Computer implemented classification of vegetation using aircraft acquired multispectral scanner data

The use of aircraft 24-channel multispectral scanner data in conjunction with computer processing techniques to obtain an automated classification of plant species association was discussed. The classification of various plant species associations was related to information needed for specific applications. In addition, the necessity for multiple selection of training fields for a single class in situations where the study area consists of highly irregular terrain was detailed. A single classification was illuminated differently in different areas, resulting in the existence of multiple spectral signatures for a given class. These different signatures result since different qualities of radiation upwell to the detector from portions that have differing qualities of incident radiation. Techniques of training field selection were outlined, and a classification obtained from a natural area in Tishomingo State Park in northern Mississippi was presented

Application of remotely sensed multispectral data to automated analysis of marshland vegetation. Inference to the location of breeding habitats of the salt marsh mosquito (Aedes Sollicitans)

The techniques used for the automated classification of marshland vegetation and for the color-coded display of remotely acquired data to facilitate the control of mosquito breeding are presented. A multispectral scanner system and its mode of operation are described, and the computer processing techniques are discussed. The procedures for the selection of calibration sites are explained. Three methods for displaying color-coded classification data are presented

Utilization of LANDSAT multispectral data in geobotanical investigations: The location of ironstone gravel in the Sam Houston National Forest

Practical techniques were developed and evaluated for deriving geobotanical information from LANDSAT MSS data acquired for a test site in the Sam Houston National Forest near Cleveland, Texas where gravel deposits exist in sufficient quantity that economical extraction would be feasible. A correlation was shown between a single spectral class and the presence of ironstone gravel. Field data indicates that this class relates to upland pine which was probably under stress as the result of a prolonged drought which was in progress at the time of data acquisition. It is suggested that the subsurface gravel produces a soil which has less field capacity for water retention, causing early appearance of water stress in the surface vegetation over these soils. In all areas within the QMC formation where this class occurred, gravel was located when borings were made

Intraoperative Multispectral Fluorescence Imaging for the Detection of the Sentinel Lymph Node in Cervical Cancer: A Novel Concept

PURPOSE: Real-time intraoperative near-infrared fluorescence (NIRF) imaging is a promising technique for lymphatic mapping and sentinel lymph node (SLN) detection. The purpose of this technical feasibility pilot study was to evaluate the applicability of NIRF imaging with indocyanin green (ICG) for the detection of the SLN in cervical cancer. PROCEDURES: In ten patients with early stage cervical cancer, a mixture of patent blue and ICG was injected into the cervix uteri during surgery. Real-time color and fluorescence videos and images were acquired using a custom-made multispectral fluorescence camera system. RESULTS: Real-time fluorescence lymphatic mapping was observed in vivo in six patients; a total of nine SLNs were detected, of which one (11%) contained metastases. Ex vivo fluorescence imaging revealed the remaining fluorescent signal in 11 of 197 non-sentinel LNs (5%), of which one contained metastatic tumor tissue. None of the non-fluorescent LNs contained metastases. CONCLUSIONS: We conclude that lymphatic mapping and detection of the SLN in cervical cancer using intraoperative NIRF imaging is technically feasible. However, the technique needs to be refined for full applicability in cervical cancer in terms of sensitivity and specificity