Precise Quantification of Land Cover before and after Planned Disturbance Events with UAS-Derived Imagery

Abstract

This paper introduces a detailed procedure to utilize the high temporal and spatial resolution capabilities of an unmanned aerial system (UAS) to document vegetation at regular intervals both before and after a planned disturbance, a key component in natural disturbance-based management (NDBM), which uses treatments such as harvest and prescribed burns toward the removal of vegetation fuel loads. We developed a protocol and applied it to timber harvest and prescribed burn events. Geographic image-based analysis (GEOBIA) was used for the classification of UAS orthomosaics. The land cover classes included (1) bare ground, (2) litter, (3) green vegetation, and (4) burned vegetation for the prairie burn site, and (1) mature canopy, (2) understory vegetation, and (3) bare ground for the timber harvest site. Sample datasets for both kinds of disturbances were used to train a support vector machine (SVM) classifier algorithm, which produced four land cover classifications for each site. Statistical analysis (a two-tailed t-test) indicated there was no significant difference in image classification efficacies between the two disturbance types. This research provides a framework to use UASs to assess land cover, which is valuable for supporting effective land management practices and ensuring the sustainability of land practices along with other planned disturbances, such as construction and mining.

UAV Thermal Mapping as a New Tool to Detect Subsurface Moisture and Document Baseline Environmental Conditions

“…These detailed images provide vegetation and soil moisture patterns along the surface route of the corridor for future comparison when the tunneling segments are bored and groundwater is potentially impacted when it underlies forest lands in the San Gabriel Mountains. Previous studies have shown that tunnels can create significant impacts on surface vegetation (Gallanes et al 1996;Behzad et al 2022;Miller et al 2022). The main objective of the study was to monitor several sites that could be used as a baseline study for assessing the future impact of the tunnel's changes in soil moisture and vegetation, but the site selected was in forested terrain and revealed new and valuable uses for the method.…”

“…2022; Miller et al. 2022). The main objective of the study was to monitor several sites that could be used as a baseline study for assessing the future impact of the tunnel's changes in soil moisture and vegetation, but the site selected was in forested terrain and revealed new and valuable uses for the method.…”

Effective Use of GCP in RPA Data Acquisition and Mapping

“…It is important to note here that ground truthing is a form of confirming on the ground what was noted in remotely sensed imagery, and often that can be done with GNSS technology that does not require a large degree of precision in terms of coordinate locations [24,25]. Ground control, however, differs from ground truthing in that the coordinate locations gathered by that GNSS hardware should be better than that of the RPA platform as they serve to correct both the horizontal and the vertical location of the imagery gathered [26]. Control points are points identified and established on the ground whose location is known with sub meter to sub centimeter accuracy.…”

SR-DeblurUGAN: An End-to-End Super-Resolution and Deblurring Model with High Performance

“…Furthermore, it is crucial to deal with biological invasions, and we need to effectively monitor invasive species monitoring, as they may affect the ecological balance and disrupt the biological habitat [7]. In terms of land management, the land cover should be assessed, such as bare ground, litter, green vegetation, destroyed vegetation, etc., to ensure that the land consolidation process is free from interference from other construction and mining operations [8]. The emergence of image restoration technology and its rapid development are due to the following reasons: firstly, the rapid development of computer technology and the increase in application fields have led to a deeper understanding of digital images; secondly, the current demand for high-quality images in agriculture, animal husbandry, forestry, industry and medicine is increasing.…”