Chunlin Huang

• Phd
• Chinese Academy of Sciences

Monitoring and mapping forest vegetation are crucial for conserving biodiversity and estimating biomass and carbon. However, spectral similarity between different vegetation types and the issue of mixed pixels in medium-resolution satellite imagery remain significant challenges for fine-scale forest classification. This study focused on the Tao Riv...

The extensive peatlands of the Tibetan Plateau (TP) play a vital role in sustaining the global ecological balance. However, the distribution of peatlands across this region and the related environmental factors remain poorly understood. To address this issue, we created a high-resolution (10 m) map for peatland distribution in the TP region using 6...

At the midpoint of the 2030 Agenda for Sustainable Development implementation, over half of the targets remain unmet due to insufficient government funding and tradeoffs among the sustainable development goals (SDGs) globally. The shortage of government funding and tradeoff between goals is a major bottleneck affecting SDGs realization. Underdevelo...

In order to anticipate residual errors and improve accuracy while reducing uncertainties, this work integrates the long short-term memory (LSTM) with the Soil and Water Assessment Tool (SWAT) to create a deep learning (DL) model that is guided by physics. By forecasting the residual errors of the SWAT model, the SWAT-informed LSTM model (LSTM-SWAT)...

Deep learning has demonstrated its effectiveness in capturing high-level features, with convolutional neural networks (CNNs) excelling in remote sensing classification. However, CNNs encounter challenges when applied to Landsat images with limited multi-spectral bands, as they struggle to learn stable features from the spectral domain and integrate...

The sensitivity of synthetic aperture radar (SAR) polarization information to snow depth changes provides new opportunities for regional snow depth retrieval in mountains with thick snow cover. However, interference from soil signals can affect the accurate quantification of snow volume scattering signals. The aim of this study was to develop a dua...

Urban green belts (UGBs), an important green infrastructure of cities, have the functions of constraining urban sprawl, which are of great significance to urban green, resilient and sustainable development. However, it remains unclear how to quantify the constraining effect of UGBs on urban sprawl and the degree of fragmentation after UGBs constrai...

The distributive characteristics of snow cover and their impacting mechanisms on ground thermal regimes in Northeast China remain evasive because of limited systematic studies. In this study, based on long-term ground-based observational data and auxiliary topographic data, geographically weighted regression kriging (GWRK) method and the temperatur...

Data assimilation plays a dual role in advancing the “scientific” understanding and serving as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has evolved into a distinct discipline within geophysics, facilitating the harmonization of theory and data and allowing land models and observations to complement and const...

Site selection for building solar farms in deserts is crucial and must consider the dune threats associated with sand flux, such as sand burial and dust contamination. Understanding changes in sand flux can optimize the site selection of desert solar farms. Here we use the ERA5-Land hourly wind data with 0.1° × 0.1° resolution to calculate the year...

Introduction: The Leaf area index (LAI) of source region of yellow river basin is an important indicator for environmental sustainability. Most studies focus on the trend of LAI in Yellow River Source Region (YRSR) in accordance with both climate change and human actives. However, quantifying the effect of human activities on LAI is difficult but u...

Snow cover plays a crucial role in the surface energy balance and hydrology and serves as a key indicator of climate change. In this study, we conducted an ensemble simulation comprising 48 members generated by randomly combining the parameterizations of five physical processes within the Noah-MP model. Utilizing the variance-based Sobol total sens...

Promoting the accessibility of basic public service facilities is key to safeguarding and improving people’s lives. Effective public service provision is especially important for the sustainable development of less developed regions. Lincang in Yunnan Province is a typical underdeveloped region in China. In parallel, multisource remote sensing data...

Recently, time series remote sensing image (TSRSI) has been reported to be an effective resource to mapping fine land use/land cover (LULC), and deep learning, in particular, has been gaining growing attention in this field. However, existing deep learning methods often only learn features from either the temporal or spatial domain, neglecting the...

Land Surface Temperature (LST) plays a crucial role in Earth’s energy balance and ecosystems. Various gap-filling methods have been developed to reconstruct seamless LST datasets to deal with the effect of data gaps caused by cloud cover, however, existing studies mainly focus on LST reconstruction under clear-sky conditions, rather than generating...

This research utilized in situ soil moisture observations in a coupled grid Soil and Water Assessment Tool (SWAT) and Parallel Data Assimilation Framework (PDAF) data assimilation system, resulting in significant enhancements in soil moisture estimation. By incorporating Wireless Sensor Network (WSN) data (WATERNET), the method captured and integra...

Introdution: One crucial method to attain Sustainable Development Goals (SDGs) involves timely adjustment of development policies, promoting the realization of SDGs through a time-series assessment of the degree of accomplishment. In practical applications, data acquisition is a significant constraint in evaluating the SDGs, not only in China but a...

Accurate fractional crop-planting area (FCPA) mapping is a challenging task as it requires leveraging the advantages of geographic data in detailed spatial expression and agricultural statistics in the description of crop types and quantitative characteristics. We present a robust method to disaggregate the agricultural statistics within each count...

Site selection is a priority for building wind and solar farms in deserts, which has to consider the dune threats associated with sand flux, such as dust contamination and sand burial. Thus, understanding changes in sand flux can optimize the site selection for wind and solar farms in deserts. Here, we use the ERA5-Land hourly wind data with 0.1°×0...

Accurate snowpack simulations are critical for regional hydrological predictions, snow avalanche prevention, water resource management, and agricultural production, particularly during the snow ablation period. Data assimilation methodologies are increasingly being applied for operational purposes to reduce the uncertainty in snowpack simulations a...

Data scarcity is a key factor impacting the current emphasis on individual indicators and the distribution of large-scale spatial objects in country-level SDG 6 research. An investigation of progress assessments and factors influencing SDG implementation in cities and counties indicates that smaller-scale regions hold greater operational significan...

Observations of kilometer-scale turbulent fluxes of sensible (H) and latent heat (LE) are required for the validation of flux estimate algorithms from satellite remote-sensing data and the development of parameterization schemes in the hydro-meteorological models. Since 2019, two sets of Optical and Microwave scintillometer (OMS) systems have been...

The degradation of Xing’an permafrost affects the stability of carbon pool and carbon emissions of the hemiboreal ecosystem in Northeast China. Due to the lack of long-term monitoring and detailed research, changes in carbon stock in terrestrial ecosystems in the Xing’an permafrost regions in Northeast China remain little known. In this study, we c...

The concept of a digital twin of Earth envisages the convergence of Big Earth Data with physics-based models in an interactive computational framework that enables monitoring and prediction of environmental and social perturbations for use in sustainable governance. Although computational advances are rapidly progressing, digital twins of Earth hav...

Rapid urbanization brings a series of dilemmas to the development of human society. To address urban sustainability, Sustainable Development Goal 11 (SDG 11) is formulated by the United Nations (UN). Quantifying progress and interactions toward SDG 11 indicators is essential to achieving Sustainable Development Goals (SDGs). However, it is limited...

Wildfires have a significant impact on the atmosphere, terrestrial ecosystems, and society. Real-time monitoring of wildfire locations is crucial in fighting wildfires and reducing human casualties and property damage. Geostationary satellites offer the advantage of high temporal resolution and are gradually being used for real-time fire detection....

Utilizing global navigation satellite system interferometric reflectometry (GNSS-IR) technology to obtain snow depth (SD) has the advantages of all-day, low cost and large amount of available data. At present, there is still a lack of in-depth research on the influence of weak surface fluctuation on SD inversion. In this paper, we investigate the i...

Long-term satellite observations of the water levels of lakes are crucial to our understanding of lake hydrological basin systems. The Ice, Cloud, and Land Elevation satellite (ICESat) and ICESat-2 were employed to monitor the water level of Qinghai Lake in the hydrological basin. The median of absolute deviation (MAD) method was exploited to remov...

With the aim of reducing the uncertainty of simulations, data assimilation methodology is increasingly being applied in operational purposes. This study aims to investigate the performance of genetic particle filter which used as snow data assimilation scheme, designed to assimilate ground-based snow depth measurements across different snow climate...

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 the spatial heterogeneity within a AMSR2 pixel and are limited by the coarse spatial resolution of the AMSR2 sens...

Grasslands are the basis for sustainable development in the northern farming-pastoral transition zone of China, with functions of human production, living, and ecology. Large-scale human activities inevitably lead to significant changes in grasslands, resulting in significant impacts on ecosystem services. To this end, we quantitatively estimated t...

The 2030 Agenda for Sustainable Development provides an ambitious vision for global sustainable development in three dimensions: economic, social and environmental. It has, however, run into major challenges posed by such problems as the lack of data, unbalanced progress, and trade-offs between the Sustainable Development Goals (SDGs). At the same...

Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product is one of the prevailing datasets for global snow monitoring, but cloud obscuration leads to the discontinuity of ground coverage information in spatial and temporal. To solve this problem, a novel spatial-temporal missing information reconstruction model based on U-Net with p...

As a result of Earth observation (EO) entering the era of big data, a significant challenge relating to by the storage, analysis, and visualization of a massive amount of remote sensing (RS) data must be addressed. In this paper, we proposed a novel scalable computing resources system to achieve high-speed processing of RS big data in a parallel di...

Atmospheric disturbance, sensor malfunctions, and other factors can cause serious gap pixels in the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference snow index (NDSI) products. In this article, MODIS NDSI gap pixels are reconstructed in a highly heterogeneous area with drastic snow accumulation and melting changes using a...

This project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia (HMA). Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems. Energy-b...

Accurate high-resolution gridded livestock distribution data are of great significance for the rational utilization of grassland resources, environmental impact assessment, and the sustainable development of animal husbandry. Traditional livestock distribution data are collected at the administrative unit level, which does not provide a sufficientl...

Atmospheric methane (CH4) concentrations have shown a puzzling resumption of growth since 2007 following a period of stabilization from 2000 to 2006. Multiple hypotheses have been proposed to explain the temporal variations in CH4 growth, which attributes the rise of atmospheric CH4 either to increases in emissions from fossil fuel activities, agri...

Precise multi-scenario projections of future economic outputs based on localised interpretations of global scenarios and major growth drivers are important for understanding long-term economic changes. However, few studies have focussed on localised interpretations, and many assume regional uniformity or use key parameters that are recursive or ext...

SDG 11, also known as sustainable cities and communities is central to achieving all 17 SDGs. However, the lack of data is the main challenge for monitoring and assessing SDG 11 indicators. As an important aspect of technological innovation and big data, Big Earth Data can offer a new key to generate knowledge about the Earth, playing a major role...

Data assimilation provides a practical way to improve the accuracy of soil moisture simulation by integrating a land surface model and satellite data. This study establishes a multi-source remote sensing data assimilation framework by incorporating a simultaneous state and parameter estimation method to acquire an accurate estimation of the soil mo...

The terrestrial carbon cycle is an important component of global biogeochemical cycling and is closely related to human well-being and sustainable development. However, large uncertainties exist in carbon cycle simulations and observations. Model-data fusion is a powerful technique that combines models and observational data to minimize the uncerta...

Texas experienced an extreme drought on record in 2011. Model simulations or satellite observations have been used to assess and analyze the drought. In this study, a method based on multi-source remote sensing data assimilation is proposed to evaluate the drought in Texas, which combines the advantages of model simulations and satellite observatio...

Accurate estimation of crop area is essential to adjusting the regional crop planting structure and the rational planning of water resources. However, it is quite challenging to map crops accurately by high-resolution remote sensing images because of the ecological gradient and ecological convergence between crops and non-crops. The purpose of this...

A snow depletion curve (SDC), the relationship between snow mass (e.g., snow depth (SD)) and fractional snow cover area (SCF), is essential to parameterize the effect of snowpack within a physically based snow model. Existing SDCs are constructed using traditional statistic methods may not be applicable in complex mountainous areas. In this study,...

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 the snow depth (SD) and the SCF. To validate our new framework, we analyzed two snow seasons from 2013 to 2015 at 46 stations in...

The lake ice phenology variations are vital for the land-surface-water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling proc...

Maize is the crop with the largest planting area in the middle reaches of the Heihe River，with large water requirements and high evapotranspiration during the growing period. Accurately obtaining the maize planting area has important significances for the adjustment of crop planting structure and reasonable planning of water resources in the region...

Lake phenology is essential for understanding the lake freeze-thaw cycle effects on terrestrial hydrological processes. The Qinghai-Tibetan Plateau (QTP) has the most extensive ice reserve outside of the Arctic and Antarctic poles and is a sensitive indicator of global climate changes. Qinghai Lake, the largest lake in the QTP, plays a critical rol...

Understanding the spatial distribution of populations at a finer spatial scale has important value for many applications, such as disaster risk rescue operations, business decision-making, and regional planning. In this study, a random forest (RF)-based population density mapping method was proposed in order to generate high-precision population de...

Daily evapotranspiration (ET) and its components of evaporation (E) and transpiration (T) at field scale are often required for improving agricultural water management and maintaining ecosystem health, especially in semiarid and arid regions. In this study, multi-year daily ET, E, and T at a spatial resolution of 100 m in the middle reaches of Heih...

The Sustainable Development Goal (SDG) 6.3.2 of the United Nations (UN) focuses on ambient water quality, while water clarity simplistically and visually reflect water quality and can potentially support SDG 6.3.2 reporting. In this study, based on extensive field data and Sentinel-3 Ocean and Land Color Instrument (OLCI) imagery, a random forest r...

A precise multi-scenario prediction of future population, based on micro-scale census data and localized interpretation of global scenarios, is significant for understanding long-term demographic changes. However, the data used in previous research need to be further refined. Few studies have focused on predicting the sex ratio at birth, which is v...

Under economic fluctuations, the sustainable development of enterprises is crucial. Currently, there are few studies on the interaction between economic policy uncertainty (EPU) and the sustainable development behavior of enterprises. Based on a panel vector autoregressive (PVAR) model, this paper explores the static and dynamic interactions among...

Common software for land data assimilation is urgently needed to implement a wide variety of assimilation applications; however, a fast, easy-to-use, and multidisciplinary application-oriented assimilation platform has not been achieved. Therefore, we developed Common software for Nonlinear and non-Gaussian Land Data Assimilation (ComDA). ComDA int...

This research was undertaken to clarify the characteristics of vegetation change and its main influencing factors on the Qinghai-Tibet Plateau. Using the greenness rate of change (GRC) and correlation factors, we analyzed the trend of vegetation change and its dominant factors from 2000 to 2015. The results indicate that the vegetation tended to im...

For more efficient development planning, food-energy-water (FEW) nexus indicators should be provided with higher spatial and temporal resolutions. This paper takes Zhangye, a typical oasis city in Northwest China’s arid region, as an example, and uses the unweighted, geometric mean method to calculate a standardized, quantitative, and transparent e...

Abstract An effective assessment of future climate change, especially future precipitation forecasting, is an important basis for the rational development of adaptive strategies for Northwest China, where the ecological environment is fragile and encompasses arid and semiarid regions. In this work, the performance of a regional climate model is ass...

This study assessed the sensitivity and uncertainty interval of the Noah land surface model with multiparameterization (Noah‐MP) using observed meteorological data from eight sites with different snow climates. A total number of 20,736 Noah‐MP physics‐ensemble simulations was conducted for each site by combining different parameterization schemes o...

Urban sustainable development has attracted widespread attention worldwide as it is closely linked with human survival. However, the growth of urban areas is frequently disproportionate in relation to population growth in developing countries; this discrepancy cannot be monitored solely using statistics. In this study, we integrated earth observati...

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 selection, priority of date and location, and global and regiona...

Technological changes in water use efficiency directly influence regional sustainable development. However, few studies have attempted to predict changes in water use efficiency because of the complex influencing factors and regional diversity. The Chinese Government has established a target of 0.6 for the effective utilization coefficient of irrig...

The performance of the Noah land surface model (LSM) with multi-parameterization options (Noah-MP) in simulating snow depth was evaluated in northern Xinjiang, China. A total number of 13,824 Noah-MP physics-ensemble simulations were conducted at the Altay site by combining different parameterization schemes of physical processes while disregarding...

A precise multi-scenario prediction of future population, based on micro-scale census data and localized interpretation of global scenarios, is significant for understanding long-term demographic changes. However, the data used in previous research need to be further refined. Few studies have focused on predicting the sex ratio at birth, which is v...

Extreme precipitation over drylands, especially deserts, has been observed, whereas the precipitation changes in Chinese deserts have been rarely studied. Here, we used a daily grid precipitation data set generated via weather station data (0.25° horizontal grid spacing) to investigate the spatial and temporal changes in extreme precipitation in Ch...

As a high-altitude inland lake，Qinghai Lake's annual change in surface water area is critical for climate change and water cycle in the cold and arid regions. In order to study the spatial and temporal variation of area of Qinghai Lake in the past 30 years，extract 459 images from Landsat 5/8 that covering Qinghai Lake from 1986 to 2017（excluding 20...

As a high-altitude inland lake，Qinghai Lake's annual change in surface water area is critical for climate change and water cycle in the cold and arid regions. In order to study the spatial and temporal variation of area of Qinghai Lake in the past 30 years，extract 459 images from Landsat 5/8 that covering Qinghai Lake from 1986 to 2017（excluding 20...

The determination of area-averaged evapotranspiration (ET) over a heterogeneous land surface at the satellite pixel scale/model grid scale (103–104 m) is crucial to the evaluation of the remote sensing ET products and development of the parameterization schemes of general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimenta...

After a destructive earthquake, most of the casualties are brought about by building collapse. Our work is focused on using a single postevent PolSAR (full-polarimetric synthetic aperture radar) imagery to extract the building damage information for effective emergency decision-making. PolSAR data is subject to sunlight and contains richer backscat...

Photos of typical land cover conditions for the (a) Balsa Blanca, (b) Lucky Hills, (c) Kendall, (d) Desert steppe, (e) Gobi, and (f) Sandy sites. https://www.researchgate.net/publication/329201358_Evaluating_Soil_Resistance_Formulations_in_Thermal-Based_Two-Source_Energy_Balance_TSEB_Model_Implications_for_Heterogeneous_Semiarid_and_Arid_Regions

Relatively small fluctuations in the surface energy balance and evapotranspiration (ET) in semiarid and arid regions can be indicative of significant changes to ecosystem health. Therefore, it is imperative to have approaches for monitoring surface fluxes in these regions. The remote sensing‐based Two‐Source Energy Balance (TSEB) model is a suitabl...

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 the cloud gaps in MODIS fractional snow cover (SCF) products. The ground information of a gap pixel was estimated by using the appropria...