Abstract Data assimilation plays a dual role in advancing the “scientific” understanding and serving as an “engineering tool” for Earth system sciences. Land data (LDA) has evolved into distinct discipline within geophysics, facilitating harmonization of theory allowing land models observations to complement constrain each other. Over recent decades, substantial progress been made theory, methodology, application LDA, necessitating holistic in‐depth exploration its full spectrum. Here, we...

Cloud obscuration leaves significant gaps in MODIS snow cover products. In this study, an innovative gap-filling method based on the concept of non-local spatio-temporal filtering (NSTF) is proposed to reconstruct cloud fractional (SCF) The ground information a gap pixel was estimated by using appropriate similar pixels remaining known part image via automatic machine learning technique. We take SCF product filling data from 2001 2016 Northern Xinjiang, China as example. results demonstrate...

Understanding the spatial distribution of populations at a finer scale has important value for many applications, such as disaster risk rescue operations, business decision-making, and regional planning. In this study, random forest (RF)-based population density mapping method was proposed in order to generate high-precision data with 100 m × grid mainland China 2015 (hereafter referred ‘Popi’). Besides commonly used elevation, slope, Normalized Vegetation Index (NDVI), land use/land cover,...

Accurate estimation of crop area is essential to adjusting the regional planting structure and rational planning water resources. However, it quite challenging map crops accurately by high-resolution remote sensing images because ecological gradient convergence between non-crops. The purpose this study explore combining application multi-temporal Sentinel-1 (S1) radar backscatter Sentinel-2 (S2) optical reflectance for maize mapping in highly complex heterogeneous landscapes middle reaches...

Abstract As part of the LAMOST medium-resolution spectroscopic survey, LAMOST-MRS-O is a non-time domain survey that aims to perform spectral observations for member stars in open cluster area. This plans obtain parameters such as radial velocity and metal abundances provide data support further study on chemical dynamical characteristics evolution clusters combination with Gaia data. We have completed ten fields obtained 235184 spectra 133792 stars. Based analyzed DR11V1.1, some particular...

The ecosystem services (ESs) and landscape patterns (LPs) in a region have marked impact on human production life even play an important role the achievement of regional Sustainable Development Goals (SDGs). Given limited consideration LPs ESs SDGs current research, it is especially crucial to provide comprehensive targeted policy support for sustainable development less developed areas from environmental perspective. Utilizing Lincang National Innovation Demonstration Zone as case study, we...

Accurate high-resolution gridded livestock distribution data are of great significance for the rational utilization grassland resources, environmental impact assessment, and sustainable development animal husbandry. Traditional collected at administrative unit level, which does not provide a sufficiently detailed geographical description distribution. In this study, we proposed scheme by integrating geographic statistics through machine learning regression models to spatially disaggregate...

Wildfires have a significant impact on the atmosphere, terrestrial ecosystems, and society. Real-time monitoring of wildfire locations is crucial in fighting wildfires reducing human casualties property damage. Geostationary satellites offer advantage high temporal resolution are gradually being used for real-time fire detection. In this study, we constructed label dataset using stable VNP14IMG product random forest (RF) model detection based Himawari-8 multiband data. The band calculation...

This article investigates how to select the optimal Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 OLI image pairs for MODIS fractional snow cover (FSC) mapping using an artificial neural network (ANN). Four issues are discussed, including date selection, location priority of location, global regional monitoring FSC with ANNs. We propose histogram quadratic distance define similarity between ANN training target test scene, which was used quantify representativeness...

Abstract This paper presents the development and application of a physically based hydrological data assimilation system (HDAS) using gridded parallelized Soil Water Assessment Tool (SWATGP) distributed model. SWAT‐HDAS software integrates remotely sensed data, including leaf area index (LAI), snow cover fraction, water equivalent, soil moisture, ground‐based observational (e.g., from discharge ground sensor networks), with SWATGP Parallel Data Assimilation Framework (PDAF) to accurately...

Abstract In this study, an innovative MODIS fractional snow cover (SCF) data assimilation (DA) prototype framework that invokes machine learning (ML) techniques and Common land model (CoLM) is proposed to improve the estimation of depth (SD) SCF. To validate our new framework, we analyzed two seasons from 2013 2015 at 46 stations in Northern Xinjiang China. We developed 12 SCF DA schemes represent different methods (direct insertion (DI) Ensemble Kalman Filter (EnKF)), observational...

As a result of Earth observation (EO) entering the era big data, significant challenge relating to by storage, analysis, and visualization massive amount remote sensing (RS) data must be addressed. In this paper, we proposed novel scalable computing resources system achieve high-speed processing RS in parallel distributed architecture. To reduce movement among nodes, Hadoop Distributed File System (HDFS) is established on nodes K8s, which are also used for computing. process innovatively use...

A multilayer feedforward artificial neural network (ANN) is developed for mountainous fractional snow cover (FSC) mapping. This trained with back propagation to learn the relationship between FSC and Moderate Resolution Imaging Spectroradiometer (MODIS) products (reflectance at seven bands, normalized difference index, land surface temperature (LST), FSC) elevation. In this paper, images from Landsat Enhanced Thematic Mapper Plus (ETM+) MODIS three periods are chosen test validate proposed...

Introduction: The Leaf area index (LAI) of source region yellow river basin is an important indicator for environmental sustainability. Most studies focus on the trend LAI in Yellow River Source Region (YRSR) accordance with both climate change and human actives. However, quantifying effect activities difficult but urgently needed. Specifically, Particle Matter 2.5 (PM2.5) can be indirect activities. Methods: In this study, we explored potential dependence temperature, precipitation, PM2.5...

Snow is one of the most important components cryosphere. Remote sensing snow focuses on retrieval parameters and monitoring variations in using satellite data. These are key inputs for hydrological atmospheric models. Over past 30 years, field remote has grown dramatically China. The 30-year achievements research different aspects China, especially (1) methods retrieving cover, depth/snow water equivalent, grain size (2) applications to snowmelt runoff modeling, response climate change,...

Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product is one of the prevailing datasets for global monitoring, but cloud obscuration leads to discontinuity ground coverage information in spatial and temporal. To solve this problem, a novel spatial-temporal missing reconstruction model based on U-Net with partial convolutions (PU-Net) proposed recover gaps MODIS Normalized Difference Snow Index (NDSI) products. Taking Yellow River Source Region as study case, which...

This research utilized in situ soil moisture observations a coupled grid Soil and Water Assessment Tool (SWAT) Parallel Data Assimilation Framework (PDAF) data assimilation system, resulting significant enhancements estimation. By incorporating Wireless Sensor Network (WSN) (WATERNET), the method captured integrated local characteristics, thereby improving regional model state estimations. The use of varying observation search radii with Local Error-subspace Transform Kalman Filter (LESTKF)...

Streamflow estimates are substantially important as fresh water shortages increase in arid and semi-arid regions where evapotranspiration (ET) is a significant contribution to the balance. In this regard, data can be assimilated into distributed hydrological model (SWAT, Soil Water Assessment Tool) for improving streamflow estimates. The SWAT has been widely used estimations, but applications combining ET products were rare. Thus, study aims develop SWAT-based assimilation system....

Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature (TB) observations have long been utilized for snow depth (SD) estimation. However, the traditional approaches which are based on ‘point-to-point’ predictions ignore spatial heterogeneity within a AMSR2 pixel and limited by coarse resolution of sensor. To solve these problems, novel deep ‘area-to-point’ SD estimation model, residual learning network combining convolutional neural networks (CNN) blocks, was proposed. The...