A5103221662- Remote Sensing and Land Use
- Remote Sensing in Agriculture
- Spectroscopy and Chemometric Analyses
- Leaf Properties and Growth Measurement
- Environmental Changes in China
- Soil Carbon and Nitrogen Dynamics
- Environmental and Agricultural Sciences
- Forest, Soil, and Plant Ecology in China
- Plant Ecology and Soil Science
- Environmental Quality and Pollution
- Rangeland Management and Livestock Ecology
- Soil erosion and sediment transport
- Remote Sensing and LiDAR Applications
- Hydrology and Watershed Management Studies
- Soil Geostatistics and Mapping
- Water Quality Monitoring and Analysis
- Regional Economic and Spatial Analysis
- Peatlands and Wetlands Ecology
- Soil and Water Nutrient Dynamics
- Land Use and Ecosystem Services
- Geochemistry and Geologic Mapping
- Flood Risk Assessment and Management
- Horticultural and Viticultural Research
- Climate change and permafrost
- Soil and Unsaturated Flow
Northwest A&F University
2016-2025
Northwest Institute of Mechanical and Electrical Engineering
2022-2025
Ministry of Agriculture and Rural Affairs
2020-2023
Dalian University of Technology
2019-2020
Ministry of Water Resources of the People's Republic of China
2019-2020
China Institute of Water Resources and Hydropower Research
2014-2019
Northeast Normal University
2019
Institute of Soil and Water Conservation
2018
Hunan Agricultural University
2011
Xianyang Normal University
2008-2009
Land uses and cultivation are important factors controlling SOC storage on the Loess Plateau. These may also affect relative importance of different mechanisms for stabilization organic matter in soil. Easily oxidizable carbon (EOC), aggregation aggregate C fractions soil were measured under land uses. Aggregates fractionated using a wet-sieving procedure to obtain distribution water-stable aggregates. The aggregates, EOC grassland forestland generally higher than those farmland....
Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate carbonate dissolution CO2 release. However, date, few studies have addressed these processes. Here, we use meta-analysis nationwide-survey datasets investigate changes in inorganic carbon (SIC) stocks China. We observe an overall decrease SIC topsoil (0-30 cm) (11.33 g C m-2 yr-1) from the 1980s 2010s. Total decreased by ∼8.99 ± 2.24% (1.37 0.37 Pg C). The average losses...
The use of a fast and accurate unmanned aerial vehicle (UAV) digital camera platform to estimate leaf area index (LAI) kiwifruit orchard is great significance for growth, yield estimation, field management. LAI, as an ideal parameter estimating vegetation plays significant role in reflecting crop physiological process ecosystem function. At present, LAI estimation mainly focuses on winter wheat, corn, soybean, other food crops; addition, forest research also predominant, but there are few...
The infection of Apple mosaic virus (ApMV) can severely damage the cellular structure apple leaves, leading to a decrease in leaf chlorophyll content (LCC) and reduced fruit yield. In this study, we propose novel method that utilizes hyperspectral imaging (HSI) technology non-destructively monitor ApMV-infected leaves predict LCC as quantitative indicator disease severity. data were collected from 360 optimal wavelengths selected using competitive adaptive reweighted sampling algorithms. A...
Different soil types can significantly affect the composition of wine grapes and final product. In this study, effects on Cabernet Sauvignon produced in Helan Mountains were evaluated. Three different representative types—aeolian, sierozem irrigation silting studied. The compositions wines measured, addition, weights 100-berry samples determined. that grown aeolian soils matured sooner than those soil. highest sugar content, total soluble solids to acid ratio anthocyanin content found from...
Leaf chlorophyll content (LCC) is one of the most important factors affecting photosynthetic capacity and nitrogen status, both which influence crop harvest. However, development rapid nondestructive methods for leaf estimation a topic much interest. Hence, this study explored use machine learning approach to enhance from spectral reflectance data. The objective was evaluate four different approaches estimating LCC apple tree leaves at five growth stages (the 1st, 2nd, 3rd, 4th 5th stages):...
Canopy chlorophyll content (CCC) is closely related to crop nitrogen status, growth and productivity, detection of diseases pests, final yield. Thus, accurate monitoring in crops great significance for decision support precision agriculture. In this study, winter wheat the Guanzhong Plain area Shaanxi Province, China, was selected as research subject explore feasibility canopy spectral transformation (CST) combined with a machine learning method estimate CCC. A hyperspectral ground dataset...
Nitrogen is one of the most important macronutrients and plays an essential role in growth development winter wheat. It very crucial to diagnose nitrogen status timely accurately for applying a precision management (PNM) strategy guidance fertilizer field. The main purpose this study was use three different prediction methods evaluate wheat plant concentration (PNC) at booting, heading, flowering, filling, whole stage Guanzhong area from unmanned aerial vehicle (UAV) hyperspectral imagery....
Leaf chlorophyll content (LCC) is a crucial indicator of nutrition in apple trees and can be applied to assess their growth status. Hyperspectral data provide an important means for detecting the LCC trees. In this study, hyperspectral measured were obtained. The original spectrum (OR) was pretreated using some spectral transformations. Feature bands selected based on competitive adaptive reweighted sampling (CARS) algorithm, random frog (RF) elastic net (EN) EN-RF EN-CARS algorithms....
The performance of three machine learning methods (support vector regression, random forests and artificial neural network) for estimating the LAI paddy rice was evaluated in this study. Traditional univariate regression models involving narrowband NDVI with optimized band combinations as well linear multivariate calibration partial least squares were also comparison. A four year field-collected dataset used to test robustness estimation against temporal variation. built on raw hyperspectral...
Soil is the largest carbon reservoir on terrestrial surface. organic (SOC) not only regulates global climate change, but also indicates soil fertility level in croplands. SOC prediction based remote sensing images has generated great interest research field of digital mapping. The short revisiting time and wide spectral bands available from Sentinel-2A (S2A) data can provide a useful resource for property prediction. However, dense surface coverage reduces direct relationship between...
Estimation of crop biophysical and biochemical characteristics is the key element for growth monitoring with remote sensing. With application unmanned aerial vehicles (UAV) as a sensing platform worldwide, it has become important to develop general estimation models, which can interpret data crops by different sensors in agroclimatic regions into comprehensible agronomy parameters. Leaf chlorophyll content (LCC), be measured soil plant analysis development (SPAD) value using SPAD-502...
Accurately measuring leaf chlorophyll content (LCC) is crucial for monitoring maize growth. This study aims to rapidly and non-destructively estimate the LCC during four critical growth stages investigate ability of phenological parameters (PPs) LCC. First, spectra were obtained by spectral denoising followed transformation. Next, sensitive bands (Rλ), indices (SIs), PPs extracted from all at each stage. Then, univariate models constructed determine their potential independent estimation....
The anthocyanins in apple leaves can indicate their growth status, and the health of not only reveals nutritional supply tree but also reflects quality fruit. Therefore, real-time monitoring monitor growth, thereby promoting development industry. This study utilizes ground hyperspectral imaging to estimate Fuji Loess Plateau through spectral transformation, feature extraction (including band selection indices construction), regression algorithm selection, establishing models for three...
Chlorophyll content is an essential parameter for evaluating the growth condition of winter wheat, and its accurate monitoring through remote sensing great significance early warnings about wheat growth. In order to investigate unmanned aerial vehicle (UAV) multispectral technology’s capability estimate chlorophyll this study proposes a method estimating relative canopy (RCCC) based on UAV images. Concretely, M350RTK with MS600 Pro camera was utilized collect data, immediately followed by...