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Time delay estimation or Time-Difference-Of-Arrival estimates is a critical component for multiple localization applications such as multilateration, direction of arrival, and self-calibration. The task is to estimate the time difference between a signal arriving at two different sensors. For the audio sensor modality, most current systems are based on classical methods such as the Generalized Cro

The Amazon rainforest is highly biodiverse and has the largest extent of the remaining intact tropical forests in the world. To this day, undisturbed tropical forests act as a carbon sink by taking up about 15% of anthropogenic carbon emissions per year. However, in the past decades, a declining trend in the carbon sink capacity in the Amazon rainforest has been observed due to increased carbon lo

This work investigates the design of beampatterns for frequency diverse arrays-multiple-input multiple-output (FDA-MIMO) in the range-angle plane, in order to improve the approximation of a desired beampattern. Recognizing that the energy radiated by the array cannot be locked at a fixed range and angle, the beampattern is designed for the equivalent beampattern at the receiving end, differing fro

The separation of multiple transmit waveforms with time and frequency synchronization constitutes a considerable challenge for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) systems. It is well-known that aliased signal returns may be separable by digital beamforming (DBF) on receive in elevation. However, the current orthogonal-waveform beamforming schemes significantly incr

This article addresses the problem of multi-target localization from acoustic time delay measurements in a 3-D underwater environment, taking into account the depth-dependent sound speed of the underwater wave propagation. Specifically, we formulate the problem as an optimal mass transport (OMT) optimization over a grid of potential candidate positions. By exploiting an iterative refinement approa

This paper focuses on the meticulous selection of optimal remote sensing and climate datasets for Gross Primary Productivity (GPP) estimation in African rangelands. Utilizing Eddy Covariance Flux Tower data, we refine data selection and employ a Light Use Efficiency (LUE) model, with Sentinel 2 for photosynthetically active vegetation quantification, MODIS for Photosynthetically Active Radiation (

This research explores herbaceous biomass estimation in African rangelands through remote sensing, emphasizing challenges and uncertainties. Comparing remote sensing data with ground validation, the study addresses spatiotemporal variations, employing advanced models and validation techniques. Harmonizing and calibrating ground data from four African countries, the research provides insights into

Forests are integral to the global carbon cycle, acting as major carbon sinks, though their capacity can be altered by climate and land use changes. India has a diverse forest ecosystem, but the dynamics and changes in its carbon stocks under a changing climate are not well understood. This study investigates the regional and temporal changes in vegetation carbon biomass (VCB) within Indian forest

Highlights: What are the main findings? A ~32-year aridity cycle is detected across China through Fourier spectrum analysis of 1950–2022 aridity data. An arid–humid climate divide is revealed by entropy-based climate stability indicators. Recent remote sensing data show a nationwide expansion of surface water bodies and localized groundwater recovery. What are the implications of the main findings

Wind energy is an important form of clean energy, and its rational utilization represents a crucial solution for mitigating the energy crisis and global warming. In this study, wind energy potential and its long-term changes in the South China Sea (SCS) are evaluated using ERA5 100 m wind data from 1944 to 2023, validated against ASCAT observations. High wind speeds and high wind power density (WP

One of the key ecological processes affected by climate change is plant carbon uptake. However, there is substantial uncertainty about how plant carbon uptake will respond to warming in mountain ecosystems, which are known for sharp temperature gradients and abrupt shifts in vegetation structure. Specifically, we lack an understanding of whether these response trajectories over time will be linear

Wildfires pose hazards for humans through fire proximity and smoke exposure, and are expected to pose increasing risks due to climate change. Existing literature has not extensively inquired how wildfires affect short-term mobility as an adaptive response to these events. We use digital trace mobility data from the Spanish Ministry of Transportation to examine how proximity to wildfires and conseq

Climate change and escalating human pressures erode the resilience of global forests, putting biodiversity, carbon storage, and societal well-being at risk. Fragmented, single-sector responses cannot keep pace with the speed or complexity of these threats. By synthesizing insights from resilience theory and global practices across ecological, social, and institutional dimensions, we propose 10 mut

Accurate forest aboveground biomass (AGB) estimation across heterogeneous subtropical regions is essential for carbon accounting and climate change mitigation. We developed XGBoost and random forest models using GEDI L4A Lidar samples and multi-source remote sensing features (Sentinel-1/2, topography) to predict AGB in Xijiang Forest Farm (Guangdong) and transferred them to Simao District (Yunnan)

Understanding the spatiotemporal dynamics of dissolved organic carbon (DOC) is essential for predicting aquatic carbon fluxes and managing water quality in boreal catchments. Traditional DOC modelling approaches are limited in their ability to represent seasonal dynamics, event-driven responses, and riparian-zone contributions. Here, we evaluate the performance of the Krycklan-HYPE model in simula

Monitoring atmospheric CO2 concentration changes across China is crucial for reducing carbon emissions and tackling global warming. Due to monitoring gap in satellite observations, this paper uses the Extremely Randomized Trees (ERT) model alongside OCO-2 satellite data and predictor variables to develop a 0.1° high-resolution monthly dataset of column-averaged dry air CO2 mole fraction (XCO2) in

Childhood stunting is a serious public health concern in Rwanda. Although stunting causes have been documented, we still lack a more in-depth understanding of their local factors at a more detailed geographic level. We cross-sectionally examined 615 height-for-age prevalence observations in the Northern Province of Rwanda, linked with their related covariates, to explore the spatial heterogeneity

Many forms of small-size radars suffer from minor clock oscillations due to crystalline impurities in their internal clocks, causing time-varying clock offsets between the transmitter and the receivers. This offset causes a bias and an increased variance in the positioning of close-range targets, limiting the achievable accuracy well beyond the expected estimation limitations. This performance is