Modeling energy flow and nutrient cycling in natural semiarid grassland ecosystems with the aid of thematic mapper data

Energy flow and nutrient cycling were modeled as affected by herbivory on selected intensive sites along gradients of precipitation and soils, validating the model output by monitoring selected parameters with data derived from the Thematic Mapper (TM). Herbivore production was modeled along the gradient of soils and herbivory, and validated with data derived from TM in a spatial data base

Online Mutual Foreground Segmentation for Multispectral Stereo Videos

The segmentation of video sequences into foreground and background regions is a low-level process commonly used in video content analysis and smart surveillance applications. Using a multispectral camera setup can improve this process by providing more diverse data to help identify objects despite adverse imaging conditions. The registration of several data sources is however not trivial if the appearance of objects produced by each sensor differs substantially. This problem is further complicated when parallax effects cannot be ignored when using close-range stereo pairs. In this work, we present a new method to simultaneously tackle multispectral segmentation and stereo registration. Using an iterative procedure, we estimate the labeling result for one problem using the provisional result of the other. Our approach is based on the alternating minimization of two energy functions that are linked through the use of dynamic priors. We rely on the integration of shape and appearance cues to find proper multispectral correspondences, and to properly segment objects in low contrast regions. We also formulate our model as a frame processing pipeline using higher order terms to improve the temporal coherence of our results. Our method is evaluated under different configurations on multiple multispectral datasets, and our implementation is available online.Comment: Preprint accepted for publication in IJCV (December 2018

Analog table look-up device identifies unknown terrain

Table provides a probability map defining unknown terrain in terms of known terrain inputs. Device consists of analog transformation network and flying spot scanner. Information is useful to manufacturers and users of remote sensing equipment and applies to automated quality control

Remote characterization of wetland vegetation and corresponding relationship to soils : final report on the evaluation of imagery-derived terrain attributes in the coastal zone

To accomplish the goals of this study, a pristine coastal barrier island environment was selected that was free from influences of urban development. This provided the optimal situation that could be expected to be encountered by military strategists and base resource managers. The site selected was Parramore Island (Figure I). Parramore Island is the seventh island ( north to south) located on the seaward margin of the southeastern Delmarva Peninsula and is one of the most dynamic and least disturbed coastal landscapes remaining in North America (McCaffrey and Dueser, 1990). The island is centered at Latitude 37° 30\u27 and Longitude 75° 40\u27 and is owned by the Nature Conservancy and managed as part of the Virginia Coast Reserve. The island is also included in the National Science Foundation\u27s Long Term Ecological Research Reserve System (LTER)

Bolus tracking with nanofilter-based multispectral videography for capturing microvasculature hemodynamics

Multispectral imaging is a highly desirable modality for material-based analysis in diverse areas such as food production and processing, satellite-based reconnaissance, and biomedical imaging. Here, we present nanofilter-based multispectral videography (nMSV) in the 700 to 950â €...nm range made possible by the tunable extraordinary-optical- transmission properties of 3D metallic nanostructures. Measurements made with nMSV during a bolus injection of an intravascular tracer in the ear of a piglet resulted in spectral videos of the microvasculature. Analysis of the multispectral videos generated contrast measurements representative of arterial pulsation, the distribution of microvascular transit times, as well as a separation of the venous and arterial signals arising from within the tissue. Therefore, nMSV is capable of acquiring serial multispectral images relevant to tissue hemodynamics, which may have application to the detection and identification of skin cancer

Multispectral data analysis Final report

Contour maps and prediction lines demonstrating existence of water depth information in multispectral dat

Multispectral Video Fusion for Non-contact Monitoring of Respiratory Rate and Apnea

Continuous monitoring of respiratory activity is desirable in many clinical applications to detect respiratory events. Non-contact monitoring of respiration can be achieved with near- and far-infrared spectrum cameras. However, current technologies are not sufficiently robust to be used in clinical applications. For example, they fail to estimate an accurate respiratory rate (RR) during apnea. We present a novel algorithm based on multispectral data fusion that aims at estimating RR also during apnea. The algorithm independently addresses the RR estimation and apnea detection tasks. Respiratory information is extracted from multiple sources and fed into an RR estimator and an apnea detector whose results are fused into a final respiratory activity estimation. We evaluated the system retrospectively using data from 30 healthy adults who performed diverse controlled breathing tasks while lying supine in a dark room and reproduced central and obstructive apneic events. Combining multiple respiratory information from multispectral cameras improved the root mean square error (RMSE) accuracy of the RR estimation from up to 4.64 monospectral data down to 1.60 breaths/min. The median F1 scores for classifying obstructive (0.75 to 0.86) and central apnea (0.75 to 0.93) also improved. Furthermore, the independent consideration of apnea detection led to a more robust system (RMSE of 4.44 vs. 7.96 breaths/min). Our findings may represent a step towards the use of cameras for vital sign monitoring in medical applications

Use of Multispectral Aerial Videography for Jurisdictional Delineation of Wetland Areas

Multispectral aerial videography was used to reproduce the jurisdictional delineation of wetland area of approximately 50 hectares in Davis County, Utah Imagery from the system consisted of three-band composite with wavelengths covering 550 nm (±10 nm), 650 nm (±10 nm), and 850 nm (±10 nm). The site was overflown at three different flight dates during the 1992 growing season (June 2, July 22, October 1). Imagery resolution varied from 0.56 m to 0.81 m. Mosaiced images were analyzed with a Supervised clustering/maximum likelihood classifier, ISODATA clustering/Euclidan classifier, statistical clustering/maximum likelihood classifier, and fuzzy c-means clustering. Overall accuracies for wetland/upland designations as compared to ground truth data varied from 60% to 75%. The ISODATA method was the poorest performer for all dates and both of two accuracy testing techniques. Supervised clustering and statistical clustering were comparable with a slight edge in accuracy to the supervised clustering. The best all-round performer was the fuzzy c-means algorithm in terms of time spent and accuracy