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Different organismal functional feeding groups (FFGs) are key components of aquatic food webs and are important for sustaining ecosystem functioning in riverine ecosystems. Their distribution and diversity are tightly associated with the surrounding terrestrial landscape through land‐water linkages. Nevertheless, knowledge about the spatial extent and magnitude of these cross‐ecosystem linkages within

Strategic forest inventories are required to support management, enable monitoring, and inform policy development. These inventories are typically developed using photointerpretation of aerial imagery, followed by manual stand delineation and attribution. The process of delineating and attributing these segments can be costly, time consuming, and subjective. Many spectrally driven segmentation algorithms

Nonlinear Bκ-embeddings (NLE) –recently introduced for the analysis of complex systems and complex spatiotemporal behavior– have been applied here to develop a reliable land degradation assessment and monitoring tool. Normalized Difference Vegetation Index (NDVI) time series, which are non-stationary and present seasonal, long-term and short-term variations, can be nonlinearly embedded into an encompassing

Insect and pathogen outbreaks have a major impact on northern forest ecosystems. Even for pathogens that have been present in a region for decades, such as beech bark disease (BBD), new waves of tree mortality are expected. Hence, there is a need for innovative approaches to monitor disease advancement in real time. Here, we test whether airborne hyperspectral imaging – involving data from 344 wavelengths

Biological soil crusts, commonly referred to as biocrusts (including lichens), play a vital ecological role in arid environments by stabilizing the soil, reducing erosion, and influencing nutrient and water cycles. Remote sensing has become an indispensable tool for mapping biocrusts because it can efficiently analyze extensive and inaccessible areas. Furthermore, spectral analysis of biocrusts provides

The goal of referring remote sensing image segmentation (RRSIS) is to extract specific pixel-level regions within an aerial image via a natural language expression. Recent advancements, particularly Transformer-based fusion designs, have demonstrated remarkable progress in this domain. However, existing methods primarily focus on refining visual features using language-aware guidance during the cross-modal

Fine-grained economic mapping through urban representation learning has emerged as a crucial tool for evidence-based economic decisions. While existing methods primarily rely on supervised or unsupervised approaches, they often overlook semi-supervised learning in data-scarce scenarios and lack unified multi-task frameworks for comprehensive sectoral economic analysis. To address these gaps, we propose

Rainfed rice fields are among the primary rice ecosystems in many Asian countries, including Thailand. High variability in rainfall amount and its distribution under climate change and climate variability, such as El Ni?o, has made this rice ecosystem highly vulnerable. Here, we report the impacts of El Ni?o on methane (CH4), carbon dioxide (CO2), water (H2O), energy exchanges, and grain yield in a

BeiDou Global Navigation Satellite System (BDS-3) PPP-B2b service greatly promotes the real-time precise point positioning applications. However, previous research works have revealed that a nonnegligible satellite-specific clock bias (SCB) exists in the PPP-B2b clock offset, causing the degradation of PPP-B2b positioning performance. In this paper, a single-station-augmented PPP-B2b considering the

Building information extraction holds significant application value in smart city development, urban planning, and management. With the accelerating process of urbanization, mid- and high-rise buildings are increasingly prevalent. In orthophotos, the roofs of tall buildings often do not fully overlap with their footprints. In satellite images from oblique angles, buildings may also be obstructed or

Accurate recognition and vectorization of agricultural cultivation field parcels (CFP) are crucial for agricultural monitoring. However, the diverse sizes and shapes of parcels, inherent blurriness of boundaries, and adhesion of densely distributed parcels pose considerable challenges in extracting complete and separable parcels from high-resolution imagery. To address these issues, we propose an end-to-end

Multi-baseline (MB) phase unwrapping (PU) represents the core processing step of MB InSAR, which overcomes discontinuous terrain height estimation. However, MBPU faces the challenge of low noise robustness. A new robust cutting plane–pure integer programming (CP-PIP) PU algorithm that considers the fringe frequency for dual-baseline InSAR is proposed to address this problem. First, we establish a closed-region

Hyperspectral target detection (HTD) aims to identify specific materials based on spectral information in hyperspectral imagery and can detect extremely small-sized objects, some of which occupy a smaller than one-pixel area. However, existing HTD methods are developed based on per-pixel binary classification, neglecting the three-dimensional cube structure of hyperspectral images (HSIs) that integrates

Major shifts in the Indian Summer Monsoon (ISM) are evident in a U-Th-dated composite δ18O record from Kailash Cave (KGC) in central India. The composite oxygen isotope record combines previously published data with the present data from sample KG-1, ranging in age from 14.62 to 12.97 thousand year before the Present (1950) (kyr BP), during the B?lling-Aller?d (B-A) interstadials. Petrographic analysis

The long-term climate stability of the Earth has been attributed to the negative feedback between the rate of CO2-consuming silicate weathering and the partial pressure of atmospheric CO2. It is generally believed that the capability of silicate weathering in feedbacking climate is mainly associated with the rapid-eroding mountains where fresh bedrock adequately exposes. In contrast, the slow-eroding

National forest inventory (NFI) data has become an indispensable reference for model training and validation when estimating forest aboveground biomass (AGB) using satellite observations. However, obtaining statistically sufficient NFI data for model training is challenging for countries with vast land areas and extensive forest coverage like Canada. This study aims to directly upscale all available

The Neogene evolution of the Asian monsoon and East Asian silicate weathering remains debated. Previous reconstructions of the silicate weathering intensity (SWI) from the Asian interior and the South China Sea have shown a notable long-term decrease since the mid-Miocene, which has been attributed primarily to global cooling. However, considerable geologic evidence indicates that uplift of the northern

The prolate spheroidal harmonic series is a well-suited tool for gravity modeling of elongated bodies. In this work, the prolate spheroidal harmonic algorithms for forward modeling of the gravitational field of homogeneous polyhedral bodies are presented. The line integral forms of the prolate spheroidal harmonic coefficients are given using the Gauss divergence and the Stokes theorems, and the discontinuities

Accurate, spatially explicit quantification of vegetation structure in drylands can improve our understanding of the important role that these critical ecosystems play in the Earth system. In semiarid woodland settings, remote sensing of vegetation structure is challenging due to low tree height, cover, and greenness as well as limited spatial and temporal availability of airborne lidar data. These

Hyperspectral (HSP) video data can offer rich spectral-spatial–temporal information crucial for capturing object dynamics, attenuating the drawbacks of classical unimodal and multi-modal tracking. Current HSP tracking arts often suffer from feature refinements and information interactions, sealing the ceiling of capabilities. This study presents ProFiT, an innovative prompt-guided frequency-aware filtering

The Dansgaard-Oeschger (DO) recurrence is a prominent feature during the last glaciation, yet its characteristics during older glacial periods remain unclear. Here, we present a precisely-dated, high-resolution stalagmite record from Luoshui Cave in central China, revealing millennial- and centennial-scale variability of the Asian summer monsoon (ASM) during 146–136.6?ka BP (before 1950?CE). The isotopic

The North Equatorial Current (NEC) is an essential part of the global warm pool and plays a key role in the subtropical and tropical circulation systems of the North Pacific. As the current is transported from east to west, significant changes in the structure and function of the associated ecosystem are expected. However, the complexity of the current systems and the region's remote location far from

Abundant, well-annotated multimodal data in remote sensing are pivotal for aligning complex visual remote sensing (RS) scenes with human language, enabling the development of specialized vision language models across diverse RS interpretation tasks. However, annotating RS images with rich linguistic semantics at scale demands expertise in RS and substantial human labor, making it costly and often impractical

In spring, many deciduous broadleaf trees start with flower emergence and then leaf emergence, which are two key phenological events, as they signal the onset of reproduction and vegetative growth in a year. These trees provide essential resources for early pollinators searching for flowers, contribute to biodiversity, and create socio-economic benefits through tourism. Accurate detection and monitoring

As camera traps have become more widely used, extracting information from images at the pace they are acquired has become challenging, resulting in backlogs that delay the communication of results and the use of data for conservation and management. To ameliorate this, artificial intelligence (AI), crowdsourcing to citizen scientists and combined approaches have surfaced as solutions. Using data from

Optical remote sensing images are crucial data sources for various applications, including agricultural monitoring, land cover classification, and urban planning. However, cloud cover often hinders their effectiveness, which poses a significant challenge to downstream tasks. To address this issue, we introduce the Similarity-based Multimodal De-Clouding Network (SMDCNet), an innovative framework that

It is widely accepted that the horizontal tectonic forces and lateral rheological contrast control the strain localization and, consequently, the evolution of mountain ranges. However, in active orogenesis involving massive surface materials redistribution, to what extent and in which way do surface processes and strong contrast in vertical rheological properties manage the stress transmission and

Until recently, the spatial-temporal changes and driving factors of vegetation net primary productivity (NPP) in global marsh wetlands remain unclear. Based on climate and MODIS NPP data, this study investigated the spatial-temporal variations of NPP and their response to climate variations in global marshes. The results indicated that annual NPP of global unchanged marshes showed a significant upward

Alpine ecosystems are critical components of the global carbon cycle, not only because they store substantial organic carbon, but also due to their high sensitivity to climate change, which has garnered considerable scientific interest. However, under ongoing climate warming, the dynamics and underlying mechanisms of alpine soil organic carbon (SOC) are not yet quantified, thereby introducing uncertainties

Climate warming was considered the primary driver of the advanced vegetation green-up onset date (VGD) in the Northern Hemisphere. However, the continuous advancement of VGD at the hemispheric scale during the hiatus in spring warming remains unexplained. Using high-quality satellite and multiple environmental datasets, we revealed two causes of VGD advancement during 2000–2014 (a period when a warming

Light pollution affects biodiversity at all levels, from genes to ecosystems, and improved monitoring and research is needed to better assess its various ecological impacts. Here, we review the current contribution of night‐time satellites to ecological applications and elaborate on the potential value of the Glimmer sensor onboard the Chinese Sustainable Development Goals Science Satellite 1 (SDGSAT‐1)

Most present-day bathymetric prediction solely addresses the linear mapping relationship between gravity signals and bathymetric data, disregarding nonlinearity’s effects, despite a probable nonlinear mapping between gravity signals and the seafloor topography. This paper investigates the consequences of excluding nonlinear terms in predicting bathymetry and reaches focused conclusions for different

Various vertical reference levels are used in the coastal zone, for various purposes. Being able to transform accurately and efficiently between them is of increasing interest since the need for seamless data over sea and land is growing due to sea-level rise, coastal engineering, and more frequent storm surges. We present a method for simultaneous calculation of models linking the ellipsoid, the geoid

Real-time processing of UAV-based agricultural remote sensing images is essential for precision agriculture, especially for low-overlap, large-format image sequence. These images, characterized by large formats, repetitive textures, and low overlap, pose significant challenges for real-time UAV photogrammetry. To address these challenges, this paper proposes a novel real-time matching and pose reconstruction

The coastal environments of the Black Sea are of high ecological and socio-economic importance. Understanding changes along this extensive and complex coastline can help us comprehend the pressures from nature, society, and extreme events, providing valuable insights for more effective management and the prevention of future adverse changes. Current methods for monitoring coastal dynamics rely on the

Accurate and complete reconstruction of the high-quality three-dimensional (3D) geometric information from stereo images has been one of the challenging tasks in the fields of photogrammetry and computer vision. Although tremendous efforts have been made in stereo matching by utilizing convolutional neural network (CNN)-based deep learning architectures, the matching ambiguities in the case of occlusions

Surface water resources are widely distributed and undergo rapid fluctuations, necessitating large-scale, high-frequency monitoring. Remote sensing technologies provide critical data for this purpose, but challenges such as data gaps and contamination hinder the effective observation of surface water dynamics at fine temporal scales. This limitation can obscure the recording of short-term water variations

Oblique photogrammetry using unmanned aerial vehicles (UAV) is crucial to 3D scene reconstruction. Nevertheless, oblique images are generally acquired with large overlaps, and sometimes with multiple views. Although this increases the level of data completeness, it introduces additional and sometimes redundant computations in tie-point matching, creating overly dense camera connections in the pose

Unmanned aerial vehicle remote sensing technology has become a key technology in crop breeding, which can achieve high-throughput and non-destructive collection of crop phenotyping data. However, the multidisciplinary nature of breeding has brought technical barriers and efficiency challenges to knowledge mining. Therefore, it is important to develop a smart breeding goal tool to mine cross-domain

Highly reactive iron (FeHR) oxyhydroxides in atmosphere dust play a critical role in determining the bioavailability of dust-derived iron in the ocean, thereby exerting substantial control over open-ocean biogeochemistry. However, the FeHR content in atmosphere dust exhibits significant variability across different landscapes, and the underlying factors contributing to this variability remain poorly

The radiative and thermal properties of the land surface are associated with its moisture content. It is necessary to advance our understanding about how changes in the exchange of water and energy fluxes between land and atmosphere shape the regional hydroclimate. This study employs the Community Earth System Model (CESM) with water tracer enabled to simulate atmospheric responses to a “wetter” Australia

Generating fine-resolution land cover maps from coarse-resolution multi-spectral images is an effective solution for addressing the mixed pixel problem inherent in remote sensing. Traditional subpixel mapping strategies, encompassing spectral unmixing followed by super-resolution mapping and image super-resolution followed by classification, often have limitations related to inadequate handling of

Accurate detection of underground natural gas micro-leakage is essential for operational safety. However, existing spectral-spatial models based on hyperspectral imagery (HSI) face challenges of limited integration with crop physiology and low interpretability. To address this, we propose LUEGNet, a novel framework that integrates the SAFY-NG crop growth model with deep learning through light use efficiency

The advances in 3D reconstruction technology, such as photogrammetry and LiDAR scanning, have made it easier to reconstruct accurate and detailed 3D models for urban scenes. Nevertheless, these reconstructed models often contain a large number of geometry primitives, making interactive manipulation and rendering challenging, especially on resource-constrained devices like virtual reality platforms

Biogenic sulfide compounds, including dimethylsulfide (DMS), dimethylsulfoniopropionate (DMSP), and dimethylsulfoxide (DMSO), play a critical role in climate feedback and global sulfur cycles. Although the impact of mesoscale eddies on marine ecosystems is well established, their influence on sulfide compounds remains unclear. This study investigates the spatial distribution and key sink-source processes

Space missions to small bodies like asteroids, comets, and moons rely on physics-based simulations to test guidance and control systems. However, accurately modeling their gravitational fields is challenging due to their highly irregular shapes and limited knowledge of their internal structures, complicating orbit planning and landing maneuvers. This study presents a new approach to model realistic

Compared to remote sensing image (RSI) segmentation methods that rely solely on label-based learning, vision-language models (VLMs) can leverage language guidance to model the inherent relationships between farmland and its surrounding environment. However, unlike natural images, where the objects are typically singular and concentrated, farmland remote sensing images often contain a variety of complex

The accurate retrieval of chlorophyll-a (Chla) concentrations in large-scale and highly-dynamic aquatic environments is challenging because of the complex and variable optical water properties, necessitating regionally-tuned or water-type-specific algorithms. In this study, we developed and validated an integrated algorithm to estimate Chla in optically diverse waters using the second-generation Coastal

The Paleocene–Eocene Thermal Maximum (PETM) was a dramatic climatic event characterized by substantial perturbation of the carbon cycle and environmental crisis in the Cenozoic. Although astronomical forcing has been proposed as a mechanism of these changes, its precise influence on carbon cycle dynamics and climate feedbacks during the PETM remain insufficiently constrained. To address this gap, developing

Chemical weathering and secondary mineral formation, both of which involve Ca cycling, are intricately linked to the carbon cycle. However, the impact of these geochemical processes on Ca cycling, particularly through secondary carbonate formation in terrestrial environments, remains poorly understood. In this study, we analysed Ca isotopic compositions in the Upper Yellow River, northeastern Tibetan

The hydroclimate evolution of the East Asian summer monsoon (EASM) during the Pliocene warm period, not clearly understood presently, is insightful for predicting its trends in future global warming. Here, we present paired biomarker records from northern South China Sea (SCS) Pliocene sediments, reconstructing sea surface temperature (SST) via TEX86 proxy and terrestrial humidity through leaf wax

The high-accumulation-rate eolian deposits in the eastern Hexi Corridor retain invaluable archives of rapid climatic fluctuations in the transition zone between the northwestern Chinese Loess Plateau, the Tengger Desert, and the northern foothills of the Qilian Mountains. High-resolution mineral magnetic and bulk grain size analyses for the Shagou loess–paleosol sequences since the last interglacial

Information on the magnitude of dust emissions in source areas is critical for understanding the Asian dust cycles. However, high-resolution records representing the intensity of dust entrainment are scarce, primarily due to intense wind erosion in source areas. Here, based on measurements of multiple proxies from peat deposits, including ash flux, grain size, elemental compositions, and lead and neodymium

The end-Permian mass extinction (EPME; ～252?Ma), known as the largest extinction event during the Phanerozoic Eon, provides a critical case study to understand the impacts of anthropogenic climate change. The warming associated with the EPME was likely triggered by the emissions of large quantities of CO2 during the eruption of the voluminous Siberian Traps (ST) volcanism, which eliminated 80 to 90?%

Major environmental changes were occurring when the first modern humans arrived in South America during the Pleistocene–Holocene transition. How these changes shaped human-environmental interactions across this period remains unclear. We analyzed the stratigraphy, biogeochemistry, and paleoclimatic models of the Ancient Tagua Tagua Lake (ATTL) in central Chile, one of the few continuous records of

When large floods occur, satellite data are useful for providing emergency managers with frequent and synoptic maps of affected areas, even on a daily basis. Only the use of on-demand SAR data enables the high-resolution monitoring of flood events through acquisitions performed day and night, and regardless of cloud cover, over different areas. However, continuous flood mapping generally requires combining

Accurate, detailed, and high-frequent bathymetry is crucial for shallow seabed areas facing intense climatological and anthropogenic pressures. Current methods utilizing airborne or satellite optical imagery to derive bathymetry primarily rely on either Structure-from-Motion and Multi-View Stereo (SfM-MVS) with refraction correction or Spectrally Derived Bathymetry (SDB). However, SDB methods often

In recent decades, severe environmental pollution and resource scarcity have made it increasingly urgent to monitor the distribution and changes of surface geological environmental elements. As the main components of geological environmental elements, different types of lithology are characterized by their diversity, fragmented distribution, and ambiguous boundaries. Remote sensing images have further

High-resolution Mars digital terrain models (DTMs) are crucial for exploration missions and scientific research. However, traditional photogrammetry is constrained by stereo image coverage and configuration, while laser altimetry suffers from sparse laser footprint distribution, leading to limited terrain accuracy. While the recent photoclinometric and deep learning methods can generate promising 3D