The Dual Processor Platform (DPP) is a novel architecture template for networked embedded systems based on a strictly asynchronous processor interconnect that allows to minimize interference with a proven predictable behavior [7]. Contrary to traditional platforms [1, 5] DPP tries to mitigate interference by isolating different tasks and mapping them onto dedicated hardware resources. Typically, two different task sets - (i) sensing/actuation/data processing and (ii) communication - are mapped onto two different physically separated processing elements (usually low-power microcontrollers), allowing each to be optimized according to their individual requirements. Such hardware partitioning is a standard approach, frequently found in more complex sensor system implementations [2]. While the communication processor handles wireless packet transmission and reception, the application processor is dedicated to the sensor data acquisition, processing and actuation. But this strict separation of resources and function also requires a processor interconnect: BOLT [7], a stateful processor interconnect specifically designed based on this paradigm allows a strict decoupling of the power, clock and time domains of the two processing elements by allowing only asynchronous message passing between the two. The strict limitation to an asynchronous interface allows for predictable run-time behavior that, in addition to typical behavior observed from experiments, has been formally verified [7]. The most notable advantages of this approach are:

Spaceborne SAR interferometry (InSAR) has the potential of detecting forest change on a global scale with fine (meter-level) spatial resolution as well as on a monthly/weekly basis regardless of day or night. This is significant to characterize the land-use change and its impact on climate change. In this paper, both single-pass and repeat-pass SAR interferometry from spaceborne sensors are combined in order to detect and quantify (with Normalized RMSE ≤ 30%) forest disturbance at a large scale (dozens of kilometers) however with a fine spatial resolution (< 1 hectare) based on two newly developed approaches. The single-pass InSAR approach is not only able to detect forest disturbance but also capable of characterizing meter (or even sub-meter) level change of forest phase-center (mean) height due to forest growth and/or degradation. These methods are extensively validated with the past and current spaceborne single-pass and repeat-pass InSAR missions (i.e. JAXA's ALOS-1, ALOS-2 and DLR's TanDEM-X) over subtropical forests in Australia as well as tropical forests in Brazil. Such techniques also serve as observing prototypes for the fusion of the future spaceborne InSAR missions (such as NASA-ISRO's NISAR and DLR's TanDEM-L).

The time variation of phase height from interferometric SAR (InSAR) from TanDEM-X is shown for 3 years, in Tapajos National Forest, Brazil. Its RMS, for one secondary stand, about a model linear in time is 0.5 m. This RMS is compared to that for 30 stands at one epoch. The single-epoch RMS for a model linear in mean field height is 2.2 m. It is suggested that the improved performance of the temporal variation may be due to errors in finding the phase height of the ground, which is necessary for single-epoch estimation, but not needed for the “change” measurement. Pending further fieldwork, a tentative conversion of 20 Mg/ha/yr corresponding to 1 m/yr, is proposed. Abrupt discontinuities, as well as phase height rates as a function of stand age/aboveground biomass, are discussed.

This letter reports the sensitivity of X-band interferometric synthetic aperture radar (InSAR) data from the first dual-spacecraft radar interferometer, TanDEM-X, to variations in tropical-forest aboveground biomass (AGB). It also reports the first tropical-forest AGB estimates from TanDEM-X data. Tropical forests account for about 50% of the world's forested biomass and play critical roles in the control of atmospheric carbon dioxide by emission through deforestation and uptake through forest growth. The TanDEM-X InSAR data used in this analysis were taken over the Tapajós National Forest, Pará, Brazil, where field measurements from 30 stands were acquired. The magnitude of the InSAR normalized complex correlation, which is called coherence, decreases by about 25% as AGB increases from 2 to 430 Mg-ha-1, suggesting more vertically distributed return-power profiles with increasing biomass. Comparison of InSAR coherences to those of small-spot (15 cm) lidar suggests that lidar penetrates deeper into the canopies than InSAR. Modeling InSAR profiles from InSAR coherence and lidar profiles yields an estimate of 0.29 dB/m for the X-band extinction coefficient relative to that of lidar. Forest AGB estimated from InSAR observations on 0.25-ha plots shows RMS scatters about the field-estimated AGB between 52 and 62 Mg-ha-1, which is between 29% and 35% of the average AGB of 179 Mg-ha-1, depending on the data analysis mode. The sensitivity and biomass-estimation performance suggest the potential of TanDEM-X observations to contribute to global tropical-forest biomass monitoring.

The National Ecological Observatory Network (NEON) is a continental-scale research platform for discovering, understanding and forecasting the impacts of climate change, land-use change, and invasive species on ecology. Site-based flux tower and field measurements will be coordinated with high resolution, regional airborne remote sensing observations. This data combined with satellite observations, national data sets and ecosystem models will extend site-based and regional coverage to the continental scale. The NEON Airborne Observation Platform (AOP) will carry remote sensing instrumentation designed to achieve sub-meter to meter scale ground resolution to bridge scales from organism and stand scales to the scale of satellite based remote sensing. The capability of the airborne system will be well beyond existing systems in its ability to produce quantitative information about ecosystem structure and functioning covering nearly 2 million hectares each year for 30 years or more.