Xiangqin Wei

Chinese Academy of Sciences | CAS · Aerospace Information Research Institute

Vegetation classification has always been the focus of remote sensing applications, especially for tropical regions with fragmented terrain, cloudy and rainy climates, and dense vegetation. How to effectively classify vegetation in tropical regions by using multi-spectral remote sensing with high resolution and red-edge spectrum needs to be further...

As the resolution of remote sensing quantitative inversion for albedo, clumping index, canopy height, and other biophysical parameter data is gradually refined, there is an increasing demand for higher spatial resolution bidirectional reflectance distribution function and angular reflectance data. In this study, we applied and evaluated Flexible Sp...

The scope of this research lies in the combination of pre-trained Convolutional Neural Networks (CNNs) and Quantum Convolutional Neural Networks (QCNN) in application to Remote Sensing Image Scene Classification(RSISC). Deep learning (RL) is improving by leaps and bounds pretrained CNNs in Remote Sensing Image (RSI) analysis, and pre-trained CNNs h...

Fine particulate matter, specifically PM2.5, has raised increasing public and governmental concerns over the past decade for its threats to the environment and public health. For large-scale PM2.5 estimation, spatial neighborhood information is frequently ignored when modeling the spatiotemporal heterogeneity of the PM2.5-aerosol optical depth (AOD...

Cloud detection plays a significant role in optical imagery, but snow has similar spectral characteristics to clouds in visible and near-infrared bands. The multi-feature combined (MFC) algorithm was proposed for the Gaofen-1 (GF-1) wide-field (WFV) imaging system data, with only three visible bands and one near-infrared band. It shows great accura...

Red-edge band is widely used for LAI estimation as it is highly correlated to vegetation growth conditions. Canopy reflectance is affected by both vegetation biophysical and biochemical characteristics. However, estimating LAI using satellite reflectance data as input rarely considers the influence of leaf chlorophyll content (LCC). This study test...

Carbon dioxide (CO2) in the atmosphere is an important variable that connects the atmosphere and terrestrial ecosystems. However, satellite-observed atmospheric CO2 concentrations are always spatially discrete, and spatiotemporally continuous atmospheric CO2 concentration maps with fine resolution are scarce at the global scale. Therefore, a spatio...

Spatiotemporal fusion has provided a feasible way to generate fractional vegetation cover (FVC) data with high spatial and temporal resolution. However, when the currently available spatiotemporal fusion methods are applied over agricultural regions, they usually underestimate high FVC values at the peak vegetation growth stage with medium FVC valu...

Soil moisture is a key parameter affecting crop growth. Gaofen-3 (GF-3) satellite is the first C-band synthetic aperture radar (SAR) produced by China, which provides full-polarization data sources for soil moisture estimation. This paper evaluated the potential of estimating soil moisture via GF-3 SAR over agricultural area using different polarim...

Fractional Vegetation Cover (FVC) is a critical land surface parameter, and several large-scale FVC products have been generated based on remote sensing data. Among these existing products, the GLASS FVC product, derived from MODIS 500 m reflectance data (MOD09A1), has achieved complete spatial-temporal continuity and satisfying accuracy. To furthe...

The Qinghai-Tibetan Plateau (QTP) has the most fragile ecosystems in the world. Over the past decades, QTP is suffering from increasing external pressures of climate change, human activities, and natural hazards, thus ecological vulnerability assessment is crucial for its sustainable development. This study proposes an objective and automatic frame...

Over recent years, miniaturized multispectral cameras mounted on an unmanned aerial vehicle (UAV) have been widely used in remote sensing. Most of these cameras are integrated with low-cost, image-frame complementary metal-oxide semiconductor (CMOS) sensors. Compared to the typical charged coupled device (CCD) sensors or linear array sensors, consu...

Fractional vegetation cover (FVC) is considered one of the most important vegetation parameters and is relevant to characterizing vegetation status and ecosystem function. An FVC with a fine spatial resolution of 30 m is essential for monitoring vegetation change and regional studies, while an FVC with a coarse spatial resolution of hundreds to tho...

Leaf area index (LAI) is an essential vegetation parameter that represents the light energy utilization and vegetation canopy structure. As the only in-operation hyperspectral satellite launched by China, GF-5 is potentially useful for accurate LAI estimation. However, there is no research focus on evaluating GF-5 data for LAI estimation. Hyperspec...

Fractional vegetation cover (FVC) is an important land surface parameter for many environmental and climate-related modeling and agricultural applications. Incorporating vegetation growth information into FVC estimation process could effectively improve FVC estimation accuracy. Methods utilizing vegetation growth information from field measurement...

Fractional vegetation cover (FVC) is an important parameter for many environmental and ecological models. Large-scale and long-term FVC products are critical for various applications. Currently, several global-scale FVC products have been generated with remote sensing data, such as VGT bioGEOphysical product Version 2 (GEOV2), PROBA-V bioGEOphysica...

Geochemical anomalies are important symbols for prospecting. To determine a new method for identifying geochemical anomalies rapidly, this study examines the possibility of using visible and near-infrared spectra of bedrock, weathered rock, and soil to assess copper content in the Baogutu stock II, Xinjiang, China. Partial least squares regression...

The newly launched GF-2 satellite is now the most advanced civil satellite in China to collect high spatial resolution remote sensing data. This study investigated the capability and strategy of GF-2 multispectral data for land use and land cover (LULC) classification in a region of the North China Plain. The pixel-based and object-based classifica...

Fractional vegetation cover (FVC) is an essential parameter for characterizing the land surface vegetation conditions and plays an important role in earth surface process simulations and global change studies. The Sentinel-2 missions carrying multi-spectral instrument (MSI) sensors with 13 multispectral bands are potentially useful for estimating F...

Fractional vegetation cover (FVC) is an essential input parameter for many environmental and ecological models. Recently, several global FVC products have been generated using remote sensing data. The Global LAnd Surface Satellite (GLASS) FVC product, which is generated from Moderate Resolution Imaging Spectroradiometer (MODIS) data, has attained a...

A fractional vegetation cover (FVC) estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed, which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarse-resolution FVC pixel were all assumed to have the same vegetation growth mod...

Fractional vegetation cover (FVC) is an important parameter for describing the land surface vegetation conditions and widely used for land surface process simulations and global change studies. Global FVC products are mainly derived from satellite data and several global FVC products have been generated. Validation of the satellite FVC products is...

Vegetation is an important land-cover type and its growth characteristics have potential for improving land-cover classification accuracy using remote-sensing data. However, due to lack of suitable remote-sensing data, temporal features are difficult to acquire for high spatial resolution land-cover classification. Several studies have extracted te...

Northern China is one of the most sensitive and vulnerable regions in the country. To combat environmental degradation in northern China, a series of vegetation protection programs, such as the Three-North Shelter Forest Program (TNFSP), have been implemented. Whether the implementation of these programs in northern China has improved the vegetatio...

Fractional vegetation cover (FVC), or green vegetation fraction, is an important parameter for characterizing conditions of the land surface vegetation, and also a key variable of models for simulating cycles of water, carbon and energy on the land surface. There are several types of FVC estimation models using remote sensing data, and evaluating t...

The wide field view (WFV) sensor on-board GF-1 satellite can acquire multi-spectral data with moderate spatial resolution, which holds great potential for monitoring the Earth's surface. This study assesses WFV data through cross-comparison of spectral band reflectances and vegetation indices with Landsat-7 Enhanced Thematic Mapper plus (ETM+) data...

Fractional vegetation cover (FVC) is an essential land surface parameter for Earth surface process simulations and global change studies. The currently existing FVC products are mostly obtained from low or medium resolution remotely sensed data, while many applications require the fine spatial resolution FVC product. The availability of well-calibr...

Leaf area index (LAI) is an important vegetation parameter that characterizes leaf density and canopy structure, and plays an important role in global change study, land surface process simulation and agriculture monitoring. The wide field view (WFV) sensor on board the Chinese GF-1 satellite can acquire multi-spectral data with decametric spatial...

Fractional vegetation cover (FVC) is an important parameter for earth surface process simulations, climate modeling, and global change studies. Currently, several FVC products have been generated from coarse resolution (~1 km) remote sensing data, and have been widely used. However, coarse resolution FVC products are not appropriate for precise lan...

An automatic fractional vegetation cover (FVC) estimation method based on image characteristics in an agricultural region was proposed in this study to remove the empiricism in determining the key parameters of empirical methods. The proposed method automatically determined the soil and vegetation lines in the two-dimensional space of the red and b...

A large number of fossil plants were collected from the Lower Permian Yierxitu Formation in the vicinity of Erdaogou Village, Tianshan Town, Hami City on the northeast margin of Tuha basin. A total of five genera and thirteen species have been identified, including three undetermined species. Most of the florae are of Codaitopsida, and almost all o...

The quasi-sliding-mode control based on non-linear surface which has variable damping characteristic is proposed for discrete-time systems with uncertainty which is boundary or slow time-variant. The strategy could ensure reduce the region of quasi-sliding mode, improve dynamic quality. The control chattering and steady-states chattering are avoide...

Automatic land cover update was an effective means to obtain objective and timely land cover maps without human disturbance. This study investigated the efficacy of multi-temporal remote sensing data and advanced non-parametric classifier on improving the classification accuracy of the automatic land cover update approach integrating iterative trai...

Forest cover information is essential for natural resource management and for climate change studies. In this paper, the fractional forest cover (FFC) in Northeast China was estimated using neural networks (NNs) based on the Global Inventory Modeling and Mapping Studies (GIMMS3g) Normalized Difference Vegetation Index (NDVI) data with 8-km resoluti...

Forest cover plays a key role in climate change by influencing the carbon stocks, the hydrological cycle and the energy balance. Forest cover information can be determined from fine-resolution data, such as Landsat Enhanced Thematic Mapper Plus (ETM+). However, forest cover classification with fine-resolution data usually uses only one temporal dat...

Temporal-related features are important for improving land cover classification accuracy using remote sensing data. This study investigated the efficacy of phenological features extracted from time series MODIS Normalized Difference Vegetation Index (NDVI) data in improving the land cover classification accuracy of Landsat data. The MODIS NDVI data...

The successful launch of Landsat 8 provides a new data source for monitoring land cover, which has the potential to significantly improve the characterization of the earth’s surface. To assess data performance, Landsat 8 Operational Land Imager (OLI) data were first compared with Landsat 7 ETM + data using texture features as the indicators. Furthe...

Fruit picking robot is required for agricultural automation for fruit harvest, and vision system is the important and crucial composition of a robot system. An automatic extraction method of fruit object under complex agricultural background for vision system in fruit picking robot is presented in this study. The method is based on an improving Ots...

Land cover classification of finer resolution remote sensing data is always difficult to acquire high-frequency time series data which contains temporal features for improving classification accuracy. This paper proposed a method of land cover classification with finer resolution remote sensing data integrating temporal features extracted from time...

Large amount of spores and pollen (mainly consist of pteridophyta spores and gymnospermous pollen), including 54 genera and 90 species, were discovered in the fifth member of Late Permian Linxi Formation, Guandi section, Linxi, Inner Mongolia. The fifth member of Linxi Formation was assumed to belong to the Late Permian, for the preservations of sp...

Reasonable ground sampling methods for the development of soil moisture remote sensing retrieval algorithm models and product validation are very important. Soil moisture has obvious variability at different spatial and temporal scales, especially for surface soil moisture. It makes the surface soil moisture sampling at medium or coarse resolution...

Currently, the calibration work of analog measurement instruments is mainly completed by manual and there are many problems waiting for being solved. In this paper, an automatic calibration system (ACS) based on Digital Signal Processor (DSP) and Charge Coupled Device (CCD) sensor is developed and a real-time calibration algorithm is presented. In...