Laboratory for
Climatology and Remote Sensing

Abstract:

Hyperspectral imaging (HSI) is increasingly gaining acceptance in the medical field. Up until now, HSI has been used in conjunction with rigid endoscopy to detect cancer in vivo. The logical next step is to pair HSI with flexible endoscopy, since it improves access to hard-to-reach areas. While the flexible endoscope’s fiber optic cables provide the advantage of flexibility, they also introduce an interfering honeycomb-like pattern onto images. Due to the substantial impact this pattern has on locating cancerous tissue, it must be removed before the HS data can be further processed. Thereby, the loss of information is to minimize avoiding the suppression of small-area variations of pixel values. We have developed a system that uses flexible endoscopy to record HS cubes of the larynx and designed a special filtering technique to remove the honeycomb-like pattern with minimal loss of information. We have confirmed its feasibility by comparing it to conventional filtering techniques using an objective metric and by applying unsupervised and supervised classifications to raw and pre-processed HS cubes. Compared to conventional techniques, our method successfully removes the honeycomb-like pattern and considerably improves classification performance, while preserving image details.

Abstract:

High landscape diversity is assumed to increase the number and level of ecosystem services. However, the interactions between ecosystem service provision, disturbance and landscape composition are poorly understood. Here we present a novel approach to include uncertainty in the optimization of land allocation for improving the provision of multiple ecosystem services. We refer to the rehabilitation of abandoned agricultural lands in Ecuador including two types of both afforestation and pasture rehabilitation, together with a succession option. Our results show that high compositional landscape diversity supports multiple ecosystem services (multifunction effect). This implicitly provides a buffer against uncertainty. Our work shows that active integration of uncertainty is only important when optimizing single or highly correlated ecosystem services and that the multifunction effect on landscape diversity is stronger than the uncertainty effect. This is an important insight to support a land-use planning based on ecosystem services.

Abstract:

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of global climate change. The rising atmospheric carbon dioxide (CO2 ) concentrations may stimulate plant photosynthesis and, thus, cause a net sink effect in the global carbon cycle. As a consequence of an enhanced photosynthesis, an increase in the net primary productivity (NPP) of C3 plants (termed CO2 fertilization) is widely assumed. This process is associated with a reduced stomatal conductance of leaves as the carbon demand of photosynthesis is met earlier. This causes a higher water-use efficiency and, hence, may reduce water stress in plants exposed to elevated CO2 concentrations ([eCO2 ]). However, the magnitude and persistence of the CO2 fertilization effect under a future climate including more frequent weather extremes are controversial. To test the CO2 fertilization effect for Central European grasslands, a data set comprising 16 years of biomass samples and environmental variables such as local weather and soil conditions was analysed by means of a novel approach. The data set was recorded on a “Free Air Carbon dioxide Enrichment” (FACE) experimental site which allows to quantify the CO2 fertilization effect under naturally occurring climate variations. The results indicate that the CO2 fertilization effect on the aboveground biomass is strongest under local average environmental conditions. Such intermediate regimes were defined by the mean +/- 1 standard deviation of the long-term average in the respective variable three months before harvest. The observed CO2 fertilization effect was reduced or vanished under drier, wetter and hotter conditions when the respective variable exceeded the bounds of the intermediate regimes. Comparable conditions, characterized by a higher frequency of more extreme weather conditions, are predicted for the future by climate projections. Consequently, biogeochemical models may overestimate the future NPP sink capacity of temperate C3 grasslands. Because temperate grasslands represent an important part of the Earth’s terrestrial surface and therefore the global carbon cycle, atmospheric CO2 concentrations [CO2 ] might increase faster than currently expected.

Abstract:

Technical development during the last two decades has brought new potential and new applications for mobile measurements. In this paper, we present six case studies where mobile measurement devices were used to acquire data for meteorological and climatological research. Three case studies deal with groundbased mobile measurements – on buses for urban climate measurements and on a vessel on a lake – and three with airborne platforms – on a cable car and on an unmanned aerial vehicle for vertical soundings and on a tethered balloon sonde for cloud physics. For each study, we describe the measurement set-up and address the potential and drawbacks of these applications. At the end, we discuss general aspects related to mobile observations especially concerning the time and space dimension of measurements.

Abstract:

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ? 40, classification errors significantly increase.

Abstract:

The relationship between canopy-level evapotranspiration (ETSci) and leaf-level transpiration (Tleaf) as well as photosynthesis (Pleaf) for a homogeneous tropical montane pasture was analyzed over five days using a combination of methods involving a laser scintillometer and a porometer. Weather conditions ranged from overcast to sunny during the period of study. The gas exchange of the leaves of the dominant pasture grass Setaria sphacelata (transpiration vs. photosynthetic CO2 net uptake ) was measured with a porometer and physiologically interpreted on the background of microclimate variables (photosynthetic active radiation (PAR) as proxy for total light intensity, temperature, water vapor deficit of the air) and soil moisture data. Water use efficiency (WUE, photosynthetic CO2 net uptake vs water loss by leaf transpiration) of the pasture was used to analyze the grass’ range of response to the environmental variables of the research area. PAR and water vapor deficit of the air (VPD) appeared to be the determinant factors for Tleaf and ETSci. WUE for the Setaria sphacelata pasture ranged from 1.9 to 5.8 µmol CO2 mmol-1 H20 day-1 and is particularly low during periods of high VPD combined with enhanced insolation during cloudless periods. ET measurements collected by the scintillometer demonstrated a strong correlation with water flux calculated using the Penman-Monteith approach (TPM) (r² = 0.95). Also, Tleaf measured with the porometer showed reasonable coincidence with the ET observations (r² = 0.78). Values of ETSci ranged from 2.26 to 4.96 mm day-1 and Tleaf ranged from 0.83 to 2.41 mm day-1, but only ETSci showed good correspondence with the available energy (net radiation). The lower correlation between Tleaf and canopy-level ETSci compared to that between ETSci and TPM was tested against contaminations from the adjacent fetch area of the scintillometer path, but no effects were found. Likewise, soil water limitations of Tleaf could be ruled out. Therefore, different correlations of ETSci and Tleaf with the incoming energy and VPD may be traced back to a direct effect of the VPD on ET in contrast to its indirect effect on Tleaf which is additionally regulated by physiological processes in the leaf stomata.

Abstract:

Ecosystems worldwide are threatened by the increasing impact of land use and climate change. To protect their diversity and functionality, spatially explicit monitoring systems are needed. In remote areas, monitoring is difficult and recurrent field surveys are costly. By using Lidar or the more cost-effective and repetitive optical satellite data, remote sensing could provide proxies for habitat structure supporting measures for the conservation of biodiversity. Here we compared the explanatory power of both, airborne Lidar and optical satellite data in modeling the spatial distribution of biodiversity of birds across a complex tropical mountain forest ecosystem in southeastern Ecuador. Weused data fromfield surveys of birds and chose three measures as proxies for different aspects of diversity: (i) Shannon diversity as a measure of ?-diversity that also includes the relative abundance of species, (ii) phylodiversity as a first proxy for functional diversity, and (iii) community composition as a proxy for combined ?- and ?-diversity.We modeled these diversity estimates using partial least-square regression of Lidar and optical texturemetrics separately and compared themodels using a leave-one-out validated R2 and root mean square error. Bird community information was best predicted by both remote sensing datasets, followed by Shannon diversity and phylodiversity. Our findings reveal a high potential of optical texture metrics for predicting Shannon diversity and a measure of community composition, but not for modeling phylodiversity. Generalizing from the investigated tropical mountain ecosystem,we conclude that texture information retrieved from multispectral data of operational satellite systems could replace costly airborne laser-scanning for modeling certain aspects of biodiversity.

Abstract:

Understanding of evapotranspiration (ET) processes over Andean mountain environments is crucial, particularly due to the importance of these regions to deliver water-related ecosystem services. In this context, the detection of spatio-temporal changes in ET remains poorly investigated for specific Andean ecosystems, like the páramo. To overcome this lack of knowledge, we implemented the energy-balance model METRIC with Landsat 7 ETM+ and MODIS-Terra imagery for a páramo catchment. The implementation contemplated adjustments for complex terrain in order to obtain daily, monthly and annual ET maps (between 2013 and 2014). In addition, we compared our results to the global ET product MOD16. Finally, a rigorous validation of the outputs was conducted with residual ET from the water balance. ET retrievals from METRIC (Landsat-based) showed good agreement with the validation-related ET at monthly and annual steps (mean bias error <8 mm·month?1 and annual deviation <17%). However, METRIC (MODIS-based) outputs and the MOD16 product were revealed to be unsuitable for our study due to the low spatial resolution. At last, the plausibility of METRIC to obtain spatial ET retrievals using higher resolution satellite data is demonstrated, which constitutes the first contribution to the understanding of spatially-explicit ET over an alpine catchment in the neo-tropical Andes.

Abstract:

Phylogenetic niche conservatism (PNC) is the tendency of species within a clade to retain ancestral traits and to persist in their primary ecological niches on geological time scales. It links evolutionary and ecological processes and has been hypothesized to explain patterns of species richness and the composition of species assemblages. Decreasing patterns of species richness along latitudinal gradients were often explained by the combination of ancient tropical climates, trait retention of tropical lineages and environmental filtering. PNC also predicts decreasing phylodiversity and family age with decreasing tropicality and has been invoked to explain these patterns along climatic gradients across latitudinal as well as elevational gradients. However, recent studies on tree assemblages along latitudinal and elevational gradients in South America found patterns contradicting the PNC framework. Our study aims to shed light on these contradictions using three different metrics of the phylogenetic composition that form a gradient from recent evolutionary history to deep phylogenetic relationships. We analyzed the relationships between elevation and taxonomic species richness, phylodiversity and family age of tree assemblages in Andean rainforests in Ecuador. In contrast to predictions of the PNC we found no associations of elevation with species richness of trees and increasing clade level phylodiversity and family age of the tree assemblages with elevation. Interestingly, we found that patterns of phylodiversity across the studied elevation gradient depended especially on the deep nodes in the phylogeny. We therefore suggest that the dispersal of evolutionarily old plant lineages with extra-tropical origins influences the recent composition of tree assemblages in the Andes. Further studies spanning broader ecological gradients and using better resolved phylogenies to estimate family and species ages are needed to obtain a deeper mechanistic understanding of the processes that drive the assembly of tree communities along elevational gradients.

Abstract:

Mountain regions worldwide present a pronounced spatiotemporal precipitation variability, which added to scarce monitoring networks limits our understanding of the generation processes involved. To improve our understanding of clouds and precipitation dynamics and cross-scale generation processes in mountain regions, we analyzed spatiotemporal rainfall patterns using satellite cloud products (SCP) in the Paute basin (900–4200m a.s.l. and 6481 km2) in the Andes of Ecuador. Precipitation models, using SCP and GIS data, reveal the spatial extension of three regimes: a three-modal (TM) regime present across the basin, a bimodal (BM) regime, along sheltered valleys, and a unimodal (UM) regime at windward slopes of the eastern cordillera. Subsequently, the spatiotemporal analysis using synoptic information shows that the dry season of the BM regime during boreal summer is caused by strong subsidence inhibiting convective clouds formation.Meanwhile, in UMregions, low advective shallow cap clouds mainly cause precipitation, influenced by water vapor from the Amazon and enhanced easterlies during boreal summer. TM regions are transition zones fromUMto BMand zones on the windward slopes of the western cordillera. These results highlight the suitability of satellite and GIS data-driven statistical models to study spatiotemporal rainfall seasonality and generation processes in complex terrain, as the Andes.

Abstract:

BACKGROUND: Early detection of cancerous lesions is still crucial for a patient's prognosis. Although diagnostic access to the oral cavity and oropharynx is comparably easy, the incidence of resulting disease remains high. This is due to the fact that in many cases, malignity is recognized too late on a purely visual basis. Previously, we discussed the application of hyperspectral imaging for early detection of precancerous and cancerous lesions of the larynx. This time, we evaluate the method in the oral cavity and oropharynx. MATERIALS AND METHODS: In 85 patients scheduled for endoscopy, hyperspectral imaging was performed. We used a rigid 0-degree endoscope, a light-adjustable monochromator, and a hyperspectral camera. For evaluation of the method, 3 patients were chosen exemplarily. Training sites from physiological and cancerous tissues were marked. Hyperspectral data from 1 patient were used to train a classifier, which was then used for automatic detection of precancerous and cancerous lesions in another 2 patients. RESULTS: Intraoperative hyperspectral imaging was performed without any problems. Classification showed sensitivities of 61 and 43%, and a specificity of 100%. CONCLUSION: This proof-of-concept study underscores the high potential of hyperspectral imaging for early recognition of cancer in the mouth and oropharynx. Besides a better prognosis for cancer patients, this approach could lead to higher cost efficiency in the health system.

Abstract:

Precipitation events are the main driving force for hydrological processes; for this reason, correctly compiling the distribution of precipitation in the study area is given high priority. Therefore, three models for assessing precipitation were implemented in DANUBIA: a mesoscale atmosphere model, an interpolation model based on station data and a satellite-supported rainfall retrieval. The satellite-based derivation of precipitation takes place using data from the European Meteosat system. In a first step, the boundaries of the raining cloud areas are delineated. Second, the precipitation rate is assigned considering the precipitation processes identified before. Comparing monthly mean precipitation in the study area for 1999 based on the atmospheric model, the interpolation method and the satellite-based technique reveal shortcomings in identifying stratiform precipitation for the satellite method. On the other hand, weather models have slight weaknesses in calculating convective precipitation. Further results show the average number of storm days from May to September between 1995 and 1999 derived using the satellite retrieval technique. The frequency distribution indicates the expected midsummer maximum in July and reveals an increase in thunderstorm frequency caused by orography within the drainage basin.

Abstract:

Operational nowcasting techniques for sea fog over the Yellow Sea rely on data from weather satellites because ground-based observations are hardly available. While there are several algorithms for detecting low stratus (LST) that are applicable to geostationary weather satellite data, sea fog retrieval is more complicated. These schemes mostly need ancillary data such as Cloud Optical Thickness (COT) and Droplet Effective Radius (DER). To retrieve the necessary parameters for sea fog detection over the Yellow Sea, the Comprehensive Analysis Program for Cloud Optical Measurement (CAPCOM) scheme developed by Kawamoto et al. (2001) was adapted to the Japanese Multifunctional Transport Satellites (MTSAT) system-Japanese Advanced Meteorological Imager (JAMI). COT and DER values were then retrieved for 64 cases over the Yellow Sea (= 85,000 LST pixels) and compared with the COT and DER products from the MYD06/MOD06, CAPCOM-MODIS (Moderate Resolution Imaging Spectroradiometer) and CloudSat (cloud radar). Results showed that the COT and DER values retrieved from JAMI were satisfactory. The MTSAT-2 JAMI data delivered better COT values than the MTSAT-1R JAMI data, due to the re-calibration of MTSAT-2 JAMI’s visible (VIS) band in 2011. Similarly, improvements were seen in DER retrieval, even though the VIS re-calibration primarily affects COT retrieval. By comparing the difference in stratus thickness calculated by MTSAT-1R and MTSAT-2, the COT and DER retrieved from MTSAT-2 JAMI can be used in ground fog retrieval schemes. These values exhibit less bias, especially in cases involving high cloud top and thin cloud thickness. Both the COT and DER retrievals from MTSAT-2 JAMI offer potential as reliable parameters for Yellow Sea fog detection.

Abstract:

Quality control is a particularly demanding problem for micrometeorological studies in complex environments. With the transition to electronic sensing and storage of climate data in high temporal resolution, traditional approaches of homogenization are insufficient for addressing the small-scale variability and spatial heterogeneity of the data. This problem can be successfully addressed by introducing a new class of control procedures based on the physical and climatological relations between different climate variables. The new approach utilizes knowledge about the interdependency of air temperature, precipitation, radiation, relative air humidity, cloud cover and visibility to develop empirical functions for determining the probability margins for the co-occurrence of specific conditions in tropical mountains and deserts. It can also be applied to other geographic settings by adjusting the parameters derived from the data itself. All procedures are integrated into a processing chain with feedback loops and combined with conventional logical and statistical checks, which enables it to detect small errors that normally pass unnoticed. The algorithms are also adapted to incorporate the short time steps of the original data to retain the potential for detailed process analyses.

Abstract:

A new rainfall retrieval technique for determining rainfall rates in a continuous manner (day, twilight, and night) resulting in a 24-h estimation applicable to midlatitudes is presented. The approach is based on satellite-derived information on cloud-top height, cloud-top temperature, cloud phase, and cloud water path retrieved from Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and uses the random forests (RF) machine-learning algorithm. The technique is realized in three steps: (i) precipitating cloud areas are identified, (ii) the areas are separated into convective and advective-stratiform precipitating areas, and (iii) rainfall rates are assigned separately to the convective and advective-stratiform precipitating areas. Validation studies were carried out for each individual step as well as for the overall procedure using collocated ground-based radar data. Regarding each individual step, the models for rain area and convective precipitation detection produce good results. Both retrieval steps show a general tendency toward elevated prediction skill during summer months and daytime. The RF models for rainfall-rate assignment exhibit similar performance patterns, yet it is noteworthy how well the model is able to predict rainfall rates during nighttime and twilight. The performance of the overall procedure shows a very promising potential to estimate rainfall rates at high temporal and spatial resolutions in an automated manner. The near-real-time continuous applicability of the technique with acceptable prediction performances at 3–8-hourly intervals is particularly remarkable. This provides a very promising basis for future investigations into precipitation estimation based on machine-learning approaches and MSG SEVIRI data.

Abstract:

The relationship between satellite-derived low cloud frequency and the occurrence of tropical montane cloud forest (TMCF) in Taiwan was investigated. From daily MODIS cloud mask products between 2003 and 2012 the low cloud class was extracted and mean low cloud frequency was calculated for Taiwan. This low cloud frequency map was blended with an existing plot-based vegetation classification for Taiwan to analyze the relationship between low cloud frequency and TMCF occurrence. Receiver operating characteristics curves and the area under the ROC curve (AUC) were used to analyze if a relationship exists. No relationship was found for all four TMCF types taken together (AUC = 0.61) and for the dominant TMCF type, Quercus montane evergreen broad-leaved cloud forest (AUC = 0.5). Strong relationships were found for the two spatially-restricted TMCF types, Fagus montane deciduous broad-leaved cloud forest (AUC = 0.91) and Pasania-Elaeocarpus montane evergreen broad-leaved forest (AUC = 0.84), as well as for the second dominant type Chamaecyparis montane mixed cloud forest (AUC = 0.74). The results show that low cloud frequency thresholds might be associated with specific cloud forest types in Taiwan. Further studies should incorporate information about cloud base height, cloud density, and cloud immersion time as well as satellite-based cloud frequency information with a higher temporal resolution. Combination with satellite-based land cover classifications for Taiwan would allow quasi-continuous observation of TMCF changes. Such knowledge would be the precondition for effective protective actions concerning this exceptional but threatened ecosystem.