Environmental Geodesy: state of the art

With ever increasing global population, intense pressure is being exerted on the Earth’s resources leading to severe changes in its land cover (e. g., deforestation), diminishing biodiversity and natural habitats, dwindling freshwater supplies, and changing weather and climatic patterns (e. g., global warming, changing sea level). Environmental monitoring techniques that provide such information are under scrutiny from an increasingly environmentally conscious society that demands the efficient delivery of such information at a minimal cost. Environmental changes vary both spatially and temporally, thereby putting pressure on traditional methods of data acquisition, some of which are very labour intensive, such as animal tracking for conservation purposes. With these challenges, conventional monitoring techniques, particularly those that record spatial changes call for more sophisticated approaches that deliver the necessary information at an affordable cost. One direction being followed in the development of such techniques involves Environmental Geodesy, which can act as stand-alone method, or to complement traditional methods. This contribution looks at its current state of the art

Hybrid symbolic-numeric methods in geosciences

Modern computing systems, like Mathematica, are blending numeric and symbolic evaluation of many algorithms improving their efficiencies (time, accuracy). In this contribution three toy-examples of the application of hybrid symbolic-numeric computations in geosciences are presented in order to illustrate the features of this advanced technique, namely: ranging GNSS satellites, computing GNSS cycle ambiguities and employing symbolic regression for verifying Kepler’s third law

Decadal rainfall variability modes in observed rainfall records over East Africa and their relations to historical sea surface temperature changes.

Detailed knowledge about the long-term interface of climate and rainfall variability is essential for managing agricultural activities in Eastern African countries. To this end, the space-time patterns of decadal rainfall variability modes over East Africa and their predictability potentials using Sea Surface Temperature (SST) are investigated. The analysis includes observed rainfall data from 1920-2004 and global SSTs for the period 1950-2004. Simple correlation, trend and cyclical analyses, Principal Component Analysis (PCA) with VARIMAX rotation and Canonical Correlation Analysis (CCA) are employed. The results show decadal signals in filtered observed rainfall record with 10 years period during March - May (MAM) and October – December (OND) seasons. During June - August (JJA), however, cycles with 20 years period are common. Too much / little rainfall received in one or two years determines the general trend of the decadal mean rainfall. CCA results for MAM showed significant positive correlations between the VARIMAX-PCA of SST and the canonical component time series over the central equatorial Indian Ocean. Positive loadings were spread over the coastal and Lake Victoria regions while negative loading over the rest of the region with significant canonical correlation skills. For the JJA seasons, Atlantic SSTs had negative loadings centred on the tropical western Atlantic Ocean associated with the wet / dry regimes over western / eastern sectors. The highest canonical correlation skill between OND rainfall and the Pacific SSTs showed that El Niño-Southern Oscillation (ENSO)/La Niña phases are associated with wet/dry decades over the region

The influence of low frequency sea surface temperature modes on delineated decadal rainfall zones in Eastern Africa region

Influence of low frequency global Sea Surface Temperatures (SSTs) modes on decadal rainfall modes over Eastern Africa region is investigated. Fore-knowledge of rainfall distribution at decadal time scale in specific zones is critical for planning purposes. Both rainfall and SST data that covers a period of 1950–2008 were subjected to a ‘low-pass filter’ in order to suppress the high frequency oscillations. VARIMAX-Rotated Principal Component Analysis (RPCA) was employed to delineate the region into decadal rainfall zones while Singular Value Decomposition (SVD) techniques was used to examine potential linkages of these zones to various areas of the tropical global oceans. Ten-year distinct decadal signals, significant at 95% confidence level, are dominant when observed in-situ rainfall time series are subjected to spectral analysis. The presence of variability at El Niño Southern Oscillation (ENSO)-related timescales, combined with influences in the 10–12 year and 16–20 year bands were also prevalent. Nine and seven homogeneous decadal rainfall zones for long rainfall season i.e. March-May (MAM) and the short rainfall season i.e. October-December (OND), respectively, are delineated. The third season of June–August (JJA), which is mainly experienced in western and Coastal sub-regions had eight homogenous zones delineated. The forcing of decadal rainfall in the region is linked to the equatorial central Pacific Ocean, the tropical and South Atlantic Oceans, and the Southwest Indian Ocean. The high variability of these modes highlighted the significant roles of all the global oceans in forcing decadal rainfall variability over the region

Solving geoinformatics parametric polynomial systems using the improved Dixon resultant

Improvements in computational and observational technologies in geoinformatics, e.g., the use of laser scanners that produce huge point cloud data sets, or the proliferation of global navigation satellite systems (GNSS) and unmanned aircraft vehicles (UAVs), have brought with them the challenges of handling and processing this “big data”. These call for improvement or development of better processing algorithms. One way to do that is integration of symbolically presolved sub-algorithms to speed up computations. Using examples of interest from real geoinformatic problems, we will discuss the Dixon-EDF resultant as an improved resultant method for the symbolic solution of parametric polynomial systems. We will briefly describe the method itself, then discuss geoinformatics problems arising in minimum distance mapping (MDM), parameter transformations, and pose estimation essential for resection. Dixon-EDF is then compared to older notions of “Dixon resultant”, and to several respected implementations of Gröbner bases algorithms on several systems. The improved algorithm, Dixon-EDF, is found to be greatly superior, usually by orders of magnitude, in both CPU usage and RAM usage. It can solve geoinformatics problems on which the other methods fail, making symbolic solution of parametric systems feasible for many problems

Interannual variability of temperature in the UTLS region over Ganges–Brahmaputra–Meghna river basin based on COSMIC GNSS RO data

Poor reliability of radiosonde records across South Asia imposes serious challenges in understanding the structure of upper-tropospheric and lower-stratospheric (UTLS) region. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission launched in April 2006 has overcome many observational limitations inherent in conventional atmospheric sounding instruments. This study examines the interannual variability of UTLS temperature over the Ganges–Brahmaputra–Meghna (GBM) river basin in South Asia using monthly averaged COSMIC radio occultation (RO) data, together with two global reanalyses. Comparisons between August 2006 and December 2013 indicate that MERRA (Modern-Era Retrospective Analysis for Research Application) and ERA-Interim (European Centre for Medium-Range Weather Forecasts reanalysis) are warmer than COSMIC RO data by 2 °C between 200 and 50 hPa levels. These warm biases with respect to COSMIC RO data are found to be consistent over time. The UTLS temperature show considerable interannual variability from 2006 to 2013 in addition to warming (cooling) trends in the troposphere (stratosphere). The cold (warm) anomalies in the upper troposphere (tropopause region) are found to be associated with warm ENSO (El Niño–Southern Oscillation) phase, while quasi-biennial oscillation (QBO) is negatively (positively) correlated with temperature anomalies at 70 hPa (50 hPa) level. PCA (principal component analysis) decomposition of tropopause temperatures and heights over the basin indicate that ENSO accounts for 73 % of the interannual (non-seasonal) variability with a correlation of 0.77 with Niño3.4 index whereas the QBO explains about 10 % of the variability. The largest tropopause anomaly associated with ENSO occurs during the winter, when ENSO reaches its peak. The tropopause temperature (height) increased (decreased) by about 1.5 °C (300 m) during the last major El Niño event of 2009/2010. In general, we find decreasing (increasing) trend in tropopause temperature (height) between 2006 and 2013

Motor Vehicles: Are they emerging threats to Lake Victoria and its environment?

Lake Victoria and its basin supports more than 30 million people, while its fishes are exported the world over. This second largest fresh water body is however experiencing stress due to eutrophication, sedimentation, declining levels and more recently the motor vehicle sector. This contribution examines the general pollution from motor vehicle and gives an in-depth analysis of motor vehicle washing along the lakeshore. The results indicate the water samples from the motor vehicle washing and urban runoff points to be slightly acidic (i.e., average pH of 6.7) and average Total at these points. The conductivity for the motor vehicle washing points averaged at 150 S/cm, while the urban runoffs point was more varied ranging from below 150 S/cm to over 400 S/cm (average 301 S/cm). A positive correlation coefficient of more than 0.7 is obtained between the total daily count of vehicles and each of the water quality parameter tested. This signifies a strong correlation between motor vehicle related activities and the pollution of the lake. In general, the motor vehicle industry is found to have a noticeable negativeeffect on the lake

The use of NDVI and its Derivatives for Monitoring Lake Victoria’s Water Level and Drought Conditions

Normalized Difference Vegetation Index (NDVI), which is a measure of vegetation vigour, and lake water levels respond variably to precipitation and its deficiency. For a given lake catchment, NDVI may have the ability to depict localized natural variability in water levels in response to weather patterns. This information may be used to decipher natural from unnatural variations of a given lake’s surface. This study evaluates the potential of using NDVI and its associated derivatives (VCI (vegetation condition index), SVI (standardised vegetation index), AINDVI (annually integrated NDVI), green vegetation function (F g ), and NDVIA (NDVI anomaly)) to depict Lake Victoria’s water levels. Thirty years of monthly mean water levels and a portion of the Global Inventory Modelling and Mapping Studies (GIMMS) AVHRR (Advanced Very High Resolution Radiometer) NDVI datasets were used. Their aggregate data structures and temporal co-variabilities were analysed using GIS/spatial analysis tools. Locally, NDVI was found to be more sensitive to drought (i.e., responded more strongly to reduced precipitation) than to water levels. It showed a good ability to depict water levels one-month in advance, especially in moderate to low precipitation years. SVI and SWL (standardized water levels) used in association with AINDVI and AMWLA (annual mean water levels anomaly) readily identified high precipitation years, which are also when NDVI has a low ability to depict water levels. NDVI also appears to be able to highlight unnatural variations in water levels. We propose an iterative approach for the better use of NDVI, which may be useful in developing an early warning mechanisms for the management of lake Victoria and other Lakes with similar characteristics

Research frame work at LACCOST, UFPE, Brazil

After finishing PhD sandwich (Rodrigo) under co-supervision of Professor Bernhard Heck in 2010 at GIK (Geodetic Institute of Geodesy) KIT, new ideas came true to start a laboratory of research dedicated to coastal studies (LACCOST) at Federal University of Pernambuco, Brazil. Also the contact made at GIK with Professor Joseph Awange spreading his ideas about “Environmental Geodesy” add latter an international cooperation with Curtin University, Australia, improving this team and including beside coastal related studies researches with spatial geodesy as background to support questions about the environment, using Brazil and South America as study case. The objectives of this paper is firstly to thank Professor Heck for keeping always looking for international cooperation with naturally become an example and model to follow up and his incredible skills to support researches all over the world. Secondly propagate what has been the topic of master’s students showing researches under development at this laboratory