A5091619201- Climate change and permafrost
- Plant Water Relations and Carbon Dynamics
- Cryospheric studies and observations
- Urban Heat Island Mitigation
- Climate variability and models
- Remote Sensing and Land Use
- Hydrology and Watershed Management Studies
- Remote Sensing in Agriculture
- Atmospheric and Environmental Gas Dynamics
- Soil Moisture and Remote Sensing
- Winter Sports Injuries and Performance
- Aeolian processes and effects
- Plant Ecology and Soil Science
- Environmental Changes in China
- Building Energy and Comfort Optimization
- Geology and Paleoclimatology Research
- Environmental and Agricultural Sciences
- Arctic and Antarctic ice dynamics
- Tree-ring climate responses
- Soil Carbon and Nitrogen Dynamics
- Regional Economic and Spatial Analysis
- Calibration and Measurement Techniques
- Meteorological Phenomena and Simulations
- COVID-19 impact on air quality
- Air Quality and Health Impacts
Northwest Institute of Eco-Environment and Resources
2017-2025
Chinese Academy of Sciences
2015-2024
University of Chinese Academy of Sciences
2021
Beijing Normal University
2011
State Key Laboratory of Remote Sensing Science
2011
Core Ideas Heihe was the first basin-scale integrated observatory network established in China. An intensive flux observation matrix experiment conducted. New techniques, e.g., wireless sensor network, matrix, and airborne remote sensing, are used. The is useful land surface processes research. Research on at catchment scale has drawn much attention over past few decades, a number of watershed observatories have been worldwide. River Basin (HRB), which contains second largest inland river...
Abstract. The alpine region is important in riverine and watershed ecosystems as a contributor of freshwater, providing stimulating specific habitats for biodiversity. In parallel, recent climate change, human activities other perturbations may disturb hydrological processes eco-functions, creating the need next-generation observational modeling approaches to advance predictive understanding such region. However, several formidable challenges, including cold harsh climate, high altitude...
Abstract. Oases and deserts generally act as a landscape matrix mosaic in arid semiarid regions. The significant difference thermal dynamic characteristics between an oasis desert surface will result oasis–desert interaction. Specifically, this refers to the interaction system via exchange of momentum, energy, water, carbon, which can lead series microclimate effects that affect structure atmospheric boundary layer, changes carbon sources sinks oasis, local ecological environment. Therefore,...
The accurate and timely estimation of regional crop biomass at different growth stages is great importance in guiding management decision making. recent availability long time series remote sensing data offers opportunities for monitoring. In this paper, four machine learning models, namely random forest (RF), support vector (SVM), artificial neural network (ANN), extreme gradient boosting (XGBoost) were adopted to estimate the seasonal corn based on field observation moderate resolution...
Abstract Gross primary production (GPP) is an important variable in studies of the carbon cycle and climate change. The Moderate Resolution Imaging Spectroradiometer (MODIS)-GPP product (MOD17) provides global GPP data for terrestrial ecosystems; however, it not well validated China. In this study, eddy covariance (EC) system observed at 10 sites northern China was used to validate MOD17. results indicated that MOD17 presents a strong bias study region due meteorological data, MODIS FPAR...
With advantages of multispatial resolutions, a high retrieval accuracy, and temporal resolution, the satellite-derived land surface temperature (LST) products are very important LST sources. However, greatest barrier to their wide application is invalid values produced by large quantities cloudy pixels, especially for regions frequently swathed in clouds. In this study, an effective method based on energy balance theory similar pixels (SP) was developed reconstruct LSTs over widely used...
The MODIS land surface temperature (LST) product is one of the most widely used data sources to study climate and energy-water cycle at a global scale. However, large number invalid values caused by cloud cover limits wide application LST. In this study, two-step improved similar pixels (TISP) method was proposed for cloudy sky LST reconstruction. TISP validated using temperature-based over various types. ground measurements were collected fifteen stations from 2013 2018 during Heihe...
This study implements the “neighboring-pixel” (NP) theoretical method, which uses spatially and temporally NPs to reconstruct cloud-contaminated pixels in daily Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) products. The 2012 MODIS LSTs of Heihe River Basin (HRB) region China are used as an example, ground-measured obtained at 17 sites from Watershed Allied Telemetry Experimental Research (HiWATER) project validate reconstruction results. results show a...
Land surface temperature (LST) products derived from the moderate resolution imaging spectroradiometer (MODIS) sensor are one of most important data sources used to research land energy and water balance at regional global scales. However, MODIS severely contaminated by cloud cover, which limits applications LST products. In this paper, based on spatio-temporal autocorrelation variables, a reconstruction algorithm depending correlations between spatial pixels in multiple time phases...
Continuous land-surface temperature (LST) observations from ground-based stations are an important reference dataset for validating remote-sensing LST products. However, a lack of evaluations the representativeness station limits reliability validation results. In this study, new practical scheme is presented products that includes key step: assessing spatial measurements. Three indicators, namely, dominant land-cover type (DLCT), relative bias (RB), and average structure scale (ASS),...
The thermal infrared sensor-2 (TIRS-2) carried on Landsat 9 is the newest (TIR) sensor for project and provides two adjacent TIR bands, which greatly benefits land surface temperature (LST) retrieval at high spatial resolution. In this article, a radiance based split window (RBSW) algorithm retrieving LST from TIRS-2 data was proposed. addition, split-window covariance-variance ratio (SWCVR) improved applied to estimating atmospheric water vapor (AWV) that required accurate retrieval....
This study presents preliminary results of the validation Moderate Resolution Imaging Spectroradiometer (MODIS) daily LST products (MOD/MYD11A1, Version 5) using longwave radiation ground measurements obtained at 12 stations in North Arid and Semi-Arid Area Cooperative Experimental Observation Integrated Research program. In this evaluation process, broadband emissivity each station was from ASTER Spectral Library or estimated MODIS narrowband Collection 5. A comparison based on those two...
The efficient use of limited water resources and improving the efficiency (WUE) arid agricultural systems is becoming one greatest challenges in agriculture production global food security because shortage increasing demand for world. In this study, we attempted to investigate interannual trends evapotranspiration WUE responses biophysical factors utilization strategies over a main cropland ecosystem (i.e., seeded maize, Zea mays L.) regions North-Western China based on continuous...
Abstract Accurate estimation of regional and global patterns ecosystem respiration (ER) is crucial to improve the understanding terrestrial carbon cycles predictive ability budget. However, large uncertainties still exist in ER due drawbacks modeling methods. Based on eddy covariance data from 132 sites China 2002 2020, we established Intelligent Random Forest (IRF) models that integrated ecological with machine learning techniques estimate ER. The results showed IRF performed better than...