Spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River during the period 2002–2011 based on the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) data

Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.

Monitoring Wildfires in Thailand: A Case Study of the ECSTAR-TeroSpace’s Earth Observation Project

The primary objective of this paper is to present a comprehensive case study on monitoring wildfires in Nakhon Nayok, Thailand, utilizing Earth observation platforms. This initiative project has been undertaken by the Excellence Center of Space Technology and Research (ECSTAR), in partnership with its spin-off startup, TeroSpace. The study aims to provide an in-depth analysis of the wildfire incidents in the region, utilizing advanced technologies such as satellite imagery and data analytics, and to identify ways to improve future wildfire management. In particular, the paper focuses on the wildfires including thermal area comparison that ravaged the land in Nakhon Nayok Province in central Thailand from March to April 18th, 2023. To conduct this study, the ECSTAR-TeroSpace analytic team utilized satellite images from Earth observation platforms: MODIS and Sentinel-2A. By presenting this case study, this paper contributes to the broader understanding of how to monitor and manage wildfires in a changing climate. The findings of this study underscore the importance of proactive and collaborative efforts in mitigating the negative impacts of wildfires in Nakhon Nayok and other regions in Thailand.

Concept Design,Modeling and Station-keeping Attitude Control of an Earth Observation Platform

The stratosphere airship provides a unique and promising platform for earth observation. Researches on the project design and control scheme for earth observation platforms are still rarely documented. Nonlinear dynamics, model uncertainties, and external disturbances contribute to the difficulty in maneuvering the stratosphere airship. A key technical challenge for the earth observation platform is station keeping, or the ability to remain fixed over a geo-location. This paper investigates the conceptual design, modeling and station-keeping attitude control of the near-space earth observation platform. A conceptual design of the earth observation platform is presented. The dynamics model of the platform is derived from the Newton-Euler formulation, and the station-keeping control system of the platform is formulated. The station-keeping attitude control approach for the platform is proposed. The multi-input multi-output nonlinear control system is decoupled into three single-input single-output linear subsystems via feedback linearization, the attitude controller design is carried out on the new linear systems using terminal sliding mode control, and the global stability of the closed-loop system is proven by using the Lyapunov theorem. The performance of the designed control system is simulated by using the variable step Runge-Kutta integrator. Simulation results show that the control system tracks the commanded attitude with an error of zero, which verify the effectiveness and robustness of the designed control system in the presence of parametric uncertainties. The near-space earth observation platform has several advantages over satellites, such as high resolution, fast to deploy, and convenient to retrieve, and the proposed control scheme provides an effective approach for station-keeping attitude control of the earth observation platform.

Improved algorithms to plan missions for agile earth observation satellites

This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.

Progress of Earth Observation in China

China is expanding and sharing its capacity for Earth observation by developing sensors,platforms,and launch capabilities in tandem with growing lunar and deep space exploration.China is considering the Moon as a viable Earth observation platform to provide high-quality,planetary-scale data.The platform would produce consistent spatiotemporal data because of its long operational life and the geological stability of the Moon.China is also quickly improving its capabilities in processing and transforming Earth observation data into useful and practical information.Programs such as the Big Earth Data Science Engineering Program(CASEarth)provide opportunities to integrate data and develop“Big Earth Data”platforms to add value to data through analysis and integration.Such programs can offer products and services independently and in collaboration with international partners for data-driven decision support and policy development.With the rapid digital transformation of societies,and consequently increasing demand for big data and associated products,Digital Earth and the Digital Belt and Road Program(DBAR)allow Chinese experts to collaborate with international partners to integrate valuable Earth observation data in regional and global sustainable development.

Recent Progress of Earth Science Satellite Missions in China

Earth Science from Space is an interdisciplinary discipline that studies the interactions,mechanisms,and evolution of the Earth system through space observation.In China,the national medium-to long-term civilian space infrastructure development plan and the space-science pilot project from the Chinese Academy of Sciences are two programs associated with advancing the Earth science from space.This paper reports recent scientific findings,developments and the status of the six missions.It is organized as the following sections:Introduction,two satellite missions that are already in orbit—the TanSat-1 for atmospheric COand the LuTan-1 for global surface deformation,a Terrestrial Ecosystem Carbon Inventory Satellite to be launched in 2022,and three missions that passed the PhaseⅡstudy and planned for near future—the Ocean Surface Current multiscale Observation,the Terrestrial Water Resources Satellite.Climate and Atmospheric Components Exploring Satellites(CACES),followed by the conclusion.

The Potential of Earth Observation Based Indicators to Assess the State of Urban Environment: An Application for the Urban Agglomeration of Athens

Earth observation (EO) provides the opportunity for periodic and spatially detailed assessment of the state of the environment in urban areas. In this study, the potential of EO based indicators (EI) to assess the state of environment in the urban agglomeration of Athens (UAA) is examined. EO based indicators as used in the study, include land surface temperature, land use, land cover and aerosols distribution. The indicators are also related to the household density and population density, as extracted from census data, for the same area. Indicators are applied at the municipal scale and are also used to estimate an aggregate environmental indicator (AEI), at municipal scale, by integrating all indicators mentioned above in a GIS environment. It is found that the urban agglomeration of Athens is practically “dichotomized”, by being divided in a western and eastern area, with considerably different environmental conditions. Results are considered important for focused interventions supporting environmental urban planning, whereas they represent the high potential of EO based indicators to monitor and assess the state of the urban environment.

Astrometry of three near Earth asteroids with the Lijiang 2.4 m telescope

Under the framework of observational campaigns organized by the GAIA Follow Up Network for Solar System Objects, three near Earth asteroids, 367943 Duende, 99942 Apophis and 2013 TV135, were observed with the Lijiang 2.4m telescope administered by Yunnan Observatories. The software package PRISM was used to calibrate the CCD fields and measure the positions of 99942 Apophis and 2013 TV135, and our own software was used for 367943 Duende. A comparison of the results show that the ephemerides of INPOP10a and JPL are consistent for 99942 Apophis and 2013 TV135, however, they are quite inconsistent for 367943 Duende. Moreover, we have found that differences between the mean values in the ephemerides of INPOP10a and JPL are about 72＂ and -199＂ in right ascension and declination respectively for 367943 Duende. Moreover, the ephemeris published by JPL is reliable in terms of the mean observed-minus-calculated （O - C） residuals in right ascension and declination of about 2.72＂ and 1.49＂ respectively.

China's Observation Network For Earth's Crust Movement Now Operational

An observation network focusing on earthquakes wascompleted one year aheadof schedule and put into operationrecently. According to scientists, this135-million-yuan (U.S.$16.3million) project could also be usedfor geodetic surveying, ionosphereand sea-level observations,

Virtual earth cloud: a multi-cloud framework for enabling geosciences digital ecosystems

Humankind is facing unprecedented global environmental and social challenges in terms of food,water and energy security,resilience to natural hazards,etc.To address these challenges,international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan.The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions(providing the best available knowledge)and avoid potentially negative impacts on society and the environment.Such knowledge platforms must build on the recent and next coming digital technologies that have transformed society–including the science and engineering sectors.Big Earth Data(BED)science aims to provide the methodologies and instruments to generate knowledge from numerous,complex,and diverse data sources.BED science requires the development of Geoscience Digital Ecosystems(GEDs),which bank on the combined use of fundamental technology units(i.e.big data,learning-driven artificial intelligence,and network-based computing platform)to enable the development of more detailed knowledge to observe and test planet Earth as a whole.This manuscript contributes to the BED science research domain,by presenting the Virtual Earth Cloud:a multi-cloud framework to support GDE implementation and generate knowledge on environmental and social sustainability.

Applying Earth Observation Technologies to Economic Consequence Modeling:A Case Study of COVID‑19 in Los Angeles County,California

Earth observation(EO) technologies,such as very high-resolution optical satellite data available from Maxar,can enhance economic consequence modeling of disasters by capturing the fine-grained and real-time behavioral responses of businesses and the public.We investigated this unique approach to economic consequence modeling to determine whether crowd-sourced interpretations of EO data can be used to illuminate key economic behavioral responses that could be used for computable general equilibrium modeling of supply chain repercussions and resilience effects.We applied our methodology to the COVID-19 pandemic experience in Los Angeles County,California as a case study.We also proposed a dynamic adjustment approach to account for the changing character of EO through longer-term disasters in the economic modeling context.We found that despite limitations,EO data can increase sectoral and temporal resolution,which leads to significant differences from other data sources in terms of direct and total impact results.The findings from this analytical approach have important implications for economic consequence modeling of disasters,as well as providing useful information to policymakers and emergency managers,whose goal is to reduce disaster costs and to improve economic resilience.

Comparison of TMI and AMSR-E sea surface temperatures with Argo near-surface temperatures over the global oceans

Satellite-derived sea surface temperatures（SSTs） from the tropical rainfall measuring mission（TRMM）microwave imager（TMI） and the advanced microwave scanning radiometer for the earth observing system（AMSR-E） were compared with non-pumped near-surface temperatures（NSTs） obtained from Argo profiling floats over the global oceans. Factors that might cause temperature differences were examined, including wind speed, columnar water vapor, liquid cloud water, and geographic location. The results show that both TMI and AMSR-E SSTs are highly correlated with the Argo NSTs; however, at low wind speeds, they are on average warmer than the Argo NSTs. The TMI performs slightly better than the AMSR-E at low wind speeds, whereas the TMI SST retrievals might be poorly calibrated at high wind speeds. The temperature differences indicate a warm bias of the TMI/AMSR-E when columnar water vapor is low, which can indicate that neither TMI nor AMSR-E SSTs are well calibrated at high latitudes. The SST in the Kuroshio Extension region has higher variability than in the Kuroshio region. The variability of the temperature difference between the satellite-retrieved SSTs and the Argo NSTs is lower in the Kuroshio Extension during spring. At low wind speeds, neither TMI nor AMSR-E SSTs are well calibrated, although the TMI performs better than the AMSR-E.

Earth Observation Brain(EOB):an intelligent earth observation system

Since the twenty-first century,with the rapid development of high-resolution earth observation satellites,the earth observation satellite system has developed from the initial single satellite observation model to the current satellite constellation formed by light and small satellites observation model.All-weather and all-directional fine earth observation can now be realized.In the future,the satellite constellation,communication satellites,navigation satellites,and aircrafts are linked through dynamic linking network to form an air-space information network to realize real-time services of intelligent air-space information.To further enhance the perception,cognition,and quick response ability of the network,we propose the concept and model of the Earth Observation Brain(EOB)−the intelligent earth system based on events perception in this paper.Then,some key technologies needed to be solved in the EOB are also described.An application example is illustrated to show the process of perception and cognition in the primary stage of the EOB.In the future,EOB can observe what change of what object,the when and where to push these right information to mobile terminal of right people at the right time and right place.Global users can obtain any data,information,and knowledge in real-time through the EOB.

Reactive scheduling of multiple EOSs under cloud uncertainties:model and algorithms

Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.

Earth observation satellite data receiving, processing system and data sharing

The China Remote Sensing Satellite Ground Station was established in 1986.It currently has three receiving stations in the north,west,and south of China,with the capacity to receive data from 15 international and domestic Earth observation satellites covering the entire Chinese territory and 70%of Asia.Meanwhile,a systematic,integrated,and standardized spatial information service system has been built.A data-sharing project for medium-resolution Earth observation satellites has been conducted and plays an important role in land,ocean,and atmospheric resource investigation and environmental monitoring.

Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm

This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling problem.Based on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the population.The results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.

Distributed cooperative task planning algorithm for multiple satellites in delayed communication environment

Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.

Optimization of earth observation satellite system based on parallel systems and computational experiments

Earth observation satellite system （EOSS） is the main space platform to collect ground information. Op- timization of EOSS is still a difficult problem, as it is a complex system concerning a great deal of design variables and uncertain factors. To solve the problem, an optimization framework based on parallel system and computational experi- ments is proposed. An artificial system for EOSS is firstly constructed, which is the integration of resource data, task data, environment data and related operation rules. Real EOSS together with artificial EOSS constitute the parallel systems for EOSS. Based on the parallel systems, concept of computational experiments is detailed. Moreover, surrogate models are built to approximate real EOSS. Genetic algorithm and improved general pattern search method are adopted to optimize the model. According to the framework, a case study is carried out. Through the results, we illustrated the proposed framework to be useful and effective for EOSS optimization problem.

Think global,cube local:an Earth Observation Data Cube’s contribution to the Digital Earth vision

The technological landscape for managing big Earth observation(EO)data ranges from global solutions on large cloud infrastructures with web-based access to self-hosted implementations.EO data cubes are a leading technology for facilitating big EO data analysis and can be deployed on different spatial scales:local,national,regional,or global.Several EO data cubes with a geographic focus(“local EO data cubes”)have been implemented.However,their alignment with the Digital Earth(DE)vision and the benefits and trade-offs in creating and maintaining them ought to be further examined.We investigate local EO data cubes from five perspectives(science,business and industry,government and policy,education,communities and citizens)and illustrate four examples covering three continents at different geographic scales(Swiss Data Cube,semantic EO data cube for Austria,DE Africa,Virginia Data Cube).A local EO data cube can benefit many stakeholders and players but requires several technical developments.These developments include enabling local EO data cubes based on public,global,and cloud-native EO data streaming and interoperability between local EO data cubes.We argue that blurring the dichotomy between global and local aligns with the DE vision to access the world’s knowledge and explore information about the planet.

Collecting volunteered geographic information from the Global Navigation Satellite System(GNSS):experiences from the CAMALIOT project

Raw observations(carrier-phase and code observations)from the Global Navigation Satellite System(GNSS)can now be accessed from Android mobile phones(Version 7.0 onwards).This paves the way for GNSS data to be utilized for low-cost precise positioning or in ionospheric or tropospheric applications.This paper presents results from data collection campaigns using the CAMALIOT mobile app.In the frst campaign,116.3 billion measurements from 11,828 mobile devices were collected from all continents.Although participation decreased during the second campaign,data are still being collected globally.In this contribution,we demonstrate the potential of volunteered geographic information(VGl)from mobile phones to fill data gaps in geodetic station networks that collect GNSS data,e.g.in Brazil,but also how the data can provide a denser set of observations than current networks in countries across Europe.We also show that mobile phones capable of dual-frequency reception,which is an emerging technology that can provide a richer source of GNSS data,are contributing in a substantial way.Finally,we present the results from a survey of participants to indicate that participation is diverse in terms of backgrounds and geography,where the dominant motivation for participation is to contribute to scientific research.