DOI: 10.1016/j.jag.2014.01.020
Scopus记录号: 2-s2.0-84897545250
论文题名: Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data
作者: Churches C ; E ; , Wampler P ; J ; , Sun W ; , Smith A ; J
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 30, 期: 1 起始页码: 203
结束页码: 216
语种: 英语
英文关键词: Deforestation
; FAO
; Fuzzy classification
; Image normalization
; Land cover
; Supervised classification
Scopus关键词: accuracy assessment
; data set
; deforestation
; Food and Agricultural Organization
; forest cover
; fuzzy mathematics
; image analysis
; image classification
; Landsat thematic mapper
; Haiti
英文摘要: This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. The thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons (PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCD12Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS)) were reclassified and compared. According to our classification, approximately 32.3% of Haiti's total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO's forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for three other recoded datasets: MCD12Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti's forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2 = 0.996 for tree cover) between spatial resolution and land cover estimates. © 2014 The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79733
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Geology Department, Grand Valley State University, 1 Campus Drive, Allendale, MI 49401, United States; Geography and Planning Department, Grand Valley State University, 1 Campus Drive, Allendale, MI 49401, United States; Natural Resources Management Department, Grand Valley State University, 1 Campus Drive, Allendale, MI 49401, United States
Recommended Citation:
Churches C,E,, Wampler P,et al. Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,30(1)