An initiative for participatory monitoring of large scale acquisitions: Opportunities and results thus far

Increasing commercial pressures on land are provoking fundamental and far-reaching changes in the relationships between people and land. Much knowledge on land-oriented investments projects currently comes from the media. Although this provides a good starting point, lack of transparency and rapidly changing contexts mean that this is often unreliable. The International Land Coalition, in partnership with Oxfam Novib, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), University of Pretoria, Centre for Development and Environment of the University of Bern (CDE), and GIZ, started to compile an inventory of land-related investments. This project aims to better understand the extent, trends and impacts of land-related investments by supporting an ongoing and systematic stocktaking exercise of the various investment projects currently taking place worldwide. It involves a large number of organizations and individuals working in areas where land transactions are being made, and able to provide details of such investments. The project monitors land transactions in rural areas that imply a transformation of land use rights from communities and smallholders to commercial use, and are made both by domestic and foreign investors (private actors, governments, government-back private investors). The focus is on investments for food or agrofuel production, timber extraction, carbon trading, mineral extraction, conservation and tourism. A novel way of using ITC to document land acquisitions in a spatially explicit way and by using an approach called “crowdsourcing” is being developed. This approach will allow actors to share information and knowledge directly and at any time on a public platform, where it will be scrutinized in terms of reliability and cross checked with other sources. Up to now, over 1200 deals have been recorded across 96 countries. Details of such transactions have been classified in a matrix and distributed to over 350 contacts worldwide for verification. The verified information has been geo-referenced and represented in two global maps. This is an open database enabling a continued monitoring exercise and the improvement of data accuracy. More information will be released over time. The opportunities arise from overcoming constraints by incomplete information by proposing a new way of collecting, enhancing and sharing information and knowledge in a more democratic and transparent manner. The intention is to develop interactive knowledge platform where any interested person can share and access information on land deals, their link to involved stakeholders, and their embedding into a geographical context. By making use of new ICT technologies that are more and more in the reach of local stakeholders, as well as open access and web-based spatial information systems, it will become possible to create a dynamic database containing spatial explicit data. Feeding in data by a large number of stakeholders, increasingly also by means of new mobile ITC technologies, will open up new opportunities to analyse, monitor and assess highly dynamic trends of land acquisition and rural transformation.

Reevaluation of the MASTER-2009 MLI and H-10 Debris Modeling

The current paper is an excerpt from the doctoral thesis ”Multi-Layer Insulation as Contribution to Orbital Debris”written at the Institute of Aerospace Systems of the Technische Universit ̈at of Braunschweig. The Multi-Layer In-sulation (MLI) population included in ESA’s MASTER-2009 (M eteoroid and Space-Debris Terrestrial Environment Reference) software is based on models for two mechanisms: One model simulates the release of MLI debris during fragmentation events while another estimates the continuo us release of larger MLI pieces due to aging related deterioration of the material. The aim of the thesis was to revise the MLI models from the base up followed by a re-validation of the simulated MLI debris population. The validation is based on comparison to measurement data of the GEO and GTO debris environment obtained by the Astronomical Institute of the University of Bern (AIUB) using ESA’s Space Debris Telescope (ESASDT), the 1-m Zeiss telescope located at the Optical Ground Station (OGS) at the Teide Observatory at Tenerife, Spain. The re-validation led to the conclusion that MLI may cover a much smaller portion of the observed objects than previously published. Further investigation of the resulting discrepancy revealed that the contribution of altogether nine known Ariane H-10 upper stage explosion events which occurred between 1984 and 2002 has very likely been underestimated in past simulations.

SMARTnet: A Sensor for Monitoring the Geostationary Ring

As the number of space debris is increasing in the geostationary ring, it becomes mandatory for any satellite operator to avoid any collisions. Space debris in geosynchronous orbits may be observed with optical telescopes. Other than radar, that requires very large dishes and transmission powers for sensing high-altitude objects, optical observations do not depend on active illumination from ground and may be performed with notably smaller apertures. The detection size of an object depends on the aperture of the telescope, sky background and exposure time. With a telescope of 50 cm aperture, objects down to approximately 50 cm may be observed. This size is regarded as a threshold for the identification of hazardous objects and the prevention of potentially catastrophic collisions in geostationary orbits. In collaboration with the Astronomical Institute of the University of Bern (AIUB), the German Space Operations Center (GSOC) is building a small aperture telescope to demonstrate the feasibility of optical surveillance of the geostationary ring. The telescope will be located in the southern hemisphere and complement an existing telescope in the northern hemisphere already operated by AIUB. These two telescopes provide an optimum coverage of European GEO satellites and enable a continuous monitoring independent of seasonal limitations. The telescope will be operated completely automatically. The automated operations should be demonstrated covering the full range of activities including scheduling of observations, telescope and camera control as well as data processing.

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Real-time localization using software defined radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Land system science and sustainable development of the earth system: A global land project perspective

Land systems are the result of human interactions with the natural environment. Understanding the drivers, state, trends and impacts of different land systems on social and natural processes helps to reveal how changes in the land system affect the functioning of the socio-ecological system as a whole and the tradeoff these changes may represent. The Global Land Project has led advances by synthesizing land systems research across different scales and providing concepts to further understand the feedbacks between social-and environmental systems, between urban and rural environments and between distant world regions. Land system science has moved from a focus on observation of change and understanding the drivers of these changes to a focus on using this understanding to design sustainable transformations through stakeholder engagement and through the concept of land governance. As land use can be seen as the largest geo-engineering project in which mankind has engaged, land system science can act as a platform for integration of insights from different disciplines and for translation of knowledge into action.

Optical Light Curve Observations to Determine Attitude States of Space Debris

The currently proposed space debris remediation measures include the active removal of large objects and “just in time” collision avoidance by deviating the objects using, e.g., ground-based lasers. Both techniques require precise knowledge of the attitude state and state changes of the target objects. In the former case, to devise methods to grapple the target by a tug spacecraft, in the latter, to precisely propagate the orbits of potential collision partners as disturbing forces like air drag and solar radiation pressure depend on the attitude of the objects. Non-resolving optical observations of the magnitude variations, so-called light curves, are a promising technique to determine rotation or tumbling rates and the orientations of the actual rotation axis of objects, as well as their temporal changes. The 1-meter telescope ZIMLAT of the Astronomical Institute of the University of Bern has been used to collect light curves of MEO and GEO objects for a considerable period of time. Recently, light curves of Low Earth Orbit (LEO) targets were acquired as well. We present different observation methods, including active tracking using a CCD subframe readout technique, and the use of a high-speed scientific CMOS camera. Technical challenges when tracking objects with poor orbit redictions, as well as different data reduction methods are addressed. Results from a survey of abandoned rocket upper stages in LEO, examples of abandoned payloads and observations of high area-to-mass ratio debris will be resented. Eventually, first results of the analysis of these light curves are provided.

Associating optical measurements and estimating orbits of geocentric objects through population-based meta-heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both, the correct associations among the observations and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. The number S corresponds to the number of fences involved in the problem. Each fence consists of a set of observations where each observation belongs to a different object. The S ≥ 3 MTT problem is an NP-hard combinatorial optimization problem. There are two general ways to solve this. One way is to seek the optimum solution, this can be achieved by applying a branch-and- bound algorithm. When using these algorithms the problem has to be greatly simplified to keep the computational cost at a reasonable level. Another option is to approximate the solution by using meta-heuristic methods. These methods aim to efficiently explore the different possible combinations so that a reasonable result can be obtained with a reasonable computational effort. To this end several population-based meta-heuristic methods are implemented and tested on simulated optical measurements. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.