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Item SEASONAL AND INTERANNUAL VARIABILITY OF EMISSIONS FROM CROP RESIDUE BURNING IN THE CONTIGUOUS UNITED STATES(2009) McCarty, Jessica; Justice, Chrisopher O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Crop residue burning is a global agricultural practice used to remove excess residues before or after harvest. Crop residue burning in the contiguous United States (CONUS) has been documented at the regional and state-level by governmental organizations and in the scientific literature. Emissions from crop residue burning in the CONUS have been found to impair local and regional air quality, leading to serious health impacts and legal disputes. Currently, there is no baseline estimate for the area and emissions of crop residue burning in the CONUS. A bottom-up model for emissions calculations is employed to calculate CO2, CO, CH4, NO2, SO2, PM2.5, PM10, and Pb emissions from crop residue burning in the CONUS for the years 2003 through 2007. These atmospheric species have negative impacts on air quality and human health and are important to the carbon cycle. Spatially and temporally explicit cropland burned area and crop type products for the CONUS, necessary for emissions calculations, are developed using remote sensing approaches. The majority of crop residue burning and emissions in the CONUS are shown to occur during the spring (April - June) and fall harvests (October - December). On average, 1,239,000 ha of croplands burn annually in the CONUS with an average interannual variability of ± 91,200 ha. In general, CONUS crop residue burning emissions vary less than ±10% interannually. The states of Arkansas, California, Florida, Idaho, Texas, and Washington emit 50% of PM10, 51% of CO2, 52% of CO, and 63% of PM2.5 from all crop residue burning in the CONUS. Florida alone emits 17% of all annual CO2, CO, and PM2.5 emissions and 12% of annual PM10 emissions from crop residue burning. Crop residue burning emissions in the CONUS account for as little as 1% of global agricultural emissions and as much as 15% of all agricultural burning emissions estimates in North America, including Mexico and Canada. The results have implications for international, federal, and state-level reporting and monitoring of air quality and greenhouse gas and carbon emissions aimed at protecting human health, mitigating climate change, and understanding the carbon cycle.Item Changes in Amazon Forest Structure from Land-Use Fires: Integrating Satellite Remote Sensing and Ecosystem Modeling(2008-11-17) Morton, Douglas; DeFries, Ruth S; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Fire is the dominant method of deforestation and agricultural maintenance in Amazonia, and these land-use fires frequently escape their intended boundaries and burn into adjacent forests. Initial understory fires may increase forest flammability, thereby creating a positive fire feedback and the potential for long-term changes in Amazon forest structure. The four studies in this dissertation describe the development and integration of satellite remote sensing and ecosystem modeling approaches to characterize land-use fires and their consequences in southern Amazon forests. The dissertation contributes three new methods: use of the local frequency of satellite-based active fire detections to distinguish between deforestation and maintenance fires, use of satellite data time series to identify canopy damage from understory fires, and development of a height-structured fire sub-model in Ecosystem Demography, an advanced ecosystem model, to evaluate the impacts of a positive fire feedback on forest structure and composition. Conclusions from the dissertation demonstrate that the expansion of mechanized agricultural production in southern Amazonia increased the frequency and duration of fire use compared to less intensive methods of deforestation for pasture. Based on this increase in the frequency of land-use fires, fire emissions from current deforestation may be higher than estimated for previous decades. Canopy damage from understory fires was widespread in both dry and wet years, suggesting that drought conditions may not be necessary to burn extensive areas of southern Amazon forests. Understory fires were five times more common in previously-burned than unburned forest, providing satellite-based evidence for a positive fire feedback in southern Amazonia. The impact of this positive fire feedback on forest structure and composition was assessed using the Ecosystem Demography model. Scenarios of continued understory fires under current climate conditions show the potential to trap forests in a fire-prone structure dominated by early-successional trees, similar to secondary forests, reducing net carbon storage by 20-46% within 100 years. In summary, satellite and model-based results from the dissertation demonstrate that fire-damaged forests are an extensive and long-term component of the frontier landscape in southern Amazonia and suggest that a positive fire feedback could maintain long-term changes in forest structure and composition in the region.Item Estimating High Spatial Resolution Clear-Sky Land Surface Longwave Radiation Budget from MODIS and GOES Data(2008-05-06) Wang, Wenhui; Liang, Shunlin; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The surface radiation budget (SRB) is important in addressing a variety of scientific and application issues related to climate trends, hydrological and biogeophysical modeling, and agriculture. The three longwave components of SRB are surface downwelling, upwelling, and net longwave radiation (LWDN, LWUP, and LWNT). Existing surface longwave radiation budget (SLRB) datasets have coarse spatial resolution and their accuracy needs to be greatly improved. This study develops new hybrid methods for estimating instantaneous clear-sky high spatial resolution land LWDN and LWUP from the Moderate Resolution Imaging Spectroradiometer (MODIS, 1km) and the Geostationary Operational Environmental Satellites (GOES, 2-10 km) data. The hybrid methods combine extensive radiation transfer (physical) and statistical analysis (statistical) and share the same general framework. LWNT is derived from LWDN and LWUP. This study is the first effort to estimate SLRB using MODIS 1 km data. The new hybrid methods are unique in at least two other aspects. First, the radiation transfer simulation accounted for land surface emissivity effect. Second, the surface pressure effect in LWDN was considered explicitly by incorporating surface elevation in the statistical models. Nonlinear models were developed using the simulated databases to estimate LWDN from MODIS TOA radiance and surface elevation. Artificial Neural Network (ANN) models were developed to estimate LWUP from MODIS TOA radiance. The LWDN and LWUP models can explain more than 93.6% and 99.6% of variations in the simulated databases, respectively. Preliminary study indicates that similar hybrid methods can be developed to estimate LWDN and LWUP from the current GOES-12 Sounder data and the future GOES-R data. The new hybrid methods and alternative methods were evaluated using two years of ground measurements at six validation sites from the Surface Radiation Budget Network (SURFRAD). Validation results indicate the hybrid methods outperform alternative methods. The mean RMSEs of MODIS-derived LWDN, LWUP, and LWNT using the hybrid methods are 16.88, 15.23, and 17.30 W/m2. The RMSEs of GOES-12 Sounder-derived LWDN and LWUP are smaller than 23.70 W/m2. The high spatial resolution MODIS and GOES SLRB derived in this study is more accurate than existing datasets and can be used to support high resolution numerical models.Item Fire Dynamics and Woody Cover Changes in the Serengeti-Mara Ecosystem 2000 to 2005 - A Remote Sensing Approach(2007-01-21) Dempewolf, Jan; DeFries, Ruth; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Serengeti-Mara savanna environment in East Africa is characterized by changing levels of woody cover and a dynamic fire regime. The relative proportion of woodland to grassland savanna affects animal habitat, biodiversity, and carbon storage, and is regulated by factors such as the fire regime (frequency, intensity, seasonality), and precipitation. The main objectives of this dissertation are to determine recent changes in woody cover at a regional scale and identify fire regimes and climate associated with these changes. Understanding these relationships is important for the assessment of future trajectories of woody cover under changing climate. Required spatially coherent data layers can only be obtained at the regional scale through the analysis of remote sensing data. Woody cover changes between 2000 and 2005 were derived from field data and a time series of MODIS satellite imagery at 500 m spatial resolution. Data layers on the controlling variables (fire frequency, seasonality, intensity and rainfall) were developed using a combination of remote sensing and model-based approaches. Burned areas were mapped using daily MODIS imagery at 250 m resolution. Outputs were used to make the requisite layers depicting fire frequency and seasonality. Fire intensity was derived using a model based on empirical relationships, mainly estimating fire fuel load as a function of rainfall and grazing. The combined data layers were analyzed using regression and decision tree techniques. Results suggest woody cover in central and northern Serengeti National Park continued to increase after 2000. Woody cover decreases were strongest in the wider Maswa Game Reserve area (MSW) under low precipitation conditions and late season burning. Woody cover losses in burned areas were also higher in the low fire frequency region of the Maasai Mara National Reserve (MNR). Fire seasonality was the most important fire regime parameter controlling woody cover in burned woodland savanna areas while fire intensity was most relevant for grassland savanna areas. Continued late season burning in drought years might cause further decrease of woody cover in MSW. MNR is expected to continue to be dominated by grassland savanna at similar fire frequency and browsing levels.Item A Direct Algorithm for Estimating Land Surface Broadband Albedos From MODIS Imagery(Institute of Electrical and Electronics Engineers, 2003-01) Liang, ShunlinLand surface albedo is a critical variable needed in land surface modeling. The conventional methods for estimating broadband albedos rely on a series of steps in the processing chain, including atmospheric correction, surface angular modeling, and narrowband-to-broadband albedo conversions. Unfortunately, errors associated with each procedure may be accumulated and significantly impact the accuracy of the final albedo products. In an earlier study, we developed a new direct procedure that links the top-of-atmosphere spectral albedos with land surface broadband albedos without performing atmospheric correction and other processes. In this paper, this method is further improved in several aspects and implemented using actual Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Several case studies indicated that this new method can predict land surface broadband albedos very accurately and eliminate aerosol effects effectively. It is very promising for global applications and is particularly suitable for nonvegetated land surfaces. Note that a Lambertian surface has been assumed in the radiative transfer simulation in this paper as a first-order approximation; this assumption can be easily removed as long as a global bidirectional reflectance distribution function climatology is available,Item Estimation of Systematic Errors of MODIS Thermal Infrared Bands(Institute of Electrical and Electronics Engineers, 2006-10) Liang, Shunlin; Liu, Ronggao G.; Liu, Jiyuan Y.This letter reports a statistical method to estimate detector-dependent systematic error in Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) Bands 20–25 and 27–36. There exist scan-to-scan overlapped pixels in MODIS data. By analyzing a sufficiently large amount of those most overlapped pixels, the systematic error of each detector in the TIR bands can be estimated. The results show that the Aqua MODIS data are generally better than the Terra MODIS data in 160 MODIS TIR detectors. There are no detector-dependent systematic errors in Bands 31 and 32 for both Terra and Aqua MODIS data. The maximum detector errors are 3.00 K in Band 21 of Terra and −8.15 K in that of Aqua for brightness temperatures of more than 250 K.Item Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 2. Validation(American Geophysical Union, 2003-03-08) Liang, Shunlin; Lucht, Wolfgang; Jin, Yufang; Schaaf, Crystal B.; Woodcock, Curtis E.; Gao, Feng; Li, XiaowenThe evaluation of the first available satellite-based global albedo product at 1-km resolution is essential for its application in climate studies. We evaluate the accuracy of the Moderate-Resolution Imaging Spectroradiometer (MODIS) albedo product using available field measurements at Surface Radiation Budget Network (SURFRAD) and Cloud and Radiation Testbed–Southern Great Plains (CART/SGP) stations and examine the consistency between the MODIS surface albedos and the Clouds and Earth’s Radiant Energy System (CERES) top-of-the-atmosphere albedos as well as historical global albedos from advanced very high resolution radiometer (AVHRR) and Earth Radiation Budget Experiment (ERBE) observations. A comparison with the field measurements shows that the MODIS surface albedo generally meets an absolute accuracy requirement of 0.02 for our study sites during April–September 2001, with the root mean square errors less than 0.018. Larger differences appear in the winter season probably due to the increased heterogeneity of surface reflectivity in the presence of snow. To examine the effect of spatial heterogeneity on the validation of the MODIS albedos using fine resolution field measurements, we derive an intermediate albedo product from four Landsat Enhanced Thematic Mapper Plus (ETM+) images at 30-m spatial resolution as a surrogate for the distributed field measurements. The surface albedo is relatively homogeneous over the study stations in growing seasons, and therefore the validation during April–September is supported. A case study over three SURFRAD stations reveals that the MODIS bidirectional reflectance distribution function model is able to capture the solar zenith angle dependence of surface albedo as shown by the field measurements. We also find that the MODIS surface shortwave albedo is consistent with the contemporary and collocated CERES top-of atmosphere albedos derived directly from broadband observations. The MODIS albedo is also well correlated with historical surface albedos derived from AVHRR and ERBE observations, and a high bias of 0.016 and a low bias of 0.034 compared to those of the latter albedos are reasonable considering the differences in instruments and retrieval algorithms as well as environmental changes.Item Consistency of MODIS surface BRDF/Albedo retrievals 1. Algorithm performance(American Geophysical Union, 2003-03-08) Liang, Shunlin; Jin, Yufang; Lucht, Wolfgang; Schaaf, Crystal B.; Gao, Feng; Li, Xiaowen; Strahler, Alan H.The first consistent year (November 2000 to November 2001) of global albedo product was produced at 1-km resolution every 16 days from the observations of the Moderate- Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA’s Terra spacecraft.We evaluated the quality of the operational albedo retrievals in two ways: (1) by examining the algorithm performance using the product quality assurance (QA) fields (this paper) and (2) by comparing retrieved albedos with those observed at ground stations and by other satellite instruments (in a companion paper). The internal diagnostics of the retrieval algorithm adequately reflect the goodness of the model fit and the random noise amplification in the retrieved albedo. Global QA statistics show that the RossThick- LiSparse-Reciprocal model fits the atmospherically corrected surface reflectances very well, and the random noise amplification factors for white sky albedo and reflectance are generally less than 1.0. Cloud obscuration is the main reason for the activation of the backup magnitude retrieval algorithm. Over the 60°S to 60°N latitude band, 50% of the land pixels acquire more than six clear looks during 14–29 September 2001, and only 5% of these pixels are inverted with the backup algorithm. The latitude dependence and temporal distribution of the QA fields further demonstrate that the retrieval status mainly follows the pattern of angular sampling determined by cloud climatology and the instrument/orbit characteristics. A case study over the west coast of the United States shows that white sky shortwave albedos retrieved from magnitude inversions agree on average with those from full inversions to within 0.033 in reflectance units and have a slightly lower bias ranging from 0.014 to 0.023. We also explored the effect of residual cloud and aerosol contamination in the atmospherically corrected surface reflectance inputs in another case study over southern Africa. The quality assurance procedure of the operational MODIS bidirectional reflectance distribution function and albedo algorithm compensates for some of these residual effects and improves the albedo retrieval results by an order of 0.005 (10%) in the visible for more than 12% of pixels.Item Mapping daily snow/ice shortwave broadband albedo from Moderate Resolution Imaging Spectroradiometer (MODIS): The improved direct retrieval algorithm and validation with Greenland in situ measurement(American Geophysical Union, 2005-05-26) Liang, Shunlin; Stroeve, Julienne; Box, Jason E.Snow/ice albedo is a critical variable in surface energy balance calculations. The Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used routinely to provide global land surface albedo. The MODIS algorithm includes atmospheric correction, surface reflectance angular modeling, and narrowband to broadband albedo conversion. In an earlier study, a "direct retrieval" methodology was proposed to calculate instantaneous albedo over snow and ice-covered surfaces directly from top-of-atmosphere (TOA) MODIS reflectance data. The method consists of extensive radiative transfer simulations for a variety of atmospheric and surface snow conditions and links the TOA reflectance with surface broadband albedo through regression analysis. Therefore the direct retrieval algorithm implicitly incorporates in a single step all three procedures used in the standard MODIS surface albedo algorithm. This study presents improvements to the retrieval algorithm including validation with in situ measurements distributed over the Greenland ice sheet. Comparison with surface observations demonstrates that the direct retrieval algorithm can produce very accurate daily snow/ice albedo with mean bias of less than 0.02 and residual standard error of 0.04.Item Continuous tree distribution in China: A comparison of two estimates from MODIS and Landsat data(American Geophysical Union, 2006-04-18) Liang, Shunlin; Liu, Ronggao; Liu, Jiyuan; Zhuang, DafangForest change is a major contributor to changes in carbon stocks and trace gas fluxes between terrestrial and atmospheric layers. This study compares two satellite estimates of percent tree distribution data sets over China. One estimate is from the Chinese National Land Cover Data Set (NLCD) generated by a multiyear national land cover project in China through visual interpretation of Landsat thematic mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) images primarily acquired in the year 2000. The other estimate is the Moderate-Resolution Imaging Spectroradiometer (MODIS) standard product (MOD44B) from the same year. The two products reveal some common features, but significant discrepancies exist. Detailed analyses are carried out with different land cover types and over different regions. Comparison results show that the difference of the total tree canopy area for the whole country is 159,000 km2. The pixel counts in the NLCD data set for dense forest are ~4 times those in the MODIS data set with the reverse holding for sparse forest. Generally, the percent tree canopy area of the NLCD data set is larger in eastern China and lower in the Tibetan plateau margin region. For different land cover types the percentage of tree canopy areas shows a good agreement for evergreen forests but a large discrepancy for deciduous forests. The largest variations are associated with grassland and nonvegetation classes. Regarding the spatial distributions of their differences, Inner Mongolia is the place where both data sets show a diverse result, but Guizhou and Fujian present the least divergence among those provinces with the tree canopy area being more than 20,000 km2.