Bogotá, the rapidly growing center of an emerging economy in the northern part of South America, is located within a biodiversity hotspot in the tropical Andes. The surrounding mountains harbor the ecosystems Páramo and Bosque Altoandino whose high water retention capacity serves as a "natural water tower" for the city's freshwater supply. Since Bogotá is steadily growing, the city spreads into its peri-urban area, thus threatening its proximal ecosystems. In this study, the land use and land cover change (LULCC) of Bogotá's surrounding area is analyzed with random forest algorithms for the period 1989 to 2016. The basin of the Rio Tunjuelo, a subbasin of the Rio Bogotá, was selected for analysis, as it is typical for the entire area in terms of relief, land use and land cover. A multiple logistic regression analysis is applied to identify different determining factors of the changes. LULCC analysis of the Rio Tunjuelo basin shows an ongoing but abating southward spread of Bogotá's outer rim, an increase of agricultural land, and decrease of natural vegetation. After an initial heavily spatial spread of urbanization in the early 1990s, the speed of urban spread declined in the past years. Statistical analysis implies that the defined natural vegetation classes must be considered as one spatial entity. The probability for their change increases with decreasing distance to established agricultural areas, which indicates human impact as a relevant factor for LULCC. Generally, the explained deviance (D 2) is low and hence it is presumed that the LULCC determining factors are not predominantly found among environmental parameters.

Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems and human livelihoods. The rate of permafrost thaw is controlled by surface and subsurface properties and processes, all of which are potentially linked with each other. Yet, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists and indigenous groups, to collect standardized metadata and data on permafrost thaw. The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters measured along transects are: snow depth, thaw depth, vegetation height, soil texture, and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. Our hope is that this openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, thus to the broad community represented by the T-MOSAIC project.

<p>The O2A (Observation to Archive) is a data-flow framework for heterogeneous sources, including multiple institutions and scales of Earth observation. In the O2A, once data transmission is set up, processes are executed to automatically ingest (i.e. collect and harmonize) and quality control data in near real-time. We consider a web-based sensor description application to support transmission and harmonization of observational time-series data. We also consider a product-oriented quality control, where a standardized and scalable approach should integrate the diversity of sensors connected to the framework. A review of literature and observation networks of marine and terrestrial environments is under construction to allow us, for example, to characterize quality tests in use for generic and specific applications. In addition, we use a standardized quality flag scheme to support both user and technical levels of information. In our outlook, a quality score should pair the quality flag to indicate the overall plausibility of each individual data value or to measure the flagging uncertainty. In this work, we present concepts under development and give insights into the data ingest and quality control currently operating within the O2A framework.</p>

Sustainable management of biodiversity requires a thorough understanding of local climate and weather, particularly in areas where ecosystems have been degraded and where life is highly adapted to or dependent on narrow ecological niches. Furthermore, society, economy, and culture of urban agglomerations are directly affected by the quality and quantity of services provided by adjacent ecosystems, which makes knowledge on regional characteristics and impact of climate variability crucial. Here, we present precipitation data from six meteorological stations spread across several orographic zones of the eastern Andes in the surroundings of Bogotá, Colombia’s biggest urban agglomeration. The time series of rainfall data are analyzed statistically, examined regarding the occurrence of cyclicity in relation to ENSO, and correlated to the Multivariate El Niño-Southern Oscillation Index (MEI). Results offer no conclusive ENSO related cycles, but show that data of most of the stations are marked by annual or semestral cyclicity. There is no straightforward correlation between MEI and monthly precipitation values, and neither filtered nor lagged values showed any conclusive and significant correlation. Stations within the same orographic zones not necessarily bring forth comparable statistical results. Temporal and spatial properties of precipitation rather appear to result from micro- and mesoscale topoclimates than from ENSO variability.

<p>Today's fast digital growth made data the most essential tool for scientific progress in Earth Systems Science. Hence, we strive to assemble a modular research infrastructure comprising a collection of tools and services that allow researchers to turn big data into scientific outcomes.</p><p>Major roadblocks are (i) the increasing number and complexity of research platforms, devices, and sensors, (ii) the heterogeneous project-driven requirements towards, e. g., satellite data, sensor monitoring, quality assessment and control, processing, analysis and visualization, and (iii) the demand for near real time analyses.</p><p>These requirements have led us to build a generic and cost-effective framework <strong>O2A</strong> (<strong>O</strong>bservation <strong>to</strong> <strong>A</strong>rchive) to enable, control, and access the flow of sensor observations to archives and repositories.</p><p>By establishing O2A within major cooperative projects like <strong>MOSES</strong> and <strong>Digital Earth</strong> in the research field Earth and Environment of the German Helmholtz Association, we extend research data management services, computing powers, and skills to connect with the evolving software and storage services for data science. This fully supports the typical scientific workflow from its very beginning to its very end, that is, from data acquisition to final data publication. </p><p>The key modules of O2A's digital research infrastructure established by AWI to enable Digital Earth Science are implementing the <strong>FAIR</strong> principles:</p><ul><li><strong>Sensor Web</strong>, to register sensor applications and capture controlled meta data before and alongside any measurement in the field</li> <li><strong>Data ingest</strong>, allowing researchers to feed data into storage systems and processing pipelines in a prepared and documented way, at best in controlled NRT data streams</li> <li><strong>Dashboards, </strong>allowing researchers to find and access data and share and collaborate among partners</li> <li><strong>Workspace, </strong>enabling researchers to access and use data with research software in a cloud-based virtualized infrastructure that allows researchers to analyse massive amounts of data on the spot</li> <li><strong>Archiving </strong>and<strong> publishing data </strong>via repositories and Digital Object Identifiers (DOI).</li> </ul>