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,

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.

Recent Progress of Earth Observation Satellites in China

Currently,China has 32 Earth observation satellites in orbit.The satellites can provide various data such as optical,multispectral,infrared,and radar.The spatial resolution of China Earth observation satellites ranges from low to medium to high.The satellites possess the capability to observe across multiple spectral bands,under all weather conditions,and at all times.The data of China Earth observation satellites has been widely used in fields such as natural resource detection,environmental monitoring and protection,disaster prevention and reduction,urban planning and mapping,agricultural and forestry surveys,land survey and geological prospecting,and ocean forecasting,achieving huge social benefits.This article introduces the recent progress of Earth observation satellites in China since 2022,especially the satellite operation,data archiving,data distribution and data coverage.

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.

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.

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.

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.

General modeling and optimization technique for real-world earth observation satellite scheduling

Over the last two decades,many modeling and optimization techniques have been developed for earth observation satellite(EOS)scheduling problems,but few of them show good generality to be engineered in realworld applications.This study proposes a general modeling and optimization technique for common and real-world EOS scheduling cases;it includes a decoupled framework,a general modeling method,and an easy-to-use algorithm library.In this technique,a framework that decouples the modeling,constraints,and optimization of EOS scheduling problems is built.With this framework,the EOS scheduling problems are appropriately modeled in a general manner,where the executable opportunity,another format of the well-known visible time window per EOS operation,is viewed as a selectable resource to be optimized.On this basis,10 types of optimization algorithms,such as Tabu search and genetic algorithm,and a parallel competitive memetic algorithm,are developed.For simplified EOS scheduling problems,the proposed technique shows better performance in applicability and effectiveness than the state-of-the-art algorithms.In addition,a complicatedly constrained real-world benchmark exampled by a four-EOS Chinese commercial constellation is provided,and the technique is qualified and outperforms the in-use scheduling system by more than 50%.

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.

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.

Current and near-term advances in Earth observation for ecological applications

There is an unprecedented array of new satellite technologies with capabilities for advancing our understanding of ecological processes and the changing composition of the Earth’s biosphere at scales from local plots to the whole planet.We identified 48 instruments and 13 platforms with multiple instruments that are of broad interest to the environmental sciences that either collected data in the 2000s,were recently launched,or are planned for launch in this decade.We have restricted our review to instruments that primarily observe terrestrial landscapes or coastal margins and are available under free and open data policies.We focused on imagers that passively measure wavelengths in the reflected solar and emitted thermal spectrum.The suite of instruments we describe measure land surface characteristics,including land cover,but provide a more detailed monitoring of ecosystems,plant communities,and even some species then possible from historic sensors.The newer instruments have potential to greatly improve our understanding of ecosystem functional relationships among plant traits like leaf mass area(LMA),total nitrogen content,and leaf area index(LAI).They provide new information on physiological processes related to photosynthesis,transpiration and respiration,and stress detection,including capabilities to measure key plant and soil biophysical properties.These include canopy and soil temperature and emissivity,chlorophyll fluorescence,and biogeochemical contents like photosynthetic pigments(e.g.,chlorophylls,carotenoids,and phycobiliproteins from cyanobacteria),water,cellulose,lignin,and nitrogen in foliar proteins.These data will enable us to quantify and characterize various soil properties such as iron content,several types of soil clays,organic matter,and other components.Most of these satellites are in low Earth orbit(LEO),but we include a few in geostationary orbit(GEO)because of their potential to measure plant physiological traits over diurnal periods,improving estimates of water and carbon budgets.We also include a few spaceborne active LiDAR and radar imagers designed for quantifying surface topography,changes in surface structure,and 3-dimensional canopy properties such as height,area,vertical profiles,and gap structure.We provide a description of each instrument and tables to summarize their characteristics.Lastly,we suggest instrument synergies that are likely to yield improved results when data are combined.

A Fast Insertion Tabu Search with Conflict-Avoidance Heuristic for the Multisatellite Multimode Crosslink Scheduling Problem

An agile earth-observing satellite equipped with multimode cameras capable of transmitting observation data to other satellites is developed to rapidly respond to requests with multiple observation modes.This gives rise to the Multisatellite Multimode Crosslink Scheduling(MMCS)problem,which involves allocating observation requests to agile satellites,selecting appropriate timing and observation modes for the requests,and transmitting the data to the ground station via the satellite communication system.Herein,a mixed integer programming model is introduced to include all complex time and operation constraints.To solve the MMCS problem,a two-stage heuristic method,called Fast insertion Tabu Search with Conflict-avoidance(FTS-C)heuristic,is developed.In the first stage,a conflict-avoidance insertion algorithm is designed to generate a high-quality initial solution by considering the requests transmission and download.Further,the tabu search-based second stage optimizes the initial solution.Finally,an extensive empirical study based on a real-world situation demonstrates that FTS-C can generate a solution with higher quality in less time than other state-of-the-art algorithms and the CPLEX solver.