Zhihui Wang

Guangzhou Institute of Geography Guangdong Academy of Sciences

Foliar functional traits refer to a range of biochemical and physiognomic characteristics of vegetation that control photosynthesis, nutrient and water cycling, and can be used to describe the functional diversity of ecosystems. In this study, we utilize NASA AVIRIS - Next Generation imaging spectroscopy data to map 15 foliar functional traits in a...

Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent...

Concurrent measurement of multiple foliar traits to assess the full range of trade‐offs among and within taxa and across broad environmental gradients is limited. Leaf spectroscopy can quantify a wide range of foliar functional traits, enabling assessment of interrelationships among traits and with the environment. We analyzed leaf trait measuremen...

Leaf spectroscopy provides an efficient way of predicting foliar functional traits, commonly using physically- and empirically-based models. However, the generality of both models has not been fully investigated, and it is not clear if inversion strategies of physically-based models can be transferred across datasets. In this study, we evaluated th...

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemica...

Many studies have focused on the impact of nitrogen deposition on plants, but due to technical limitations, research on the responses of forest canopy to manipulated nitrogen deposition is relatively scarce. Based on a canopy nitrogen addition (CN) platform, this study used laboratory analysis and unmanned aerial vehicle (UAV) observations to asses...

In temperate forests, leaf phenology is a sensitive indicator of climate change and a major regulator of seasonal carbon and water cycling. Many studies have documented large intra-site leaf phenology variability across individual trees but conventional approaches for monitoring individual tree-scale leaf phenology are often limited to a small spat...

Remote sensing has transformed the monitoring of life on Earth by revealing spatial and temporal dimensions of biological diversity through structural, compositional and functional measurements of ecosystems. Yet, many aspects of Earth’s biodiversity are not directly quantified by reflected or emitted photons. Inclusive integration of remote sensin...

Rapid urbanization and increasing population have widely caused the urban heat island effect. Due to the decreasing distance between cities, there is an urgent need to reevaluate regional heat island intensity (RHII) in an urban agglomeration scale by considering all cities together instead of from conventional single city perspective. Using cropla...

Aims Unmanned aerial vehicles (UAVs), i.e. drones, have recently emerged as cost-effective and flexible tools for acquiring remote sensing data with fine spatial and temporal resolution. It provides a new method and opportunity for plant ecologists to study issues from individual to regional scales. However, as a new method, UAVs remote sensing app...

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and h...

Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In terrestrial systems, aboveground and belowground vegetation quantity and quality are coupled, and both influ...

Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In grassland systems, aboveground and belowground vegetation quantity and quality are coupled, and both influen...

Quantifying how biodiversity affects ecosystem functions through time over large spatial extents is needed for meeting global biodiversity goals yet is infeasible with field-based approaches alone. Imaging spectroscopy is a tool with potential to help address this challenge. Here, we demonstrate a spectral approach to assess biodiversity effects in...

The photosynthetic capacity or CO2-saturated photosynthetic rate (Vmax), chlorophyll, and nitrogen are closely linked leaf traits that determine C4 crop photosynthesis and yield. Accurate, timely, rapid, and nondestructive approaches to predict leaf photosynthetic traits from hyperspectral reflectance are urgently needed for high-throughput crop mo...

Nitrogen (N) is considered as one of the most important plant macronutrients and proper management of N therefore is a prerequisite for modern agriculture. Continuous satellite-based monitoring of this key plant trait would help to understand individual crop N use efficiency and thus would enable site-specific N management. Since hyperspectral imag...

Understanding the ecological effects of human activities on an ecosystem is integral to the implementation of conservation management plans. The plasticity of plant functional traits presents an opportunity to examine the capacity for intraspecific functional trait variations to be indicators of anthropogenic landscape modifications. The presence o...

Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long‐standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in L...

The proper management of nitrogen (N) is a prerequisite for sustainable fertilization in modern agriculture. Methods for N-retrieval from Earth Observation (E.O.) data have been mainly based on empirical algorithms. In the present study, two methods (physically based / hybrid) for the assessment of crop nitrogen content (N area) and concentration (...

Foliar nitrogen is a critical factor in leaf physiological processes, plant growth, and ecosystem functioning, which has been proposed as one of the essential biodiversity variables. Nitrogen has been quantified by a number of empirical approaches using hyperspectral data, but the retrieval of nitrogen through a physically based approach remains a...

Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs) are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In thi...

Forest ecosystems respond very sensitively to climate and atmospheric changes. Feedback mechanisms can be measured via changes in albedo, energy balance and carbon storage. The Bavarian Forest National Park is a unique forest ecosystem with large non-intervention zones, which promote a large scale re-wilding process with low human interference. It...

Leaf nitrogen content has so far been quantified through empirical techniques using hyperspectral remote sensing. However, it remains a challenge to estimate the nitrogen content in fresh leaves through inversion of physically based models. Leaf nitrogen has been found to correlate with leaf traits (e.g., leaf chlorophyll, dry matter, and water) we...