Coronavirus Disease 2019 (COVID-19) is a highly infectious virus that has created health crisis for people all over the world. Social distancing proved to be an effective non-pharmaceutical measure slow down spread of COVID-19. As unmanned aerial vehicle (UAV) flexible mobile platform, it promising option use UAV social distance monitoring. Therefore, we propose lightweight pedestrian detection network accurately detect pedestrians by human head in real-time and then calculate between on...

The accurate assessment of the global gross primary productivity (GPP) vegetation is key to estimating carbon cycle. Temperature (Ts) and soil moisture (SM) are essential for growth. It acknowledged that Ts has shown an increasing trend, yet SM a decreasing trend. However, importance changes on ecosystems remains unclear, as strongly coupled through soil-atmosphere interactions. Using solar-induced chlorophyll fluorescence (SIF) proxy GPP by decoupling changes, our investigation shows plays...

The climate change is expected to trigger changes in vegetation phenology, temperature, and soil moisture (SM), altering the productivity of ecosystems. Despite numerous existing efforts, however, their contradicting conclusions suggest that how impacted by these factors still remains unclear Northern Hemisphere ecosystems (≥25°N). This study used optimal fingerprint (OFP) method redundancy analysis (RDA) attribute importance key drivers from 2001 2019 based on long-term remote sensing...

The novel coronavirus 2019 (COVID-19)-imposed restrictions in 2020 and 2021 led to a notable reduction human activity, providing an opportunity study the impact of activity on global vegetation productivity. impacts productivity are particular interest, as carbon sinks serve one main pathways for neutrality. This investigated COVID-19 pandemic by leveraging remotely sensed big data model data. revealed reduced atmospheric emissions increased radiation reaching surface these two years....

Vegetation phenology is a key indicator of vegetation-climate interactions and carbon sink changes in ecosystems. Therefore, it very important to understand the temporal spatial variability vegetation driving climatic determinants [e.g., temperature (Ts) soil moisture (SM)]. greenness photosynthetic were derived using double logistic (DL) method enhance index (EVI) solar-induced chlorophyll fluorescence (SIF) spring autumn phenology, respectively. The growing season length (GSL) (about 100...

In a complex urban scene, observation from single sensor unavoidably leads to voids in observations, failing describe objects comprehensive manner. this paper, we propose spatio-temporal-spectral-angular model integrate observations UAV and mobile mapping vehicle platform, realizing joint, coordinated operation both air ground. We develop multi-source remote sensing data acquisition system effectively acquire multi-angle of scenes. Multi-source fusion solves the missing problem caused by...

The goal of pan-sharpening tasks is to fuse panchromatic (PAN) images and low-spatial-resolution (LR) multispectral (MS) for the purpose aggregating texture spectral information. Although traditional embedding-based methods achieve competitive results, they are limited by shallow network not suitable large-scale datasets. In this study, we design a novel multiscale locally linear embedding residual (LLERN) that consists two phases: preservation phase structural phase. As pretreatment...

The rapid development and commercialization of Unmanned Aerial Vehicle (UAV) technology has made it possible to conduct urban traffic information extraction using UAV images. However, the large variations targets in environments, complex foregrounds backgrounds cities, severe tree shadow occlusions pose great challenges car road In this study, we propose a lightweight, Efficient Dual Contextual Parsing Network (EDCPNet) address above issues. proposed EDCP module EDCPNet is mainly composed...

Dear Editor, In pansharpening task, the most existing deep-learning-based pan-sharpening methods fail to fully utilize different level features, inevitably leading spectral or spatial distortions. To address this challenge, in letter, we propose a dual-branch multi-level feature aggregation network for (DMFANet). The experimental results on WorldView-II (WV-II) and QuickBird (QB) dataset confirmed notable superiority of our method over current state-of-the-art from quantitative qualitative...

Pan-sharpening is a technique used to create high-resolution multispectral (HRMS) images by merging low-resolution (LRMS) with corresponding panchromatic (PAN) images. Despite achieving state-of-the-art performance, existing sharpening networks based on deep learning methods suffer from spectral distortion and insufficient spatial texture enhancement. To address this challenge, letter introduces novel cross spectral-spatial fusion network for pan-sharpening remote sensing images, called...

Urban vegetation phenology is important for understanding the relationship between human activities on urban ecosystems and carbon cycle. The rural environmental meteorological factors were studied across urban-rural gradients. However, of intra-urban urbanization intensity (UI) gradients at start season (SOS) unclear. Here, we used remote sensing data to quantitatively assess SOS UI mid-high latitudes in northern hemisphere. results showed that area widely presented earlier than vegetation....

Object detection on drone-view images is vital for applications like intelligent transportation, abnormal behavior detection, and urban surveillance. However, the diverse perspectives altitudes from which Unmanned Aerial Vehicle (UAV) capture scenes pose challenges due to multi-scale differences small object sizes. To address this, we propose CSSDet, emphasizing enhancement. CSSDet integrates an additional head objects employs a bidirectional weighted feature pyramid network effective...

Abstract. 3D Real Scene is an important part of new infrastructure construction, which provides a unified spatial base for economic and social development informatization various departments. According to the demand real digital this paper aims study method indoor outdoor structured monomer reconstruction city Scene, develop twin platform, strive lead Scene. The main research contents are as follows: 1) Spatio-temporal-spectral-angular remote sensing observation system data fusion model; 2)...

Cloud pollution on remote sensing images seriously affects the actual use rate of images. Therefore, cloud detection is an indispensable part image preprocessing and availability screening. Aiming at lack short wave infrared thermal bands in ZY-3 high-resolution satellite resulting poor effect, considering obvious difference geographic height between ground surface objects, this paper proposes a thick thin method combining spectral information digital model (DHM) based multi-scale...

Remote sensing technology has made significant advancements, leading to the widespread adoption of unmanned aerial vehicles (UAVs) in critical tasks such as smart cities, traffic surveillance, and disaster assistance. However, identification objects from drone-view images poses substantial challenges: 1) small object; 2) scale variance; 3) non-uniform distribution; 4) occlusion. To address these challenges, this paper introduces a novel strategy for remote data collection via multiple UAVs...

A method is described for scanning electron microscope (SEM) autoradiography whereby preservation of high resolution cell surface details retained together with degelatination the emulsion without gross loss or redistribution silver grains. This should provide a convenient medium-sized marker SEM (using secondary, backscattered and X-ray imaging) topographic studies biosynthesized molecules, receptors antigens, using indirect direct labelling procedures radio-labelled ligands.