A5084616489- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Species Distribution and Climate Change
- Remote Sensing and LiDAR Applications
- Plant Water Relations and Carbon Dynamics
- Remote Sensing and Land Use
- Urban Heat Island Mitigation
- Atmospheric and Environmental Gas Dynamics
- Ecology and Vegetation Dynamics Studies
- Remote-Sensing Image Classification
- Leaf Properties and Growth Measurement
- COVID-19 impact on air quality
- Agricultural risk and resilience
- Hydrology and Watershed Management Studies
- Tree-ring climate responses
- Smart Agriculture and AI
- Flood Risk Assessment and Management
- Climate Change, Adaptation, Migration
- Urban Green Space and Health
- Air Quality and Health Impacts
- Ecosystem dynamics and resilience
- Foreign Language Teaching Methods
- Tropical and Extratropical Cyclones Research
- Sustainable Agricultural Systems Analysis
- Cryospheric studies and observations
North Carolina State University
2016-2024
North Central State College
2024
RMIT University
2019
Boston University
2014-2018
Beijing Normal University
2014
University of North Carolina at Chapel Hill
2009-2013
George Mason University
2009
Monash University
1982-1984
UNSW Sydney
1982-1984
The University of Western Australia
1982
Vegetation phenology controls the seasonality of many ecosystem processes, as well numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series datasets, together consisting almost 750 years observations, characterizing vegetation in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through PhenoCam network. For each archived...
Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new opportunities to monitor, map, characterize temporal dynamics in land surface properties with unprecedented spatial detail quality. By combining from the Operational Land Imager MultiSpectral Instrument on-board Sentinel-2A -2B, remote sensing community now has access moderate (10–30 m) resolution repeat periods ~3 days mid-latitudes. At same time, large combined data volume introduce substantial challenges for...
Abstract. Plant phenology regulates ecosystem services at local and global scales is a sensitive indicator of change. Estimates phenophase transition dates, such as the start spring or end fall, can be derived from sensor-based time series, but must interpreted in terms biologically relevant events. We use PhenoCam archive digital repeat photography to implement consistent protocol for visual assessment canopy 13 temperate deciduous forest sites throughout eastern North America, perform...
This paper provides a review and summary status of the research underway by NASA Terra Aqua Suomi-NPP Land Discipline Team to provide continuity global land data products from Moderate resolution Imaging Spectroradiometer (MODIS) Visible Infrared Radiometer Suite (VIIRS). The two MODIS instruments on Earth Observing System (morning overpass) (afternoon platforms have provided more than twenty years data. peer-reviewed generated are now being transitioned production using VIIRS inputs, with...
As the Earth’s population continues to grow and demand for food increases, need improved timely information related properties dynamics of global agricultural systems is becoming increasingly important. Global land cover maps derived from satellite data provide indispensable regarding geographic distribution areal extent croplands. However, use information, such as cropping intensity (defined here number cycles per year), not routinely available over large areas because mapping this remote...
By the end of this century, mean annual temperatures in Northeastern United States are expected to warm by 3–5 °C, which will have significant impacts on structure and function temperate forests region. To improve understanding these impacts, we exploited two recent climate anomalies explore how springtime phenology deciduous respond future warming. Specifically, 2010 2012 were warmest record States, with that roughly equivalent lower warming scenarios projected for region decades from now....
Abstract Vegetation green leaf phenology directly impacts gross primary productivity (GPP) of terrestrial ecosystems. Satellite observations land surface (LSP) provide an important means to monitor the key timing vegetation development. However, differences between satellite‐derived LSP proxies and in situ measurements GPP make it difficult quantify impact climate‐induced changes on annual GPP. Here, we used 1,110 site‐years from eddy‐covariance towers association with time series satellite...
Agricultural systems are geographically extensive, have profound significance to society, and affect regional energy, climate, water cycles. Since most suitable lands worldwide been cultivated, there is a growing pressure increase yields on existing agricultural lands. In tropical subtropical regions, multicropping widely used food production, but regional-to-global information related practices poor. The high temporal resolution moderate spatial of the MODIS sensors provide an ideal source...
A spring phenology model that combines photoperiod with accumulated heating and chilling to predict leaf-out dates is optimized using PhenoCam observations coupled into the Community Land Model (CLM) 4.5. In head-to-head comparison (using satellite data from 2003 2013 for validation) grid cells over Northern Hemisphere deciduous broadleaf forests (5.5 million km2 ), we found revised substantially outperformed standard CLM seasonal-deciduous submodel at both coarse (0.9 × 1.25°) fine (1 km)...
The growing numbers of land change models makes it difficult to select a model at the beginning an analysis, and is often arbitrary researcher’s discretion. How when multiple are suitable, represents critical research gap currently understudied, where trade-offs choosing one over another unknown. Repeatable methods needed conduct cross-model comparisons understand among same calibration validation data used. Several assess accuracy have been proposed that emphasize quantity allocation, while...
Observations of vegetation phenology at regional-to-global scales provide important information regarding seasonal variation in the fluxes energy, carbon, and water between biosphere atmosphere. Numerous algorithms have been developed to estimate phenological transition dates using time series remotely sensed spectral indices. A key challenge, however, is that different inconsistent results. This study provides a comprehensive comparison start season (SOS) end (EOS) estimated from 500 m...
Land surface phenology (LSP) is a consistent and sensitive indicator of climate change effects on Earth's vegetation. Existing methods estimating LSP require time series densities that, until recently, have only been available from coarse spatial resolution imagery such as MODIS (500 m) AVHRR (1 km). products these datasets improved our understanding phenological at the global scale, especially over era (2001-present). Nevertheless, may obscure important finer scale patterns longer-term...
The mapping of field boundaries can provide important information for increasing food production and security in agricultural systems across the globe. Remote sensing a viable way to map large geographic extents, yet few studies have used satellite imagery where sizes are small, heterogeneous, irregularly shaped. Here we very-high-resolution WorldView-3 (0.5 m) mask region-based convolutional neural network (Mask R-CNN) delineate smallholder Northeast India. We found that our models had...
Leaf area index (LAI) is an important biophysical indicator of forest health that linearly related to productivity, serving as a key criterion for potential nutrient management. A single equation was produced model surface reflectance values captured from the Sentinel-2 Multispectral Instrument (MSI) with robust dataset field observations loblolly pine (Pinus taeda L.) LAI collected LAI-2200C plant canopy analyzer. Support vector machine (SVM)-supervised classification used improve fit by...