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Full-Text Articles in Social and Behavioral Sciences

Surface Temperature Mapping Of The University Of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries, Alexander Savelyev, Ramanathan Sugumaran Jan 2008

Surface Temperature Mapping Of The University Of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries, Alexander Savelyev, Ramanathan Sugumaran

Faculty Publications

The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 µm was flown at the average altitude of 600 m, achieving ground resolution of 29 cm. Ground control data was used to construct the pixelto-temperature conversion model, which was later used to produce temperature maps of the entire campus and also for validation of the model. The temperature map then was used to assess the building rooftop conditions and steam line faults in the study area. Assessment …


Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.) Jan 2008

Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Remote sensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seasons, resulting in different color tones of vegetation. The rise and fall of NDVI values decide the biological response, either the green up or brown down [1]. Vegetation in green up period appears with more vegetative vigor and during brown down period it has a dry appearance. This paper proposes a novel method that identifies vegetative patterns in satellite images and then alters vegetation color to simulate seasonal changes based on training …


Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.) Jan 2008

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …