A5017629083- Remote Sensing and Land Use
- Remote Sensing in Agriculture
- Leaf Properties and Growth Measurement
- Greenhouse Technology and Climate Control
- Plant Water Relations and Carbon Dynamics
- Irrigation Practices and Water Management
- Horticultural and Viticultural Research
- Spectroscopy and Chemometric Analyses
- Smart Agriculture and AI
- Ziziphus Jujuba Studies and Applications
- Plant Physiology and Cultivation Studies
- Soil Geostatistics and Mapping
- Soil Moisture and Remote Sensing
- Urban Heat Island Mitigation
- Semiconductor Quantum Structures and Devices
- Advanced Fiber Laser Technologies
- Forest, Soil, and Plant Ecology in China
- Environmental and Agricultural Sciences
- Urban Green Space and Health
- Image Enhancement Techniques
- Video Surveillance and Tracking Methods
- Advanced Image Fusion Techniques
- Research in Cotton Cultivation
- Photonic and Optical Devices
- Nuts composition and effects
Tarim University
2014-2025
Gembloux Agro-Bio Tech
2018-2020
University of Liège
2018-2020
Agricultural Information Institute
2016
Chinese Academy of Agricultural Sciences
2016
Indian Institute of Science Bangalore
1984
Accurate cotton maps are crucial for monitoring growth and precision management. The paper proposed a county-scale mapping method by using random forest (RF) feature selection algorithm classifier based on selecting multi-features, including spectral, vegetation indices, texture features. contribution of features to classification accuracy was also explored in addition spectral index. In addition, the optimal time, importance, best extraction were evaluated. results showed that named gray...
In order to address the challenge of early detection cotton verticillium wilt disease, naturally infected plants in field, which were divided into five categories based on degree disease severity, have been investigated this study. Canopies analyzed with spectral data measured, and various preprocessing techniques, including multiplicative scatter correction (MSC) MSC-continuous wavelet analysis algorithms, used predict severity. With a combination support vector machine (SVM) models such...
Chlorophyll content is highly susceptible to environmental changes, and monitoring these changes can be a crucial tool for optimizing crop management providing foundation research in plant physiology ecology. This expected deepen our scientific understanding of ecological adaptation mechanisms, offer basis improving agricultural production, contribute ecosystem management. study involved the collection hyperspectral data, image SPAD data from jujube leaves. These were then processed using SG...
The rapid and accurate estimation of the nitrogen content fruit trees helps to achieve a precise management orchards. Hyperspectral data were collected from leaves apple tree canopies at different fertility stages through field experiments investigate relationship between spectral reflectance canopy leaves. Two preprocessing methods, Savitzky–Golay (SG) smoothing multiple scattering correction (MSC), used extract feature bands by combining successive projection method (SPA) competitive...
The presence of haze significantly degrades the quality remote sensing images, resulting in issues such as color distortion, reduced contrast, loss texture, and blurred image edges, which can ultimately lead to failure application systems. In this paper, we propose a superpixel-based visible dehazing algorithm, namely SRD. To begin, images are divided into content-aware patches using superpixels, cluster adjacent pixels considering their similarities brightness. We assume that each...
Abstract. The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by urbanization and climate change. Although dynamics extent were commonly modeled with conversion from non-urban using cellular-automata (CA)-based models, gradual changes impervious surface area (ISA) at the pixel level limitedly explored in previous studies. In this paper, we developed a dataset fractional 1 km resolution 2020 2100 (5-year...
Cotton is an economically valuable crop worldwide, and accurate rapid leaf moisture content, nitrogen soil plant analysis development (SPAD) value estimations are crucial for cotton growth. In this study, high-resolution spectral data were collected the Tahe 2 variety in Alar City, Xinjiang. The raw spectra preprocessed using four methods: first derivative, standard normal variate transformation, second multiplicative scatter correction. Wavelet coefficients at multiple scales generated from...
Hazy weather reduces contrast, narrows the dynamic range, and blurs details of remote sensing image. Additionally, color fidelity deteriorates, causing shifts image distortion, thereby impairing utility data. In this paper, we propose a lightweight sensing-image-dehazing network, named LRSDN. The network comprises two tailored, modules arranged in cascade. first module, axial depthwise convolution residual learning block (ADRB), is for feature extraction, efficiently expanding convolutional...
Mathematical models have been widely employed for the simulation of growth dynamics annual crops, thereby performing yield prediction, but not fruit tree species such as jujube (Zizyphus jujuba). The objectives this study were to investigate potential use a modified WOFOST model predicting by introducing age key parameter. was established using data collected from dedicated field experiments performed in 2016–2018. Simulated dry weights leaves, stems, fruits, total biomass and leaf area...
Few studies were focused on yield estimation of perennial fruit tree crops by integrating remotely-sensed information into crop models. This study presented an attempt to assimilate a single leaf area index (LAI) near maximum vegetative development stages derived from Landsat satellite data calibrated WOFOST model predict yields for jujube trees at the field scale. Field experiments conducted in three growth seasons calibrate input parameters model, with validated phenology error −2, −3, and...