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Hyper-temporal remote sensing helps in relating epiphyllous liverworts and evergreen forests.

Authors :
Jiang, Yanbin
Bie, C.A.J.M.
Wang, Tiejun
Skidmore, A.K.
Liu, Xuehua
Song, Shanshan
Shao, Xiaoming
Rocchini, Duccio
Source :
Journal of Vegetation Science; Mar2013, Vol. 24 Issue 2, p214-226, 13p
Publication Year :
2013

Abstract

Question Is there, at the macro-habitat scale, a relationship between the fraction of evergreen forests and the presence probability of epiphyllous liverworts? Can these two parameters be estimated and mapped using an NDVI-based indicator that is derived from time-series of SPOT- VGT imagery? Location Southern China. Methods Applying the ISODATA algorithm, we classified SPOT- VGT NDVI time-series imagery and produced an NDVI map at 1-km<superscript>2</superscript> resolution containing 128 NDVI classes. That map and the National Land Cover Map of China (2000) were used to prepare a scheme for field sampling. For 537 1-km<superscript>2</superscript> areas, located in 19 blocks of 100 km × 100 km, field data were collected. They represented 51 preselected NDVI classes that were assumed to contain evergreen forests. Data on the fractions of forest and evergreen forest, the fraction of evergreen forest in forest present and presence probability of epiphyllous liverworts were regressed against different NDVI class-specific indicators by means of weighted least-squares regression ( WLSR). Results The SPOT- VGT NDVI for March was found to best explain the variation between 1-km<superscript>2</superscript> areas in the presence probability of epiphyllous liverworts ( R<superscript>2</superscript> = 0.64; linear relationship; RMSE = 0.38) as the area fraction (%) of evergreen forest ( R<superscript>2</superscript> = 0.90; exponential relationship; RMSE = 6.1%). Epiphyllous liverworts were only found within 1-km<superscript>2</superscript> areas when the SPOT- VGT NDVI value for March was more than 0.50 (model estimate: 0.43 ± 0.20) and the fraction of evergreen forest in 1 km<superscript>2</superscript> was above 14% (model estimate: 5 ± 35%). The estimation errors (with 95% confidence interval) of these two relationships were calculated using a bootstrap resampling method with 1000 replications; they were, respectively, 0.49-0.76 and 0.85-0.94 for R<superscript>2</superscript>, and 0.11-0.23 and 5.2-11.9% for RMSE. Other positive relationships were found between the presence probability of epiphyllous liverworts and the fraction of evergreen forest ( R<superscript>2</superscript> = 0.64, linear relationship; RMSE = 0.38) and between the fraction of evergreen forest and forest within 1-km<superscript>2</superscript> areas ( R<superscript>2</superscript> = 0.80, linear relationship; RMSE = 29%). Conclusion We show that for southern China, the fraction of evergreen forest and the presence probability of epiphyllous liverworts can directly be inferred by making use of SPOT- VGT NDVI imagery. The findings are fully consistent with earlier reported hotspots for epiphyllous liverworts. At the macro-habitat scale, the presence probability of epiphyllous liverworts proved quantitatively related to the fraction of evergreen forest. This suggests causal relationships with patch size and/or rainfall patterns. We believe that the derived maps may serve as a foundation for a range of further studies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11009233
Volume :
24
Issue :
2
Database :
Complementary Index
Journal :
Journal of Vegetation Science
Publication Type :
Academic Journal
Accession number :
85040569
Full Text :
https://doi.org/10.1111/j.1654-1103.2012.01453.x