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In this paper we propose minimal solvers for relative pose estimation for two views of the projected silhouettes of two 3D cylinders. Using such line features instead of the standard point feature correspondences means more stable information (i.e. more stable to lighting condition, seasons, changes in environment etc.). Such features also lead to more compact and semantically interpretable repres

Droughts are often long-lasting phenomena, without a distinct start or end and with impacts cascading across sectors and systems, creating long-term legacies. Nevertheless, our current perceptions and management of droughts and their impacts are often event-based, which can limit the effective assessment of drought risks and reduction of drought impacts. Here, we advocate for changing this perspec

The Fine Resolution Explorer for Salinity, Carbon and Hydrology (FRESCH) is presented. The science case and the mission objectives are discussed before presenting the mission concept. FRESCH is an L-band antenna array operated in beamforming mode providing data at a spatial resolution of 10-15 km to study the biogeochemical and physical phenomena taking place at the interfaces of ocean, land and i

The critical soil moisture threshold (SMth) of plant water stress distinguishes whether vegetation is in an energy-limited or water-limited regime. Accurate quantification of SMth for grasslands holds significant implications for drought monitoring and efficient grassland management. However, our understanding of SMth within global grasslands remains limited. In this study, we investigated the rel

Snowpack atop sea ice plays a vital role in the Arctic heat and energy balance by reducing the energy transfer between the atmosphere and the ocean. This study presents an improved snow depth retrieval model over Arctic multiyear ice (MYI) from the Microwave Radiometer Imager (MWRI) data of the Fengyun-3 (FY-3) series satellites using the optimal machine learning approach identified. Validation ag

Surface soil moisture (SM) is a crucial variable representing the water content in soil at the topmost soil layer. Accurate data of SM are essential for various purposes, including the monitoring of drought, vegetation modeling, weather forecasting, and agriculture management. Over the past decades, microwave remote sensing has been employed to estimate SM at large scales, with the Sentinel-1 sate

Monitoring the changes of ecosystem functioning is pivotal for understanding the global carbon cycle. Despite its size and contribution to the global carbon cycle, Africa is largely understudied in regard to ongoing changes of its ecosystem functioning and their responses to climate change. One of the reasons is the lack of long-term in situ data. Here, we use eddy covariance to quantify the net e

The traditional remote sensing ecological index (RSEI), based on principal component analysis (PCA) to integrate four evaluation indexes: greenness (NDVI), humidity (WET), dryness (NDBSI), and heat (LST), is insufficient to comprehensively consider the influence of each eco-environment evaluation index on eco-environment quality (EEQ). In this research, a new comprehensive remote sensing ecologica

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO2) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carb

Remote sensing observations of variables related to vegetation at microwave and optical/infrared wavelengths are presented over three regions in Europe in the Iberian peninsula, northern Finland and central Europe. They include the instrumented sites of Las Majadas, Sodankyla and Reusel. The final goal is to better constrain land carbon cycle models using the complementarities of vegetation optica

Study region: Two hyper-arid regions (Atbara and Kassala stations) in Sudan. Study focus: The study aims to evaluate the potential of the D-vine Copula-based quantile regression (DVQR) model for estimating daily ETo during 2000–2015 based on various input structures. Further, the DVQR model was compared with Multivariate Linear quantile regression (MLQR), Bayesians Model Averaging quantile regress

Agroecosystem photosynthesis is key to coping with global climate change. In farmland where human activities are highly involved, the interaction between environmental factors and their influences on gross primary productivity (GPP) are insufficiently understood. Particularly, the irrigation and mulching in water-saving agriculture can alter the crop responses to environmental change. Based on edd

Efforts to develop effective climate mitigation strategies for agriculture require methods to estimate nitrous oxide (N2O) emissions from soil. Process-based biogeochemical models have been often used for field- and large-scale estimates, while the sensitivity and uncertainty of model applications to incubation experiments are less investigated. In this study, a process-oriented model (CoupModel)

This paper considers the problem of jointly designing the transmit waveforms and weights for a frequency diverse array (FDA) in a spectrally congested environment in which unintentional spectral interferences exist. Exploiting the properties of the interference signal induced by the processing of the multi-channel mixing and low-pass filtering FDA receiver, the interference covariance matrix struc

In this paper, we argue that modern pre-integration methods for inertial measurement units (IMUs) are accurate enough to ignore the drift for short time intervals. This allows us to consider a simplified camera model, which in turn admits further intrinsic calibration. We develop the first-ever solver to jointly solve the relative pose problem with unknown and equal focal length and radial distort

Understanding influence of vegetation on past temperature changes in the Arctic region would help isolate uncertainty and build understanding of its broader climate system, with implications for paleoclimate reconstructions and future climate change. Using an Earth system model EC-Earth, we conduct a series of simulations to investigate the impact of vegetation-climate feedback on the Arctic clima

Variability on centennial to multi-centennial timescales is mentioned as a feature in reconstructions of the Holocene climate. As more long transient model simulations with complex climate models become available and efforts have been made to compile large proxy databases, there is now a unique opportunity to study multi-centennial variability with greater detail and a large amount of data than ea

The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. Thus, the datasets of catchment-level characteristics are essential for limnology studies. Lakes are widely spread on the Tibetan Plateau (TP), with a total lake area exceeding 50000km2, accounting for more than half of the total lake a

Crop production security is an essential guarantee for the prosperity of country and the well-being of people. In the context of frequent occurrence of extreme weather events, how to comprehensively evaluate the risk of multiple hazards and quantitatively describe spatial differences will be one of the significant topics in agricultural disaster mitigation. In this study, based on the gridded mete