Earth Science Research Research Articles

Subimal Ghosh Receives 2020 Devendra Lal Memorial Medal

Subimal Ghosh was awarded the 2020 Devendra Lal Memorial Medal at the virtual AGU Fall Meeting in December. The medal is for “outstanding Earth and/or space sciences research by a scientist belonging to and working in a developing country.”

COBRA: A Research Accelerator for the Crustal Ocean Biosphere

Abstract The deep seafloor covers two-thirds of Earth's surface area, but our understanding of the ecosystems and resources found in the deep ocean, as well as the ability of deep-sea ecosystems to withstand human perturbation, is limited. These deep-sea habitats demand urgent study as there are emergent human uses in the form of deep-sea mining and carbon sequestration that will fundamentally alter physical, chemical, and biological conditions that took millions of years to establish. We propose the international network COBRA, a research accelerator for the crustal ocean biosphere. COBRA will bring together diverse stakeholders and experts, including interdisciplinary academic and government scientists, private institutions, policy makers, data systems engineers, industry experts, and others to coordinate efforts that generate new knowledge and inform decision making about activities that could affect the deep ocean and, by extension, all of society. We will also train the next generation of leaders in ocean exploration, science, and policy through an innovative virtual program to carry this effort into future generations of ocean and earth science research. COBRA will inform policies relating to emergent industrial uses of the deep ocean, decrease the likelihood of serious harm to the environment, and maintain ecosystem services for the benefit of society.

Trends in the Collaboration Pattern of Moroccan Research in Earth Sciences from 1984 to 2019: A Case Study

The output of the Moroccan researchers in Earth sciences and their collaboration trends were studied for the period 1984-2019 using the example of the Journal of African Earth Sciences, the preferred journal of this community, and by using simple bibliometric indicators such as collaboration rate and collaboration level. The main results of the study are: (1) Moroccan researchers participated in 253 articles among which, only 12 were singleauthor papers. Multi-authorship is the rule with a mode of 4 authors per paper for 45 articles; (2) the number of authors reached 1251 in all papers. When only international collaboration is considered, 1051 authors are found, from which about 48% are from Morocco and 52% belong to other 31 countries; (3) International collaboration, which was exclusively with French researchers and institutions until the 1990s, grew in number but declined in share to 33- 42% in the last 15 years, while collaboration with other countries became more important because of the internationalization of research programs.

Stalagmite Layers Reveal Hidden Climate Stories

A global investigation discovers where annually laminated stalagmites are found, analyzes their growth properties, and explains how they can be best used in Earth science research.

Semantic Segmentation of High Resolution Satellite Imagery using Generative Adversarial Networks with Progressive Growing

ABSTRACT With increase in urbanization and Earth Sciences research into urban areas, the need to quickly and accurately segment urban rooftop maps has never been greater. Current machine learning techniques struggle to produce high accuracy maps in dense urban zones where there is high image noise and foot print overlap. In this paper, we evaluate a training methodology for pixel-wise segmentation for high-resolution satellite imagery using progressive growing of generative adversarial networks as a solution. We apply our model to segmenting building rooftops and compare these results to conventional methods for rooftop segmentation. We evaluate our approach using the SpaceNet version 2 and xView datasets. Our experiments show that for SpaceNet, progressive Generative Adversarial Network (GAN) training achieved a test accuracy of 93% compared to 89% for traditional GAN training and 87% for U-Net architecture, while for xView, we achieved 71% accuracy using progressive GAN training compared to 69% through traditional GAN training and 65% using U-Net.

A Review of Machine Learning Applications in Land Surface Modeling

Machine learning (ML), as an artificial intelligence tool, has acquired significant progress in data-driven research in Earth sciences. Land Surface Models (LSMs) are important components of the climate models, which help to capture the water, energy, and momentum exchange between the land surface and the atmosphere, providing lower boundary conditions to the atmospheric models. The objectives of this review paper are to highlight the areas of improvement in land modeling using ML and discuss the crucial ML techniques in detail. Literature searches were conducted using the relevant key words to obtain an extensive list of articles. The bibliographic lists of these articles were also considered. To date, ML-based techniques have been able to upgrade the performance of LSMs and reduce uncertainties by improving evapotranspiration and heat fluxes estimation, parameter optimization, better crop yield prediction, and model benchmarking. Widely used ML techniques used for these purposes include Artificial Neural Networks and Random Forests. We conclude that further improvements in land modeling are possible in terms of high-resolution data preparation, parameter calibration, uncertainty reduction, efficient model performance, and data assimilation using ML. In addition to the traditional techniques, convolutional neural networks, long short-term memory, and other deep learning methods can be implemented.

Rapid Response and Novel Research in Earth Science (NASA)

Rapid Response and Novel Research in Earth Science (NASA)

The risk of catastrophic climate change: Future energy implications

Increasing discussion is occurring, in both the popular media and scientific research papers, about the risk of catastrophic climate change (CCC). Earth Science researchers have produced evidence that the damage function from ongoing climate change is not linear: damages rise disproportionately with global average temperature increase. This short paper explores the implications of CCC for future energy forecasting and policy. It is argued that the time available is now too short to continue framing the problem solution in terms of a shift to zero carbon fuels or carbon dioxide removal. Also, given the large uncertainties remaining in forecasting future climate—especially regional precipitation—solar radiation management is likely too risky. Instead, major reductions in global fossil fuel energy are needed, largely through energy conservation. The global response to the current pandemic shows the potential for rapid social change in the face of a crisis.

The Effect of DEM on the Land Use/Cover Classification Accuracy of Landsat OLI Images

Land use provides crucial data for earth science research and its accuracy has always been a hot topic. Various auxiliary data are used to improve the classification accuracy of land use. The digital elevation model (DEM) is one of the common auxiliary data since topography directly affects the surface landscape. However, few researches focus on the impact of the DEM on the classification accuracy of images. In this study, the terrain steepness index (TSI) was initially put forward to study the effect of the DEM on the classification accuracy of the land use/cover. Seven areas with different terrain were taken as the studied areas and the classification and regression tree was utilized to derive thematic land use/cover maps. It indicated that the DEM had an impact on classification accuracy in a certain TSI extent. The developed quadratic model accurately described the correlation between the DEM and the TSI. Based on the model, the DEM with 30 m resolution had a positive impact on the classification accuracy, when the TSI varies from 9.106 to 34.014. It was concluded that the TSI index for the DEM could be effectively used in the land use/cover classification.

Reviewer Acknowledgements for Earth Science Research, Vol. 10, No. 1

Reviewer Acknowledgements for Earth Science Research, Vol. 10, No. 1, 2021.

Very High Spatial Resolution Downscaled SMAP Radiometer Soil Moisture in the CONUS Using VIIRS/MODIS Data

Satellite remote sensing has been providing passive microwave soil moisture (SM) retrievals of a global spatial coverage and a high revisit frequency for research and applications in earth and environmental sciences, specifically after the soil moisture active and passive (SMAP) was launched in 2015. But, the spatial resolution of SM data is restricted to tens of kilometers, which is insufficient for regional or watershed scale studies. In this article, an SM downscaling algorithm was developed based on the vegetation modulated apparent thermal inertia relationship between SM and changes in land surface temperature (LST). The algorithm used data sets from the North America Land Data Assimilation System Noah model outputs and the advanced very high resolution radiometer data of the long term data record from 1981 to 2018. Here, the downscaling model was applied to visible/infred LST data from the visible infrared imaging radiometer suite at 400-m and the moderate resolution imaging spectroradiometer at 1 km to downscale the L2 radiometer half-orbit 9 km SMAP SM from 2018 to 2019 for the contiguous United States. The 400-m/1-km downscaled SM products were validated using 125 in situ SM ground measurements acquired from the International Soil Moisture Network. The validation results summarized by SM network show that the overall unbiased RMSE for 400-m of the improved/original downscaling algorithms and 1-km SM outperform 9-km SM by 0.01, 0.007, and 0.012 m3/m3 volumetric soil moisture, respectively, which indicates a fairly good performance of the downscaling algorithm. It is also found that precipitation has an impact on the 9-km SMAP SM.

Key Points of Geoscience Research and Its Future Development Trend

In recent years, with the development of economy and the progress of society, the people’s thinking consciousness level has been continuously improved, thus effectively promoting the development and deepening of earth science research work. Researchers say that as one of the important basic disciplines, the number of disciplines involved in earth science is relatively complex, and among them, the contents studied by a large number of disciplines are closely related to human survival. Therefore, it is of great significance and value for the improvement and optimization of the earth’s ecological environment to effectively promote the rational implementation and deepening of the earth’s scientific research. In this study, by sorting out and analyzing a large number of data of geoscience research work at home and abroad, the researchers made an in-depth analysis and exploration of the key points of geoscience research work at home and abroad and the future development trend of geoscience research work, aiming at pointing out the direction for the development of geoscience research work in China, thus laying a good foundation and guarantee for improving and optimizing the comprehensive quality of geoscience research work.

Discussion on the Current Situation of China's Geoscience Talent Team and Suggestions for Future Development

A large number of research data show that since the state approved the current situation of China’s geoscientists and the Chinese geologist database project in 1989, the construction of geoscientists has always been a key issue in China’s scientific field. In recent years, with the continuous improvement and optimization of comprehensive national strength, China has paid more attention to earth science research work, thus effectively promoting the construction of earth science talents. However, after a lot of practice, the researchers said that at present, there are still some deficiencies in the process of training and building geoscience talents in China, which greatly improved the level of geoscience research in China. In order to solve this problem, the researchers analyzed a large number of data, and put forward corresponding suggestions on the training of geoscience talents in China, aiming at further promoting the rational optimization of geoscience talents in China.

Geodiversity Assessment with Crowdsourced Data and Spatial Multicriteria Analysis

This paper presents an approach to geodiversity assessment based on spatial multicriteria analysis. Instead of relying solely on weighted linear combination (WLC) for aggregating factor ratings and weights to compute a synthetic measure of geodiversity, the approach employs WLC in concert with its local version called L-WLC to provide a more comprehensive assessment approach. As part of the approach, the assessment input data comprised of geodiversity factor ratings and weights were obtained through crowdsourcing. A geoinformation crowdsourcing tool called the geo-questionnaire was used to obtain data from 57 Earth science researchers worldwide. These data served as the bases for a group assessment of geodiversity. The reliability of assessment was evaluated by means of spatially explicit uncertainty analysis. The results showed the efficacy of local spatial multicriteria analysis techniques (L-WLC) used in concert with a global technique (WLC) on the example of geodiversity assessment for Karkonosze National Park in southwestern Poland.

Using Remote Sensing to Discover Historic Context of Human‐Environmental Water Resource Dynamics

AbstractAnalysis of historic and contemporary high‐resolution imagery can help to fill knowledge gaps in land cover and management history in locations where documentation is non‐existent or records are difficult to access. Historic imagery dating back to the 1960s can be used to structure quantitative investigation and mapping of land use and land cover change across space and time to enhance earth science, policy, and social science research. Imagery can further inform municipal planning and implementation in areas of natural resource allocation, infrastructure, and hazard mitigation. For management and public education, historic imagery can help people to understand environmental processes and the impacts of human activity in the local environment. Here we emphasize the value of high‐resolution historic satellite imagery from the Corona and Keyhole satellite programs to inform environmental research, public education, and environmental management. Within the Region of Arequipa in southern Peru we highlight examples of urban development, agricultural expansion, river channelization, and glacial retreat via comparison of historic and modern satellite imagery. By incorporating these types of historic imagery data in formats accessible to non‐professionals, public engagement as well as research into human‐environmental investigations will be greatly enhanced.

Quantitative author inputs to Earth science research publications: survey results, insights and potential applications

AbstractResults are reported of what is believed to be the first survey of the quantitative contributions Earth scientists make to their research publications. Based on a return of 26 (from 45; 254 total documents), two key patterns are observed. For most articles, there is a steady decrease in the roles of the first through fifth authors. The former fall from 65 ± 14% for two-author outputs, to 52 ± 9% for five, to 46 ± 10% for ten; fifth authors are perceived as having contributed 5–6%. The term ‘balanced’ is used to describe such contributor lists. The second pattern, which is labelled ‘imbalanced’, is recognized with teams of five or more and involves the first author shouldering a disproportionately large amount of the work; consequently, the inputs of the third and lesser authors range from small to negligible (5–1%). In some cases, it is observed in a few of a researcher’s publications (≤3); in others, it is more pervasive. There are two basic explanations: estimation problems and excessive numbers of authors, which can be split into two and three subcategories, respectively. The key features of the survey data are dwelt upon. The work concludes with an exploration of a proposed H-Index-type metric that is weighted by the contribution fractions a researcher makes to their publications. This, I contend, would be more reflective of their impact.

BOOK REVIEW. Annalen des Naturhistorischen Museums in Wien, Serie A, 113 (2011), dedicated to the 60th birthday of Werner E. Piller.

This volume is a collection of papers dedicated to Werner E. Piller (Vienna, 27th May, 1951) by some of his colleagues on the occasion of his 60th birthday. The papers deal with some of the many facets of Piller’s research fields, investigations that may help to show a more complete general picture of the Earth history The book comprises 24 papers, by a total of 54 authors (see the web page at http://www.nhmwien.ac.at/verlag/wissenschaftliche_publikationen/annalen_serie_a/113_2011). The introduction of F.F. Steininger is an excellent summary to the Piller’s academic life spent so far in Vienna and Graz (Austria). The papers focus on Piller’s main Earth Science research fields, ranging from systematics and facies analysis, through stratigraphy and biostratigraphy, to ecology and palaeoecology. Most of the papers deals with facies (siliciclastic, carbonates, pelagic and shallow water sediments) and Recent and fossil biotic assemblages (in reference order: dinoflagellates, cold-water corals, coralline red algae, calcareous sponges, gastropods, bryozoans, brachiopods, water strides, turtles, mammals, dasycladalean green algae, marine ostracods, ophiuroids). Those researchers, who work in the above-mentioned fields, certainly know and often use results obtained by Werner Piller. However, those who know him personally, recognizing his important contribution to Earth Sciences, enjoy marvellous features of his extraordinary personality.

Crustal structure of the metasedimentary Kisseynew domain and bounding volcanic–plutonic domains, Trans-Hudson orogen, Canada

The Kisseynew domain (KD) is the largest component of the Paleoproterozoic Trans-Hudson orogen (THO) in Saskatchewan and Manitoba. It is bounded to the north by the Lynn Lake – Leaf Rapids (LL-LR) domain and to the south by the Glennie – Flin Flon (G-FF) complex. The THO was the focus of one of the study areas of Lithoprobe, Canada’s national Earth science research project (1984–2005). To further investigate the crustal structure of the KD and its bounding domains, this study reprocesses reflection line S3a across its northern boundary, analyses four 2.5-D gravity profiles, carries out 3-D gravity inversions for two areas, and replicates results from reflection lines 7 and 10 across the southern boundary of the KD. The reprocessed seismic section enhances the continuity of reflections within the crust. The reflectivity is representative of the complex tectonic development of the boundary zone and clearly identifies a subsurface deformation zone consistent with the boundary. The reflection section also shows that a lower plate (at about 30 to 50 km depth), interpreted as remnant lower crust of the G-FF complex, extends 30 km further northward than in the original section. Lines 7 and 10 illustrate the complex nature of the transition from the KD to the G-FF complex. The gravity analyses show that the variability and complexities of the boundary region between the LL-LR domain and KD, and the G-FF complex and KD, as indicated by the geological and Bouguer gravity maps, extend at depth throughout the crust.

Drones: tecnología con futuro promisorio en la gestión forestal

La variabilidad climática plantea importantes retos que actualmente enfrentan los ecosistemas forestales. Para mejorar el entendimiento de sus procesos vitales es necesario contar con tecnologías de vanguardia, una de los cuales son los vehículos aéreos no tripulados (VANT) que desempeñan un papel fundamental. Si bien, los VANT se han usado para diferentes tareas y servicios; existe un vacío de información sobre el estado del arte de los enfoques, usos y tendencias en la gestión forestal. Este estudio es una aportación al conocimiento, en términos de volumen de investigación a través del tiempo; diferenciada por revistas y por países; artículos y autores más influyentes; redes de colaboración científica; tipos de vegetación y campos de estudio; hardware y software relevante utilizado. Los resultados mostraron 117 artículos científicos publicados del 2012 al 2019, principalmente de China y Estados Unidos de América, y cinco clústeres de colaboración científica. Los estudios se enfocaron, principalmente, en los atributos individuales de la estructura forestal, inventarios y monitoreo del vigor forestal. Los bosques templados fueron los ecosistemas más estudiados alrededor del mundo, mientras que los drones de multirrotor los más usados con el sensor RGB de DJI como la marca líder dominante. El Photoscan fue el programa fotogramétrico más aplicado en investigación forestal. Por último, se confirma que el uso de los VANT se ha expandido exponencialmente en el último lustro. En México, se prevé que dicho potencial se incremente, a partir de su megadiversidad, gran tradición forestal y los investigadores que están especializándose en el tema.

Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses.

The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to handle. Therefore, the use of low-cost radar sensors is becoming more relevant. In this article, to make the usage of radar simpler and more efficient, we developed with automotive radar technology. We introduce basic radar techniques and present two radar sensors with their specifications. To record the radar data, we developed a system with an integrated camera and sensors. The weight of the whole system is about 315 g for the small radar and 450 g for the large one. The whole system was integrated into a UAV and test flights were performed. After that, several flights were carried out, to verify the system with both radar sensors. Thereby, the records provide an insight into the radar data. We demonstrated that the recording system works and the radar sensors are suitable for the usage in a UAV and future earth science research because of its autonomy, precision, and lightweight.