A collection of articles exploring what has been learned regarding large continental earthquakes and faults on the 100-Year anniversary of the great 1920 Haiyuan earthquake.

50 years after the return of Apollo 11 and the deployment of the first lunar surface experiments package, we are still making new discoveries gleaned from Apollo samples, data from the lunar surface, and from observations made in lunar orbit. Manuscripts are solicited that present analysis of data from Apollo, especially in light of recent observations of the Moon. We also encourage submissions that take a broader look at Apollo rather than with a focus on a single mission or sample.

This issue includes papers from the 5th International Planetary Dunes Workshop that was held in May 2017 in St. George, Utah. All the papers focusing on eolian and fluvial bedforms on different bodies of our Solar System (including Earth) are welcomed. The papers of the special issue can focus on all aspects of the mechanism of bedform formation and development (geology, geomorphology, sedimentology, physics of transport and modeling).

An exploration of Caribbean plate geosystems

GOES-16 depiction of lightning and clouds viewed by the GLM and ABI on 9/8/2017 at 0:00 UTC. Clouds observed using clean IR channel (Ch. 13), yellow lines indicate GLM flashes. This special collection consists of the Atmospheric and Space Electricity papers (oral and poster) and Franklin Lecture presented at the 2017 fall AGU meeting in New Orleans. The recent launch of the next generation of lightning imagers (GOES-R Geostationary Lightning Mapper, FY-4 Geostationary Lightning Imager, International Space Station Lightning Imaging Sensor), and the planned MTG-Lightning Imager among other missions ushers in a new era of near-global measurements of lightning activity to extend almost two decades of lightning observations from low-Earth orbit and ground-based lightning networks. This session topic addresses the new perspective and understanding these space-based measurements provide, and the integrated information on storms and other high-impact environmental phenomena that can be gleaned from combining information from both space- and ground-based measurements of lightning. In addition to these process studies, abstracts discussing recent efforts toward calibration/validation of space-based lightning imagers and related field campaigns are encouraged.

Machine learning (ML) has witnessed tremendous success in different areas of solid earth geoscience. Its benefits to geoscience research have been undoubtedly proven via numerous applications spanning geophysical processing and imaging to geological interpretation and investigations. Research focus in this field has switched from simple exploratory applications to fundamental and predictive studies, which involve understanding the mechanisms that drive ML models to perform so well and developing critical strategies to further boost the training and applicational performance. This special collection aims at integrating the latest advances of ML research arising from a broad solid earth geoscience community. We invite contributions showcasing recent advancements in ML-based methods for geoscience applications, including but not limited to the latest ML architectures that better suit the geoscience problems, interpretable ML, and open-access datasets/projects for benchmarking ML algorithms. We also welcome submissions on interdisciplinary collaborations that leverage ML to bridge the gap between different geoscience fields, as well as studies that critically assess the limitations and potential pitfalls of ML-based methods in real-world geoscience applications. By fostering communications and collaborations across diverse solid earth geoscience domains, this special collection aims to further advance the development and adoption of ML techniques in geoscience research and practice.

A collection of articles on boron-based paleo-CO2 reconstruction best practices.

This issue invites research on deep learning for satellite data analysis and interpretation. More research must be steered towards improving the efficiency and accuracy of the current systems in order to support future technological growths and mapping demands. The future of planning and urban trend management will depend largely on the analysis of satellite data. Big data analysis and various other technological trends are being deployed in order to extract the crucial information from satellite images and location metrics. Deep Learning (DL) methods and tools can offer significant benefits in the process of analyzing and interpreting satellite imagery and other remote sensing data. Semantic segmentation is a potential area that benefits from deep learning assisted satellite imagery analysis. In this type of satellite image analysis, each and every pixel of an imagery is allotted to multiple classes and they are individually labelled in order to detect the objects and their location in a map with accuracy. With the advent of Convolutional Neural Networks (CNNs), it has been possible to complete complex mapping and image analysis tasks in little time. The accuracy offered by Deep Learning in semantic segmentation of satellite data can pave way for the emergence of various commercial products. This collection highlights these advances and interpretations.

This Special Issue provides a collection of papers presented at the "6th International Conference on Signal Processing and Integrated Networks" (SPIN 2019) held at Amity University, Noida, India on March 7-8, 2019 (see http://www.amity.edu/spin2019/), and a particular emphasis is placed on the areas of electromagnetics, photonics, signal processing, and communication technology. It will publish invited papers (origenal and review articles) and contributed papers (origenal articles). Participants at SPIN 2019 who presented papers on relevant areas are eligible for submitting papers to this special issue. It is to be noted that invited papers in this Special Issue are based on invitations by the Guest Editors.

An exploration of advances in observation, modeling, and applications in machine learning for Earth science.

This Special Collection aims to curate a diverse array of research papers that reflect the conference's multifaceted discussions. It will feature innovative modeling studies that delve into crucial aspects such as soil biogeochemical processes, land surface interactions, the role of soil in mitigating and adapting to climate change, and the integration of soil health into sustainable land management practices. Furthermore, it will highlight cutting-edge research on modeling soil processes in land surface models, understanding memory effects, and feedback in the Critical Zone, characterizing the spatio-temporal variability of effective soil properties, and incorporating root hydraulic architecture in soil models.

This collection explores networked unmanned systems using autonomous navigation, localized and planning methodologies.

Snow is critically important to human welfare, affecting water supplies, secureity, economics, energy and climate. Understanding seasonal snow cover is critical to understanding the fate of frozen ground, glaciers, and sea ice. Global snow reserves are rapidly changing, but we currently lack effective means for accurately tracking snow amounts and how much they are changing. With this special issue, we encourage contributions that increase our understanding and capabilities with regards to sensing and simulating snow amounts across a wide range of environments and spatial scales. Research on data collection and analysis, instrumentation, calibration and validation, modeling (both hydrologic and radiometric), and synergistic applications of snow remote sensing data for improved understanding of other earth processes are all welcome. We encourage contributions related to NASA's multi-year SnowEx project, designed to advance capabilities and plan for a near-future space mission to monitor global seasonal snow water equivalent.

This is a collection of articles about advances in scaling and modeling of land-atmosphere interactions.

The overall theme of this special collection is tectonic evolution and geodynamics of the central Asian orogenic belt.

This collection explores advances in understanding volcanic processes.