Date of Award
Master of Science
Satellite remote sensing is the most applied method for detection and measurement of electromagnetic energy and its interaction with Earth surface. the analysis of the data acquired can provide important information with uses in areas as like weather forecasting, military intelligence and environmental and resources location. Due to the great distance from where the samples are taken and even with the most sophisticated sensor it is impossible to have an exactly replica of the Earth surface. As a result, scientist analyze imagery where a single pixel can be the representation of a 30 by 30 meters area of land. This could create misrepresentation of the properties, materials or distribution of the area of interest. As it is known, the veracity of a research depends on the reliability, precision and repeatability of sensors from which the data is collected.
"Mid-range" sensing is a short and long-term solution for spatial loss problem. This method measures the environment every few meters and generates several measure points that reciprocate a single pixel on a satellite measure allowing the description of the area of interest with more precision. This method is currently taken to the next stage by position more mid-range sensing station on different ecosystems and studying the relationships between their readings and the satellite images to create algorithms and model to approximate the spatial error and improve the data representativeness.
The main objective of this study is to analyze the current mid-range sensing system used by the System Ecology Lab at the University of Texas at El Paso, its working conditions and identify its limitation. This to prototype an autonomous robust tram unit that will be able to travel through the existing tramlines and to take reliable and relevant measurements that will allow development of new technologies and algorithms that will improve the remote sensing methods through image processing and mathematical models with low-budget investment in hardware.
The first stage consists in field tests of the current system, this would allow understand the functionality of the unit, its limitations, visualize improvement opportunities and analyze the working environment. Once the working conditions are defined a new design would be propose
and using engineering software simulations of strong winds loads, and instrumentation distribution will be prepared to calculate the center of mass and run a finite element and structural analyze on critical parts to validate the proposed prototype.
The analysis made to the cart structure along with the selection of materials ensures that this unit will perform correctly regardless the weather conditions. The prototype presented in this work have a stiffer, "weather-proof" structure and compartments that will improve the measurement taking at the JER site and allow it to have a permanent positioning on site. This improves the productivity of the research work by eliminating assembly/disassemble task. Thanks to the autonomy given to this unit, it could measure the field three times per week, increasing the previous number of measures taken with the old model and have the capability of running even when there is no one present at the site. By implementing simultaneous sensing with different sensor will open the doors for development of low-cost technology that through image processing will be able to obtain similar results that the ones obtain with expensive spectrometers.
Received from ProQuest
Quetzalcoatl Mendoza Rosas
Mendoza Rosas, Quetzalcoatl, "Design Of Robotic Tram Unit For Field Data Collection" (2018). Open Access Theses & Dissertations. 116.