index, greenness index, and anthocyanin reflectance index), and four TFs (correlation 1, correlation 2, entropy 2, and second moment 3) were selected. The identification models based on the OWs, VIs, and TFs provided overall accuracies of 83.3%, 89.5%, and 86.5%, respectively. The TF results were especially encouraging. The models with the combination of spectral features and TFs exhibited better performance than those using the spectral features or TFs alone. The accuracies of the models with the combined features (OWs and TFs, Vis, and TFs) were 90.6% and 95.8%, respectively. These values were 7.3% and 6.3% higher, respectively, than those of the models using only the OWs or VIs. The model with the combined feature (VIs and TFs) had the highest accuracy (95.8%) and was used to map the yellow rust lesions on wheat leaves with different damage levels. The results showed that the yellow rust lesions on the leaves could be identified accurately. Overall, the combination of spectral features and TFs of hyperspectral images significantly improved the identification accuracy of wheat yellow rust.
Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters
Authors: Mukherjee Lipi , Zhai Peng-Wang , Gao Meng , Hu Yongxiang , A. Franz Bryan , Werdell P. Jeremy
Published: May 2020

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.
Statistical Gap-Filling of SEVIRI Land Surface Temperature
Authors: Dumitrescu Alexandru , Brabec Marek , Cheval Sorin
Published: May 2020

A reliable and practically useable method for gap filling in hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI LST) data using ERA5 Land Skin Temperature (ERA5ST) co-variate and additional easily accessible data (elevation, time, solar radiation info) is proposed. The suggested approach provides estimates to all weather conditions and it is based on a probabilistic model via modern regression models. We have tested two classes of regression models of different complexity and flexibility, namely multiple linear regression (MLR), and generalized additive model (GAM). This analysis uses as main input the hourly LST data set over Romania, through 2016 and 2017, extracted from MSG-SEVIRI images, which is an operational product of the Land Surface Analysis–Satellite Application Facility (LSA-SAF). The comparison between the estimated LST and the original LST values shows that GAM model, that takes into account the distance between missing LST locations and the nearest non-missing locations (GAM2), provides the best results, hence this was used to fill the gaps from the analyzed remote sensing product. Considering the fact that the best covariate (ERA5ST) has global coverage and it is available at high spatial resolution and temporal resolution, the proposed approach could be also used to perform the gap-filling of other existing LST remote sensing products.
Column Integrated Water Vapor and Aerosol Load Characterization with the New ZEN-R52 Radiometer
Authors: Almansa Antonio Fernando , Cuevas Emilio , Barreto África , Torres Benjamín , García Omaira Elena , Delia García Rosa , Velasco-Merino Cristian , Cachorro Victoria Eugenia , Berjón Alberto , Mallorquín Manuel , López César , Ramos Ramón , Guirado-Fuentes Carmen , Negrillo Ramón , de Frutos Ángel Máximo
Published: May 2020

The study shows the first results of the column-integrated water vapor retrieved by the new ZEN-R52 radiometer. This new radiometer has been specifically designed to monitor aerosols and atmospheric water vapor with a high degree of autonomy and robustness in order to allow the expansion of the observations of these parameters to remote desert areas from ground-based platforms. The ZEN-R52 device shows substantial improvements compared to the previous ZEN-R41 prototype: a smaller field of view, an increased signal-to-noise ratio, better stray light rejection, and an additional channel (940 nm) for precipitable water vapor (PWV) retrieval. PWV is inferred from the ZEN-R52 Zenith Sky Radiance (ZSR) measurements using a lookup table (LUT) methodology. The improvement of the new ZEN-R52 in terms of ZSR was verified by means of a comparison with the ZEN-R41, and with the Aerosol Robotic Network (AERONET) Cimel CE318 (CE318-AERONET) at Izaña Observatory, a Global Atmosphere Watch (GAW) high mountain station (Tenerife, Canary Islands, Spain), over a 10-month period (August 2017 to June 2018). ZEN-R52 aerosol optical depth (AOD) was extracted by means of the ZEN–AOD–LUT method with an uncertainty of ±0.01 ± 0.13*AOD. ZEN-R52 PWV extracted using a new LUT technique was compared with quasi-simultaneous (±30 s) Fourier Transform Infrared (FTIR) spectrometer measurements as reference. A good agreement was found between the two instruments (PWV means a relative difference of 9.1% and an uncertainty of ±0.089 cm or ±0.036 + 0.061*PWV for PWV <1 cm). This comparison analysis was extended using two PWV datasets from the same CE318 reference instrument at Izaña Observatory: one obtained from AERONET (CE318-AERONET), and another one using a specific calibration of the 940-nm channel performed in this work at Izaña Atmospheric Research Center Observatory (CE318-IARC), which improves the PWV product.
Geostatistical Based Models for the Spatial Adjustment of Radar Rainfall Data in Typhoon Events at a High-Elevation River Watershed
Authors: Wang Keh-Han , Chu Ted , Yang Ming-Der , Chen Ming-Cheng
Published: May 2020

Geographical constraints limit the number and placement of gauges, especially in mountainous regions, so that rainfall values over the ungauged regions are generally estimated through spatial interpolation. However, spatial interpolation easily misses the representation of the overall rainfall distribution due to undersampling if the number of stations is insufficient. In this study, two algorithms based on the multivariate regression-kriging (RK) and merging spatial interpolation techniques were developed to adjust rain fields from unreliable radar estimates using gauge observations as target values for the high-elevation Chenyulan River watershed in Taiwan. The developed geostatistical models were applied to the events of five moderate to high magnitude typhoons, namely Kalmaegi, Morakot, Fungwong, Sinlaku, and Fanapi, that struck Taiwan in the past 12 years, such that the QPESUMS’ (quantitative precipitation estimation and segregation using multiple sensors) radar rainfall data could be reasonably corrected with accuracy, especially when the sampling conditions were inadequate. The interpolated rainfall values by the RK and merging techniques were cross validated with the gauge measurements and compared to the interpolated results from the ordinary kriging (OK) method. The comparisons and performance evaluations were carried out and analyzed from three different aspects (error analysis, hyetographs, and data scattering plots along the 45-degree reference line). Based on the results, it was clearly shown that both of the RK and merging methods could effectively produce reliable rainfall data covering the study watershed. Both approaches could improve the event rainfall values, with the root-mean-square error (RMSE) reduced by up to roughly 30% to 40% at locations inside the watershed. The averaged coefficient of efficiency (CE) from the adjusted rainfall data could also be improved to the level of 0.84 or above. It was concluded that the original QPESUMS rainfall data through the process of RK or merging spatial interpolations could be corrected with better accuracy for most stations tested. According to the error analysis, relatively, the RK procedure, when applied to the five typhoon events, consistently made better adjustments on the original radar rainfall data than the merging method did for fitting to the gauge data. In addition, the RK and merging methods were demonstrated to outperform the univariate OK method for correcting the radar data, especially for the locations with the issues of having inadequate numbers of gauge stations around them or distant from each other.
Local, Daily, and Total Bio-Optical Models of Coastal Waters of Manfredonia Gulf Applied to Simulated Data of CHRIS, Landsat TM, MIVIS, MODIS, and PRISMA Sensors for Evaluating the Error
Authors: Cavalli Rosa Maria
Published: May 2020

The spatial–temporal resolution of remote data covers coastal water variability, but this approach offers a lower accuracy than in situ observations. Two of the major error sources occur due to the parameterization of bio-optical models and spectral capability of the remote data. These errors were evaluated by exploiting data acquired in the coastal waters of Manfredonia Gulf. Chlorophyll-a concentrations, absorption of the colored dissolved organic material at 440 nm (aCDOM440nm), and tripton concentrations measured in situ varied between 0.09–1.76 mgm−3, 0.00–0.41 m−1, and 1.97–8.90 gm−3. In accordance with the position and time of in situ surveys, 36 local models, four daily models, and one total bio-optical model were parameterized and validated using in situ data before applying to Compact High-Resolution Imaging Spectrometer (CHRIS) mode 1, CHRIS mode 2, Landsat Thematic Mapper (TM), Multispectral Infrared and Visible Imaging Spectrometer (MIVIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Precursore Iperspettrale della Missione Applicativa (PRISMA) simulated data. Concentrations retrieved from PRISMA data using local models highlighted the smallest errors. Because tripton abundance is great and tripton absorptions were better resolved than those of chlorophyll-a and colored dissolved organic material (CDOM), tripton concentrations were adequately retrieved from all data using total models, while only local models adequately retrieved chlorophyll-a concentrations and aCDOM440nm from CHRIS mode 1, CHRIS mode 2, MIVIS, and MODIS data. Therefore, the application of local models shows smaller errors than those of daily and total models; however, the capability to resolve the absorption of water constituents and analyze their concentration range can dictate the model choice. Consequently, the integration of more models allows us to overcome the limitations of the data and sensors.
The Impact of Canopy Reflectance on the 3D Structure of Individual Trees in a Mediterranean Forest
Authors: Jurado J. , Ramos M. , Enríquez C. , Feito F.
Published: May 2020

The characterization of 3D vegetation structures is an important topic, which has been addressed by recent research in remote sensing. The forest inventory requires the proper extraction of accurate structural and functional features of individual trees. This paper presents a novel methodology to study the impact of the canopy reflectance on the 3D tree structure. A heterogeneous natural environment in a Mediterranean forest, in which various tree species (pine, oak and eucalyptus) coexist, was covered using a high-resolution digital camera and a multispectral sensor. These devices were mounted on an Unmanned Aerial Vehicle (UAV) in order to observe the tree architecture and the spectral reflectance at the same time. The Structure from Motion (SfM) method was applied to model the 3D structures using RGB images from the high-resolution camera. The geometric accuracy of the resulting point cloud was validated by georeferencing the study area through multiple ground control points (GCPs). Then, the point cloud was enriched with the reflected light in four narrow-bands (green, near-infrared, red and red-edge). Furthermore, the Normalized Difference Vegetation Index (NDVI) was calculated in order to measure the tree vigor. A comprehensive analysis based on structural and spectral features of individual trees was proposed. A spatial segmentation was developed to detect single-trees in a forest and for each one to identify the crown and trunk. Consequently, structural parameters were extracted, such as the tree height, the diameter at breast height (DBH) and the crown volume. The validation of these measurements was performed by field data, which were taken using a Total Station (TS). In addition, these characteristics were correlated with the mean reflectance in the tree canopy. Regarding the observed tree species, a statistical analysis was carried out to study the impact of reflectance on the 3D tree structure. By applying our method, a more detailed knowledge of forest dynamics can be gained and the impact of available solar irradiance on single-trees can be analyzed.