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您的检索式：作者名="Edson Luis Bolfe"
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| 1 | Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon显示文摘Previous research has explored the potential to integrate lidar and optical data in aboveground biomass(AGB)estimation,but how different data sources,vegetation types,and modeling algorithms influence AGB estimation is poorly understood.This research conducts a comparative analysis of different data sources and modeling approaches in improving AGB estimation.RapidEye-based spectral responses and textures,lidar-derived metrics,and their combination were used to develop AGB estimation models.The results indicated that(1)overall,RapidEye data are not suitable for AGB estimation,but when AGB falls within 50–150 Mg/ha,support vector regression based on stratification of vegetation types provided good AGB estimation;(2)Lidar data provided stable and better estimations than RapidEye data;and stratification of vegetation types cannot improve estimation;(3)The combination of lidar and RapidEye data cannot provide better performance than lidar data alone;(4)AGB ranges affect the selection of the best AGB models,and a combination of different estimation results from the best model for each AGB range can improve AGB estimation;(5)This research implies that an optimal procedure for AGB estimation for a specific study exists,depending on the careful selection of data sources,modeling algorithms,forest types,and AGB ranges. | Yunyun Feng Dengsheng Lu Qi Chena Michael Keller Emilio Moran Maiza Nara dos-Santos Edson Luis Bolfe Mateus Batistella | 2017 | International Journal of Digital Earth2017，10，10： | 2 |
| 2 | Corn Water Variables Assessments from Earth Observation Data in the Sao Paulo State, Southeast Brazil显示文摘Landsat satellite images and agrometeorological data were used together for modelling the crop coefficient (Kc) in irrigation pivots composed by a mixture of corn hybrids from a commercial farm for grains and silage, located at the northwestern side of Sao Paulo state, Brazil. After developing relationships between Kc and the accumulated degree-days (DDac) and having yield data for 2012 available, they were applied in the whole state, to upscale the crop water variables, during the GS (growing seasons) of a second-harvest crop from March to August. Spatial thermohydrological differences among the main corn growing regions were clear. The largest CWP (crop water productivity) values and SD (standard deviations) were for Itapetininga with an average value of 1.60 ± 0.43 kg m-3, while the lowest ones were for Presidente Prudente (0.81±0.21 kg m-3). As corn is important for these growing regions, being inside of the priorities from the Brazilian Ministry of Agriculture, these results should be considered for a rational exploration, including both, irrigation and rainfed conditions, as the actual water scarcity can bring much competition with other non-agricultural sectors. | Antonio Heriberto de Castro Teixeira Femando Braz Tangerino Hemandez Ricardo Guimaraes Andrade Janice Freitas Leivas Daniel de Castro Victoria Edson Luis Bolfe | 2015 | Journal of Hydraulic Engineering2015，1，1： | 0 |
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