Related papers: Water Level Estimation Using Sentinel-1 Synthetic …
We propose a pipeline for combined multi-class object geolocation and height estimation from street level RGB imagery, which is considered as a single available input data modality. Our solution is formulated via Markov Random Field…
Precise Soil Moisture (SM) assessment is essential in agriculture. By understanding the level of SM, we can improve yield irrigation scheduling which significantly impacts food production and other needs of the global population. The…
Monocular depth estimation has experienced significant progress on terrestrial images in recent years, largely due to deep learning advancements. However, it remains inadequate for underwater scenes, primarily because of data scarcity.…
Synthetic aperture radar (SAR) interferometry (InSAR) is performed using repeat-pass geometry. InSAR technique is used to estimate the topographic reconstruction of the earth surface. The main problem of the range-Doppler focusing technique…
Analysis of sediments from rivers, lakes, reservoirs, wetlands and other constructed surface water impoundments is an important tool to characterize the function and health of these systems, but is generally carried out manually. This is…
Atmospheric water harvesting is urgently needed given increasing global water scarcity. Current sorbent-based devices that cycle between water capture and release have low harvesting rates. We envision a radically different multi-material…
A single-camera synthetic Schlieren method is introduced to measure the height of a dynamic free liquid surface in a container with a flat bottom. Markers placed on the bottom, seen through the free surface, are virtually displaced due to…
Mapping land surface disturbances supports disaster response, resource and ecosystem management, and climate adaptation efforts. Synthetic aperture radar (SAR) is an invaluable tool for disturbance mapping, providing consistent time-series…
Rain fills the atmosphere with water particles, which breaks the common assumption that light travels unaltered from the scene to the camera. While it is well-known that rain affects computer vision algorithms, quantifying its impact is…
Rain streaks will inevitably be captured by some outdoor vision systems, which lowers the image visual quality and also interferes various computer vision applications. We present a novel rain removal method in this paper, which consists of…
Climate change is intensifying extreme weather events, causing both water scarcity and severe rainfall unpredictability, and posing threats to sustainable development, biodiversity, and access to water and sanitation. This paper aims to…
Reconstructing high-resolution rainfall fields is essential for flood forecasting, hydrological modeling, and climate analysis. However, existing spatial interpolation methods-whether based on automatic weather station (AWS) measurements or…
In cities with tall buildings, emergency responders need an accurate floor level location to find 911 callers quickly. We introduce a system to estimate a victim's floor level via their mobile device's sensor data in a two-step process.…
In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide risk mitigation. We focus first on landslide detection and…
We review the systematic uncertainties that have plagued attempts to obtain high precision and high accuracy from ground-based photometric measurements using CCDs. We identify two main challenges in breaking through the 1% precision…
Surface runoff shapes planetary landscapes, but global hydrological models often lack the resolution and flexibility to simulate dynamic surface water bodies beyond Earth. Recent studies of Mars have revealed abundant geological and…
Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (characterized by soil nature, infiltration capacity and moisture),…
We investigate the use of a point cloud measurement in terrain-aided navigation. Our goal is to aid an inertial navigation system, by exploring ways to generate a useful measurement innovation error for effective nonlinear state estimation.…
A potential framework to estimate the volume of water stored in a porous storage reservoir from seismic data is neural networks. In this study, the man-made groundwater reservoir is modeled as a coupled poroviscoelastic-viscoelastic medium,…
The sea level observations from satellite altimetry are characterised by a sparse spatial and temporal coverage. For this reason, along-track data are routinely interpolated into daily grids. The latter are strongly smoothed in time and…