His primary areas of investigation include Remote sensing, Remote sensing, Cartography, Elevation and Aerial photography. His work in Remote sensing addresses subjects such as Pixel, which are connected to disciplines such as Impervious surface. Borrowing concepts from South carolina, he weaves in ideas under Remote sensing.
John R. Jensen interconnects Thematic Mapper and Data mining in the investigation of issues within Cartography. His Elevation study combines topics in areas such as Terrain, Hydrology, Land cover, Vegetation and Lidar. His study on Aerial photography also encompasses disciplines like
John R. Jensen mainly focuses on Remote sensing, Remote sensing, Hydrology, Aerial photography and Thematic Mapper. The various areas that John R. Jensen examines in his Remote sensing study include Land cover and Vegetation. John R. Jensen has included themes like Change detection, Multispectral image, Geospatial analysis, Land use and Hazardous waste sites in his Remote sensing study.
His Geospatial analysis study typically links adjacent topics like Data science. His study looks at the relationship between Hydrology and topics such as Transect, which overlap with Wetland classification. His Geographic information system research is multidisciplinary, relying on both Resource management, Digital image processing, Water level, Photogrammetry and Digital elevation model.
John R. Jensen spends much of his time researching Remote sensing, Remote sensing, Hyperspectral imaging, Artificial intelligence and Change detection. His Remote sensing study frequently draws connections between adjacent fields such as Hydrology. His studies in Remote sensing integrate themes in fields like Panchromatic film, Thematic map and Hazardous waste sites.
His Hyperspectral imaging research is multidisciplinary, incorporating perspectives in Irrigation, Biomass, Leaf area index, Nutrient and Multilayer perceptron. His research investigates the connection between Artificial intelligence and topics such as Pattern recognition that intersect with issues in Decision tree. He has researched Image segmentation in several fields, including Pixel and Remote sensing application.
His primary scientific interests are in Remote sensing, Artificial intelligence, Change detection, Land cover and Remote sensing. The concepts of his Remote sensing study are interwoven with issues in Hydrology and Cartography, Terrain. His Change detection research incorporates themes from Calibration and Pattern recognition.
His work carried out in the field of Land cover brings together such families of science as Image enhancement, Satellite imagery and Hazardous waste sites. Many of his research projects under Remote sensing are closely connected to Temporal resolution with Temporal resolution, tying the diverse disciplines of science together. His Image segmentation research integrates issues from Pixel and Remote sensing application.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Introductory Digital Image Processing: A Remote Sensing Perspective
John R. Jensen.
Remote Sensing of the Environment: An Earth Resource Perspective
John R. Jensen.
Introductory Digital Image Processing
John R. Jensen.
Remote Sensing of Urban/Suburban Infrastructure and Socio‐Economic Attributes
John R. Jensen;Dave C. Cowen.
Photogrammetric Engineering and Remote Sensing (2011)
Object-based change detection using correlation image analysis and image segmentation
J. Im;J. R. Jensen;J. A. Tullis.
Journal of remote sensing (2008)
An evaluation of LIDAR- and IFSAR-derived digital elevation models in leaf-on conditions with USGS Level 1 and Level 2 DEMs
Michael E Hodgson;John R Jensen;Laura Schmidt;Steve Schill.
Remote Sensing of Environment (2003)
A change detection model based on neighborhood correlation image analysis and decision tree classification
Jungho Im;John R. Jensen.
Remote Sensing of Environment (2005)
Synergistic Use of Lidar and Color Aerial Photography for Mapping Urban Parcel Imperviousness
Michael E. Hodgson;John R. Jensen;Jason A. Tullis;Kevin D. Riordan.
Photogrammetric Engineering and Remote Sensing (2003)
Detecting residential land-use development at the urban fringe
J. R. Jensen;D. L. Toll.
An Evaluation of Lidar-derived Elevation and Terrain Slope in Leaf-off Conditions
Michael E. Hodgson;John Jensen;George T. Raber;Jason Tullis.
Photogrammetric Engineering and Remote Sensing (2005)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: