Shishi Liu

• Doctor of Philosophy
• Associate Professor at Huazhong Agricultural University

The normalized difference vegetation index (NDVI) is the most widely used vegetation index for monitoring vegetation vigor and cover. As NDVI time series are usually derived at coarse or medium spatial resolutions, pixel size often represents a mixture of vegetated and non-vegetated surfaces. In heterogeneous urban areas, mixed pixels impede the ac...

Estimating crop leaf nitrogen concentration (LNC, %) with the canopy bidirectional reflectance factor (BRF) is an effective method for detecting the nitrogen (N) deficiency in crops. It is challenging to remotely estimate LNC across growth stages and seasons with a general empirical model, since the complex change in canopy structure under N defici...

The dike-pond system (DPS) is the integration of a natural or man-made pond and crop cultivation on dikes, widely distributed in the Pearl River Delta and Jianghan plain in China. It plays a key role in preserving biodiversity, enhancing the nutrient cycle, and increasing crop production. However, DPS is rarely mapped at a large scale with satellit...

Demands for rape seeds oil rapidly increase in recent years. The empirical model based on the remotely sensed data provides an efficient approach to predict the rapeseed yield at small scale. The vegetation indices (VIs) derived from the remotely sensed data at the stage of the peak leaf area index (LAI) are usually the main determinant of the empi...

Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the abili...

Nitrogen (N), phosphorous (P), and potassium (K) are important macronutrients to crops. Deficiencies of these nutrients can change the pigment content in leaves and affect photosynthesis, resulting in the similar spectral characteristics at some wavelengths. Thus, one of the most important challenges in crop nutrient stress assessment through the c...

Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the abili...

Mapping rice cropping systems is important for grain yield prediction and food security assessments. Both single- and double-season rice are the dominant rice systems in central China. However, because of increasing labor shortages and high costs, there has been a gradual decline in double-season rice. Ratoon rice (RR) has been proposed as an alter...

Due to the intensive rotation and environmental concerns related with the over-fertilization, optimizing nitrogen (N) fertilization is crucial to winter oilseed rape cultivation in the Yangtze River Basin in China. Although remote sensing techniques have been applied to aid the site-specific crop N management, most studies are conducted for a speci...

The use of controlled release urea (CRU) was proposed as a promising approach to improve crop yield and nitrogen use efficiency (NUE) of crops in varying regions. However, such beneficial effects have not been well assessed in winter oilseed rape (Brassica napus L.), which usually has a period longer than 200 days. In this regional scale study cove...

Monitoring the above ground biomass (AGB) in winter oilseed rape is important for improving the agronomic management efficiency and predicting yield to ensure edible oil and biofuel supplies. The Yangtze River Basin in China accounts for one-fifth of the rapeseed yield in the world. However, the fragmented farming lands in the Yangtze River Basin m...

The photochemical reflectance index (PRI) has emerged to be a pre-visual indicator of water stress. However, whether the varying shaded-leaf fractions, which may be caused by multiple view angles or the changing crop density in the field, affect the performance of PRI in detecting water stress of crops is still uncertain. This study evaluated the i...

A R T I C L E I N F O Keywords: Annual land cover change detection Spatio-temporal land cover filter Urban area A B S T R A C T Annual analyses of land cover dynamics in urban areas provide a thorough understanding of the urbanization effects on environment and valuable information for the improvement of urban growth modeling. However, most current...

The photochemical reflectance index (PRI) has emerged to be a pre-visual indicator of water stress. However, whether the varying shadow fraction, which may be caused by multiple view angles or the changing crop density in the field, affects the performance of PRI in detecting water stress of crops is still uncertain. This study evaluated the impact...

Inversion of radiative transfer models (RTM) provides an avenue for assessment of crop status in precision agriculture. The potential of PROSAIL inverted using Tree-structure Parzen Estimators (TPE), a hyper-parameter searching algorithm to retrieve crop variables was evaluated in this study using a simulated dataset and an actual field experiment...

This study aimed to investigate whether the optimal vegetation indices (VIs) derived from the in situ hyperspectral data to estimate the nitrogen nutrition index (NNI) can also be used at the local scale using unmanned aerial vehicle (UAV) multispectral images, and whether texture metrics derived from UAV images could improve the remote estimation...

This study quantified the impacts of land-use/cover change (LUCC) on gross primary production (GPP) during 2000–2013 in a typical densely urbanized Chinese city, Wuhan. GPP was estimated at 30-m spatial resolution using annual land cover maps, meteorological data of the baseline year, and the normalized difference vegetation index (NDVI), which was...

Timely estimation of the vertical heterogeneity of leaf nitrogen concentration (LNC) from canopy reflectance using hyperspectral sensing is important for precision N management during winter oilseed rape productivity. However, current research pays little attention to LNC assessments by only taking LNC's vertical distribution into consideration, le...

Monitoring crop phenology is essential for evaluating crop productivity and crop management. Remote sensing provides an efficient way to monitor crop phenological metrics at a large-scale. However, the widely used AVHRR and MODIS images are less reliable at a small-scale and in areas with heterogeneous land covers, such as the patchy cropland in So...

Monitoring crop phenology is essential for evaluating crop productivity and crop management. Remote sensing provides an efficient way to monitor crop phenological metrics at a large-scale. However, the widely used AVHRR and MODIS images are less reliable at a small-scale and in areas with heterogeneous land covers, such as the patchy cropland in So...

Accurate assessments of chlorophyll density (ChD) using hyperspectral techniques are important for effective evaluation of plant productivity and precise nitrogen (N) management in winter oilseed rape. To develop a quantitative estimation model for determining ChD in winter oilseed rape, field experiments with different N fertilizer levels were con...

This study aims to find the optimal vegetation indices (VIs) to remotely estimate plant nitrogen concentration (PNC) in winter oilseed rape across different growth stages. Since remote sensing cannot "sense" N in live leaves, remote estimation of PNC should be based on understanding the relationships between PNC and chlorophyll (Chl), carotenoid co...

This study analyzed grassland gross primary production (GPP) estimated by the Temperature and Greenness (TG) model and the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm along the mean precipitation gradient and as a function of interannual variability in site-level precipitation. The calibrated TG model and MODIS algorithm appeare...

This study analyzed the vertical distribution of gravimetric water content (GWC), relative water content (RWC), and equivalent water thickness (EWT) in winter wheat during heading and early ripening stages, and evaluated the position of leaf number at which Vegetation Indexes (VIs) can best retrieve canopy water-related properties of winter wheat....

Soil moisture plays an important role in the coupled water, energy, and carbon cycles. In addition to surface processes such as evapotranspiration, the boundary fluxes that influence soil moisture are closely related to surface or subsurface runoff. To elucidate how uncertainties in representing surface and subsurface hydrology may influence simula...

The Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) is a new tool for analyzing and visualizing climate data. Here we provide some pointers, background information, and examples to show how the system works.

This data set provides standardized output variables for gross primary productivity (GPP), net ecosystem exchange (NEE), leaf area index (LAI), ecosystem respiration (Re), latent heat flux (LE), and sensible heat flux (H) from 24 terrestrial biosphere models for 47 eddy covariance flux tower sites in North America. Each model used standardized inpu...

This study established relationships among plant available soil moisture and reflectance and vegetation indices (VIs) derived from AVIRIS and MODIS data in grassland ecosystem in California. Strong correlations were observed between soil moisture and different forms of reflectance in the red-edge, near infrared and shortwave infrared bands. Both gr...

The 2011 Sendai Earthquake has hit the north-east of Japan triggering a destructive tsunami that has caused extensive damage. A fast and effective post-disaster assessment is highly imperative for the recovery of this region. This study modeled the tsunami-affected areas of coastal Fukushima Prefecture using Landsat-7 ETM+ data and terrain analysis...

We investigated the impact of soil moisture on gross primary production (GPP), chlorophyll content, and canopy water content represented by remotely sensed vegetation indices (VIs) in an open grassland and an oak savanna in California. We found for the annual grassland that GPP late in the growing season was controlled by the declining soil moistur...

Annual grasses are more sensitive to water availability than other plant functional types since they have shallow root systems. Monitoring the relationship between soil-water availability and grass growth can improve our knowledge of the phenological timing of water needs and physiological activities such as flowering and senescence. Webcams have p...

Optical remote sensing cannot provide direct quantification of soil moisture, but here we test the idea that plant available soil moisture can be inferred through calibration of images that quantify plant-leaf water and photosynthetic relationships. We measured relationships between volumetric soil water content in the rooting zone of annual grassl...