Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits.

Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and WorldView-2 same-day paired satellite imagery and handheld multispectral proximal sensors on two days during the 2012-2013 winter cover crop season. We compared two processing levels from three satellites with spatially aggregated proximal data for red and green spectral bands as well as the normalized difference vegetation index (NDVI). We then compared NDVI estimated fractional green cover to in-situ photographs, and we derived cover crop biomass estimates from NDVI using existing calibration equations. We used slope and intercept contrasts to test whether estimates of biomass and fractional green cover differed statistically between sensors and processing levels. Compared to top-of-atmosphere imagery, surface reflectance imagery were more closely correlated with proximal sensors, with intercepts closer to zero, regression slopes nearer to the 1:1 line, and less variance between measured values. Additionally, surface reflectance NDVI derived from satellites showed strong agreement with passive handheld multispectral proximal sensor-sensor estimated fractional green cover and biomass (adj. R2 = 0.96 and 0.95; RMSE = 4.76% and 259 kg ha-1, respectively). Although active handheld multispectral proximal sensor-sensor derived fractional green cover and biomass estimates showed high accuracies (R2 = 0.96 and 0.96, respectively), they also demonstrated large intercept offsets (-25.5 and 4.51, respectively). Our results suggest that many passive multispectral remote sensing platforms may be used interchangeably to assess cover crop biophysical traits whereas SPOT 5 required an adjustment in NDVI intercept. Active sensors may require separate calibrations or intercept correction prior to combination with passive sensor data. Although surface reflectance products were highly correlated with proximal sensors, the standardized cloud mask failed to completely capture cloud shadows in Landsat 7, which dampened the signal of NIR and red bands in shadowed pixels.

Understanding the natural expansion of white mangrove (Laguncularia racemosa) in an ephemeral inlet based on geomorphological analysis and remote sensing data.

The interactions between local tides and river discharges are crucial in the processes related to the recruitment of mangrove propagules in estuarine systems. This investigation aimed to determine the causes of the recent natural recruitment and expansion of Laguncularia racemosa in mudflats within an ephemeral inlet in Mexico. We conducted a fluvial and coastal geomorphology assessment with spaceborne and UAV-based images. We deployed and recorded continuous data loggers in the estuarine system to assess water level and salinity. Depending on the available data, we used a combination of cloud-computing Google Earth Engine, UAV-Digital Surface Models, LiDAR, Google Earth images, and biophysical variables to monitor mangrove forests from 2005 to 2022. When the inlet is open, the estuarine system presents a full tidal range (∼1-1.5 m) with a strong salinity gradient (0-35 mS/cm), in contrast to the strong freshwater influence and minimal water level variability (<10 cm) that prevails for three months when the inlet is closed. Once the mouth of the river closes, there is considerable sediment accumulation, creating mudflat areas adjacent to the mangrove forests where Laguncularia racemosa propagules begin to establish under minimal water level variability and oligohaline conditions. After 16 years, the new forest expanded by 12.3 ha, presenting a very high density (10000 stems/ha), a considerable basal area (54-63 m2/ha), and a maximum canopy height of 15.8 m, which largely surpasses that of other semiarid Laguncularia racemosa forests within permanent open-inlet systems or even in ephemeral inlets with different hydrological conditions. Our study will help to understand the causes of natural Laguncularia racemosa recruitment in extremely dynamic systems.

Analysis of the implementation effects of ecological restoration projects based on carbon storage and eco-environmental quality: A case study of the Yellow River Delta, China.

As an important means to address global climate change and land-use/land-cover (LULC) change, ecological restoration projects (ERPs) have a large effect on carbon storage functions and eco-environmental quality. However, the various ERPs carried out in the Yellow River Delta region have important implications for ecological security strategies in China. Therefore, based on land-use data and remote sensing image data, with the help of ArcGIS and Google Earth Engine (GEE) platforms, this study uses the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, an improved remote sensing ecological index (RSEI) model and other methods to deeply examine the evolutionary trends of eco-environmental quality and carbon storage during the implementation of ERPs in the Yellow River Delta and selects key implementation areas for in-depth analysis to determine the implementation effects of ERPs. Our findings suggested that the RSEI and carbon storage levels in the study area had opposite evolutionary trends from 2001 to 2020. Among them, the RSEI showed a fluctuating upwards trend (0.4461 (2001) and 0.5185 (2020)), while the total carbon stock showed a fluctuating downwards trend (30.67 Tg (2001) and 26.40 Tg (2020)). However, from 2015 to 2020, the RSEI and carbon storage were at a relatively stable level, which indirectly indicated that the ERPs carried out during the period from 2015 to 2020 had achieved a good comprehensive implementation effect. In addition, the areas with better improvement effects from 2015 to 2020 were primarily located in the mouth of the Yellow River Delta (Areas C and D), and their RSEI and the total carbon stock showed a certain upwards trend. This research can promote the formulation of the management strategy of ERPs in the Yellow River Delta, which is of tremendous importance to the ecological environmental preservation and high-quality development of the Yellow River Basin.

Assessment of pixel-oriented k-NN machine learning algorithm performance for the interannual remote sensing monitoring of eelgrass beds at the mouth of the Romaine.

Eelgrass cover extent is among the most reliable indicators for measuring changes in coastal ecosystems. Eelgrass has colonized the mouth of the Romaine River and has become a part of environmental monitoring there since 2013. The presence of eelgrass in this area is an essential factor for the early detection of changes in the Romaine coastal ecosystem. This will act as a trigger for an appropriate environmental response to preserve ecosystem health. In this paper, a cost- and time-efficient workflow for such spatial monitoring is proposed using a pixel-oriented k-NN algorithm. It can then be applied to multiple modellers to efficiently map the eelgrass cover. Training data were collected to define key variables for segmentation and k-NN classification, providing greater edge detection for the presence of eelgrass. The study highlights that remote sensing and training data must be acquired under similar conditions, replicating methodologies for collecting data on the ground. Similar approaches must be used for the zonal statistic requirements of the monitoring area. This will allow a more accurate and reliable assessment of eelgrass beds over time. An overall accuracy of over 90% was achieved for eelgrass detection for each year of monitoring.

Remote sensing monitoring of mining tailings in the fluvial-estuarine-coastal ocean continuum of the Lower Doce River Valley (Brazil).

Water clarity is a key parameter of aquatic ecosystems impacted by mining tailings. Tracking down tailings dispersion along the river basin requires a regional monitoring approach. The longitudinal fluvial connectivity, river-estuary-coastal ocean, and the lateral connectivity, river-floodplain-alluvial lakes are interconnected by hydrological flows, particularly during high fluvial discharge. The present study aims to track the dispersal of iron ore tailing spill, from the collapse of the Fundão dam (Mariana, MG, Brazil), on November 5, 2015, in the Lower Doce River Valley. A semi-empirical model of turbidity data, as a water clarity proxy, and multispectral remote sensing data (MSI Sentinel-2), based on different hydrological conditions and well-differentiated water types, yielded an accuracy of 92%. Five floods (> 3187m3 s-1) and five droughts (< 231m3 s-1) events occurred from 2013 to 2020. The flood of January 2016 occurred one month after the mining slurries reached the coast, intruding tailings on some alluvial and coastal plain lakes with highly turbid waters (> 400 NTU). A fluvial plume is formed in the inner shelf adjoining the river mouth on high flow. The dispersion of river plume was categorized as plume core (turbidity > 200 NTU), plume core and inner shelf waters (100-199 NTU), other shelf water (50-99 NTU), and offshore waters (< 50 NTU). Fluvial discharge and local winds are the main drivers for river plume dispersion and transport of terrigenous material along the coast. This work provides elements for evaluating the impact of mining tailings and an approach for remote sensing regional monitoring of surface water quality.

Structural Health Monitoring of Fatigue Cracks for Steel Bridges with Wireless Large-Area Strain Sensors.

This paper presents a field implementation of the structural health monitoring (SHM) of fatigue cracks for steel bridge structures. Steel bridges experience fatigue cracks under repetitive traffic loading, which pose great threats to their structural integrity and can lead to catastrophic failures. Currently, accurate and reliable fatigue crack monitoring for the safety assessment of bridges is still a difficult task. On the other hand, wireless smart sensors have achieved great success in global SHM by enabling long-term modal identifications of civil structures. However, long-term field monitoring of localized damage such as fatigue cracks has been limited due to the lack of effective sensors and the associated algorithms specifically designed for fatigue crack monitoring. To fill this gap, this paper proposes a wireless large-area strain sensor (WLASS) to measure large-area strain fatigue cracks and develops an effective algorithm to process the measured large-area strain data into actionable information. The proposed WLASS consists of a soft elastomeric capacitor (SEC) used to measure large-area structural surface strain, a capacitive sensor board to convert the signal from SEC to a measurable change in voltage, and a commercial wireless smart sensor platform for triggered-based wireless data acquisition, remote data retrieval, and cloud storage. Meanwhile, the developed algorithm for fatigue crack monitoring processes the data obtained from the WLASS under traffic loading through three automated steps, including (1) traffic event detection, (2) time-frequency analysis using a generalized Morse wavelet (GM-CWT) and peak identification, and (3) a modified crack growth index (CGI) that tracks potential fatigue crack growth. The developed WLASS and the algorithm present a complete system for long-term fatigue crack monitoring in the field. The effectiveness of the proposed time-frequency analysis algorithm based on GM-CWT to reliably extract the impulsive traffic events is validated using a numerical investigation. Subsequently, the developed WLASS and algorithm are validated through a field deployment on a steel highway bridge in Kansas City, KS, USA.

Laser Remote Sensing of Lake Kinneret by Compact Fluorescence LiDAR.

Harmful algal blooms in freshwater reservoirs became a steady phenomenon in recent decades, so instruments for monitoring water quality in real time are of high importance. Modern satellite remote sensing is a powerful technique for mapping large areas but cannot provide depth-resolved data on algal concentrations. As an alternative to satellite techniques, laser remote sensing is a perspective technique for depth-resolved studies of fresh or seawater. Recent progress in lasers and electronics makes it possible to construct compact and lightweight LiDARs (Light Detection and Ranging) that can be installed on small boats or drones. LiDAR sensing is an established technique; however, it is more common in studies of seas rather than freshwater reservoirs. In this study, we present an experimental verification of a compact LiDAR as an instrument for the shipborne depth profiling of chlorophyll concentration across the freshwater Lake Kinneret (Israel). Chlorophyll depth profiles of 3 m with a 1.5 m resolution were measured in situ, under sunlight conditions. A good correlation (R2 = 0.89) has been established between LiDAR signals and commercial algae profiler data. A non-monotonic algae depth distribution was observed along the boat route during daytime (Tiberias city-Jordan River mouth-Tiberias city). The impact of high algal concentration on water temperature laser remote sensing has been studied in detail to estimate the LiDAR capability of in situ simultaneous measurements of temperature and chlorophyll concentration.

Silk fibroin fibers decorated with urchin-like Au/Ag nanoalloys: a flexible hygroscopic SERS sensor for monitoring of folic acid in human sweat.

Surface-enhanced Raman scattering (SERS) spectroscopy has become a powerful and sensitive analytical tool for the detection and assessment of chemical/biological molecules in special scenarios. Herein we propose a flexible hygroscopic SERS biocompatible sensor based on the silk fibroin fibers (SFF) decorated with urchin-like Au/Ag nanoalloys (NAs). The hybrid SFF-Au/Ag NAs with a stronger absorbance capacity (500∼1100 nm) and excellent hygroscopicity provide a remarkable higher near-infrared (NIR)-SERS activity than that of bare urchin-like Au/Ag NAs. The interesting NIR-SERS sensor enables the limit of detection (LOD) of folic acid (FA) to be achieved at nanomolar (nM, 10-9 M) level, facilitating the ultrasensitive monitoring of FA in human sweat and offering reliable real-time personal health management in the near future.

IR characterization of plant leaves, endemic to semi-tropical regions, in two senescent states.

We are developing a robust and economic electro-optical remote sensing methodology to monitor the state of health and hydration of trees, endemic to subtropical regions. We measured reflectance spectra with Fourier transform infrared (FTIR) of three samples of two different oak trees. We find that spectral bands suitable for monitoring the state of the health and senescence of the oak include intervals around 0.9 µm and 1.8 µm. The easiest and the most cost-effective strategy would be to implement an electro-optical remote sensing radiometric system featuring a commercial camera incorporating a traditional charge-coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS) detectors and a wideband transmission filter, from about 0.8 to 1 µm.

Rapid High-Resolution Mosaic Acquisition for Photoacoustic Remote Sensing.

Mechanical stages are routinely used to scan large expanses of biological specimens in photoacoustic imaging. This is primarily due to the limited field of view (FOV) provided by optical scanning. However, stage scanning becomes impractical at higher scanning speeds, or potentially unfeasible with heavier samples. Also, the slow scan-rate of the stages makes high resolution scanning a time-consuming process. Some clinical applications such as microsurgery require submicron resolution in a reflection-mode configuration necessitating a method that can acquire large field of views with a small raster scanning step size. In this study, we describe a method that combines mechanical stages with optical scanning for the rapid acquisition of high-resolution large FOVs. Optical scanning is used to acquire small frames in a two-dimensional grid formed by the mechanical stages. These frames are captured with specific overlap for effective image registration. Using a step size of 200 nm, we demonstrate mosaics of carbon fiber networks with FOVs of 0.8 × 0.8 mm2 captured in under 70 s with 1.2 µm image resolution. Larger mosaics yielding an imaging area of 3 × 3 mm2 are also shown. The method is validated by imaging a 1 × 1 mm2 section of unstained histopathological human tissue.

Use of space and home range characteristics of Lepilemur mittermeieri, an endangered sportive lemur endemic to the Ampasindava peninsula, north-west Madagascar.

Lepilemur mittermeieri, a little-studied sportive lemur of north-west Madagascar, endemic to the Ampasindava Peninsula, faces habitat loss through forest degradation and rapid fragmentation. Understanding its habitat requirement is the first step toward preservation of this threatened forest-dependent species. In this study, we gathered data on the use of space and home range characteristics of L. mittermeieri. We studied individuals from early March to the end of June 2015 and 2016, in three sites of the Ampasindava peninsula. We radio-tracked 15 individuals to obtain detailed information on the size and location of home ranges (around 450 hr of tracking). Direct observation and morphometric measurements provided additional data sets. Both kernel density estimation (KDE) and minimum convex polygon (MCP) methods yielded similar home range sizes (an average of 2.01 ha with KDE method and 1.96 ha with MCP method). We did not find differences in home range size between males and females, with respect to forest type or proximity to the forest edge. Home ranges overlapped and individuals showed low levels of territoriality. We highlighted a sexually-dimorphic trait: males have longer upper canine than females. Our results constitute the first set of ecological information on Lepilemur mittermeieri and could be the basis for a conservation strategy for this endangered species with a very small distribution area.

Dental bleaching on teeth submitted to enamel microabrasion 30 years ago-a case report of patients' compliance during bleaching treatment.

OBJECTIVES: The present dental bleaching case report describes a new method that precisely quantifies the daily wearing-times of the bleaching product by inserting a microsensor in the acetate custom tray. The bleaching efficacy was also discussed since the patient was previously submitted to enamel microabrasion. METHODS: The patient was submitted to enamel microabrasion in 1987, and bleaching treatment was performed in 2005. In 2017, re-bleaching was executed using 10% peroxide carbamide. The electronic microsensor, TheraMon (TheraMon® microelectronic system; Sales Agency Gschladt, Hargelsberg, Austria), was embedded in the labial region of the upper and lower acetate trays to evaluate the wearing-times of the acetate trays/bleaching product. The patient was instructed to wear the tray for 6 to 8 h/day while sleeping. After 24 days of bleaching treatment, the data obtained from the TheraMon electronic devices was collected and interpreted. RESULTS: The patient did not entirely follow the bleaching treatment as recommended, as there was no evidence of use of the upper and lower trays for some days; additionally, the bleaching product was used for shorter and longer periods than was instructed. CONCLUSIONS: The TheraMon microeletronic device precisely measured the wearing-times of the acetate tray/bleaching product during the bleaching treatment. Teeth submitted to enamel microabrasion presented with a healthy clinical appearance after 30 years. CLINICAL SIGNIFICANCE: Measuring the length and frequency of use of an acetate tray/bleaching product can be important to clinicians and patients for obtaining a controlled and adequate bleaching treatment.

Development of a Remote-Controlled Implantable Rat Sacral Nerve Stimulation System.

OBJECTIVES: Sacral nerve stimulation (SNS) is a surgical treatment of urinary and fecal incontinence. Despite its clinical efficacy, the mechanisms of action of SNS are still poorly known. This may be related to the use of acute stimulation models. Up to date, no rodent model of chronic SNS implants has been developed. Therefore, the aim of this study was to create a fully implantable and remotely controllable stimulating device to establish an animal model of chronic SNS. MATERIALS AND METHODS: The stimulating device consisted of an implantable pulse generator linked to a platinum electrode. The communication with the device was made through an inductive link which allowed to adjust the stimulation parameters; that is, to turn the device on and off or check the battery status remotely. Rats underwent two surgical procedures. In the first procedure, we achieved chronic sacral stimulation but the implanted electrode was not fixated. In the second procedure, the electrode was fixated in the sacral foramen using dental resin. In both cases, the correct positioning of the electrode was evaluated by computed tomography (CT) imaging and the presence of tail tremor in response to high intensity stimulation. We only tested the function of implanted electrode with fixation using micturition frequency assessment following bipolar or unipolar SNS for three days after recovery. RESULTS: CT imaging showed that implantation of the electrode required fixation as we found that the second surgical procedure yielded a more precise placement of the implanted electrode. The correct placement of implanted electrode observed with imaging was always correlated with a successful tail tremor response in rats, therefore we pursued our next experiments with the second surgical procedure and only assessed the tail tremor response. We found that both bipolar and unipolar SNS reduced micturition frequency. CONCLUSION: This stimulating device provides an efficient method to perform chronic SNS studies in rats.

Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager.

Here, we present a proof-of-concept on remote sensing of ocean plastics using airborne shortwave infrared (SWIR) imagery. We captured red, green, and blue (RGB) and hyperspectral SWIR imagery with equipment mounted on a C-130 aircraft surveying the "Great Pacific Garbage Patch" at a height of 400 m and a speed of 140 knots. We recorded the position, size, color, and type (container, float, ghost net, rope, and unknown) of every plastic piece identified in the RGB mosaics. We then selected the top 30 largest items within each of our plastic type categories (0.6-6.8 m in length) to investigate SWIR spectral information obtained with a SASI-600 imager (950-2450 nm). Our analyses revealed unique SWIR spectral features common to plastics. The SWIR spectra obtained ( N = 118 items) were quite similar both in magnitude and shape. Nonetheless, some spectral variability was observed, likely influenced by differences in the object optical properties, the level of water submersion, and an intervening atmosphere. Our simulations confirmed that the ∼1215 and ∼1732 nm absorption features have potential applications in detecting ocean plastics from spectral information. We explored the potential of SWIR remote sensing technology for detecting and quantifying ocean plastics, thus provide relevant information to those developing better monitoring solutions for ocean plastic pollution.

Initial in vitro and in vivo evaluation of a self-monitoring prosthetic bypass graft.

OBJECTIVE: Prosthetic grafts used for lower extremity revascularization and dialysis access fail because of hyperplastic stenosis and thrombosis. Graft surveillance is advocated to monitor function; however, graft failure can occur between episodic examinations. An innovative sensor with wireless, microchip technology allows automated surveillance with assessment of graft function using a "cloud"-based algorithm. We performed proof-of-concept experiments with in vitro and in vivo models to assess the feasibility such a real-time graft surveillance system. METHODS: A self-monitoring graft system was evaluated consisting of a prosthetic conduit of expanded polytetrafluoroethylene and a sensor unit, and a microsensor, microelectronics, battery, and remote processor with a monitor. The sensor unit was integrated on the extraluminal surface of expanded polytetrafluoroethylene grafts without compromise to the lumen of the conduit. The grafts were tested in vitro in a pulsatile, recirculating flow system under physiologic flow parameters. The hemodynamic parameters were varied to assess the ability to obtain wireless signal acquisition reflecting real-time flow properties in vitro. Segments of custom tubing with reduced diameters were inserted into the model to mimic stenosis proximal and distal to the grafts. After characterization of the initial data, the self-monitoring grafts were implanted in an ovine carotid model to assess proof of concept in vivo with 30-day follow-up of signal acquisition as well as arteriographic and histologic analysis. RESULTS: In vitro flow data demonstrated the device was able to determine factors related to prosthetic graft function under varied hemodynamic flow conditions. Wireless signal acquisition using Bluetooth technology (Bluetooth SIG, Inc, Kirkland, Wash) allowed remote data analysis reflecting graft flow parameters through changes in microsensor voltage and frequency. Waveform analysis was applied to construct an algorithm using proprietary software and determine a parameter for graft flow characteristics. This algorithm allowed determination of the degree of stenosis and location of stenosis location (proximal or distal) for display on a remote monitor in real time. Subsequent in vivo experiments confirmed the ability of the system to generate signal acquisition through skin and soft tissue under biologic conditions with no arteriographic stenosis and a favorable healing response at 30-day harvest. CONCLUSIONS: Initial in vitro and in vivo experiments demonstrate the ability for a self-monitoring graft system to remotely monitor hemodynamic parameters reflecting graft function using wireless data transmission. This automated system shows promise to deliver real-time data that can be analyzed by cloud-based algorithms alerting the clinician of a change in graft function or development of stenosis for further diagnostic study or intervention before graft failure.

Single-shot stand-off chemical identification of powders using random Raman lasing.

The task of identifying explosives, hazardous chemicals, and biological materials from a safe distance is the subject we consider. Much of the prior work on stand-off spectroscopy using light has been devoted to generating a backward-propagating beam of light that can be used drive further spectroscopic processes. The discovery of random lasing and, more recently, random Raman lasing provide a mechanism for remotely generating copious amounts of chemically specific Raman scattered light. The bright nature of random Raman lasing renders directionality unnecessary, allowing for the detection and identification of chemicals from large distances in real time. In this article, the single-shot remote identification of chemicals at kilometer-scale distances is experimentally demonstrated using random Raman lasing.

Wafer-scale integrated micro-supercapacitors on an ultrathin and highly flexible biomedical platform.

We present wafer-scale integrated micro-supercapacitors on an ultrathin and highly flexible parylene platform, as progress toward sustainably powering biomedical microsystems suitable for implantable and wearable applications. All-solid-state, low-profile (<30 µm), and high-density (up to ~500 µF/mm(2)) micro-supercapacitors are formed on an ultrathin (~20 µm) freestanding parylene film by a wafer-scale parylene packaging process in combination with a polyaniline (PANI) nanowire growth technique assisted by surface plasma treatment. These micro-supercapacitors are highly flexible and shown to be resilient toward flexural stress. Further, direct integration of micro-supercapacitors into a radio frequency (RF) rectifying circuit is achieved on a single parylene platform, yielding a complete RF energy harvesting microsystem. The system discharging rate is shown to improve by ~17 times in the presence of the integrated micro-supercapacitors. This result suggests that the integrated micro-supercapacitor technology described herein is a promising strategy for sustainably powering biomedical microsystems dedicated to implantable and wearable applications.

Mini-UAV based sensory system for measuring environmental variables in greenhouses.

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Chlorophyll and suspended sediment mapping to the Caribbean Sea from rivers in the capital city of the Dominican Republic using ALOS AVNIR-2 data.

This study aims to study the distribution of contaminants in rivers that flow into the Caribbean Sea using chlorophyll-a (Chl-a) and suspended sediment (SS) as markers and ALOS AVNIR-2 satellite sensor data. The Haina River (HN) and Ozama and Isabela Rivers (OZ-IS) that flow through the city of Santo Domingo, the capital of the Dominican Republic, were chosen. First, in situ spectral reflectance/Chl-a and SS datasets obtained from these rivers were acquired in March 2011 (case A: with no rain influence) and June 2011 (case B: with rain influence), and the estimation algorithm of Chl-a and SS using AVNIR-2 data was developed from the datasets. Moreover, the developed algorithm was applied to AVNIR-2 data in November 2010 for case A and August 2010 for case B. Results revealed that for Chl-a and SS estimations under cases A and B conditions, the reflectance ratio of AVNIR-2 band 4 and band 3 (AV4/AV3) and the reflectance of AVNIR-2 band 4 (AV4) were effective. The Chl-a and SS mapping results obtained using AVNIR-2 data corresponded with the field survey results. Finally, an outline of the distribution of contaminants at the mouth of the river that flows into the Caribbean Sea was obtained for both rivers in cases A and B.

Spatio-temporal evolutionary analysis of surface ecological quality in Pingshuo open-cast mine area, China.

The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann-Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990-2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region.