KEYWORDS: Body temperature, Animal model studies, Thermography, Sensors, Data modeling, Solar radiation models, Thermal modeling, Cameras, Smart sensors, Physiology
Lizards are an "excellent group of organisms" to examine the habitat and microhabitat use mainly
because their ecology and physiology is well studied. Due to their behavioral body temperature
regulation, the thermal environment is especially linked with their habitat use. In this study, for
mapping and understanding lizard's distribution at microhabitat scale, an individual of Timon Lepidus
was kept and monitored in a terrarium (245×120×115cm) in which sand, rocks, burrows, hatching
chambers, UV-lamps, fog generators and heating devices were placed to simulate its natural habitat.
Optical cameras, thermal cameras and other data loggers were fixed and recording the lizard's body
temperature, ground surface temperature, air temperature, radiation and other important environmental
parameters. By analysis the data collected, we propose a Cellular Automata (CA) model by which the
movement of lizards is simulated and translated into their distribution. This paper explores the
capabilities of applying GIS techniques to thermoregulatory activity studies in a microhabitat-scale. We
conclude that microhabitat use of lizards can be explained in some degree by the rule based CA model.
In this study, we monitored the quality of fresh tea leaves as raw materials of tea products by
hyperspectral technology, as a way to explore the potential of hyperspectral remote sensing to detect
the taste-related chemical components with low concentration in living plants. At leaf scale, empirical
models have been established to find the relationships between quality-related chemicals in fresh tea
leaves and foliar spectral data. Tea polyphenols (TP) and amino acid (AA) and water-soluble protein
(SP) are three target chemicals in this paper. Near infrared spectroscopy (NIRS) was also been applied
to estimate these chemicals for dried and ground leaves in laboratory. They are compared in terms of
retrieval precision. Two main methodologies have been employed for modelling: (a) two bands
normalized ratio index (NRI), (b) partial least squares (PLS) regression. The PLS method was
performed using the original and transformed spectra: mean centred spectra, standard first derivative
and standard normal variate (SNV) transformed spectra. The results demonstrated that the biochemical
parameters related to the quality of tea can be estimated with satisfactory accuracy both at dried
powder and fresh leaf scales.
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