A5102734338- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Remote Sensing and Land Use
- Advanced Image Fusion Techniques
- Plant Water Relations and Carbon Dynamics
- Tree-ring climate responses
- Ecology and Vegetation Dynamics Studies
- Soil erosion and sediment transport
- Land Use and Ecosystem Services
- Smart Agriculture and AI
- Remote-Sensing Image Classification
- Environmental Quality and Pollution
- Rangeland Management and Livestock Ecology
- Chaos-based Image/Signal Encryption
- Plant and animal studies
- Water Quality Monitoring and Analysis
- Plant responses to water stress
- Ecology and Conservation Studies
- Cognitive Computing and Networks
- Plant Ecology and Soil Science
- Natural Fiber Reinforced Composites
- Fiscal Policy and Economic Growth
- Plant Parasitism and Resistance
- Regional Development and Environment
- Analysis of environmental and stochastic processes
Beijing Normal University
2024
Xinjiang University
2020-2022
Oil Crops Research Institute
2022
Chinese Academy of Agricultural Sciences
2022
Central China Normal University
2020
Chinese Academy of Social Sciences
2009
Institute of Finance and Trade Economics
2009
Satellite remote sensing provides the changes information of Earth surface on large spatial scale in a long time series and has been widely used ecology. However, possible impact from human activities generally occurs smaller could be detected longer time, which requires data having both higher temporal resolution. Meanwhile, development spatiotemporal fusion algorithm an opportunity for requirements. In this paper, based deep learning, we proposed residual convolutional neural network...
Abstract Groundwater is increasingly becoming a permanent and steady water source for the growth reproduction of desert plant species due to frequent channel cutoff events in arid inland river basins. Although it widely acknowledged that accessibility groundwater has significant impact on maintaining their ecological function, little known about use strategies availability Daryaboyi Oasis, Central Tarim Basin. This study initially determined desirable stressing depths based morphological...
The relationship between the growth characteristics of vegetation and factors that limit protection relevant populations communities needs to be clarified. To gain a deeper understanding mechanism couples groundwater with Populus euphratica in desert ecosystem, as well explore effect its competitive Tamarix chinensis under restrictive conditions self-development community succession, we established 11 typical sample plots Daliyaboyi Oasis Taklimakan Desert. In current study, evaluated these...
The chlorophyll content has a direct effect on photosynthesis of crops. In order to explore quick and convenient method for estimating the Brassica napus facilitate efficient crop monitoring, we measured actual value with SPAD-502 detector, collected aerial images B. an unmanned vehicle(UAV) carrying RGB camera in this study. total number 270 samples were divided into regions according planting conditions different varieties field. Then, empirical formula, there 36 colors' characteristic...
Populus euphratica is an important tree species in desert ecosystems. The protection and restoration of natural forests requires accurate positioning information. use Sentinel-2 images to map the distribution at a large scale faces challenges associated with discriminating between Tamarix chinensis. To address this problem, study selected Daliyabuyi Oasis hinterland Taklimakan Desert as site sought distinguish from First, we determined peak spectral difference period (optimal time window)...
Surface water is an important factor affecting vegetation change in desert areas. However, little research has been conducted on the effects of surface expansion. In this study, annual spatial distribution range and Daliyabuyi Oasis from 1990 to 2020 was extracted using Landsat time-series images. Based multi-temporal multi-scale remote sensing images, several plots were selected demonstrate process landform expansion, influence expansion analyzed. The results show that coverage have...
Random sampling is an important approach to field vegetation surveys. However, surveys in desert areas are difficult because determining appropriate quadrat size that represent the sparse and unevenly distributed challenging. In this study, we present a methodology for optimization based on low-altitude high-precision unmanned aerial vehicle (UAV) images. Using Daliyaboyi Oasis as our study area, simulated random analyzed frequency distribution variation fractional cover (FVC) index of...
Populus euphratica is a unique constructive tree species within riparian desert areas that essential for maintaining oasis ecosystem stability. The Tarim River Basin contains the most densely distributed population of P. forests in world, and obtaining accurate distribution data mainstream would provide important support its protection restoration. We propose new method automatically extracting using Sentinel-1 2 Landsat-8 images based on Google Earth Engine cloud platform random forest...
Understanding vegetation water utilization can provide scientific basis for protection and rational distribution of resources in arid desert oasis area. In this study, sapling (DBH≤10 cm), mature (10 cm<DBH≤40 overmature (DBH>40 cm) Populus euphratica were chosen as sample trees natural Dariaboui. We measured oxygen isotopes xylem potential sources (surface water, soil 0-3 m layer groundwater) P. with different tree ages. The IsoSource model was used to study euphratica. results showed that...
It is highly necessary to apply unmanned aerial vehicle (UAV) remote sensing technology forest health assessment. To prove the feasibility of quantitative inversion photosynthetic pigment content (PPC) in Populus euphratica Oliv. individual tree canopy (PeITC) by using multispectral UAV images, this study, Parrot Sequoia+ system was manipulated collect images (Populus Oliv.) sample plots Daliyabuyi Oasis from 2019 2020, and PPCs five trees per plot were determined six plots. The crown...
The existing remote sensing image datasets target the identification of objects, features, or man-made targets but lack ability to provide date and spatial information for same feature in time-series images. temporal is important machine learning methods so that networks can be trained support precision classification, particularly agricultural applications specific crops with distinct phenological growth stages. In this paper, we built a high-resolution unmanned aerial vehicle (UAV) dataset...
The rapid development of unmanned aerial vehicle (UAV) remote sensing could provide critical data support for estimating the real-time crop growth status. In this study, vegetation indexes (VI) and texture features (T) in multispectral images were extracted, entropy method was used to construct a comprehensive index (CGI) which ultimately reflected winter wheat. Afterwards, predictive models wheat established evaluated by using machine learning modeling methods BPNN, RF SVM with different...