Regional distribution of forest height and biomass from multisensor data fusion

Regional distribution of forest height and biomass from multisensor data fusion

[1] Elevation data acquired from radar interferometry at C‐band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post‐processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m)...

SPOT-5 Spectral and Textural Data Fusion for Forest Mean Age and Height Estimation

Precise estimation of the forest structural parameters supports decision makers for sustainable management of the forests. Moreover, timber volume estimation and consequently the economic value of a forest can be derived based on the structural parameter quantization. Mean age and height of the trees are two important parameters for estimating the productivity of the plantations. This research ...

Multisensor Data Fusion

Multisensor Data Fusion

IMultisensor data fusion refers to the acquisition, processing and synergistic combination of information gathered by various knowledge sources and sensors to provide a better understanding of a phenomenon. It is a fascinating and rapidly evolving field that has generated a lot of excitement in the research and development community. These concepts are being applied to a wide variety of fields ...

Fusion of Heterogeneous Multisensor Data

One of the main future tasks in the field of reconnaissance and surveillance is the data fusion of heterogeneous systems. For this purpose, sensor data of airborne and spaceborne systems, which acquire the data from the same scene with different spatial and spectral coverage, are used. The employment of different sensors offers the opportunity to take benefit of the specific sensor characterist...