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- Air quality (1)
- Fall foliage coloration (1)
- Fire emission inventory (1)
- Foliage phase (1)
- GF-1 WFV (1)
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- HJ CCD (1)
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Articles 1 - 7 of 7
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Prototype For Monitoring And Forecasting Fall Foliage Coloration In Real Time From Satellite Data, Xiaoyang Zhang, Mitchell D. Goldberg, Yunyue Yu
Prototype For Monitoring And Forecasting Fall Foliage Coloration In Real Time From Satellite Data, Xiaoyang Zhang, Mitchell D. Goldberg, Yunyue Yu
Xiaoyang Zhang
While determining vegetation phenology from the time series of historical satellite data has been widely investigated throughout the last decade, little effort has been devoted to real-time monitoring and short-term forecasting. The latter is more important for numerical weather modeling, ecosystem forecasting, forest and crop management, and health risk warning. In this study we developed a prototype approach for the real-time monitoring and short-term forecasting of fall foliage status (including low coloration, moderate coloration, near-peak coloration, peak coloration, and post-peak coloration) using temporal satellite observations. The algorithm combined the climatology of vegetation phenology and temporally available satellite observations to establish …
Daily Modis 500 M Reflectance Anisotropy Direct Broadcast (Db) Products For Monitoring Vegetation Phenology Dynamics, Yanmin Shuai, Crystal Schaaf, Xiaoyang Zhang, Alan Strahler, David P. Roy, Jeffery Morisette, Zhuosen Wang, Joanne Nightingale, Jaime Nickerson, Andrew D. Richardson, Donghui Xie, Jindi Wang, Xiaowen Li, Kathleen Strabala, James E. Davies
Daily Modis 500 M Reflectance Anisotropy Direct Broadcast (Db) Products For Monitoring Vegetation Phenology Dynamics, Yanmin Shuai, Crystal Schaaf, Xiaoyang Zhang, Alan Strahler, David P. Roy, Jeffery Morisette, Zhuosen Wang, Joanne Nightingale, Jaime Nickerson, Andrew D. Richardson, Donghui Xie, Jindi Wang, Xiaowen Li, Kathleen Strabala, James E. Davies
Xiaoyang Zhang
Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on …
A Cross Comparison Of Spatiotemporally Enhanced Springtime Phenological Measurements From Satellites And Ground In A Northern U.S. Mixed Forest, Liang Liang, Mark D. Schwartz, Zhuosen Wang, Feng Gao, Crystal B. Schaaf, Bin Tan, Jeffrey T. Morisette, Xiaoyang Zhang
A Cross Comparison Of Spatiotemporally Enhanced Springtime Phenological Measurements From Satellites And Ground In A Northern U.S. Mixed Forest, Liang Liang, Mark D. Schwartz, Zhuosen Wang, Feng Gao, Crystal B. Schaaf, Bin Tan, Jeffrey T. Morisette, Xiaoyang Zhang
Xiaoyang Zhang
Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed …
Sensitivity Of Mesoscale Modeling Of Smoke Direct Radiative Effect To The Emission Inventory: A Case Study In Northern Sub-Saharan African Region, Feng Zhang, Jun Wang, Charles Ichoku, Edward J. Hyer, Zhifeng Yang, Cui Ge, Shenjian Su, Xiaoyang Zhang, Shobha Kondragunta, Christine Wiedinmyer, Johannes W. Kaiser, Arlindo Da Silva
Sensitivity Of Mesoscale Modeling Of Smoke Direct Radiative Effect To The Emission Inventory: A Case Study In Northern Sub-Saharan African Region, Feng Zhang, Jun Wang, Charles Ichoku, Edward J. Hyer, Zhifeng Yang, Cui Ge, Shenjian Su, Xiaoyang Zhang, Shobha Kondragunta, Christine Wiedinmyer, Johannes W. Kaiser, Arlindo Da Silva
Xiaoyang Zhang
An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of …
Interannual Variation In Biomass Burning And Fire Seasonality Derived From Geostationary Satellite Data Across The Contiguous United States From 1995 To 2011, Xiaoyang Zhang, Shobha Kondragunta, David Roy
Interannual Variation In Biomass Burning And Fire Seasonality Derived From Geostationary Satellite Data Across The Contiguous United States From 1995 To 2011, Xiaoyang Zhang, Shobha Kondragunta, David Roy
Xiaoyang Zhang
Wildfires exhibit a strong seasonality that is driven by climatic factors and human activities. Although the fire seasonality is commonly determined using burned area and fire frequency, it could also be quantified using biomass consumption estimates that directly represent biomass loss (a combination of the area burned and the fuel loading). Therefore, in this study a data set of long-term biomass consumed was derived from geostationary satellite data to explore the interannual variation in the fire seasonality and the possible impacts of climate change and land management practices across the Contiguous United States (CONUS). Specifically, daily biomass consumed data were …
Reconstruction Of Daily 30 M Data From Hj Ccd, Gf-1 Wfv, Landsat, And Modis Data For Crop Monitoring, Mingquan Wu, Xiaoyang Zhang, Wenjiang Huang, Zheng Niu, Changyao Wang, Wang Li, Pengyu Hao
Reconstruction Of Daily 30 M Data From Hj Ccd, Gf-1 Wfv, Landsat, And Modis Data For Crop Monitoring, Mingquan Wu, Xiaoyang Zhang, Wenjiang Huang, Zheng Niu, Changyao Wang, Wang Li, Pengyu Hao
Xiaoyang Zhang
With the recent launch of new satellites and the developments of spatiotemporal data fusion methods, we are entering an era of high spatiotemporal resolution remote-sensing analysis. This study proposed a method to reconstruct daily 30 m remote-sensing data for monitoring crop types and phenology in two study areas located in Xinjiang Province, China. First, the Spatial and Temporal Data Fusion Approach (STDFA) was used to reconstruct the time series high spatiotemporal resolution data from the Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field-of-view camera (GF-1 WFV), Landsat, and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Then, …
Near-Real-Time Global Biomass Burning Emissions Product From Geostationary Satellite Constellation, Xiaoyang Zhang, Shobha Kondragunta, Jessica Ram, Christopher Schmidt, Ho-Chung Huang
Near-Real-Time Global Biomass Burning Emissions Product From Geostationary Satellite Constellation, Xiaoyang Zhang, Shobha Kondragunta, Jessica Ram, Christopher Schmidt, Ho-Chung Huang
Xiaoyang Zhang
Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport …