DOI: 10.1016/j.foreco.2016.05.047
Scopus记录号: 2-s2.0-84975528395
论文题名: Spatial interpolators for improving the mapping of carbon stock of the arboreal vegetation in Brazilian biomes of Atlantic forest and Savanna
作者: Scolforo H.F. ; Scolforo J.R.S. ; de Mello J.M. ; de Mello C.R. ; Morais V.A.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2016
卷: 376 起始页码: 24
结束页码: 35
语种: 英语
英文关键词: Exponential
; Geostatistics
; GIS
; Regression
Scopus关键词: Forestry
; Geographic information systems
; Mapping
; Regression analysis
; Vegetation
; Above-ground carbons
; Categorical variables
; Exponential
; Exponential semivariogram
; Geo-statistics
; Geographical models
; Regression
; Statistical criterion
; Interpolation
; arboreal species
; biome
; carbon sequestration
; data set
; geostatistics
; GIS
; kriging
; mapping method
; numerical model
; regression analysis
; savanna
; vegetation structure
; Atlantic Forest
; Brazil
; Minas Gerais
英文摘要: The aim of this study was to map aboveground carbon stock of arboreal vegetation in the Savanna and Atlantic forest biomes in Minas Gerais State, Brazil, in order to assess the best spatial technique for mapping. The dataset was obtained from 148 forest fragments of these biomes. The best form of mapping was based on statistical criteria and mapping quality. The exponential semivariogram model was selected for conducting the study. The geographical model developed in this study for regression-kriging application was fitted having as input longitude and biome variables, and, globally, has presented good spatial behavior of the carbon stock distributed along the Minas Gerais State. From mapping carbon stock by different techniques, it was found that regression-kriging mapping was the most efficient. In addition, as the semivariograms were fitted for each biome using kriging and co-kriging, it is possible to stand out the flexibility for using regression-kriging, including biome as a categorical variable in the geographical model. Another result was the high correlation found between different forms of mapping, which adds reliability for this study. Thus, it was concluded that the carbon stock distribution in the arboreal vegetation of these two biomes is spatially structured. Ordinary kriging and co-kriging have presented satisfactory results, however, regression-kriging has been more reliable for mapping and estimating carbon stock distribution, in the Minas Gerais State. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64809
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Forestry and Environmental Resources, North Carolina State University, 2820 Faucette Dr., Campus Box 8001, Raleigh, NC, United States; Department of Forest Science, Federal University of Lavras, Campus Universitario, LEMAF, Campus Box 3037, Lavras, Minas Gerais, Brazil; Department of Engineering, Federal University of Lavras, Campus Universitario, DEG, Campus Box 3037, Lavras, Minas Gerais, Brazil; Department of Forest Science, Mato Grosso State University, Rod. MT 208, KM 147 - Jardim Tropical, Campus Box 324, Alta Floresta, Mato Grosso, Brazil
Recommended Citation:
Scolforo H.F.,Scolforo J.R.S.,de Mello J.M.,et al. Spatial interpolators for improving the mapping of carbon stock of the arboreal vegetation in Brazilian biomes of Atlantic forest and Savanna[J]. Forest Ecology and Management,2016-01-01,376