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Maps are used to describe far-off places . It is an aid for navigation and military strategies. Mapping of the lands are important and the mapping work is based on (i). Natural resource management & development (ii). Information technology…
Due to the evolving nature of power grids and model uncertainty, the online stability assessment of electrical power systems is always a challenging problem. This paper aims to provide a theoretical framework for estimating the region of…
Accurate characterization of subsurface heterogeneity is important for the safe and effective implementation of geological carbon storage (GCS) projects. This paper explores how machine learning methods can enhance data assimilation for GCS…
Accurate rainfall forecasting, particularly for extreme events, remains a significant challenge in climatology and the Earth system. This paper presents novel physics-informed Graph Neural Networks (GNNs) combined with extreme-value…
Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting ecosystems and inflicting substantial economic damages across agriculture, forestry, and fisheries. Due to the fast growth of global trade and…
Effective water resource management is crucial in agricultural regions like northeastern Thailand, where limited water retention in sandy soils poses significant challenges. In response to this issue, the Aerial Image Water Resource (AIWR)…
This contribution provides a strategy for studying and modelling the deforestation and soil deterioration in the natural forest reserve of Peten, Guatemala, using a poor spatial database. A Multispectral Image Processing of Spot and TM…
An accurate and precise understanding of global irrigation usage is crucial for a variety of climate science efforts. Irrigation is highly energy-intensive, and as population growth continues at its current pace, increases in crop need and…
This paper investigates the impacts of climate change on groundwater droughts making use of regional projections and standardized indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index…
Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time, landslide early warning systems (LEWS) for real-time disaster monitoring must estimate…
The Gromov-Wasserstein (GW) distance quantifies discrepancy between metric measure spaces and provides a natural framework for aligning heterogeneous datasets. Alas, as exact computation of GW alignment is NP hard, entropic regularization…
This paper proposes a new notion of distributional Input-to-State Stability (dISS) for dynamic systems evolving in probability spaces over a domain. Unlike other norm-based ISS concepts, we rely on the Wasserstein metric, which captures…
Current Landsat Level 2 surface temperature products are derived using a single-channel (SC) methodology to estimate per-pixel surface temperature (ST) maps from Level~1 radiance data. A known issue with the Level 2 uncertainty, however, is…
Water consumption is an increasingly critical dimension of computing sustainability, especially as AI workloads rapidly scale. However, current water impact assessment often overlooks where and when water stress is more severe. To fill in…
The prevailing approaches for ET retrievals are either limited in spatiotemporal coverage or largely influenced by choice of input data or simplified model physics, or a combination thereof. Here, using an independent mass conservation…
Spatial Online Analytical Processing System involves the non-categorical attribute information also whereas standard Online Analytical Processing System deals with only categorical attributes. Providing spatial information to the data…
Statistical modeling of dependent directional data remains relatively underexplored, particularly in high-dimensional spatial settings. Existing approaches for spatial angular data primarily rely on wrapped Gaussian process (WGP) models,…
Extreme floods cause casualties, and widespread damage to property and vital civil infrastructure. We here propose a Bayesian approach for predicting extreme floods using the generalized extreme-value (GEV) distribution within gauged and…
Extreme precipitation events occurring over large spatial domains pose substantial threats to societies because they can trigger compound flooding, landslides, and infrastructure failures across wide areas. A hybrid framework for spatial…
Both in terrestrial and extraterrestrial environments, the precise and informative model of the ground and the surface ahead is crucial for navigation and obstacle avoidance. The ground surface is not always flat and it may be sloped, bumpy…