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Meyer, H.; Lehnert, L.; Wang, Y.; Reudenbach, C.; Nauss, T. & Bendix, J. (2017): From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?. International Journal of Applied Earth Observation and Geoinformation 55, 21-31.
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DOI: 10.1016/j.jag.2016.10.001
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Abstract:
Abstract:
Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its
extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility
to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground
biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the appli-
cability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional
scales. Using machine learning techniques, it is tested whether the full hyperspectral information is
needed or if multispectral information is sufficient to accurately estimate pasture degradation prox-
ies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to
high resolution multispectral satellite data is assessed. 1183 hyperspectral measurements and vegeta-
tion records were performed at 18 locations on the QTP. Random Forests models with recursive feature
selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predic-
tors. Separate models were calculated using NBI from hyperspectral data as well as from the same data
resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared
to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and
AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral
measurements were used (cross validated R2 = 0.89). In contrast, errors in AGB estimations were consid-
erably higher (cross validated R2 = 0.32). Only small differences in accuracy were observed between the
models based on hyperspectral compared to multispectral data. The application of the models to satellite
images generally resulted in an increase of the estimation error. Though this reflects the challenge of
applying in situ measurements to satellite data, the results still show a high potential to map pasture
degradation proxies on the QTP. Thus, this study presents robust methodology to remotely detect and
monitor pasture degradation at high spatial resolutions.
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Keywords: |
biomass |
Tibetan Plateau |
Pasture degradation |
Hyperspectral measurements |
Random forests |
Qinghai-Tibet Plateau |
Regionalization |
Vegetation cover |
Fries, A. (2012): Implementation of new methods for the regionalization of climate data Philipps-University-Marburg, phd thesis
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Abstract:
Abstract:
The thermal structure of a megadiverse mountain ecosystem in southern Ecuador is examined on the basis of temperature measurements inside the natural mountain forest and at open sites along an altitudinal gradient from 1700m to 3200m. The data is used to calculated maps of monthly average minimum, mean and maximum 2m air temperature for the period 1999-2007, needed by ecological projects. The maps are generated by combining the straightforward detrending technique by using a Digital Elevation Model and satellite-based land cover classification. The results reveal a clear thermal differentiation over the year, partly triggered by the change of synoptic weather situation but also by land cover effects. Thermal amplitudes are particularly low during the main rainy season when cloudiness and air humidity are high but markedly pronounced in the relative dry season when daily irradiance and outgoing nocturnal radiation causes distinct differences between the land cover units. Particularly the lower pasture areas gained by slash and burn of the natural forest exhibit the most extreme thermal conditions while the atmosphere inside the mountain forest is slightly cooler due to the regulating effects of the dense vegetation. Thus, clearing the forest clearly reduces the thermal regulation function (regulating ecosystem services) of the ecosystem which might become problematic under future global warming.
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Keywords: |
Ecuador |
climate |
Regionalization |
air temperature |
thermal structure |