Modeling and sensitivity analysis of fire emissions in southern Africa during SAFARI 2000

This paper uses three recently generated southern African satellite burned area products for the month of September 2000 in a sensitivity study of regional biomass burning emissions for a number of trace gases and particulates. Differences in the extent and location of areas burned among products generated from Moderate Resolution Imaging Spectroradiometer (MODIS), Systeme Pour l'Observation de la Terre (SPOT-VEGETATION), and Along Track Scanning Radiometer (ATSR-2) data are significant and result in different emissions estimates for woodland and grassland land cover types. Due to the different emission profiles in woodlands and grasslands, favoring relatively more products of incomplete combustion in woodlands compared with products of complete combustion in grasslands in the late dry season, these changes are not proportional to the differences in the burned area amounts. The importance of accurate burned area information not just in terms of the total area but also in terms of its spatial distribution becomes apparent from our modeling results. This paper highlights the urgent need for satellite data producers to provide accuracy assessments associated with satellite-derived products. Preferably, these accuracy data will be spatially explicit, or defined in a way that can be applied in a spatially explicit modeling context, to enable emissions uncertainties to be defined with respect to different landscape units in support of greenhouse gas emissions reporting.     

The 3D Chinese head and face modeling

Perfect fit for people has always been a target for product design. Designers commonly use traditional anthropometric dimensions for 3D product design thus creating a lot of fitting problems when dealing with the complexities of human body shapes. The development of recent 3D anthropometric survey has created an opportunity for complex shape analysis on human model by collecting 3D scan data. Using 3D point cloud data from the SizeChina survey, a methodology of creating a homologous 3D head and face model was demonstrated in this study. Anatomical and virtual landmarks, and surface modeling algorithm based on point cloud data were applied in building the model. The head and face models for all scans had the same amount of vertices with consistent features. The average Chinese models showed obvious differences between male and female. The variations of head and face shapes were analyzed using Principal Component Analysis and the results showed that the largest variations among people were general size, especially for width and depth. However face height, forehead, back of the head, chin and jaw area were also important when describing the 3D shape. The results from this study may be useful in the design of head and facial products.     

A SeaWiFS global monthly coarse-resolution reflectance dataset

A global monthly reflectance dataset from September 1997 to December 1999 at 8 km spatial resolution was derived from Sea Wide Field of view Sensor (SeaWiFS). This dataset, used for prototyping MODIS Land/ Atmosphere algorithms, is now available for release to the broader community. This Letter describes the data processing, data format, and how these value-added data and some tools for their analysis may be obtained.     

Dynamic Assessment of Functional Lipidomic Analysis in Human Urine

The development of enabling mass spectrometry platforms for the quantification of diverse lipid species in human urine is of paramount importance for understanding metabolic homeostasis in normal and pathophysiological conditions. Urine represents a non‐invasive biofluid that can capture distinct differences in an individual's physiological status. However, currently there is a lack of quantitative workflows to engage in high throughput lipidomic analysis. This study describes the development of a MS/MS^ALL shotgun lipidomic workflow and a micro liquid chromatography–high resolution tandem mass spectrometry (LC–MS/MS) workflow for urine structural and mediator lipid analysis, respectively. This workflow was deployed to understand biofluid sample handling and collection, extraction efficiency, and natural human variation over time. Utilization of 0.5 mL of urine for structural lipidomic analysis resulted in reproducible quantification of more than 600 lipid molecular species from over 20 lipid classes. Analysis of 1 mL of urine routinely quantified in excess of 55 mediator lipid metabolites comprised of octadecanoids, eicosanoids, and docosanoids generated by lipoxygenase, cyclooxygenase, and cytochrome P450 activities. In summary, the high‐throughput functional lipidomics workflow described in this study demonstrates an impressive robustness and reproducibility that can be utilized for population health and precision medicine applications.     

Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data

The remote sensing of Earth surface changes is an active research field aimed at the development of methods and data products needed by scientists, resource managers, and policymakers. Fire is a major cause of surface change and occurs in most vegetation zones across the world. The identification and delineation of fire-affected areas, also known as burned areas or fire scars, may be considered a change detection problem. Remote sensing algorithms developed to map fire-affected areas are difficult to implement reliably over large areas because of variations in both the surface state and those imposed by the sensing system. The availability of robustly calibrated, atmospherically corrected, cloud-screened, geolocated data provided by the latest generation of moderate resolution remote sensing systems allows for major advances in satellite mapping of fire-affected area. This paper describes an algorithm developed to map fire-affected areas at a global scale using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance time series data. The algorithm is developed from the recently published Bi-Directional Reflectance Model-Based Expectation change detection approach and maps at 500 m the location and approximate day of burning. Improvements made to the algorithm for systematic global implementation are presented and the algorithm performance is demonstrated for southern African, Australian, South American, and Boreal fire regimes. The algorithm does not use training data but rather applies a wavelength independent threshold and spectral constraints defined by the noise characteristics of the reflectance data and knowledge of the spectral behavior of burned vegetation and spectrally confusing changes that are not associated with burning. Temporal constraints are applied capitalizing on the spectral persistence of fire-affected areas. Differences between mapped fire-affected areas and cumulative MODIS active fire detections are illustrated and discussed for each fire regime. The results reveal a coherent spatio-temporal mapping of fire-affected area and indicate that the algorithm shows potential for global application.     

Cilioretinal arteries. A study based on review of stereo fundus photographs and fluorescein angiographic findings

The incidence of cilioretinal arteries in 2,000 eyes of 1,000 consecutive patients was determined by review of stereo color fundus photographs and fluorescein angiographs. One or more cilioretinal arteries were present in 49.5% of all patients or in 32.1% of the eyes. The arteries occurred bilaterally in 14.6% and contributed to some portion of the macular circulation in 18.7% of the patients. A great deal of variability of size, number, and distribution of cilioretinal vessels was observed. Prior studies that were based on direct visualization of the fundus have reported cilioretinal arteries in 7% to 29.6% of patients examined. Careful review of stereo fundus photographs and early phase fluorescein angiographs aided in the observation of these vessels that might otherwise have been unrecognized. We believe the method of review accounts for the high incidence of cilioretinal arteries in our series.     

Agricultural burning in the Southeastern United States detected by MODIS

The southeastern United States, including the states of Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia, had a high occurrence of fire activity as detected by the 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA Active Fire Product (MOD 14). The analysis of the satellite data from 2001 to 2004 showed that agricultural burning in the southeastern United States accounted for an average of 16% of annual fire activity. The southeastern region contributed an average of 33% of all agricultural burning detected in the contiguous United States. Crop residues that burned in the southeast included rice, winter wheat, sugarcane, soybean and cotton. Much of the agricultural burning occurred in June and from October to January and was related to the harvest of winter wheat and rice in the spring and the harvest of sugarcane, soybean and cotton in the fall and winter. The results showed that cropland burning was spatially dependent on crop type and temporally dependent on management practices (planting/harvesting). Arkansas, Florida, and Louisiana contributed more than 75% of all agricultural burning in the southeast. A 250 m MODIS land cover map cover for 2004 was developed for these three states using a decision tree classification and validation from a field campaign in the fall of 2004. Compared to the standard MODIS 1 km Land Cover Dataset (MOD 12) product ([Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., Schaaf, C. (2002), Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of the Environment, 83, 287-302.]), the 250 m classified images contained on average 50% more cropland area and improved the estimation of cropland area based on validation from ground control sites of croplands. Results from the decision tree classification for each state revealed that in 2004 agricultural burning contributed 73%, 54%, and 33% of total fires for Arkansas, Florida, and Louisiana, respectively.     

Effect of wavelength selection on characterization of fire size and temperature

Over the past two decades, Dozier's 1981 retrieval method has been used with observations from various moderate-resolution (～ 1 km) spaceborne sensors to estimate the instantaneous sub-pixel area and temperature of wildfires. The method requires simultaneous observations at two different wavelengths. Traditionally these wavelengths have resided in the middle- and long-wave infrared regions, for example the 4 and 11 @m channels of the NOAA Advanced Very High Resolution Radiometer (AVHRR). Development of recent and upcoming sensors, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS), have spawned interest in using other wavelength combinations, particularly in the short-wave infrared, for sub-pixel active fire characterization. We demonstrate that for realistic wildfires, which are composed of both flaming and smouldering components, the location of these two wavelengths can cause large differences in the fire temperatures and areas that are retrieved using Dozier's method. In the worst case considered, differences of 250 K in temperature and 80% in area were observed.     

A new land cover map of central Africa derived from multi-resolution,multi-temporal AVHRR data

We describe a new map of the central Africa region that was derived from National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) observations using a fusion of Local Area Coverage (LAC, 1 km), Global Area Coverage (GAC, 8 km), and ancillary information. The land cover map, produced for the Central Africa Regional Program for the Environment (CARPE), offers a synoptic view of the extent of central African dense humid forests, at relatively fine spatial resolution. Land cover types include dense humid forest, disturbed or degraded forest and various savanna classes. Ancillary information includes political and park boundaries, settlements, rivers and roads. Map validation was performed using a combination of field visits and finer resolution imagery (Landsat Multi-Spectral Scanner (MSS)). Forest cover type mapping errors were at most 20 per cent. The resulting map is useful for addressing a number of resource management issues, a few of which are examined.