Disturbance Events Research Articles

ABOUT RESEARCH PROGRAMS AT THE RADIO TELESCOPE "URAN-4" IRA NASU – MONITORING OF FLUXES OF POWERFUL RADIO SOURCES, STUDY OF THE SUN'S SUPERCORONA, OBSERVATIONS OF SOLAR ECLIPSE

During 2020–2023, an initiative series of observation programs was carried out on a radiometer designed and manufactured by V.V. Galanin. Among them are observations of ionospheric scintillations of powerful radio sources Cas A, Cyg A, Vir A, Tau A, Per A, on the URAN-4 radio telescope (IRA NASU) at frequencies of 20 and 25 MHz. The observations were carried out at various states of Solar and geomagnetic activity and allow us to analyze the response of the ionosphere in the region of the Odessa Magnetic Anomaly to disturbing events. It was found that the radio source 3C 84 (Per A) is the least noisy at the location of the URAN-4 antenna and is well suited for studying the ionospheric response during magnetic storms. The recorded scintillation periods of the studied radio sources, on "calm" days, are in the range of 1-2 minutes. During magnetic storms, the periods of scintillations are reduced to 10-30 seconds. The paper considers the features of the response of scintillations of different radio sources to a magnetic storm, since they shine through different spatial regions of the ionosphere. Of particular interest are observations of the radio source Tau A (3C 144), which annually, in June, shines through the Solar Supercorona. Processing scans of such observations of the 3C 144 source shows an increase flux variations with an average "period" of about 5-10 seconds. Observations were also made to record the features of radio background variations during partial Solar eclipse. It is shown that during a Solar eclipse, the level of background radio noise increases significantly. At the same time, the background level on the next day after the eclipse was still quite high. A more detailed analysis of this effect is planned and, if possible, repeated observations.

Highly discriminative and adaptive feature extraction method based on NMF–MFCC for event recognition of Φ-OTDR

To enhance the capability of phase-sensitive optical time domain reflectometers (Φ-OTDR) to recognize disturbance events, an improved adaptive feature extraction method based on NMF–MFCC is proposed, which replaces the fixed filter bank used in the traditional method to extract the mel-frequency cepstral coefficient (MFCC) features by a spectral structure obtained from the Φ-OTDR signal spectrum using nonnegative matrix factorization (NMF). Three typical events on fences are set as recognition targets in our experiments, and the results show that the NMF–MFCC features have higher distinguishability, with the corresponding recognition accuracy reaching 98.47%, which is 7% higher than that using the traditional MFCC features.

Case Study of a Severe Ice Storm Impacting Distribution Networks in Oklahoma

Reliability and resiliency assessment of an electrical distribution network (DN) for extreme disasters are essential for system optimization and future planning. Conventional reliability indices may not be effective in characterizing dynamic disturbance events in DNs. A unique opportunity to empirically explore these issues arose when a week of unseasonably cold weather moved through the State of Oklahoma. On October 26, 2020, a rare ice storm resulted in one of the most widespread power disruptions ever experienced in the state's history. This article documents the outcomes of an investigation conducted in collaboration with a utility provider who operates and maintains one of the affected DNs. Based on supplied network data, this article explores the quantification of operational resilience for a more insightful characterization of outage events. The results demonstrate important failure mechanisms and potential opportunities to improve resiliency.

The Holocene silicon biogeochemistry of Yellowstone Lake, USA

Silicon (Si) is an essential macronutrient for diatoms, an important component of lacustrine primary productivity that represents a link between the carbon and silicon cycles. Reconstructions of lake silicon cycling thus provide an underexploited window onto lake and catchment biogeochemistry. Silicon isotope geochemistry has potential to provide these reconstructions, given the competing source and process controls can be deconvolved. The silica-rich volcanic and hydrothermal systems in Yellowstone National Park are a great source of dissolved silicon into Yellowstone Lake, a system with high silicon, and thus carbon, export rates and the formation of diatom–rich sediment. Yellowstone Lake sediments should be an archive of past silicon biogeochemistry, although the effect of sublacustrine hydrothermal activity or hydrothermal explosion events is unclear.Here, we analysed lake water, tributaries, and hydrothermal vent fluids from Yellowstone Lake for their dissolved Si concentrations, isotope composition (δ30Si) and Ge/Si ratios to evaluate the sources of variability in the lake's Si cycle. Bulk elemental composition and biogenic SiO2 (bSiO2) content, together with δ30Si and Ge/Si ratios from a single diatom species, Stephanodiscus yellowstonensis, were analysed in two sediment cores spanning the last 9880 cal. yr BP. We investigate these datasets to identify long term Holocene changes in hydrothermal activity and effects of large and short-term events i.e., hydrothermal and a volcanic eruption.Combinations of bSiO2, δ30Si and Ge/Si with XRF and lithology data revealed that Yellowstone Lake has a resilient biogeochemical system: hydrothermal explosions are visible in the lithology but have no identifiable impact on bSiO2 accumulation or on the δ30Si signature. Both cores show similarities that suggest a stable and homogeneous dSi source across the entire lake. A narrow range of δ30Si and Ge/Si values suggests that the productive layer of the lake was well mixed and biogeochemically stable, with consistently high hydrothermal inputs of Si throughout the Holocene to buffer against the disturbance events. Variation in bSiO2 concentration through time is weakly correlated with an increase towards younger sediment in the δ30Si fossil diatom record in both cores. This increase mirrors that seen in ocean records, and follows changes known in summer insolation, summer temperatures and lake water-column mixing since the deglaciation. This suggests that climate forcing, and soil formation ultimately govern the silicon isotope record, which we suggest is via a combination of changes in weathering stoichiometry, diatom production, and relative proportion of dSi sources.

Mapping Forest Abrupt Disturbance Events in Southeastern China—Comparisons and Tradeoffs of Landsat Time Series Analysis Algorithms

Forest change monitoring is a fundamental and routine task for forest survey and planning departments, and the resulting forest change information acts as an underlying asset for sustainable forest management strategy development, ecological quality assessment, and carbon cycle research. The traditional ground-based manual monitoring of forest change has the disadvantages of high time and labor costs, low accessibility, and poor timeliness over wide regions. Remote sensing technology has become a popular approach for multi-scale forest change monitoring due to its multiple available spatial, spectral, temporal, and radiometric resolutions and wide coverage. Particularly, the free access policy of long time series archive data of Landsat (around 50 years) has triggered many automated analysis algorithms for landscape-scale forest change analysis, such as VCT, LandTrendr, BFAST, and CCDC. These automated algorithms differ in their principles, parameter settings, execution complexity, and disturbance types to be detected. Thus, selecting a suitable algorithm to satisfy the particular forest management demands is an urgent and challenging task for forest managers in a given forested area. In this study, Lishui City, Zhejiang Province, a typical plantation forest region in Southern China where forest disturbance widely and frequently exists, was selected as the study area. Based on the GEE platform, the algorithmic adaptability of VCT, LandTrendr, and CCDC in monitoring abrupt forest disturbance events was compared and assessed. The results showed that the kappa coefficients of the abrupt disturbance events detected by the three algorithms were at 0.704 (LandTrendr), 0.660 (VCT), and 0.727 (CCDC), and the corresponding overall accuracies were at 0.852, 0.830, and 0.862, respectively. The validated disturbance occurrence time consistency reached nearly 80% for the three algorithms. In light of the characteristics of forest disturbance occurrence in southeastern China as well as the algorithmic complexity, efficiency, and adaptability, LandTrendr was recommended as the most suitable one in this region or other similar regions. Overall, the forest change monitoring process based on GEE is becoming more simplified and easily implemented, and the comparisons and tradeoffs in this study provide a reference for the choice of long time series forest monitoring algorithms.

Evaluation of Tree-Growth Rate in the Laurentides Wildlife Reserve Using GEDI and Airborne-LiDAR Data

Loss of forest cover and derived effects on forest ecosystems services has led to the establishment of land management policies and forest monitoring systems, and consequently to the demand for accurate and multitemporal data on forest extent and structure. In recent years, spaceborne Light Detection and Ranging (LiDAR) missions, such as the Global Ecosystem Dynamics Investigation (GEDI) instrument, have facilitated the repeated acquisition of data on the vertical structure of vegetation. In this study, we designed an approach incorporating GEDI and airborne LiDAR data, in addition to detailed forestry inventory data, for estimating tree-growth dynamics for the Laurentides wildlife reserve in Canada. We estimated an average tree-growth rate of 0.32 ± 0.23 (SD) m/year for the study site and evaluated our results against field data and a time series of NDVI from Landsat images. The results are in agreement with expected patterns in tree-growth rates related to tree species and forest stand age, and the produced dataset is able to track disturbance events resulting in the loss of canopy height. Our study demonstrates the benefits of using spaceborne-LiDAR data for extending the temporal coverage of forestry inventories and highlights the ability of GEDI data for detecting changes in forests’ vertical structure.

A novel dynamic inertial control of wind turbines based on event size estimation

High penetration of variable renewable energy sources causes volatile grid frequency movements in low inertia systems. Large-scale wind turbines (WTs) are stipulated to participate in frequency control upon occurring a disturbance event. This paper proposes a novel inertial control scheme aimed at improving the frequency nadir based on frequency event size (FES) estimation. Upon occurring a frequency event, the WTs immediately inject a stepwise active power into the grid, and its corresponding frequency deviation is measured to estimate the FES using mean absolute error solution of a sinusoidal exponential function regression. Subsequently, an inertial control is developed to mitigate the frequency movements taking into account the available kinetic energy in rotating masses of WTs and estimated FES. To ensure a safe rotor speed recovery to its maximum power point tracking mode within this scheme, the rotor speed recovery time, and the second frequency drop can be flexibly adjusted. The WTs overproduction and recovery stages are dynamically adapted to wind speed fluctuations based on the defined modifications and rules. Additionally, the scheme considers the latency of communication delay during FES estimation. The proposed method is validated using a large-scale wind farm integrated into IEEE 9-bus and 39-bus test systems in Digsilent PowerFactory. Comparison results with existing methods in the literature demonstrate that the proposed scheme achieves better frequency nadir improvement across various types and sizes of events and wind speeds. Furthermore, it exhibits robust performance against communication latencies. Finally, the experimental results support the findings in terms of FES estimation.

The effects of a moderate severity hurricane on gap characteristics in a longleaf pine (Pinus palustris Mill.) woodland

Modern forestry research emphasizes infusing management practices with an understanding of natural disturbance regimes—often called ecological forestry. Forestry practices that emulate aspects of natural disturbance regimes are considered an effective approach to balance silvicultural and ecological objectives. Silvicultural research is often available to guide successful regeneration in many forest types, but little information is available about gap patterns from common disturbances in the eastern U.S. like hurricanes. We examined the size, shape, and spatial distribution of canopy gaps formed in a longleaf pine woodland by Hurricane Michael across multiple landscape factors including stand size, composition, and soil types. We found high variation in many gap characteristics but no significant differences in gap size or shape among landscape factors. However, spatial distribution of gaps differed among landscape types in nuanced ways. We also found that stand size complexity may prevent the formation of very large gaps that can disrupt fire continuity in systems managed with frequent fire. The results highlight the ecological importance of hurricane events and provide insight into hurricane gap formation at the landscape scale. The implementation of silviculture practices that emulate a large, rapid, single disturbance event may be more practically applied than management based on disturbances such as lightning or insects which occur over longer timeframes.

Biogeomorphology from space: Analyzing the dynamic interactions between hydromorphology and vegetation along the Naryn River in Kyrgyzstan based on dense satellite time series

The structure and development of river corridors are controlled by an interplay of hydrological, geomorphological and ecological processes over a range of spatial and temporal scales. The majority of existing studies on fluvial biogeomorphology focus either on conceptual development or on investigations on the scales of single geomorphic units or study reaches. With this study, we extend the view on biogeomorphology beyond the reach scale using satellite time series. We take the Naryn River in Kyrgyzstan as an example for demonstrating our approach to biogeomorphological analysis of river corridors. The Naryn is still in a natural state on an entire flow length of more than 600 km with full longitudinal and lateral connectivity. Along the central part of the catchment, the Naryn is a highly dynamic braided river system. This makes this river ideal to study large scale biogeomorphological dynamics. In our study, we follow the well-established concept of biogeomorphological succession. We mapped the different succession stages in the field and used the results to derive spectral-temporal indices characterizing the different biogeomorphological succession stages. Monthly time series of the modified difference water index as well as the normalized difference vegetation index derived from the Landsat archive have been used to compute statistical trends and changepoints by means of a Bayesian time series decomposition algorithm. The results are then evaluated regarding biogeomorphological succession and disturbance events. The results show that dense satellite time series are well suited to derive indicators of biogeomorphological interactions on large spatial scale. The temporally continuous nature of this kind of observations allows an observation of processes and an interpretation for instance against the background of the theory of adaptive cycles and panarchy. In conclusion, the suggested approach has the potential to give new insights in the structure and functioning of entire river corridors or networks.

Magnetosphere–Ionosphere Drivers of Transient‐Large‐Amplitude Geomagnetic Disturbances: Statistical Analysis and Event Study

AbstractWe present a comprehensive statistical analysis of high‐frequency transient‐large‐amplitude (TLA) magnetic perturbation events that occurred at 12 high‐latitude ground magnetometer stations throughout Solar Cycle 24 from 2009 to 2019. TLA signatures are defined as one or more second‐timescale dB/dt interval with magnitude ≥6 nT/s within an hour event window. This study characterizes high‐frequency TLA events based on their spatial and temporal behavior, relation to ring current activity, auroral substorms, and nighttime geomagnetic disturbance (GMD) events. We show that TLA events occur primarily at night, solely in the high‐latitude region above 60° geomagnetic latitude, and commonly within 30 min of substorm onsets. The largest TLA events occurred more often in the declining phase of the solar cycle when ring current activity was lower and solar wind velocity was higher, suggesting association to high‐speed streams caused by coronal holes and subsequent corotating interaction regions reaching Earth. TLA perturbations often occurred preceding or within the most extreme nighttime GMD events that have 5–10 min timescales, but the TLA intervals were often even more localized than the ∼300 km effective scale size of GMDs. We provide evidence that shows TLA‐related GMD events are associated with dipolarization fronts in the magnetotail and fast flows toward Earth and are closely temporally associated with poleward boundary intensifications (PBIs) and auroral streamers. The highly localized behavior and connection to the most extreme GMD events suggests that TLA intervals are a ground manifestation of features within rapid and complex ionospheric structures that can drive geomagnetically induced currents.

A Nonlinear Model for Evaluating Dynamic Resilience of Water Supply Hydropower Generation‐Environment Conservation Nexus System

AbstractUndesirable disturbances (e.g., extraordinary drought) are prone to cause cascading failures of water supply‐hydropower generation‐environment conservation (WHE) nexus system. Simulating a dynamic resilience of the nexus system can provide opportunities for pre‐disturbance effective prevention and post‐disturbance recovery from the cascading failures. Previous dynamic resilience simulating is often based on the linear assumption which is not applicable for the WHE nexus system that involves nonlinear processes. To improve simulation accuracy of the dynamic resilience of the WHE nexus system, a novel nonlinear dynamic resilience model that incorporates both a WHE nexus model and a second‐order Volterra (SOV) model is proposed. The WHE nexus model simulates amount of impact propagated by an original disturbance event on each subsystem, while the SOV model captures nonlinear relationship between the amount of impact and a corresponding dynamic resilience. The proposed model was applied to the Liuchong River Basin, China, under different dry year scenarios. The results show that the dynamic resilience simulated through the SOV model performs better than that through a first‐order Volterra model which is suitable for a linear system, with Nash‐Sutcliffe efficiencies of water supply, hydropower generation, and environment conservation subsystems increasing by 36.8%, 70.9%, and 17% respectively. Among the WHE nexus system, the water supply subsystem is found to be the least resilient. Moreover, the proposed nonlinear model is more suitable for simulating and predicting dynamic resilience when a severer water resources drought occurs. The proposed model helps to guide resilience management of water resource system by combining nexus and resilience thinking.

A rebbachisaurid-mimicking titanosaur and evidence of a Late Cretaceous faunal disturbance event in South-West Gondwana

The evolution of ecosystems during the late Mesozoic on the southern landmasses is complex and still poorly known. Starting from a single vicariant Laurasian–Gondwanan scenario, the paleobiogeographic and biostratigraphic models have become more complex, including vicariant, dispersal, and local extinctions as major drivers of changes in the Cretaceous ecosystems during the isolation and posterior fragmentation of Gondwana. However, the direct effects of replacement and the adaptive evolution of terrestrial vertebrates to fill vacant ecological niches after disruptive ecological events have been poorly discussed. Here, we provide a preliminary description of a nearly complete new titanosaurian sauropod from the Upper Cretaceous of Patagonia, Inawentu oslatus gen. et. sp. nov., that shows remarkable convergent anatomical traits with rebbachisaurid sauropods. A phylogenetic analysis recovers it within a not previously recovered titanosaurian subclade, named Clade A, which would be endemic to the Upper Cretaceous of South America. The convergent evolution between rebbachisaurids and Clade A members is interpreted as the result of the same ecological niche exploitation. The biostratigraphic scenario during the Late Cretaceous of South America leads to interpret rapid speciation of the titanosaurs because of filling the empty ecological niche left by the extinction of the rebbachisaurids, an idea concordant with a regional disturbance event of the ecosystems in this continent between 90 and 85 Ma.

Influence of nuisance variables on the PMU-based disturbance classification in power transmission systems

Abstract The online classification of grid disturbances in power transmission systems has been investigated since many years and shows promising results on measured and simulated PMU signals. Nonetheless, a practical deployment of machine learning techniques is still challenging due to robustness problems, which may lead to severe misclassifications in the model application. This paper formulates an advanced evaluation procedure for disturbance classification methods by introducing additional measurement noise, unknown operational points, and unknown disturbance events in the test dataset. Based on preliminary work, Siamese Sigmoid Networks are used as classification approach and are compared against several benchmark models for a simulated power transmission system at 400 kV. Different test scenarios are proposed to evaluate the disturbance classification models assuming a limited and full observability of the grid with PMUs.

Controllable Transient Power Sharing of Inverter-Based Droop Controlled Microgrid

The transient power shared by inverter-based distributed generators (DGs) restricts the normal operating range and overstresses the power electronic devices under disturbing events. Additionally, the inevitable incorporation of DC side voltage dynamic during transient worsens the uncoupled dynamics between active and reactive power. Furthermore, unsafe transient power supplied by DGs can easily destabilize system operation. Therefore, this paper proposes a control strategy that controls the transient power distributed between several DGs integrated into a microgrid. To comprehensively design the proposed control, (i) an extended steady state and transient modeling of a microgrid that incorporates DC side dynamics in AC side-based model is first carried out. (ii) After that, designing the proposed control is systematically conducted and verified using frequency and time domain analyses. (iii) Moreover, the effectiveness of the proposed control is compared with state-of-the-art control strategies. The results demonstrate that the proposed control prevents power electronics-based DGs from sharing the majority of transient currents when integrated with other DGs, especially, inertial sources. The results show that the power overshoot and oscillation are reduced more than two times whereas the settling time is decreased by about three times, ensuring quick stabilized, and reliable integration of power electronics DGs in microgrids.

The anthropogenic imprint on temperate and boreal forest demography and carbon turnover.

The sweeping transformation of the biosphere by humans over the last millennia leaves only limited windows into its natural state. Much of the forests that dominated temperate and southern boreal regions have been lost and those that remain typically bear a strong imprint of forestry activities and past land-use change, which have changed forest age structure and composition. Here, we ask how would the dynamics, structure and function of temperate and boreal forests differ in the absence of forestry and the legacies of land-use change? Global. 2001-2014, integrating over the legacy of disturbance events from 1875 to 2014. Trees. We constructed an empirical model of natural disturbance probability as a function of community traits and climate, based on observed disturbance rate and form across 77 protected forest landscapes distributed across three continents. Coupling this within a dynamic vegetation model simulating forest composition and structure, we generated estimates of stand-replacing disturbance return intervals in the absence of forestry for northern hemisphere temperate and boreal forests. We then applied this model to calculate forest stand age structure and carbon turnover rates. Comparison with observed disturbance rates revealed human activities to have almost halved the median return interval of stand-replacing disturbances across temperate forest, with more moderate changes in the boreal region. The resulting forests are typically much younger, especially in northern Europe and south-eastern North America, resulting in a 32% reduction in vegetation carbon turnover time across temperate forests and a 7% reduction for boreal forests. The current northern hemisphere temperate forest age structure is dramatically out of equilibrium with its natural disturbance regimes. Shifts towards more nature-based approaches to forest policy and management should more explicitly consider the current disturbance surplus, as it substantially impacts carbon dynamics and litter (including deadwood) stocks.

Power instruction correction based frequency response strategy for grid forming inverter in islanded microgrids

Grid forming (GFM) inverter interfaced energy storage system can offer frequency support for islanded microgrids (IMGs), and the frequency response relies on the GFM inverter’s power output and power instruction interaction. However, droop control, a primary GFM method, faces challenges in reducing frequency deviations during significant disturbances due to the constant power instruction, potentially triggering the relay. To enhance the security of IMGs, this paper proposes a power instruction correction (PIC) based frequency response strategy for GFM inverter in IMGs. Firstly, the fundamental principle of the PIC strategy that originates the basic droop control is theoretically analyzed. When disturbances are insignificant, the PIC strategy maintains the basic droop control structure. In the event of a significant disturbance, the PIC strategy promptly corrects the active power instruction by estimating the disturbance approximately to reduce frequency deviations. Secondly, by analyzing specific operating modes and switching logic, the detailed implementation of the PIC strategy is presented. Finally, the superiority of the PIC strategy is verified through simulation and hardware-in-the-loop experiments.

Catchment-scale patterns of geomorphic activity and vegetation distribution in an alpine glacier foreland (Kaunertal Valley, Austria)

The interaction between geomorphological and ecological processes plays a significant role in determining landscape patterns in glacier forelands. However, the spatial organization of this biogeomorphic mosaic remains unclear due to limited catchment-scale data. To address this gap, we used a multi-proxy analysis to map potential geomorphic activity related to surface changes induced by sediment transport on drift-mantled slopes and a glaciofluvial plain. High-resolution vegetation data were used to generate a catchment-scale map delineating vegetation cover and stability thresholds. The two maps were integrated, and an exploratory regression analysis was conducted to investigate the influence of geomorphic activity on vegetation colonization. The multi-proxy analysis resulted in an accurate mapping of catchment-wide geomorphic activity, with a validation accuracy ranging from 75.3% through field mapping to 85.9% through plot sampling. Through vegetation cover mapping, we identified biogeomorphic stability thresholds, revealing a mosaic of vegetation distribution. Distinct colonization patterns emerged across different geomorphic process groups, influenced by process magnitude and the time since the last disturbance event. The exploratory regression analysis showed that vegetation distribution is significantly affected by geomorphic processes. Based on the overlay of results regarding geomorphic activity and vegetation distribution, we suggest an age-independent framework that indicates four potential situations of biogeomorphic succession.

Towards time and cost‐efficient habitat assessment: Challenges and opportunities for benthic ecology and management

Abstract To the untrained eye, soft‐sediment habitats are often viewed as vast expanses of featureless sand and mud. With new technology, it is finally possible to begin to map the ecological heterogeneity of these ecosystems to reveal their importance for ecosystem service provision and open up new opportunities to manage their use and protect them. When compared with terrestrial or marine vegetated habitats, the characterization of unvegetated soft sediments still lacks rapid and cost‐effective practices that allow the direct collection of ecological data at multiple spatial and temporal scales facilitating direct relevance to conservation and management. New technologies that allow for the building of maps that incorporate multiple scales of heterogeneity also provide new ways of upscaling necessarily detailed and small‐scale process studies. The study of the relationship between benthic structure, biodiversity and ecosystem functioning can benefit from a range of established and novel techniques and creates new opportunities to empirically test generalities and predictions based on theory or small‐scale experimental studies. The capacity to map ecological changes rapidly and at scale and to link small‐scale experiments to landscapes uncovers new insights for seafloor conservation including rapid response to disturbance events, broad‐scale ecologically meaningful mapping and assessments of biodiversity–ecosystem function and biodiversity–ecosystem services relationships. As technology advances and becomes more accessible to all, it offers promising new avenues of research to expand our current capabilities, and the adoption of nested approaches, with a synergy of different samplings simultaneously covering several scales and resolutions, is likely to have the most benefit, supporting decision‐making with ecologically insightful data, as well as the timely assessment of the outcomes of conservation actions.

Deep learning and automatic reference label harvesting for Sentinel-1 SAR-based rapid tropical dry forest disturbance mapping

The advent of temporally dense radar data such as the Sentinel-1 SAR have opened the door for rapid forest disturbance detection in the humid tropics. Tropical dry forest disturbance detection, however, were challenged by seasonality and more open canopy characteristics. In this manuscript, we proposed a Sentinel-1 SAR and deep learning based rapid forest disturbance detection approach for tropical dry forests. We demonstrated a weakly supervised method for reference label harvesting based on medium resolution globally available forest and forest disturbance maps. We trained a deep neural network model to derive forest and forest disturbance probabilities from Sentinel-1 images in the first step. We then implemented a probabilistic disturbance detection and refinement method to map forest disturbances in near real-time in two test regions in Paraguay and Mozambique. We mapped new forest disturbances in an emulated near real-time scenario for 2020 and 2021 and evaluated the spatial accuracy of the disturbance alerts by generating area adjusted precision, recall and F-1 score. We also evaluated the improvement in timeliness of disturbance detection by estimating mean time difference of disturbance events detection with that of Landsat-based GLAD alerts. The generated alerts in Paraguay and Mozambique achieved a precision, recall and F-1 score of 0.99, 0.61, 0.75 and 0.97, 0.51, 0.66, respectively. The proposed method detected disturbances with a mean of 21 days (± 18 days) earlier in Paraguay and 18 days (± 18 days) earlier in Mozambique than the Landsat-based GLAD alerts. These results demonstrated the efficacy of the proposed method and its viability to be used in an operational setting to generate large area rapid near real-time disturbance alerts in the dry tropics.

A novel method for identification of disturbance from surface coal mining using all available Landsat data in the GEE platform

Coal mining has contributed to a solid and stable global economy. Surface mining and underground mining are the principal methods for extraction of coal worldwide and given the developments in mining technology and equipment, these methods are increasingly generating more and more coal. Surface mining is also a subject that cannot be overlooked in the context of sustainable development because amongst human activities it causes comparatively strong land disturbance. Much of the damage and assessment of land and ecosystems from surface mining occurs at the site, and at the regional scale; hence access to the mining data is limited. Moreover, it is difficult for remote sensing to extract information on larger-scale areas with high precision. As a consequence, a frequency index of open coal mining can be created by merging the vast high-resolution images acquired by Landsat sensors with the spectral properties of open coal scraped from the overburden layer. Such indices and morphological principles can be used to develop strategies for quickly identifying the open coal boundaries in a vast area without mine-related information. In addition, LandTrendr may be used to reconstruct the spatial and temporal processes of surface disturbance and remediation caused by regional surface coal mining to identify surface mining disturbance and reclamation. Seven typical mining locations worldwide were selected to test and confirm the proposed method's practicality and robustness, including delivering accurate findings based on randomly testing sample points and comparing the mature data outputs. The results showed that: (1) the overall accuracy of the open coal areas identified by the OCFI (Open Coal Frequency Index) was over 85 % (range 0.85–0.96). In all study areas, the accuracy of recognizing disturbance and reclamation events was greater than 76 %. (2) The surface mining disturbed 3046.42 km2 of land and 1487.39 km2 was reclaimed in the seven mining areas investigated between 1986 and 2018, resulting in a reclamation rate of 48.82 %. The proposed method is more accurate and faster in identifying open coal locations than the current commonly used land cover datasets based on comparisons with other data products. The approach can extract surface coal mining in the absence of mining data and offer precise boundary data for mining research, which can be extremely useful for extending mining operations.