Shortwave Infrared Research Articles

Broadband SWIR emission through Cr3+-Ni2+ energy transfer in YAGG fluorescent ceramics for bioimaging applications

Short-wave infrared (SWIR) light in the 1000–1700 nm range has high penetration capability through biological tissues and is non-destructive, making it widely used in biomedical applications and near-infrared imaging. Currently, the development of SWIR light sources is urgently needed. This paper discusses the luminescent properties of the near-infrared emitting transition metal ions Cr3+ and Ni2+. By using the traditional high-temperature solid-state method, we successfully synthesized YAGG:3.5 %Cr3+-0.5 %Ni2+ (YAGG:Cr-Ni) garnet-based phosphor ceramic in one step. The phosphor ceramic emits ultra-broadband NIR-I (600–900 nm, FWHM=131 nm) and SWIR (1100–1700 nm, FWHM=377 nm) light when excited by a 450 nm commercial blue LED. Position analysis combined with density functional theory (DFT) simulation confirmed the effective substitution of luminescent center ions for the [Al/GaO6] sites. Spectral and lifetime analyses further verified the energy transfer process between Cr3+ and Ni2+ is dipole-quadrupole interaction. Additionally, this phosphor ceramic has a high thermal conductivity of 8.018 W·m⁻¹·K⁻¹ at room temperature. Finally, SWIR pc-LED devices were fabricated by packaging the phosphor ceramic with a 450 nm commercial blue LED, achieving skeletal and venous imaging of biological tissues up to 20 mm thick, providing a new approach for the development of SWIR devices.

Surface Vibration‐Mediated and Multiphonon Relaxation‐Assisted Antithermal‐Quenching Shortwave Infrared Emission in Ho‐Based Double Perovskite With Long Lifetime

AbstractThermal quenching generally predominates in Er3+ 1540 nm luminescence quenching at elevated temperatures, due to intensified lattice vibration and efficient overtone vibrational relaxation by O─H stretch. This issue impedes practical device applications of shortwave infrared Er‐doped phosphors. Herein, with the mediation of surface vibrational phonons, anti‐thermal quenching of Er3+ 1540 nm emission is reported in (220)‐dominated Er3+‐doped Cs2NaHoCl6 double perovskite. The downshifting emissions can be boosted with rising temperatures from 303 to 543 K, reaching 225%@483 K of the initial intensity at 303 K, accompanied with a long lifetime of 33.02 ms at 483 K. By combining temperature‐dependent in situ Raman and Fourier transform infrared spectroscopies with the excited‐state dynamics results, the coordination role of water molecules is verified, serving as promoters instead of quenchers on the (220) facet at high temperatures. Furthermore, efficient energy transfer from Ho3+ to Er3+ enables intense 1540 nm emission with a photoluminescence quantum yield of 78.1% under 450 nm excitation. Finally, a compact thermally stable phosphor‐converted light‐emitting diode (LED) is designed as a narrowband shortwave infrared light source with a blue LED chip. This work pushes the improved understanding of achieving thermal‐enhanced Er3+ luminescence for potential broad applications.

A pan-cancer dye for solid-tumour screening, resection and wound monitoring via short-wave and near-infrared fluorescence imaging.

The efficacy of fluorescence-guided surgery in facilitating the real-time delineation of tumours depends on the optical contrast of tumour tissue over healthy tissue. Here we show that CJ215-a commercially available, renally cleared carbocyanine dye sensitive to apoptosis, and with an absorption and emission spectra suitable for near-infrared fluorescence imaging (wavelengths of 650-900 nm) and shortwave infrared (SWIR) fluorescence imaging (900-1,700 nm)-can facilitate fluorescence-guided tumour screening, tumour resection and the assessment of wound healing. In tumour models of either murine or human-derived breast, prostate and colon cancers and of fibrosarcoma, and in a model of intraperitoneal carcinomatosis, imaging of CJ215 with ambient light allowed for the delineation of nearly all tumours within 24 h after intravenous injection of the dye, which was minimally taken up by healthy organs. At later timepoints, CJ215 provided tumour-to-muscle contrast ratios up to 100 and tumour-to-liver contrast ratios up to 18. SWIR fluorescence imaging with the dye also allowed for quantifiable non-contact wound monitoring through commercial bandages. CJ215 may be compatible with existing and emerging clinical solutions.

Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize

Maize (Zea mays L.) is one of the most important grain crops in the world. Drought caused by climate change in recent years may greatly threaten water supply and crop production, even if the drought only lasts for a few days or weeks. Therefore, effective daily drought monitoring for maize is crucial for ensuring food security. A pivotal challenge in current related research may be the selection of data collection and the methodologies in the construction of these indices. Therefore, orthorectified reflectance in the short-wave infrared (SWIR) band, which is highly sensitive to variations in vegetation water content, was daily obtained from the MODIS MCD43A4 product. Normalized Difference Water Index (NDWI) calculated using the NIR and SWIR bands and days after planting (DAP) were normalized to obtain the Vegetation Water Index (VWI) and normalized days after planting (NDAP), respectively. The daily dynamic threshold model for different agricultural drought grades was constructed based on the VWI and NDAP with double-logistic fitting functions during the maize growing season, and its specific threshold was determined with historical drought records. Verification results indicated that the VWI had a good effect on the daily agricultural drought monitoring of spring maize in the “Golden Maize Belt” in northeast China. Drought grades produced by the VWI were completely consistent with historical records for 84.6% of the validation records, and 96.2% of the validation records differed by only one grade level or less. The VWI can not only daily identify the occurrence and development process of drought, but also well reflect the impact of drought on the yield of maize. Moreover, the VWI could be used to monitor the spatial evolution of drought processes at both regional and precise pixel scales. These results contribute to providing theoretical guidance for the daily dynamic monitoring and evaluation of spring maize drought in the “Golden Maize Belt” of China.

Characterization of regolith-hosted rare earth element deposits using reflectance spectroscopy: Framework towards an efficient and reliable field exploration tool

With a growing demand for the rare earth elements (REE), exploration of regolith-hosted REE resources worldwide has been thriving in recent years and development of a rapid and reliable field-based tool will greatly facilitate the survey and exploration. In this study, we use visible and short-wave infrared (VNIR-SWIR) reflectance spectroscopy to comprehensively evaluate the applicability of the technique to explore regolith-hosted REE resources, exemplified by three representative regolith-hosted REE deposits in China. Neodymium among the REE shows reliably detectable spectral features in the VNIR-SWIR spectroscopy down to concentrations of 10–50 ppm in field samples with heterogeneous mineral grain sizes. The Nd spectral intensity of electronic transition at the band of ∼800 nm is correlated with bulk Nd concentrations and can be used as semi-quantitative indicators for the Nd concentrations, thereby the total REE in regolith. Moreover, VNIR-SWIR spectroscopy is demonstrated to be capable of delineating favorable ore-bearing mineralogy by characterizing the abundance and type of clay minerals and Fe (oxyhydr)oxides, and the crystallinity of kaolinite-group minerals. However, the Nd spectral features of samples with high bulk Fe2O3 contents (>3 wt%) are significantly masked due to overlapping by the strong absorption features of ferric (oxyhydr)oxides. VNIR-SWIR spectroscopy is deemed to be applicable to the exploration of regolith-hosted REE resources developed from Fe-poor felsic rocks.

An innovative variant based on generative adversarial network (GAN): Regression GAN combined with hyperspectral imaging to predict pesticide residue content of Hami melon

The rapid and non-destructive detection of pesticide residues in Hami melons plays substantial importance in protecting consumer health. However, the investment of time and resources needed to procure sample data poses a challenge, often resulting in limited data set and consequently leading insufficient accuracy of the established models. In this study, an innovative variant based on generative adversarial network (GAN) was proposed, named regression GAN (RGAN). It was used to synchronically extend the visible near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data and corresponding acetamiprid residue content data of Hami melon. The support vector regression (SVR) and partial least squares regression (PLSR) models were trained using the generated data, and subsequently validate them with real data to assess the reliability of the generated data. In addition, the generated data were added to the real data to extend the dataset. The SVR model based on SWIR-HSI data achieved the optimal performance after data augmentation, yielding the values of Rp2, RMSEP and RPD were 0.8781, 0.6962 and 2.7882, respectively. The RGAN extends the range of GAN applications from classification problems to regression problems. It serves as a valuable reference for the quantitative analysis of chemometrics.

Rapid identification of moxa wool storage period based on hyperspectral imaging technology and machine learning

Moxa wool (MW), derived from the dried leaves of Artemisiaargyi, plays a significant role in traditional Chinese medicine. However, the quality of MW varies with its storage period, impacting its therapeutic efficacy. Traditional methods for quality detection are limited and destructive. To address this, we propose a non-destructive detection method using hyperspectral imaging technology and machine learning algorithms to accurately identify the storage period of MW. Nevertheless, hyperspectral data poses challenges due to its high dimensionality and redundancy, leading to increased computational complexity. To overcome this, we employed principal component analysis (PCA), competitive adaptive reweighted sampling (CARS), and successive projection algorithm (SPA) for data dimensionality reduction and wavelength selection. The results demonstrate that these techniques significantly enhance the accuracy of MW storage year identification. For Nanyang MW, the CARS+SVM model achieved the highest accuracy rates of 99.8% in the visible-near-infrared (VNIR) range and 99.55% in the shortwave infrared (SWIR) range. Similarly, for Qichun MW, the SPA+SVM model achieved identification accuracies of 99.78% and 99.47% in the VNIR and SWIR ranges, respectively. This research provides valuable insights into the rapid detection of MW quality by indication of storage years and presents a novel approach for quality control of MW in the field of traditional Chinese medicine. The combination of hyperspectral imaging and machine learning offers a promising solution for efficient and accurate MW identification, contributing to the advancement of traditional medicine practices.

Thermal Emissions of Active Craters at Stromboli Volcano: Spatio‐Temporal Insights From 10 Years of Satellite Observations

AbstractOpen‐vent volcanoes continuously emit magmatic products and frequently feature multiple adjacent craters. Temporal shifts of thermal emissions between craters are especially detectable by InfraRed satellites. Here, SENTINEL‐2 and LANDSAT‐8/9 Short Wave InfraRed (SWIR) high‐spatial resolution satellite data, are combined to investigate 10 years (2013–2023) of thermal activity at Stromboli volcano (Italy). The correlation between Volcanic Radiative Power (VRP, in Watts) and Volcanic Radiative Energy (VRE, in Joules), retrieved by moderate MODIS and VIIRS Middle InfraRed (MIR) data, with the Thermal Index SWIR (TISWIR) data, allows us to quantify long‐term series of heat fluxes (VRPSWIR) and energy (VRESWIR). Combining moderate and higher spatial resolution data and fitting cumulative trends of TISWIR with VREMIR allows to measure thermal activity sourced by single craters during Strombolian activity. Long‐term results highlight that thermal emissions are clustered in the northern and southern parts of the crater terrace, with total energy emitted (∼12 × 1014 J) equally distributed. The thermal increase since April 2017 marked a reactivation of shallow magma transportation and an intensification of the activity after the 2014 eruption. Distinct thermal behaviors are shown by the NE, C, and SW craters, related to mechanisms of explosions. We found that short‐term thermal variations match well those resolved by ground‐based signals, and the NE crater as the most sensitive to the transition to higher‐intensity activity. Our multispatial/multisensory investigation allows, for the first time, the long‐term quantification of heat flux from Stromboli's craters, with an improved understanding of open‐vent dynamics and a new approach to monitor multiple active craters.

Computing imaging in shortwave infrared bands enabled by MoTe2/Si 2D‐3D heterojunction‐based photodiode

AbstractBreakthroughs brought about by two‐dimensional (2D) materials in the field of photodetection have opened up new possibilities in infrared imaging. However, challenges still exist in fabricating high‐density detector arrays using such materials, which are essential for traditional imaging systems. In this study, we present a state‐of‐the‐art computing imaging system that utilizes a MoTe2/Si self‐powered photodetector coupled with flexible Hadamard modulation algorithms. This system demonstrates remarkable capability to produce high‐quality images in the shortwave infrared (SWIR) band, surpassing the capabilities of devices based on alternative material systems. The exceptional infrared imaging capability primarily stems from the MoTe2/Si photodetector's inherent features, including an ultra‐wide spectral range (265–1550 nm) and extremely high sensitivity (linear dynamic range (LDR) up to 123 dB, responsivity (R) up to 0.33 A W–1, external quantum efficiency (EQE) up to 43% and a specific detectivity (D*) exceeding 2.9 × 1011 Jones). Moreover, the imaging system demonstrates the ability to achieve high‐quality edge imaging of objects in the SWIR band (1550 nm), even in strong scattering environments and under low sampling rate conditions (sampling rate of 25%). We believe that this work will effectively advance the application scope of 2D materials in the field of computational imaging in SWIR bands.image

Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part II: OSEs and Results

Abstract The assimilation of data from hyperspectral infrared sounders in global data assimilation systems has historically been focused on observations in the longwave infrared (LWIR) region of the spectrum (650-1100 cm−1), despite the often concurrent availability of measurements from the shortwave infrared (SWIR) region of the spectrum (2150-2550 cm−1), because issues (like solar effects) have generally prevented the assimilation of SWIR observations. Recent advances in radiative transfer models have worked to address some of the previous challenges in simulating SWIR observations, and the assimilation of SWIR data (e.g. from potential future small-satellites) is now a feasible prospect. Still, a better understanding of how these observations perform in a data assimilation system and impact resulting analyses and NWP forecasts is necessary. In this study, the value of SWIR observations in global NWP is assessed by assimilating SWIR observations from the Cross-track Infrared Sounder (CrIS) in NOAA’s Global Data Assimilation System (GDAS). The methodologies used to enable the assimilation of these observations, including the implementation of a scene-dependent observation error and the enhancement of quality control procedures, are discussed, as are the results of Observing System Experiments (OSEs) conducted to evaluate the impact of assimilating SWIR observations on forecast skill. The overall results show that SWIR assimilation produces similar forecast impacts to LWIR assimilation. The ability to demonstrate that the assimilation or SWIR observations in NWP is a realistic prospect may help to shape future constellations of small-satellites to serve as a beneficial complement to the current constellation if hyperspectral IR sounders.

Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part I: Background and Methods

Abstract Radiance observations from Earth-observing satellites have a significant positive impact on numerical weather prediction (NWP) forecasts, but some spectral regions are not fully exploited. Observations from hyperspectral infrared (IR) sounders in the longwave region (650-1100 cm−1), for instance, are routinely assimilated in many NWP models, but observations in the shortwave region (2155-2550 cm−1) are not. Each of these regions provides information on the temperature structure of the atmosphere, but the shortwave IR (SWIR) region is considered challenging to assimilate due to noise equivalent delta temperature (NEDT) that is highly variable depending on scene brightness temperature and to phenomena that are difficult to model, like non-Local Thermodynamic Equilibrium (NLTE) and solar reflectance. With recent advances in small-satellite technology, SWIR temperature sounders may provide an agile and cost-effective complement to the current constellation of IR sounders. Therefore, a better understanding of the use and impact of SWIR observations in data assimilation for NWP is warranted. In part one of this study, as presented here, the amount of unique information (as determined by Empirical Orthogonal Decomposition (EOD)) made available to a data assimilation system by Cross-track Infrared Sounder (CrIS) SWIR observations is reviewed, recent advancements to the Community Radiative Transfer Model (CRTM) for the simulation of CrIS shortwave radiances are tested, and enhancements to NOAA’s Global Data Assimilation System (GDAS) for the assimilation of CrIS SWIR observations are implemented and evaluated. Part two of this study, which seeks to assess the value of assimilating shortwave IR observations in global NWP, is also introduced.

Seasonal Dynamics of the Land-Surface Characteristics in Arid Regions Retrieved by Optical and Microwave Satellite Data

Establishing a quantitative relationship between Synthetic Aperture Radar (SAR) data and optical data can facilitate the fusion of these two data sources, enhancing the time-series monitoring capabilities for remote sensing of a land surface. In this study, we analyzed the Normalized Difference Vegetation Index (NDVI) and Shortwave Infrared Transformed Reflectance (STR) with the backscatter coefficients in vertical polarization VV (σ0VV) and cross polarization VH (σ0VH) across different seasons. We used optical and microwave satellite data spanning from the southern Gobi Desert region to the steppe region in northern Mongolia. The results indicate a relatively high correlation between the NDVI derived from Sentinel-2 and σ0VH (RVH = 0.29, RVH = 0.44, p < 0.001) and a low correlation between the NDVI and σ0VV (RVH = 0.06, RVH = 0.14, p < 0.01) in the Gobi Desert region during summer and fall. STR showed a positive correlation with both σ0VH and σ0VV except in spring, with the highest correlation coefficients observed in summer (RVV = 0.45, RVV = 0.44, p < 0.001). In the steppe region, significant seasonal variations in the NDVI and σ0VH were noted, with a strong positive correlation peaking in summer (RVH = 0.71, p < 0.001) and an inverse correlation with σ0VV except in summer (RVV = −0.43, RVV = −0.34, RVV = −0.13, p < 0.001). Additionally, STR showed a positive correlation with σ0VH and σ0VV in summer (RVH = 0.40, RVV = 0.39, p < 0.001) and fall (RVH = 0.38, RVV = 0.09, p < 0.01), as well as an inverse correlation in spring (RVH= −0.17, RVV= −0.38, p < 0.001) and winter (RVH = −0.21, RVV = −0.06, p < 0.001). The correlations between the NDVI, STR, σ0VH, and σ0VV were shown to vary by season and region. In the Gobi Desert region, perennial shrubs are not photosynthetic in spring and winter, and they affect backscatter due to surface roughness. In the steppe region, annual shrubs were found to be the dominant species and were found to photosynthesize in spring, but not enough to affect the backscatter due to surface roughness.

Shortwave Infrared Imaging of a Quantum Dot-Based Magnetic Guidewire Toward Non-Fluoroscopic Peripheral Vascular Interventions.

Peripheral vascular interventions (PVIs) offer several benefits to patients with lower extremity arterial diseases, including reduced pain, simpler anesthesia, and shorter recovery time, compared to open surgery. However, to monitor the endovascular tools inside the body, PVIs are conducted under X-ray fluoroscopy, which poses serious long-term health risks to physicians and patients. Shortwave infrared (SWIR) imaging of quantum dots (QDs) has shown great potential in bioimaging due to the non-ionizing penetration of SWIR light through tissues. In this paper, a QD-based magnetic guidewire and its system is introduced that allows X-ray-free detection under SWIR imaging and precise steering via magnetic manipulation. The QD magnetic guidewire contains a flexible silicone tube encapsulating a QD polydimethylsiloxane (PDMS) composite, where HgCdSe/HgS/CdS/CdZnS/ZnS/SiO2 core/multi-shell QDs are dispersed in the PDMS matrix for SWIR imaging upon near-infrared excitation, as well as a permanent magnet for magnetic steering. The SWIR penetration of the QD magnetic guidewire is investigated within an artificial tissue model (1% Intralipid) and explore the potential for non-fluoroscopic PVIs within a vascular phantom model. The QD magnetic guidewire is biocompatible in its entirety, with excellent resistance to photobleaching and chemical alteration, which is a promising sign for its future clinical implementation.

Innovative strategies for protein content determination in dried laver (Porphyra spp.): Evaluation of preprocessing methods and machine learning algorithms through short-wave infrared imaging

In this study, we explored the application of Short-Wave Infrared (SWIR) hyperspectral imaging combined with Competitive Adaptive Reweighted Sampling (CARS) and advanced regression models for the non-destructive assessment of protein content in dried laver. Utilizing a spectral range of 900–1700 nm, we aimed to refine the quality control process by selecting informative wavelengths through CARS and applying various preprocessing techniques (standard normal variate [SNV], Savitzky-Golay filtering [SG], Orthogonal Signal Correction [OSC], and StandardScaler [SS]) to enhance the model's accuracy. The SNV-OSC-StandardScaler- Support vector regression (SVR) model trained on CARS-selected wavelengths significantly outperformed the other configurations, achieving a prediction determination coefficient (Rp2) of 0.9673, root mean square error of prediction of 0.4043, and residual predictive deviation of 5.533. These results highlight SWIR hyperspectral imaging's potential as a rapid and precise tool for assessing dried laver quality, aiding food industry quality control and dried laver market growth.

Artificial Amacrine Retinal Circuits.

Event-based imaging represents a new paradigm in visual information processing that addresses the speed and energy efficiency shortcomings inherently present in the current complementary metal oxide semiconductor-based machine vision. Realizing such imaging systems has previously been sought using very large-scale integration technologies that have complex circuitries consisting of many photodiodes, differential amplifiers, capacitors, and resistors. Here, we demonstrate that event-driven sensing can be achieved using a simple one-resistor, one-capacitor (1R1C) circuit, where the capacitor is modified with colloidal quantum dots (CQDs) to have a photoresponse. This sensory circuit emulates the motion-tracking function of the biological retina, in which the amacrine cells in the bipolar-to-ganglion synaptic pathway produce a transient spiking signal only in response to changes in light intensity but remain inactive under constant illumination. When extended to a 2D imaging array, the individual sensors work independently and output signals only when a change in the light intensity is detected; hence, the concept of the frame in image processing is thereby removed. In this work, we present the fabrication and characterization of a CQD photocapacitor-based 1R1C circuit that has a spectral response at 1550 nm in the short-wave infrared (SWIR). We report on the key performance parameters including peak responsivity, noise, and optical noise equivalent power and discuss the operating mechanism that is responsible for spiking responses in these artificial retinal circuits. The present work sets the foundation for expanding the bioinspired vision sensor capability toward midwave infrared (MWIR) and long-wave infrared (LWIR) spectral regions that are invisible to human eyes and mainstream semiconductor technologies.

Synergic Surface Modifications of PbS Quantum Dots by Sodium Acetate in Solid-State Ligand Exchange toward Short-Wave Infrared Photodetectors.

PbS quantum dots (QDs) are promising for short-wave infrared (SWIR) photodetection and imaging. Solid-state ligand exchange (SSLE) is a low-fabrication-threshold QD solid fabrication method. However, QD treatment by SSLE remains challenging in seeking refined surface passivation to achieve the desired device performance. This work investigates using NaAc in the ligand exchange process to enhance the film morphology and electronic coupling configuration of QD solids. By implementing various film and photodetector device characterization studies, we confirm that adding NaAc with a prominent adding ratio of 20 wt % NaAc with tetrabutylammonium iodide (TBAI) in the SSLE leads to an improved film morphology, reduced surface roughness, and decreased trap states in the QD solid films. Moreover, compared to the devices without NaAc treatment, those fabricated with NaAc-treated QD solids exhibit an enhanced performance, including lower dark current density (<100 nA/cm2), faster response speed, higher responsivity, detectivity, and external quantum efficiency (EQE reaching 25%). The discoveries can be insightful in developing efficient, low-cost, and low-fabrication-threshold QD SWIR detection and imager applications.

TW-scale few-cycle short-wave infrared laser based on nonlinear compression in a large-core gas-filled hollow core fiber

In this Letter, we present the generation of terawatt-scale few-cycle short-wave infrared (SWIR) lasers using nonlinear compression in a large-core gas-filled hollow core fiber. Through the experimental verification, we investigate the energy scaling properties and nonlinear pulse propagation in the argon-filled hollow core fiber. At static pressure, the system delivers pulses with 5.55 mJ/9.04 fs at a central wavelength of 1.45 μm, resulting in a peak power of about 0.5 TW. Subsequently, based on the chirped input pulses and pressure gradient, the system delivers terawatt-scale two-cycle SWIR pulses with 9.52 mJ/10.65 fs, resulting in a record peak power of about 0.7 TW. This study marks a crucial advancement in the field of SWIR ultra-intense, ultrashort pulse nonlinear interaction platforms. This high-energy, few-cycle SWIR source has significant applications in high-intensity THz radiation, x-ray generation, and other fields of strong-field physics.

Normalized Difference Red-NIR-SWIR: A new Sentinel-2 three-band spectral index for mapping freshly-opened swiddens in the tropics

Swidden agriculture is undergoing a rapid but overlooked transition and transformation in the tropics, complicating global carbon budgeting and sustainable livelihood assessment of swiddeners. Remotely sensed algorithms for accurately detecting swiddening practices have been slowly developed to generate annual updates on their dynamics. This is primarily because, using medium spatial resolution imagery (≥30 m), it is challenging to identify the exact boundary of swidden patches. Spectral-based approaches have by far dominated the detection and mapping of swidden agriculture, but the potential of Sentinel-2 has not been examined. To reconstruct annual information of swidden agriculture, a new Sentinel-2 three-band spectral index, i.e., the Normalized Difference Red, Near-infrared (NIR), and Shortwave-infrared (SWIR), or NDRII, has been developed to map freshly-opened swiddens in tropical regions. As Red (visible), NIR, and SWIR spectral band combinations (i.e., the VNIR-SWIR spectroscopy) are sensitive to vegetation-moisture variations and thermal anomalies caused by slash and burn in tropical uplands during the dry season, NDRII delineates exact patches of freshly opened swiddens. The latest 20-m map facilitates probing into the landscape patterns of newly opened swiddens and underlines their prevalence in Laos for the first time. Established within the VNIR-SWIR spectroscopy of Sentinel-2 and Landsat-8 Operational Land Imager, the NDRII algorithm contributes to reconstructing historical datasets of tropical swiddens via integrating state-of-the-art approaches that use temporally stacked observations with available VNIR/SWIR satellite imagery and further understanding the dynamics of landscape pattern and disturbance due to rapid transition and transformation.

Modeling of Soil Cation Exchange Capacity Based on Chemometrics, Various Spectral Transformations, and Multivariate Approaches in Some Soils of Arid Zones

Cation exchange capacity is a crucial metric for managing soil fertility and promoting agricultural sustainability. An alternative technique for the non-destructive assessment of important soil parameters is reflectance spectroscopy. The main focus of this paper is on how to analyze and predict the content of various soil cation exchange capacities (CEC) in arid conditions (Sohag governorate, Egypt) at a low cost using laboratory analysis of CEC, visible near-infrared and shortwave infrared (Vis-NIR) spectroscopy, partial least-squares regression (PLSR), and Ordinary Kriging (OK). Utilizing reflectance spectroscopy with a spectral resolution of 10 nm and laboratory studies with a spectral range of 350 to 2500 nm, 104 surface soil samples were collected to a depth of 30 cm in the Sohag governorate, Egypt (which is part of the dry region of North Africa), in order to accomplish this goal. The association between the spectroradiometer and CEC averaged values was modeled using PLSR in order to map the predicted value using Ordinary Kriging (OK). Thirty-one soil samples were selected for validation. The predictive validity of the cross-validated models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), residual prediction deviation (RPD), and ratio of performance to interquartile distance (RPIQ). The results indicate that ten transformation methods yielded calibration models that met the study’s requirements, with R2 &gt; 0.6, RPQ &gt; 2.5, and RIQP &gt; 4.05. For evaluating CEC in Vis-NIR spectra, the most efficient transformation and calibration model was the reciprocal of Log R transformation (R2 = 0.98, RMSE = 0.40, RPD = 6.99, and RIQP = 9.22). This implies that combining the reciprocal of Log R with PLSR yields the optimal model for predicting CEC values. The CEC values were best fitted by four models: spherical, exponential, Gaussian, and circular. The methodology used here does offer a “quick”, inexpensive tool that can be broadly and quickly used, and it can be readily implemented again in comparable conditions in arid regions.

High SNR eSWIR Image Sensor Applied in Advanced Hyperspectral Imager Aboard China’s GaoFen-5 Satellite and ZY-1 Satellite

This paper presents an extended short-wave infrared (eSWIR) image sensor, a large format infrared focal plane array (IRFPA), applied in advanced hyperspectral imager (AHSI) aboard China’s three GaoFen-5 satellites and two more followed ZY-1 satellites. Hyperspectral imaging has been emerged as a very important application in Earth observation instruments, for the spectral detection provides the spectrum information of ground objects except for the spatial imaging of the objects. AHSI has a 60-km swath width and a 30-m spatial resolution, and has high signal-to-noise ratio (SNR) in spectrum of interest. Large format infrared focal plane arrays which are ordinarily used in staring infrared imaging have some special performance requirements when applied in hyperspectral imaging, such as higher quantum efficiency, lower dark current, lower noise and selectable current conversion gain to match the different radiation flux of different subdivided spectral bands. We developed a format of 2048×512 HgCdTe/Si IRFPA sensor (equivalent 2012×256 after pixel overlapping and binning) in which 2012 pixels meet the demands of 60km swath width and 256 pixels line meet the 200 spectral bands. The sensor has 8-level gains selectable by spectral bands, and array dark current densities on an order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-10</sup> A/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , quantum efficiency exceeding 80%, and the operability of 99.5% at operating temperature of around 110K. The SNR of this FPA achieved 150 when illuminated under 5×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> photons/pixel.