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008			151021t2009 xxu||||| |||| 00| 0 eng d
040			_aCR-TuBCO _cCR-TuBCO _bEspañol
041			_aeng
100	1		_999311 _aNieschelze, J.
100	1		_965164 _aErasmi, S.
100	1		_962655 _aDietz, J.
100	1		_978518 _aHolscher, D. _eautores/as
245	1	0	_aSatellite-based prediction of rainfall interception by tropical forest stands of a human-dominated landscape in Central Sulawesi, Indonesia
260			_aAmsterdam (Países Bajos): _bELSEVIER, _c2009
270			_aSan José, C.R.
300			_a9 páginas: _b4 figuras, 3 tablas
504			_aIncluye 62 referencias bibliográficas en las páginas 234-235
520			_aRainforest conversion to other land use types drastically alters the hydrological cycle in which changes in rainfall interception contribute significantly to the observed differences. However, little is known about the effects of more gradual changes in forest structure and at regional scales. We studied land use types ranging from natural forest over selectively-logged forest to cacao agroforest in a lower montane region in Central Sulawesi, Indonesia, and tested the suitability of high-resolution optical satellite imagery for modeling observed interception patterns. Investigated characteristics indicating canopy structure were mean and standard deviation of reflectance values, local maxima, and self-similarity measures based on the grey level co-occurrence matrix and geostatistical variogram analysis. Previously studied and published rainfall interception data comprised twelve plots and median values per land use type ranged from 30% in natural forest to 18% in cacao agroforests. A linear regression model with local maxima, mean contrast and normalized digital vegetation index (NDVI) as regressors was able to explain more than 84% (R2 adj) of the variation encountered in the data. Other investigated characteristics did not prove significant in the regression analysis. The model yielded stable results with respect to cross-validation and also produced realistic values and spatial patterns when applied at the landscape level (783.6 ha). High values of interception were rare and localized in natural forest stands distant to villages, whereas low interception characterized the intensively used sites close to settlements. We conclude that forest use intensity significantly reduced rainfall interception and satellite image analysis can successfully be applied for its regional prediction, and most forest in the study region has already been subject to human-induced structural changes.
650	1	0	_9164594 _aSILVICULTURA
650	1	4	_9151105 _aINDICE DE SUPERFICIE FOLIAR
650	1	0	_9142878 _aCUBIERTA DE COPAS
650	1	0	_9166634 _aTEXTURA
650	1	0	_9160794 _aPRONOSTICO DEL TIEMPO
650	1	0	_9157103 _aPAISAJE AGRICOLA
650	1	0	_9138300 _aBOSQUE TROPICAL
691			_aINDONESIA
773	0		_tJournal of Hydrology (Indonesia) _gVolumen 364, números 3-4, páginas 227-235 _d(2009)
856	4	0	_uhttps://doi.org/10.1016/j.jhydrol.2008.10.024 _qpdf _yeng
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906			_a20091204 _b20110714
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