Spherically Stratified Point Projection: Feature Image Generation for Object Classification Using 3D LiDAR Data

Three-dimensional point clouds have been utilized and studied for the classification of objects at the environmental level. While most existing studies, such as those in the field of computer vision, have detected object type from the perspective of sensors, this study developed a specialized strategy for object classification using LiDAR data points on the surface of the object. We propose a method for generating a spherically stratified point projection (sP2) feature image that can be applied to existing image-classification networks by performing pointwise classification based on a 3D point cloud using only LiDAR sensors data. The sP2’s main engine performs image generation through spherical stratification, evidence collection, and channel integration. Spherical stratification categorizes neighboring points into three layers according to distance ranges. Evidence collection calculates the occupancy probability based on Bayes’ rule to project 3D points onto a two-dimensional surface corresponding to each stratified layer. Channel integration generates sP2 RGB images with three evidence values representing short, medium, and long distances. Finally, the sP2 images are used as a trainable source for classifying the points into predefined semantic labels. Experimental results indicated the effectiveness of the proposed sP2 in classifying feature images generated using the LeNet architecture.

Topography as a determinant of bird distribution in secondary Atlantic Forest fragments

The spatial distribution of Neotropical birds at local scales is often associated with plant successional stages and unique microhabitats such as bamboo stands and treefall gaps. Only 15% of the Atlantic Forest remains, yet this habitat is home to more than 200 endemic birds. Understanding the distribution of bird species within the Atlantic Forest can improve the test of ecological hypotheses related to habitat use and habitat selection. This study analyses the distribution of birds among different types of relief (lowlands, ravines, hillsides, and hilltops) in 41 forest fragments of different sizes (1 to 384.5 ha) within the Atlantic Forest, south east Brazil. The presence and absence data were analysed with dynamic occupancy models to determine the influence of area and topography in the distribution of bird species. Of the 169 species detected, we were able to estimate an occupancy probability of 67. Among them, relief type was an important variable for 26 species (39%). Most species showed a preference for lowlands and ravines, and some showed an association of combinations of these two reliefs with hillsides and hilltops. These preferences might be related to distribution of preferred food, nesting microhabitats, and thermoregulation. For the endemic and threatened Atlantic Forest mountain birds, the ecological association with areas of relief is a strong, and previously unsuspected, spatial distribution pattern. Our results suggest that the ecology and distribution of birds in tropical forests across hilly regions could be better understood if topography is considered. This pattern should be better investigated among other taxa in tropical forests.

Occupancy patterns of prey species in a biological corridor and inferences for tiger population connectivity between national parks in Bhutan

Site occupancy models, accounting for imperfect detection and the influence of anthropogenic and ecological covariates, can indicate the status of species populations. They may thus be useful for exploring the suitability of landscapes such as biological corridors, to ensure population dispersal and connectivity. Using occupancy probability models of its principal prey species, we make inferences on landscape connectivity for the movement of the tiger Panthera tigris between protected areas in Bhutan. We used camera-trap data to assess the probability of site occupancy (Ψ) of the sambar Rusa unicolor, wild boar Sus scrofa and barking deer Muntiacus muntjak in biological corridor no. 8, which connects two national parks in central Bhutan. At least one prey species was recorded at 17 out of 26 trapping locations. The probability of site occupancy was highest for the barking deer (Ψ = 0.52 ± SE 0.09) followed by sambar (Ψ = 0.49 ± SE 0.03) and wild boar (Ψ = 0.45 ± SE 0.07). All three species had higher occupancy probability at lower altitudes. Sambar occupancy was greater farther from settlements and on steeper and/or south-facing slopes. Barking deer also had higher occupancy on south-facing slopes, and wild boar occurred mainly close to rivers. Our findings suggest that this biological corridor could facilitate dispersal of tigers. Protecting prey species, and minimizing anthropogenic disturbance and habitat fragmentation, are vital for tiger dispersal and thus functional connectivity amongst populations in this area.

Occupancy and detection of Wavyrayed Lampmussel Lampsilis fasciola in Ontario, Canada

Freshwater mussels (Bivalvia: Unionidae) are the most imperilled taxon in Canada. To facilitate species recovery efforts, an understanding of species distribution and habitat that supports species persistence is needed. Detecting mussels presents unique challenges, however, requiring considerable effort due to their complex life-histories and widespread declines. Here, observations of the imperilled Wavyrayed Lampmussel (Lampsilis fasciola Rafinesque 1820) from the Grand and Thames rivers, Ontario, Canada were used to quantify species detection and occupancy probabilities, and the relationship between occupancy probability and substrate size. The best model for the data included a river-specific covariate for detection and an intercept model for occupancy. Detection probability of Wavyrayed Lampmussel was higher in the Grand River than the Thames River. Limited variation in substrate size measurements restricted occupancy modeling, but field measurements qualitatively aligned with previous habitat descriptions. Overall, knowledge of species detection and occupancy probabilities for Wavyrayed Lampmussel will not only enhance the understanding of species distribution and habitat associations, but also ensure that the response of the species to threats and recovery actions are captured.

Factors Associated with Detection Probability and Site Occupancy of the Long-Tailed Skink (Eutropis longicaudata) in the Aluoi Area, Central Vietnam

Lizard species are rarely detected with perfect accuracy, regardless of the method employed. Nondetection of a species at a site does not necessarily mean the species was absent unless the detection probability was 100%. We assessed the influence of site covariates (less disturbed habitat and disturbed habitat) and sample covariates (temperature, humidity, rainfall) on the occupancy of Eutropis longicaudata in the Aluoi area, central Vietnam. Based on detection/nondetection data over nine visits at 40 less disturbed sites and 39 sites with disturbed habitats, the distribution of E. longicaudata was estimated using site occupancy models. From the best model, we estimated a site occupancy probability of 0.595, a 12.05% increase over the naive occupancy of 0.531 at which E. longicaudata skinks were actually observed. The site covariate of the less disturbed habitat was an important determinant of site occupancy, which was not associated with the variable of disturbance habitats. In the combined AIC model weight, p(precipitation), p(temperature), and p(humidity) have 92%, 36%, and 21% of the total, respectively; providing evidence that environmental conditions (especially precipitation) were important sample covariates in modelling detection probabilities of E. longicaudata. In terms of occupancy probability, the combined weight for the ψ(less disturbed habitat) model and the ψ(disturbed habitat) model were 60% and 32%, respectively. Our results substantiate the importance of incorporating detection and occupancy probabilities into studies of habitat relationships and suggest that the less disturbed habitat associated with weather conditions influence the occupancy of E. longicaudata in central Vietnam.

Improved Indoor Positioning by Means of Occupancy Grid Maps Automatically Generated from OSM Indoor Data

In recent years, there is a growing interest in indoor positioning due to the increasing amount of applications that employ position data. Current approaches determining the location of objects in indoor environments are facing problems with the accuracy of the sensor data used for positioning. A solution to compensate inaccurate and unreliable sensor data is to include further information about the objects to be positioned and about the environment into the positioning algorithm. For this purpose, occupancy grid maps (OGMs) can be used to correct such noisy data by modelling the occupancy probability of objects being at a certain location in a specific environment. In that way, improbable sensor measurements can be corrected. Previous approaches, however, have focussed only on OGM generation for outdoor environments or require manual steps. There remains need for research examining the automatic generation of OGMs from detailed indoor map data. Therefore, our study proposes an algorithm for automated OGM generation using crowd-sourced OpenStreetMap indoor data. Subsequently, we propose an algorithm to improve positioning results by means of the generated OGM data. In our study, we used positioning data from an Ultra-wideband (UWB) system. Our experiments with nine different building map datasets showed that the proposed method provides reliable OGM outputs. Furthermore, taking one of these generated OGMs as an example, we demonstrated that integrating OGMs in the positioning algorithm increases the positioning accuracy. Consequently, the proposed algorithms now enable the integration of environmental information into positioning algorithms to finally increase the accuracy of indoor positioning applications.

A first-passage approach to diffusion-influenced reversible binding and its insights into nanoscale signaling at the presynapse

Synaptic transmission between neurons is governed by a cascade of stochastic calcium ion reaction–diffusion events within nerve terminals leading to vesicular release of neurotransmitter. Since experimental measurements of such systems are challenging due to their nanometer and sub-millisecond scale, numerical simulations remain the principal tool for studying calcium-dependent neurotransmitter release driven by electrical impulses, despite the limitations of time-consuming calculations. In this paper, we develop an analytical solution to rapidly explore dynamical stochastic reaction–diffusion problems based on first-passage times. This is the first analytical model that accounts simultaneously for relevant statistical features of calcium ion diffusion, buffering, and its binding/unbinding reaction with a calcium sensor for synaptic vesicle fusion. In particular, unbinding kinetics are shown to have a major impact on submillisecond sensor occupancy probability and therefore cannot be neglected. Using Monte Carlo simulations we validated our analytical solution for instantaneous calcium influx and that through voltage-gated calcium channels. We present a fast and rigorous analytical tool that permits a systematic exploration of the influence of various biophysical parameters on molecular interactions within cells, and which can serve as a building block for more general cell signaling simulators.

Understanding distribution and occupancy of Himalayan Monal in Uttarkashi district, Uttarakhand

The Himalayan Monal is a conservation priority species in its entire distribution range. Its population is declining in many areas due to various anthropogenic threats. The information on species distribution and its abundance is lacking in many areas which are vital for conservation and management planning. Hence, through the present study, we have assessed the abundance and occupancy of Himalayan monal in Uttarkashi district (Uttarakhand). We used camera traps and conventional sign surveys for documenting the species during 2018-2019. We installed a total of 69 camera traps (2819 trap nights) and surveyed 54 trails (650 km) which represents entire habitat and topographic variability of the landscape. The occupancy and detection probability was modelled using the habitat variables. The top model showed that occupancy probability of Himalayan monal was positively influenced by the slope (β =27.52 ±16.25) and negatively influenced by Reserve Forest (RF) (β= −8.14 SE ± 4.99). The observed naïve occupancy of Himalayan Monal was 0.69 in the study area, which was slightly lower than the estimated occupancy. However, in the null model, the site occupancy estimated was found to be 0.82±0.08 and with detection probability 0.23±0.03. The overall abundance of monal was estimated about 171.58 ±10.2 in the study area with an average density of 0.62/ km2. The activity pattern analysis indicates that monal remains very active between 6.00 hrs −12.00 hrs and relatively less active during mid-day when humans are most active 11.30 hrs-16.30 hrs. The present study is a first attempt to estimate occupancy and abundance using camera traps as well as sign survey for the species primarily from non-Protected Area (PA). We found that Himalayan monal is abundant outside the PAs, which is a good indication for its long-term viability and also identified areas for conservation and management prioritization in Uttarkashi.

Analysis of well testing results for single phase flow in reservoirs with percolation structure

Constructing an accurate geological model of the reservoir is a preliminary to make any reliable prediction of a reservoir’s performance. Afterward, one needs to simulate the flow to predict the reservoir’s dynamic behaviour. This process usually is associated with high computational costs. Therefore, alternative methods such as the percolation approach for rapid estimation of reservoir efficiency are quite desirable. This study tries to address the Well Testing (WT) interpretation of heterogeneous reservoirs, constructed from two extreme permeabilities, 0 and K. In particular, we simulated a drawdown test on typical site percolation mediums, occupied to fraction “p” at a constant rate Q/h, to compute the well-known pressure derivative (dP/dlnt). This derivative provides us with “apparent” permeability values, a significant property to move forward with flow prediction. It is good to mention that the hypothetical wellbore locates in the middle of the reservoir with assumed conditions. Commercial software utilized to perform flow simulations and well test analysis. Next, the pressure recorded against time at different realizations and values of p. With that information provided, the permeability of the medium is obtained. Finally, the permeability change of this reservoir is compared to the permeability alteration of a homogeneous one and following that, its dependency on the model parameters has been analysed. The result shows a power-law relation between average permeability (considering all realizations) and the occupancy probability “p”. This conclusion helps to improve the analysis of well testing for heterogeneous reservoirs with percolation structures.

Seasonal monitoring of Hida salamander Hynobius kimurae using environmental DNA with a genus-specific primer set

The diversity and the abundance of amphibians have dramatically declined globally over the past 30 years, and the monitoring and conservation of their habitats is essential. However, traditional methods such as bait trapping and mark-recapture are costly, and morphological identification usually requires a high level of taxonomic expertise. Here, seasonal surveillances of Hida salamander Hynobius kimurae were performed by means of environmental DNA (eDNA) analysis with Hynobius-specific primers and a species-specific TaqMan probe. Water sampling and visual surveys were conducted seasonally in a stream in Kyoto Prefecture, Japan. Detection rates of eDNA were then calculated by real-time PCR, and eDNA site occupancy probability was estimated by multi-scale occupancy modeling. The eDNA-based detection rate of Hida salamander was 76.7%, whereas the visual survey-based detection rate was 23.3%, and target eDNA was detected at almost all sites where the presence of target species was visually confirmed. Moreover, factors relating to the site- and sample-level occurrence probabilities of the target eDNA differed depending on the developmental stage of the target species. Our findings support previous studies showing that eDNA analysis enables an effective assessment of amphibian distributions without damaging the organisms or their habitat, and we compare for the first time the site occupancy probability of amphibian eDNA throughout the life cycle of an amphibian species. The present study contributes to the development of eDNA analysis as a tool for understanding the distribution and seasonal activity of amphibian species and will thus aid in the planning of conservation measures and habitat restoration for these species.