Spatial Match Research Articles

The Detri2match conceptual framework: Matching detritivore and detritus traits to unravel consumption rules in a context of decomposition

Abstract From soil to freshwater ecosystems, decomposition can be conceived as the result of interactions between organic matter and a diversity of organisms. This function is driven in part by detritivores, invertebrates that feed on detritus or graze on its associated microbes and that have a significant but extremely variable contribution to decomposition. In order to better understand and predict detritivore–detritus pairwise interactions, we propose a conceptual framework, called Detri2match, to study the consumption of detritus by detritivores, using a trait‐matching approach at the individual detritivore level. Here, we focus on the interaction between saprophagous detritivores that fragment plant detritus. We propose a novel definition of a saprophagous detritivore as an animal that consumes plant detritus when its traits match sufficiently the traits of its resource, passing through five interaction facets of consumption. These include (1) a spatial match rule regarding the encounter, (2) a biomechanical match rule regarding ingestion, (3) a digestive match rule regarding assimilation, (4) an energetic match rule regarding the fulfilment of metabolic needs and (5) a nutritional match rule regarding the fulfilment of chemical element needs in adapted proportions. The main goal of this framework is to guide future research to establish generic rules of misunderstood detritus–detritivore pairwise interactions by identifying relevant interaction facets and their key associated traits for both detritivores and detritus. This investigation should be conducted over the temporal variability of trait‐matching constraints throughout the whole decomposition process. Coupled with adequate accumulation of trait information, the Detri2match framework could also facilitate predictions by inference of non‐tested pairwise detritivore–litter interactions. We also outline conceptual, methodological and analytical challenges of this framework. The main challenge would be to scale up these pairwise rules at the detrital network level and to test their genericity, which would contribute to a better understanding of the functioning of the detrital network and its contribution to decomposition. Read the free Plain Language Summary for this article on the Journal blog.

Factors Contributing to Slab Locations and Geometries in Reconstructions of Past Mantle Flow

AbstractIndividual sinking slabs present markedly different geometries between 410 and 660 km depths, from vertical slabs penetrating the lower mantle to slabs stagnating above the lower mantle. The proposed factors determining these contrasted geometries include mantle viscosity and the magnitude and evolution of trench retreat. Here, we assess the success of paleo‐geographically driven global mantle flow models in matching slabs in tomographic models between 400 km and 1,000 km depth. We quantify the spatial match between predicted present‐day mantle temperature anomalies and vote maps of tomographic models. We investigate the sensitivity of the spatial match to input parameters of the mantle flow model: imposed tectonic reconstruction, model start age, and viscosity contrast between the upper and lower mantle. We evaluate the visual match between model slabs and tomographic vote maps for three circum‐Pacific regions with contrasted slab dip angles between 400 km and 1,000 km depth. Predicted model slabs better match slabs inferred from tomography when there is an increase in viscosity at 660 km depth. The temporal evolution of the models and the global match at present day suggest that the subduction history could be refined in the global tectonic reconstructions that we considered. For example, we suggest that the subduction to the east of Japan should be offset by approximately 100 km to the west at ∼80 Ma to match the anchoring of a continuous slab into the lower mantle suggested by tomography.

Carbon surplus or carbon deficit under land use transformation in China?

With the progression of industrialization and urbanization, terrestrial ecosystems have experienced varying degrees of degradation in their carbon sequestration capabilities, leading to functional loss in some regions. Consequently, the issue of reducing emissions and enhancing carbon sinks, especially in addressing the carbon imbalance brought on by urban and industrial developments, has become a focal point for international organizations and the academic community. Existing studies have separately investigated the effects of changes in single land use types, such as built-up land, forest land, and cropland, on carbon emissions or carbon sequestration. However, few studies have discussed carbon emissions and carbon sequestration within the same framework. This study, based on remote sensing data from 2000 to 2020, utilizes spatial autocorrelation analysis and spatial Durbin model to reveal the long-term trends in land use intensity and carbon balance in China. It was found that the carbon balance index decreased annually by 3.42%, from 0.2406 to 0.0760 during that period. In particular, the eastern and central regions of China exhibited increasingly evident carbon deficits, with most areas along the southeastern coast transitioning from a carbon surplus to a carbon deficit. Over two decades, China’s land use intensity and carbon balance developed a stronger negative spatial dependence. The spatial match and mismatch between land use intensity and carbon deficit are the primary clustering types for their spatial correlation. Each unit increase in land use intensity decreased the local city carbon balance by 0.755 but raised the carbon balance in adjacent areas by 2.740. This indicates that land use intensity impacts the local carbon balance negatively but benefits neighboring regions. There is also evident spatial inequality in different economic zones, with the strongest impact in the Northeast, followed by the Western, Eastern, and Central regions. The resolution of these issues reveals the spatial inequalities and remote driving effects of land use transformation on carbon balance across different scales, from the “entire region” to “economic divisions”. The results of this study provide theoretical and empirical evidence for emissions reduction and carbon sequestration in cities at different levels of land use intensity.

Evaluating the spatiotemporal dynamics of ecosystem service supply-demand risk from the perspective of service flow to support regional ecosystem management: A case study of yangtze river delta urban agglomeration

The inappropriate spatio-temporal distribution of natural capital during rapid urbanization has increased ecosystem service supply-demand (ESSD) risks, posing great challenges to the sustainable growth of human well-being, especially in urban agglomerations. Although methods focusing on the spatial match or temporal dynamics of ESSD in risk assessment have been established, a comprehensive understanding of the spatial dynamics underlying ecosystem service flows (ESF) is still missing. Due to the spatiotemporal heterogeneity of various ESSD risks within urban agglomerations, incorporating these elements into a unified spatial planning framework is still difficult. This study integrated the spatio-temporal analysis method of ESSD considering ESF and the spatial clustering method to propose an ESSD risk assessment and management framework: evaluating ES supply, demand and flow, incorporating ESF to quantify ESSD across various timeframes, assessing ESSD risks based on the current status and dynamic trends, and using Self-Organizing Map to identify optimal ESSD risk bundles (ESSDR_Bs). The results showed high ESSD risks of high temperature regulation, nitrogen purification, phosphorus purification, and food production in Yangtze River Delta urban agglomeration. While the ESSD risks of biodiversity conservation, carbon sequestration, soil retention, water yield, and tourism culture were relatively low, a concerning trend of decreasing surpluses was observed in general. In addition, six ESSDR_Bs were identified, and differentiated ecological management strategies were proposed for each bundle. This study provided a novel perspective for efficiently understanding and regulating the ESSD risks in urban agglomerations.

Alpine Rhododendron population contractions lead to spatial distribution mismatch with their pollinators under climate change

The effect of global climate change on plant–pollinator interaction is not limited to changes in phenology and richness within communities but also includes the spatial mismatch caused by the inconsistency of geographical distribution changes. Subsequently, the pollinator interaction network may be remodeled or even disrupted. In this study, we simulated the suitable habitat niche of 15 Rhododendron species and their eight pollinator species as well as their overlapping versus geographical mismatch under the current and three future climate change scenarios in 2090s, using MaxEnt. Results showed that the suitable habitat of all Rhododendron species would decrease in 2090s. In particular, 10, 8, and 13 Rhododendron–pollinator assemblages would have a reduced spatial match region under the climate change scenarios, mainly due to the contraction of the suitable habitat of Rhododendron species. The results provide novel insights into the response of plant–pollinator interactions to global warming, useful to prioritize conservation actions of alpine plant ecosystems.

Study on the future development prospects of biomass energy in towns, townships, and subdistricts under multi-scenarios —A case study of Harbin City

Biomass energy is the most likely new energy source to replace fossil fuels. This study presents a prediction method for biomass energy supply-demand and changes in supply-demand patterns that connects the past and future. In the study, carbon peaking and carbon neutrality are taken as the time base. The FLUS model is used to simulate future land allocation in four basic scenarios: natural development scenario, agricultural development scenario, low-carbon development scenario and industrial development scenario; and townships, towns, and subdistricts are taken as the basic statistical unit. Based on this, we have examined the suitability of future development of biomass energy in rural and urban areas in each scenario, as well as its contribution to the future energy system transformation that substitutes for fossil energy. This method has been applied to the case study of townships, towns, and subdistricts in Harbin City in China. The study results show that: The degrees to which biomass energy potential can substitute for fossil energy in the four scenarios in 2030 reach 4.21%, 5.62%, 5.47%, and 3.82%, respectively. Under agricultural development scenario, the supply-demand balance areas account for 48.94%, meaning this scenario has the largest potential for energy development and transition; low-carbon development scenario sees the highest degree of spatial supply-demand match, and thus enjoys the most advantages in energy transportation. The degrees to which biomass energy potential can substitute for fossil energy under the four scenarios in 2060 reach 2.01%, 6.96%, 5.35%, and 1.26% respectively. Agricultural development scenario still has the largest development potential, with the proportion of supply-demand balance areas jumping to 50.46%; Finally, low supply-high demand mismatch clusters are mainly concentrated in the main urban area and the central areas of townships, towns, and subdistricts. The high supply-low demand mismatch clusters are mainly distributed in the northeast. Under low-carbon development scenario, the low supply-high demand mismatch ratio has been reduced to 0.92%, the lowest supply-demand mismatch among all scenarios. Therefore, low-carbon development scenario enjoys the most spatial match advantages. This study will serve as an assessment method to advance the spatial development of biomass, and provide a geospatial basis for optimizing the layout of future energy development. Compared with previous studies, it has more spatial attributes, better reflects the complexity of biomass energy changes and is more connected with the measurement results and future policy making. In future research, we will combine multiple types of clean energy into the comparison and combined use to form a more comprehensive and specific research framework for new energy conversion. Longer-term macro-planning will go beyond the application boundaries of this research.

Landslide risk on photovoltaic power stations under climate change

To achieve the net-zero carbon dioxide emission goals, the number of solar photovoltaic (PV) power stations (PPSs) installed worldwide has increased. An increasing number of PPSs are exposed to natural hazards, such as landslides. However, the socioeconomic impact of landslide risk on PPSs has rarely been assessed nationally. In this study, we assessed the landslide risk for PPSs by combining statistical susceptibility and physical-based hazard analyses under three representative concentration pathways (RCPs). We found that the cumulative landslide-susceptible area (LSA) during the current, 2040s, and 2090s periods could vary depending on RCP scenarios: 2895 (RCP2.6), 3417 (RCP6.0) and 5492 km2 (RCP8.5). Especially, under RCP6.0, due to the spatial match with the distribution of LSA and the PPSs, the landslide risk on PPSs could become about 60 million dollars per year. This loss would be 24 million dollars more than the risk of RCP2.6. This study provides insights into the economic loss of PPSs from landslides in the Republic of Korea and suggests that severe climate change would bring a significant increase in this economic loss, which may occur in other countries with large mountainous areas.

A triphenylamine-based near-infrared fluorescence turn off probe for nitroreductase imaging

Nitroreductase (NTR) is an essential biomarker for various diseases and widely used to evaluate the hypoxia status in tumor cells. In this work, we developed a near-infrared (NIR) fluorescence “on-off” probe PTP based on a triphenylamine scaffold, with an intrinsic long wavelength emission more than 700 nm. This probe showed typical aggregation-induced emission (AIE) properties with the increase of PBS fraction (fw), which might be attributed to the restriction of intramolecular motions (RIM) effect in high aqueous solution. The frontiers molecular orbitals (FMO) of the probe PTP and the resulting reduction compounds (PT-OH and TPA-OH) were calculated to determine their structure differences. The two nitro groups were reduced in response to NTR and then released the substance TPA-OH through the 1,6-rearrangement-elimination, resulting in simultaneous fluorescence decrease. This process was also demonstrated by the DFT/TD-DFT and docking calculations, indicating a favorable structural and spatial match between the probe and NTR. More importantly, the probe was successfully used to visualize the NTR distribution in living A431 cells with nontoxicity. It exhibited a time-dependent fluorescence quenching behavior at the cellular level, making it of great potential in NTR detection for other biosystems.

Temporal visuomotor synchrony induces embodiment towards an avatar with biomechanically impossible arm movements

Visuomotor synchrony in time and space induces a sense of embodiment towards virtual bodies experienced in first-person view using Virtual Reality (VR). Here, we investigated whether temporal visuomotor synchrony affects avatar embodiment even when the movements of the virtual arms are spatially altered from those of the user in a non-human-like manner. In a within-subjects design VR experiment, participants performed a reaching task controlling an avatar whose lower arms bent in inversed and biomechanically impossible directions from the elbow joints. They performed the reaching task using this “unnatural avatar” as well as a “natural avatar,” whose arm movements and positions spatially matched the user. The reaching tasks were performed with and without a one second delay between the real and virtual movements. While the senses of body ownership and agency towards the unnatural avatar were significantly lower compared to those towards the natural avatar, temporal visuomotor synchrony did significantly increase the sense of embodiment towards the unnatural avatar as well as the natural avatar. These results suggest that temporal visuomotor synchrony is crucial for inducing embodiment even when the spatial match between the real and virtual limbs is disrupted with movements outside the pre-existing cognitive representations of the human body.

Is there a spatial match between roadkill and mitigation measures identified by functional connectivity modeling?

Linear transportation infrastructure affects the ability of wildlife species to live and move through anthropized landscapes. Mitigation measures are thus needed to maintain population viability. Several methods have been employed to determine optimal locations for these measures, including connectivity modeling, which targets areas with the strongest connectivity and/or potential connectivity gains. However, these results are seldom compared to biological data, such as roadkill. The objective of our study is to: i) to gain a deeper understanding of the relationships between roadkill and connectivity, ii) to spatially identify road sections with a high risk of roadkill and, iii) to compare high-risk roadkill areas with the locations identified for potential mitigation measures. We performed a generalized linear model to explain occurrence and abundance of roadkill and predict high-risk roadkill areas. The mitigation measures corresponded to either i) existing crossing structures that could be enhanced to facilitate wildlife passage, selected from the initial connectivity or ii) new wildlife crossings designed to reconnect habitats identified through connectivity gains.Our results indicate that connectivity significantly influences the occurrence and abundance of roadkill. However, the high-risk roadkill areas only partially align with the locations designated for mitigation measures. Since some roadkill occurs outside of high-connectivity areas, factors other than connectivity must also be taken into consideration. This study offers valuable insights and underscores the complexity of the relationships between connectivity, roadkill, and mitigation efforts. Furthermore, by integrating spatial modeling, mitigation strategies, and roadkill data, this study contributes to a deeper understanding of corridor restoration areas and their importance in species conservation.

A novel nitroreductase-responsive turn-off fluorescent probe based on AIEgen and its bioimaging application

Nitroreductase (NTR) is frequently employed as a biomarker to assess the level of hypoxia in tumor tissues. To date, the majority of NTR-reactive probes have focused on the luminescence "turn on" characteristic, which has been plagued by background interferences. In this study, we present the first report of an NTR-responsive "turn-off" fluorescent probe, TPEDCH-PBN, based on AIEgen. This probe exhibits typical aggregation-induced emission (AIE) properties in high PBS fraction, which may be attributed to the restriction of intramolecular motions (RIM) effect. DFT/TD-DFT calculations were employed to determine the discrepancies in structure and electron density distribution among TPEDCH, TPEDCH-PBNOH and TPEDCH-PBN. Additionally, docking calculations were utilized to elucidate the structure-function relationship between the probe and NTR, revealing a favorable structural and spatial match. Photophysical investigations demonstrated the probe's high selectivity towards NTR with the detection limit of 0.68 μg/mL. The dynamic quenching process of TPEDCH-PBN upon NTR was examined, and the quenching constant Ksv was determined to be 53.6 g−1.L. In addition, the NTR detection ability of probe TPEDCH-PBN as well as its time-dependent fluorescence quenching behaviors were confirmed by cell imaging of probe in A549 cells. Overall, this study proposed a novel molecular design approach for the biomarker detection probe, which may prove to be more extensively applicable.

Using fMRI to localize target regions for implanted brain-computer interfaces in locked-in syndrome

ObjectiveElectrocorticography (ECoG)-based brain-computer interface (BCI) systems have the potential to improve quality of life of people with locked-in syndrome (LIS) by restoring their ability to communicate independently. Before implantation of such a system, it is important to localize ECoG electrode target regions. Here, we assessed the predictive value of functional magnetic resonance imaging (fMRI) for the localization of suitable target regions on the sensorimotor cortex for ECoG-based BCI in people with locked-in syndrome. MethodsThree people with locked-in syndrome were implanted with a chronic, fully implantable ECoG-BCI system. We compared pre-surgical fMRI activity with post-implantation ECoG activity from areas known to be active and inactive during attempted hand movement (sensorimotor hand region and dorsolateral prefrontal cortex, respectively). ResultsResults showed a spatial match between fMRI activity and changes in ECoG low and high frequency band power (10 – 30 and 65 – 95 Hz, respectively) during attempted movement. Also, we found that fMRI can be used to select a sub-set of electrodes that show strong task-related signal changes that are therefore likely to generate adequate BCI control. ConclusionsOur findings indicate that fMRI is a useful non-invasive tool for the pre-surgical workup of BCI implant candidates. SignificanceIf these results are confirmed in more BCI studies, fMRI might be used for more efficient surgical BCI procedures with focused cortical coverage and lower participant burden.

Measuring the Spatial Match between Service Facilities and Population Distribution: Case of Lanzhou

With rapid urbanization and population growth, achieving equitable distribution of urban facilities in the city center has become a critical research focus due to limited land space and high population density. In this study, we propose a technical method to measure the spatial matching between urban service facilities and population at the grid resolution scale, using Baidu heat map and POI data. The method includes spatial heterogeneity analysis and spatial matching analysis between population density and service facilities. We apply the method to the main urban area of Lanzhou, a valley-type city in the upper reaches of the Yellow River, and measure the spatial matching between service facilities and population aggregation. Our results reveal the distribution characteristics of various service facilities and population aggregation in different time slots, and demonstrate that transportation facilities have the highest spatial matching with population aggregation, followed by real estate and education services, with rental business services exhibiting the lowest. The proposed method offers a new perspective for urban planners and decision-makers to understand the matching state between residents’ activity patterns and service facilities. Our findings can provide theoretical support for urban planning and optimize the layout of service facilities and regional function allocation.

Pulse high energy Fe: ZnSe laser pumped by Q-switched Er: YAG laser.

We report a pulse Fe: ZnSe laser pumped by an optical chopper Q-switched Er: YAG laser. By analyzed the spatial and temporal match of the gain and chopper, the maximum energy of the optical chopper Q-switched Er: YAG laser is 31mJ with the pulse width of 165 ns. By employing this Er: YAG laser as pump laser of Fe: ZnSe crystal, the maximum output energy of Fe: ZnSe laser is 10mJ with the pulse width of 80 ns at room temperature, that is the maximum energy of Fe: ZnSe laser at this Q-switched system to the best of our knowledge. We also study the directly Q-switched Fe: ZnSe laser, and the 2.7mJ mid-infrared laser with the pulse width of 200 ns is obtained at 80 K.

Rational design of a ratiometric fluorescent probe for imaging lysosomal nitroreductase activity

Overexpressed nitroreductase (NTR) is often utilized to evaluate the hypoxic degree in tumor tissues, thus it is of great importance to develop high selective and efficient optical method to detect NTR. The dynamic fusion and function of lysosome promoted us to explore the possible appearance of NTR inside this organelle and to probe its behavior in a cellular context. In this work, a ratiometric fluorescent probe based on an extended π-π conjugation of a triphenylamine unit was designed for NTR detection and lysosomes imaging. The dual-emission mechanism of the probe in the presence of catalytic NTR was confirmed by theoretical study. The structure–function relationship between probe and NTR was revealed by docking calculations, suggesting a suitable structural and spatial match of them. The photophysical studies showed the probe had high selectivity, rapid response and a wide pH range towards NTR. MTT assay indicated the probe had low cytotoxicity in both normal (HUVEC) and tumor (MCF-7) cells. Furthermore, the inverse fluorescent imaging results confirmed the probe was NTR-active and exhibited time- and concentration-dependent fluorescence signals. In addition, the relatively high Pearson’s correlation coefficient (0.99 in HepG2 and 0.97 in MCF-7 cells, compared to Lyso-Tracker Red) demonstrated the probe had excellent lysosomes colocalization. This study illustrates a ratiometric detection of NTR agent for lysosomes fluorescent imaging, which may provide a novel insight in molecular design.

MVFRnet: A Novel High-Accuracy Network for ISAR Air-Target Recognition via Multi-View Fusion

Inverse Synthetic Aperture Radar (ISAR) is a promising technique for air target imaging and recognition. However, the traditional monostatic ISAR only can provide partial features of the observed target, which is a challenge for high-accuracy recognition. In this paper, to improve the recognition accuracy of air targets, we propose a novel recognition network based on multi-view ISAR imaging and fusion, called Multi-View Fusion Recognition network (MVFRnet). The main structure of MVFRnet consists of two components, the image fusion module and the target recognition module. The fusion module is used for multi-view ISAR data and image preprocessing and mainly performs imaging spatial match, image registration, and weighted fusion. The recognition network consists of the Skip Connect Unit and the Gated Channel Transformation (GCT) attention module, where the Skip Connect Unit ensures the extraction of global depth features of the image and the attention module enhances the perception of shallow contour features of the image. In addition, MVFRnet has a strong perception of image details and suppresses the effect of noise. Finally, simulated and real data are used to verify the effectiveness of the proposed scheme. Multi-view ISAR echoes of six types of aircraft are produced by electromagnetic simulation software. In addition, we also build a millimeter wave ground-based bistatic ISAR experiment system and collect multi-view data from an aircraft model. The simulation and experiment results demonstrate that the proposed scheme can obtain a higher recognition accuracy compared to other state-of-the-art methods. The recognition accuracy can be improved by approximately 30% compared with traditional monostatic recognition.

Towards reliable monitoring of grass species in nature conservation: Evaluation of the potential of UAV and PlanetScope multi-temporal data in the Central European tundra

The reliability of remote sensing technology is essential for its efficient operational applications in nature conservation practices. In our study, multi-temporal, multispectral, and hyperspectral data from an Unoccupied Aerial Vehicle (UAV) with a ground sampling distance (GSD) of 3 cm were applied to a permanent research plot (1 ha), while spaceborne PlanetScope multi-temporal data with GSD of 3 m were used for a wider area of 250 ha. The main aim of the study was to evaluate the potential of these data for monitoring vegetation at the species level in the Central European relict arcto-alpine tundra (in the Krkonoše Mountains, Czech Republic). We evaluated both types of data and their performance for various classifiers, and the benefits of adding multi-temporal aspects to the classification and robustness of remote sensing for monitoring grass species. This study addresses the requirements of nature conservation practices in the Krkonoše Mts. National Park to find a suitable method for monitoring changes in dominant and expanding grass species in response to global warming. The object-based Support Vector Machine, pixel-based Random Forest and Maximum Likelihood classifiers were evaluated. We confirmed that the UAV multispectral and hyperspectral data with GSD of 3 cm can monitor dominant grass species (Nardus stricta, Calamagrostis villosa, Molinia caerulea, Deschampsia cespitosa) in tundra with excellent accuracy (95.9% and 94.0% overall accuracy for multi-temporal and mono-temporal composites, respectively). The best F1-scores for these species ranged from 94.7 to 99.4%. However, the accuracies were substantially lower for small and sparse growing species (Avenella flexuosa and Carex bigelowii). Unexpectedly, the UAV multispectral and hyperspectral data yielded comparable results. The multi-temporal approach improved the accuracy of all types of data. Overall, we confirmed the robustness of the remote sensing approach for grass monitoring at the species level given the high spatial match between various classification outputs. Our study established a workflow for reliable monitoring of tundra grass vegetation according to the requirements of nature conservation and proposed innovative measures for the spatial accuracy assessment of classification outputs.

A Heterogeneous Sampling Strategy to Model Earthquake-Triggered Landslides

Regional modeling of landslide hazards is an essential tool for the assessment and management of risk in mountain environments. Previous studies that have focused on modeling earthquake-triggered landslides report high prediction accuracies. However, it is common to use a validation strategy with an equal number of landslide and non-landslide samples, scattered homogeneously across the study area. Consequently, there are overestimations in the epicenter area, and the spatial pattern of modeled locations does not agree well with real events. In order to improve landslide hazard mapping, we proposed a spatially heterogeneous non-landslide sampling strategy by considering local ratios of landslide to non-landslide area. Coseismic landslides triggered by the 2008 Wenchuan Earthquake on the eastern Tibetan Plateau were used as an example. To assess the performance of the new strategy, we trained two random forest models that shared the same hyperparameters. The first was trained using samples from the new heterogeneous strategy, and the second used the traditional approach. In each case the spatial match between modeled and measured (interpreted) landslides was examined by scatterplot, with a 2 km-by-2 km fishnet. Although the traditional approach achieved higher AUCROC (0.95) accuracy than the proposed one (0.85), the coefficient of determination (R2) for the new strategy (0.88) was much higher than for the traditional strategy (0.55). Our results indicate that the proposed strategy outperforms the traditional one when comparing against landslide inventory data. Our work demonstrates that higher prediction accuracies in landslide hazard modeling may be deceptive, and validation of the modeled spatial pattern should be prioritized. The proposed method may also be used to improve the mapping of precipitation-induced landslides. Application of the proposed strategy could benefit precise assessment of landslide risks in mountain environments.

Radio and infrared study of the supernova remnant candidate HESS J1912+101

Aims.We provide new insights into theγ-ray emission from HESS J1912+101, a TeV supernova remnant candidate probably associated with the radio pulsar PSR J1913+1011.Methods.We obtained new observations at 1.5 GHz using the VLA in the D configuration, with the purpose of detecting the radio shell of the putative remnant. In addition, we observed a single pointing at 6.0 GHz toward PSR J1913+1011 to look for a radio pulsar wind nebula. We also studied the properties of the surrounding interstellar medium using data of the13CO, HI, and infrared emissions, obtained from public surveys.Results.We do not find evidence of a radio shell down to the sensitivity of the new image at 1.5 GHz. We detect faint diffuse emission around PSR J1913+1011 at 6.0 GHz, which could represent a radio pulsar wind nebula powered by the pulsar. We find dense ambient gas at ~60 km s−1, which shows a good spatial correspondence with the TeV emission only in the western and eastern directions. There is also dense gas near the center of HESS J1912+101, where the TeV emission is weak. Using infrared data, we identify an active star-forming region in the western part of the shell.Conclusions.Based on the poor spatial match between the ambient gas and the TeV emission (which shows a good correlation in the western and eastern directions and an anticorrelation in the other directions), we conclude that the hadronic mechanism alone does not give a satisfactory explanation of theγrays from HESS J1912+101. Additional contributions may come from leptonic processes in the shell of the supernova remnant, together with contributions from PSR J1913+1011 and its pulsar wind nebula and/or from the star-forming region. A confident determination of the distance to the putative remnant is necessary to determine whether these sources are associated or just appear superimposed in the line of sight.

A near real-time web-system for predicting fire spread across the Cerrado biome

Wildfires are aggravating due to climate change. Public policies need territorial intelligence to prevent and promptly fight fires, especially in vast regions like Brazil. To this end, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.04 ha spatial resolution. In both versions, the model attains 65–89% of spatial match. Model results together with ancillary data, e.g., historical burned areas and annual CO2 emissions from fires, are available on an interactive web-platform that serves as a tool for fire prevention and fight, particularly in the selected conservation units where the platform is being used for daily operations.