Multi-frequency, Multi-temporal, Brush Fire Scar Analysis in a Semi-Arid Urban Environment

The number of forest fires has increased dramatically over the past five years in western areas of the United States, due to both human and natural causes. Urban areas, such as the city of Phoenix, continue to increase in size and population, with a majority of the development occurring in rural areas that have burned, or are threatened by brush fires. As people move into these environments there is an increased risk of damage to human property and lives due to fires. These areas have experienced a number of recent brush fires that have been expensive to fight, and caused a considerable amount of property damage. The ability to predict and control fires is thus increasingly important as urban centers encroach upon rural lands. Remote sensing can be utilized to characterize fire scarred areas, and predict areas that have an increased risk for burning again in the future. Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), Landsat Thematic Mapper (TM), and Spaceborne Imaging Radar - C (SIR-C) remote sensing data have been combined with a geographic information system (GIS) to characterize fire scars in a semi-arid urban area outside of Phoenix, Arizona. This data was also used to quantify the relationship of fire scar age to vegetative recovery. In addition to the remote sensing aspect of this project, an initial geomorphological investigation was conducted to determine the effect of fire on sediment flux and landscape evolution. Detailed topographic surveys, combined with sediment trap data, were used to examine differences in erosion between burned and unburned catchments. These results have implications for potential flooding risks due to removal of vegetative cover by fires. By combining remote sensing data with a GIS database, and through comparison with geomorphic/sedimentological investigations, this work may permit city officials and urban planners to better calculate potential risks for both future fire and flood hazards within the region

FUSING GEDI LIDAR AND TANDEM-X INSAR OBSERVATIONS FOR IMPROVED FOREST STRUCTURE AND BIOMASS MAPPING

The upcoming NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission presents an unprecedented opportunity to advance current global biomass estimates. However, gaps are expected between GEDI’s ground tracks, requiring the development of fusion-based methodologies to contiguously map forest biomass at satisfactory resolutions and accuracies. This dissertation is built on the complementary advantages of observations from GEDI and DLR’s TerraSAR-X/TanDEM-X (TDX)) Interferometric Synthetic Aperture Radar (InSAR) mission. To meet the goal of mapping forest structure and biomass contiguously and accurately, three types of fusion strategies have been investigated. First, a simulated GEDI-derived digital terrain model (DTM) was utilized to improve height estimation from TDX. Forest heights were initially derived from TDX coherence alone as a baseline using the widely used Random Volume over Ground (RVoG) scattering model. Here, assumptions about RVoG parameters – extinction coefficient (σ) and ground-to-volume amplitude ratio (µ) – were made. Using an external DTM derived from simulated GEDI lidar data, RVoG model was used to calculate spatially varied σ values and derived forest heights with better accuracy. TDX forest height estimation was further improved with the aid of simulated GEDI-derived DTM and canopy heights. The additional use of simulated GEDI canopy heights as RVoG input not just refined σ but also enabled the estimation of µ. Based on these parameters, forest heights were improved across three different forest types; biases were reduced from 1.7–3.8 m using only simulated GEDI DTMs to -0.9–1.1 m by using both simulated GEDI DTMs and canopy heights. Finally, wall-to-wall TDX heights were used to improve biomass estimates from simulated GEDI data over three contrasting forest types. When using simulated GEDI sampled observations alone, uncertainties were estimated statistically to be 9.0–19.9% at 1 km. These were improved to 5.2–11.7% at the same resolution by upscaling simulated GEDI footprint biomass with TDX heights. The GEDI/TDX data fusion also enabled the generation of biomass maps at a fine spatial resolution of 100 m, with uncertainties estimated to be 6.0–14.0%. Through the exploration of these fusion strategies, it has been demonstrated that a fusion-based mapping method could realize the generation of forest biomass products from GEDI with unprecedented resolutions and accuracies, while taking advantage of global seamless observations from TDX

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry was held on 1–15 July 2021. The scope of this online conference was to gather experts that are well-known worldwide who are currently working in chemical sensor technologies and to provide an online forum for the presention and discussion of new results. Throughout this event, topics of interest included, but were not limited to, the following: electrochemical devices and sensors; optical chemical sensors; mass-sensitive sensors; materials for chemical sensing; nano- and micro-technologies for sensing; chemical assays and validation; chemical sensor applications; analytical methods; gas sensors and apparatuses; electronic noses; electronic tongues; microfluidic devices; lab-on-a-chip; single-molecule sensing; nanosensors; and medico-diagnostic testing