Land surface temperature (LST) is a crucial parameter that reflects land–atmosphere interaction and has thus attracted wide interest from geoscientists. Owing to the rapid development of Earth ...observation technologies, remotely sensed LST is playing an increasingly essential role in various fields. This review aims to summarize the progress in LST estimation algorithms and accelerate its further applications. Thus, we briefly review the most‐used thermal infrared (TIR) LST estimation algorithms. More importantly, this review provides a comprehensive collection of the widely used TIR‐based LST products and offers important insights into the uncertainties in these products with respect to different land cover conditions via a systematic intercomparison analysis of several representative products. In addition to the discussion on product accuracy, we address problems related to the spatial discontinuity, spatiotemporal incomparability, and short time span of current LST products by introducing the most effective methods. With the aim of overcoming these challenges in available LST products, much progress has been made in developing spatiotemporal seamless LST data, which significantly promotes the successful applications of these products in the field of surface evapotranspiration and soil moisture estimation, agriculture drought monitoring, thermal environment monitoring, thermal anomaly monitoring, and climate change. Overall, this review encompasses the most recent advances in TIR‐based LST and the state‐of‐the‐art of applications of LST products at various spatial and temporal scales, identifies critical further research needs and directions to advance and optimize retrieval methods, and promotes the application of LST to improve the understanding of surface thermal dynamics and exchanges.
Plain Language Summary
Land surface temperature (LST) is a crucial geophysical parameter related to surface energy and water balance of the land‐atmosphere system. Satellite remote sensing provides the best way to measure LST and generate various LST products at regional and global scales. In this review, to facilitate the application of LST products in different fields, we first present the physical meaning of satellite‐derived LST. Subsequently, we summarize recent advances in LST retrieval and validation methods, with a special focus on the state‐of‐the‐art product collections, product accuracies and intercomparisons, and main problems in current LST products as well as their possible solutions. Additionally, we also review the major applications of LST products in agricultural drought monitoring, thermal environment monitoring, thermal anomaly monitoring, and climate change. Finally, we offer recommendations or perspectives to promote LST retrieval methods and their applications. This review will aid the user in gaining a thorough comprehensive understanding of satellite‐derived LST products and promoting their appropriate applications.
Key Points
State‐of‐the‐art satellite‐derived land surface temperature (LST) product levels, sources, uncertainties, and differences are provided
Typical applications of LST products in various fields are summarized
Future directions for the generation and applications of LST products are recommended
This paper considers the joint design of transmit waveforms and receive filters for airborne multiple-input-multiple-output (MIMO) radar systems. The aim is to maximize the output ...signal-to-interference-plus-noise ratio (SINR) such that we can achieve enhanced detection performance for a slow-moving target that might be obscured by clutter and jamming. We devise a cyclic algorithm to tackle the non-convex joint design problem. Considering practical implementation issues, we extend the algorithm to deal with constrained designs (i.e., the design of waveforms under a constant-envelope constraint and a similarity constraint, respectively). The convergence of all the devised algorithms is guaranteed. We provide several numerical examples to demonstrate the effectiveness of the proposed algorithms.
Bioactive species, including reactive oxygen species (ROS, including O
2
&z.rad;
−
, H
2
O
2
, HOCl,
1
O
2
, &z.rad;OH, HOBr,
etc.
), reactive nitrogen species (RNS, including ONOO
−
, NO, NO
2
, ...HNO,
etc.
), reactive sulfur species (RSS, including GSH, Hcy, Cys, H
2
S, H
2
S
n
, SO
2
derivatives,
etc.
), ATP, HCHO, CO and so on, are a highly important category of molecules in living cells. The dynamic fluctuations of these molecules in subcellular microenvironments determine cellular homeostasis, signal conduction, immunity and metabolism. However, their abnormal expressions can cause disorders which are associated with diverse major diseases. Monitoring bioactive molecules in subcellular structures is therefore critical for bioanalysis and related drug discovery. With the emergence of organelle-targeted fluorescent probes, significant progress has been made in subcellular imaging. Among the developed subcellular localization fluorescent tools, ROS, RNS and RSS (RONSS) probes are highly attractive, owing to their potential for revealing the physiological and pathological functions of these highly reactive, interactive and interconvertible molecules during diverse biological events, which are rather significant for advancing our understanding of different life phenomena and exploring new technologies for life regulation. This review mainly illustrates the design principles, detection mechanisms, current challenges, and potential future directions of organelle-targeted fluorescent probes toward RONSS.
The dynamic fluctuations of bioactive species in living cells are associated with numerous physiological and pathological phenomena. The emergence of organelle-targeted fluorescent probes has significantly facilitated our understanding on the biological functions of these species. This review describes the design, applications, challenges and potential directions of organelle-targeted bioactive species probes.
With accelerating consumption of nonrenewable energy resource, mankind is currently facing the dilemma of energy crisis and global warming caused by excessive greenhouse gas emissions. ...Photoelectrocatalytic (PEC) technique to convert the main greenhouse gas CO2 into hydrocarbon fuels can solve these two issues with one stone. Herein, we summarize the latest developments of semiconductor-based PEC CO2 reduction for solar fuels production in a more comprehensive manner. Our endeavors start with elucidation of the fundamental principles of CO2 reduction technology and influencing factors of PEC CO2 reduction technique, followed by specific introduction on four quintessentially designed PEC CO2 reduction systems, and then multifarious photoelectrodes utilized for these photosystems are systematically introduced. Modification rationales for crafting photoelectrodes with high conversion efficiency and good stability are elucidated. Besides, strategies developed for fine-tuning of selectivity of PEC CO2 reduction products are also discussed. Finally, future outlooks and challenges in this booming research field are reviewed. It is anticipated that our Review would provide enriched and guided information on rational construction of high-performance photoelectrodes for solar-to-chemical fuels conversion.
The integration of Fe dopant and interfacial FeOOH into Ni‐MOFs Fe‐doped‐(Ni‐MOFs)/FeOOH to construct Fe−O−Ni−O−Fe bonding is demonstrated and the origin of remarkable electrocatalytic performance of ...Ni‐MOFs is elucidated. X‐ray absorption/photoelectron spectroscopy and theoretical calculation results indicate that Fe‐O−Ni−O−Fe bonding can facilitate the distorted coordinated structure of the Ni site with a short nickel–oxygen bond and low coordination number, and can promote the redistribution of Ni/Fe charge density to efficiently regulate the adsorption behavior of key intermediates with a near‐optimal d‐band center. Here the Fe‐doped‐(Ni‐MOFs)/FeOOH with interfacial Fe−O−Ni−O−Fe bonding shows superior catalytic performance for OER with a low overpotential of 210 mV at 15 mA cm−2 and excellent stability with ≈3 % attenuation after a 120 h cycle test. This study provides a novel strategy to design high‐performance Ni/Fe‐based electrocatalysts for OER in alkaline media.
Iron doping and FeOOH decorating leads to interfacial Fe−O−Ni−O−Fe bonding in Fe‐doped‐(Ni‐MOF)/FeOOH. This interfacial bonding can regulate the active Ni site to give the appropriate adsorption behavior of intermediates for the oxygen evolution reaction (OER). As a result, Fe‐doped‐(Ni‐MOF)/FeOOH shows outstanding catalytic performance with low overpotential, small Tafel slope, and high durability.
This paper proposes a different thermal channel combination split-window (DTCC-SW) method to estimate the land surface temperature (LST) and sea ST (SST) from the Chinese Gaofen-5 (GF-5) satellite ...thermal infrared (TIR) data. A nonlinear combination of two adjacent channels CH 8.20 (centered at <inline-formula> <tex-math notation="LaTeX">8.20~\mu \text{m} </tex-math></inline-formula>) and CH 8.63 (centered at <inline-formula> <tex-math notation="LaTeX">8.63~\mu \text{m} </tex-math></inline-formula>) was proposed to estimate LST for low-emissivity surfaces. A nonlinear combination of two adjacent channels, CH 10.80 (centered at <inline-formula> <tex-math notation="LaTeX">10.80~\mu \text{m} </tex-math></inline-formula>) and CH 11.95 (centered at <inline-formula> <tex-math notation="LaTeX">11.92~\mu \text{m} </tex-math></inline-formula>), was developed to estimate LST and SST for high-emissivity surfaces under dry atmospheric conditions, and a nonlinear combination of two channels, CH 8.63 and CH 11.95 , was used to estimate LST and SST for high-emissivity surfaces under wet atmospheric conditions. The numerical values of the DTCC-SW coefficients were obtained using a statistical regression method from synthetic data simulated with an accurate atmospheric radiative transfer model moderate spectral resolution atmospheric transmittance mode 5 over a wide range of atmospheric and surface conditions. The LST (SST), mean emissivity, and atmospheric water vapor content were divided into several tractable subranges to improve the fitting accuracy. The experimental results and the preliminary evaluation results showed that the root-mean-square error between the actual and estimated LSTs (SSTs) is less than 0.7 K (0.3 K), provided that the land surface emissivities are known, which indicates that the proposed DTCC-SW method can accurately estimate the LST and SST from the GF-5 TIR data.
Photodynamic therapy (PDT) is ineffective against deeply seated metastatic tumors due to poor penetration of the excitation light. Herein, we developed a biomimetic nanoreactor (bio-NR) to achieve ...synergistic chemiexcited photodynamic-starvation therapy against tumor metastasis. Photosensitizers on the hollow mesoporous silica nanoparticles (HMSNs) are excited by chemical energy in situ of the deep metastatic tumor to generate singlet oxygen (
O
) for PDT, and glucose oxidase (GOx) catalyzes glucose into hydrogen peroxide (H
O
). Remarkably, this process not only blocks the nutrient supply for starvation therapy but also provides H
O
to synergistically enhance PDT. Cancer cell membrane coating endows the nanoparticle with biological properties of homologous adhesion and immune escape. Thus, bio-NRs can effectively convert the glucose into
O
in metastatic tumors. The excellent therapeutic effects of bio-NRs in vitro and in vivo indicate their great potential for cancer metastasis therapy.
Viscosity, as a vital microenvironment parameter, is tightly associated with multitudinous cellular processes and diseases. Recently, precise visualization of viscosity has started to arouse more and ...more interest. However, owing to the complicated character, it is still a huge challenge to directly observe viscosity in living systems. In this regard, mounting fluorescence probes are being increasingly fabricated to map viscosity inside live cells and small animals. In this minireview, the viscosity‐sensitive small molecular fluorescent probes used in bioimaging are comprehensively summarized, mainly focusing on the last three years. Moreover, the current challenges and opportunities for the development of viscosity‐specific fluorescent probes will be discussed.
Viscosity, as a vital microenvironment parameter, is tightly associated with multitudinous cellular processes and diseases. In this minireview, the viscosity‐sensitive small molecular fluorescent probes used in bioimaging are comprehensively summarized, mainly focusing on the last three years. Moreover, the current challenges and opportunities for the development of viscosity‐specific fluorescent probes will be discussed.
In this study, the spatiotemporal change patterns and driving factors of land surface temperature (LST) on the Yunnan-Kweichow Plateau (YKP) during 2000–2020 are investigated by using the Thermal and ...Reanalysis Integrating Moderate-resolution Spatial-seamless (TRIMS) LST dataset provided by National Tibetan Plateau Data Center. The YKP LST spatiotemporal change patterns are revealed at annual, seasonal, monthly, and daily scales. Furthermore, seven driving factors such as air temperature, land cover types, normalized difference vegetation index, precipitation, solar radiation, elevation, and latitude are quantified the impacts on LST spatial heterogeneity at annual scale. The main findings are as follows: (1) Annual mean LST increases by 0.016 K/year. Annual mean daytime LST slightly decreases by 0.009 K/year. Annual mean nighttime LST significantly increases by 0.042 K/year. (2) The trend and seasonal components of the daily, daily mean daytime, and daily mean nighttime LST have five and four breakpoints respectively, indicating that the variation of LST is unstable during 2000–2020 on the YKP. (3) The LST lapse rates at nighttime are generally higher than those at daytime on the YKP at the annual, seasonal, and monthly scales. The LST maximum lapse rate is 0.59 K/100 m in summer nighttime, and the LST minimum lapse rate is 0.18 K/100 m in winter daytime. (4) The controlling effects of seven factors are generally stronger in the nighttime than those in the daytime. The factors of elevation and air temperature dominate the LST spatial distribution on the YKP, with a contribution rate of >70 %. In addition, the interactions among the seven factors are all enhancing the effects on the spatial distribution of annual mean LST, including bivariate enhancement and nonlinear enhancement. This study contributes to the mitigation and adaptation to climate change of LST in the plateau and plays a theoretical reference role in formulating corresponding policies for environmental protection.
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•Revealing the spatiotemporal variations of LST at annual, seasonal, monthly, and daily scales over the YKP, respectively.•Illustrating the variation pattern of LST and its attribution at annual scale over the YKP.•Estimating the lapse rates of LST by multiple linear regression model at annual, seasonal, monthly scales over the YKP.•Detecting the number of breakpoints of daily mean LST by BFAST algorithm at daily scale over the YKP.
Road traffic elements are important components of roads and the main elements of structuring basic traffic geographic information databases. However, the following problems still exist in the ...detection and recognition of road traffic elements: dense elements, poor detection effect of multi-scale objects, and small objects being easily affected by occlusion factors. Therefore, an adaptive spatial feature fusion (ASFF) YOLOv5 network (ASFF-YOLOv5) was proposed for the automatic recognition and detection of multiple multiscale road traffic elements. First, the K-means++ algorithm was used to make clustering statistics on the range of multiscale road traffic elements, and the size of the candidate box suitable for the dataset was obtained. Then, a spatial pyramid pooling fast (SPPF) structure was used to improve the classification accuracy and speed while achieving richer feature information extraction. An ASFF strategy based on a receptive field block (RFB) was proposed to improve the feature scale invariance and enhance the detection effect of small objects. Finally, the experimental effect was evaluated by calculating the mean average precision (mAP). Experimental results showed that the mAP value of the proposed method was 93.1%, which is 19.2% higher than that of the original YOLOv5 model.
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