相关论文: Spatial analysis of airborne laser scanning point …
Reliable extraction of cosmological information from observed cosmic microwave background (CMB) maps may require removal of strongly foreground contaminated regions from the analysis. In this article, we employ an artificial neural network…
We explore a variety of statistics of clusters selected with cosmic shear measurement by utilizing both analytic models and large numerical simulations. We first develop a halo model to predict the abundance and the clustering of weak…
GROUSE (Grassmannian Rank-One Update Subspace Estimation) is an iterative algorithm for identifying a linear subspace of R^n from data consisting of partial observations of random vectors from that subspace. This paper examines local…
We investigate the promise of the Ly-alpha forest for high precision cosmology in the era of the Sloan Digital Sky Survey using low order N-point statistics. We show that with the existing data one can determine the amplitude, slope and…
Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structures can enable important clinical applications. We present a…
Occlusion caused by vegetation is an essential problem for remote sensing applications in areas, such as search and rescue, wildfire detection, wildlife observation, surveillance, border control, and others. Airborne Optical Sectioning…
Precision mapping of landslide inventory is crucial for hazard mitigation. Most landslides generally co-exist with other confusing geological features, and the presence of such areas can only be inferred unambiguously at a large scale. In…
Extremely large aperture arrays (ELAAs) can offer massive spatial multiplexing gains in the radiative near-field region in beyond 5G systems. While near-field channel modeling for uniform linear arrays has been extensively explored in the…
We address the problem of comparing and aligning spatial point configurations in $\mathbb{R}^3$ arising from structured geometric patterns. Each pattern is decomposed into arms along which we define a normalized finite-difference operator…
Reliable large-scale data on the state of forests is crucial for monitoring ecosystem health, carbon stock, and the impact of climate change. Current knowledge of tree species distribution relies heavily on manual data collection in the…
Spatial documentation is exponentially increasing given the availability of Big IoT Data, enabled by the devices miniaturization and data storage capacity. Bayesian spatial statistics is a useful statistical tool to determine the dependence…
Spatial fields in the Earth and environmental sciences are often available at multiple scales or resolutions. While coarse-scale data (e.g., from global circulation models) are often abundant, they lack the local detail provided by…
Fine-resolution maps of forest aboveground biomass (AGB) effectively represent spatial patterns and can be flexibly aggregated to map subregions by computing spatial averages or totals of pixel-level predictions. However, generalized…
Forecasting future states of sensors is key to solving tasks like weather prediction, route planning, and many others when dealing with networks of sensors. But complete spatial coverage of sensors is generally unavailable and would…
Deforestation, as one of the challenging environmental problems in the world, has been recorded the most serious threat to environmental diversity and one of the main components of land-use change. In this paper, we investigate spatial…
Spatial correlation in areal unit count data is typically modelled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution. The spatial correlation structure implied by this model depends on a…
Nitrogen dioxide (NO$_2$) is a primary constituent of traffic-related air pollution and has well established harmful environmental and human-health impacts. Knowledge of the spatiotemporal distribution of NO$_2$ is critical for exposure and…
Spatial regression or geographically weighted regression models have been widely adopted to capture the effects of auxiliary information on a response variable of interest over a region. In contrast, relationships between response and…
Forest regeneration is a spatial multifaceted process with numerous unknown variables. The individual area or the area potentially available (APA) to an individual plant embodies an idea widely used in population ecology but it has fewer…
The constant increase in energy consumption has created the necessity of extending the energy transmission and distribution network. Placement of powerlines represent a risk for bird population. Hence, better understanding of deaths induced…