Monitoring the water level and volume changes of lakes reservoirs is essential for deepening our understanding temporal spatial dynamics resources in Yellow River Basin, with a view to better utilizing managing resources. In recent years, there have been many studies on monitoring inland waters, but they were mainly focused radar altimetry full waveform LiDAR ICESat, which was retired 2010. Few based latest photon-counting ICESat-2 reported. Compared previous sensors, has great advantages...

Deferred neural rendering (DNR) is an emerging computer graphics pipeline designed for high-fidelity and robotic perception. However, DNR heavily relies on datasets composed of numerous ray-traced images demands substantial computational resources. It remains under-explored how to reduce the reliance high-quality while maintaining fidelity. In this paper, we propose DNRSelect, which integrates a reinforcement learning-based view selector 3D texture aggregator deferred rendering. We first...

Weather radar holds the capability to monitor extensive migration of bird and insect species. In particular, polarimetric weather can enhance aerial ecological monitoring by quantifying target shape through measurement polarization moments. This paper introduces an intelligent algorithm classify using data. A image dataset was formed intentionally curating typical migratory data birds insects captured radar. Next, point features spatial texture were extracted from images in for training a...

Monitoring and forecasting aerial animal migration benefit biological conservation, aviation safety, agricultural production. Due to the lack of large-scale observation data quantitative knowledge mechanisms, it is difficult build a numerical simulation system for prediction. However, extensive deployment weather radars makes possible obtain information. Meanwhile, artificial intelligence technologies provide new insights into modeling complex system. In this article, we develop...

Abstract Each year, billions of birds migrate across the globe, and interpretation weather radar signals is increasingly being used to document spatial temporal migration patterns in Europe America. Such approaches are yet be applied East Asian‐Australasian Flyway (EAAF), one most species‐rich threatened flyways world. Logistical challenges limit direct on‐ground monitoring migratory many parts EAAF, resulting knowledge gaps on population status site use that evidence‐based conservation...

Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications, especially crop monitoring and disaster warning. Evaluating the dependability of satellite-derived soil on a large scale is crucial. In this study, we assessed level 2 (L2) SM product Chinese Fengyun-3C (FY-3C) radiometer against in-situ measurements collected Automatic Moisture Observation Stations (CASMOS) during one-year period 1 January 2016 to 31...

For sustainable conservation and management of wetlands, it is essential to quantify the evolution progress driving mechanisms wetlands. This study examined Baiyangdian Wetland as a research area, remote images statistical yearbooks were used data sources. Dominant zones wetland defined based on spatial characteristics land cover frequency. A transfer matrix random forest analyze process mechanism typical wetlands in North China Plain. Based results, following conclusions arrived: (1) There...

Abstract The analysis of wetland patterns and their driving mechanisms is the research focus discussion in ecology. In this study, we tried to analyse spatial differentiation community landscape levels dominated by hydro‐ecological processes. were explored focus. This study was based on 30‐year land cover data Baiyangdian Wetland Nature Reserve North China Plain, China, constructing an ecological response relationship matrix between inundation frequency vegetation for divide at level. By a...

Predicting future lake levels under climate change is critical for advancing our understanding of hydrological processes in a changing environment. However, continuous and long-term prediction challenging due to discrepancies multi-source data the lack integration models scenarios. Physical statistical have been used prediction, however, physical are difficult calibrate often fail account effects changes. In this study, level model was proposed by assimilating hydrophysical based on water...

The weather radar can operate in all weathers and time, has a large coverage area. Besides monitoring the weather, receive other echoes including biological echoes. In order to utilise capability, recognising classifying local insect bird is one of biggest obstacles for analysing their migration, foraging, reproduction activities. Here, pixel-wise classification method based on fully convolutional network (FCN) proposed which trained by reflectivity spectral width images. Moreover, increase...

Weather radar data can capture large-scale bird migration information, helping solve a series of migratory ecological problems. However, extracting and identifying information from weather remains one the challenges aeroecology. In recent years, deep learning was applied to field processing proved be an effective strategy. This paper describes method for biological target echoes images. model uses two-stream CNN (Atrous-Gated CNN) architecture generate fine-scale predictions by combining key...

This study addresses the problem of restricted ability for large-scale monitoring due to limited cruising time unmanned aerial vehicles (UAV) by identifying an optimal leaf ChlorophyII content (LCC) inversion machine learning model at different scales and under parameterization schemes based on simultaneous observations ground sampling, UAV flight, satellite imagery. The following results emerged: (1) correlation coefficient between most remote sensing features (RSFs) LCC increased as scale...

Weather radar plays an important role in monitoring aerial animal migration, providing a stable data source for biological studies with large-scale coverage and consecutive-time samples. The accurate estimation of bird density from weather echoes is fundamental quantitative studies. We analyzed the observation model radar, proposed method to build quantification by jointly utilizing dual-polarization Doppler scanning radar. designed detailed process remove tracks or non-bird targets,...

Abstract Automatic soil moisture data with a temporal resolution of 1 hr, spatial 30 km, from the period June 1–September 1, 2017, and Henan province in China, simulation results Community Land Model (CLM4.0) were first compared, calibration study was further conducted investigated. The operational status instruments confirmed, passed quality control. corresponding performed using CLM4.0. Small scale variations observed contents found, but relatively large simulated contents. Since bias weak...

Weather radars provide continuous recording over extensive spatial coverage, which is valuable for biologists who observe and study biological activities a wide range of temporal scales. Through the interpretation weather radar observations, powerful inferences can be obtained. However, when it comes to certain problems, such as determination parameters related airborne densities, data needs processed based on assumptions before. This article analyses calculates impact phenomenon migratory...

Ground clutter poses a significant challenge to the accuracy of weather radar products, especially for aeroecology monitoring. Operational commonly employs fixed coherent pulse integration (CPI) suppression. However, phenomenon strong spanning multiple CPIs can result in severe spectral leakage. The independent implementation suppression within each CPI fails fully utilize data, significantly compromising effectiveness. Therefore, we propose an adaptive (ACPI) method based on amplitude-phase...

Accurately and timely crop yield simulation is essential for effective agricultural management food security. Soil moisture (SM) plays a major factor that directly influences growth yield, especially in the arid regions. However, hydrological models are significant means of studying cycle, united with estimating large-scale area. This paper aims to identify most SM layer from Variable Infiltration Capacity (VIC) growth, then builds VIC-WOFOST model explore ability jointly assimilating leaf...