The use of multispectral sensing techniques to detect ponderosa pine trees under stress from insect or pathogenic organisms Annual progress report

Ground and aerial imaging techniques to detect tree damage caused by bark beetles in forested area

Hyperspectral, thermal and LiDAR remote sensing for red band needle blight detection in pine plantation forests

PhD ThesisClimate change indirectly affects the distribution and abundance of forest insect pests and pathogens, as well as the severity of tree diseases. Red band needle blight is a disease which has a particularly significant economic impact on pine plantation forests worldwide, affecting diameter and height growth. Monitoring its spread and intensity is complicated by the fact that the diseased trees are often only visible from aircraft in the advanced stages of the epidemic. There is therefore a need for a more robust method to map the extent and severity of the disease. This thesis examined the use of a range of remote sensing techniques and instrumentation, including thermography, hyperspectral imaging and laser scanning, for the identification of tree stress symptoms caused by the onset of red band needle blight. Three study plots, located in a plantation forest within the Loch Lomond and the Trossachs National Park that exhibited a range of red band needle blight infection levels, were established and surveyed. Airborne hyperspectral and LiDAR data were acquired for two Lodgepole pine stands, whilst for one Scots pine stand, airborne LiDAR and Unmanned Aerial Vehicle-borne (UAV-borne) thermal imagery were acquired alongside leaf spectroscopic measurements. Analysis of the acquired data demonstrated the potential for the use of thermographic, hyperspectral and LiDAR sensors for detection of red band needle blight-induced changes in pine trees. The three datasets were sensitive to different disease symptoms, i.e. thermography to alterations in transpiration, LiDAR to defoliation, and hyperspectral imagery to changes in leaf biochemical properties. The combination of the sensors could therefore enhance the ability to diagnose the infection.Natural Environment Research Council (NERC) for funding this PhD program (studentship award 1368552) and providing access to specialist equipment through a Field Spectroscopy Facility loan (710.114). I would like to thank NERC Airborne Research Facility for providing airborne data (grant: GB 14-04) that made the PhD a challenge, to say the least. My sincere gratitude goes to the Douglas Bomford Trust for providing additional funds, which allowed for completion of the UAV-borne part of this research

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challengespublishersversionPeer reviewe

A review of current and potential applications of remote sensing to study the water status of horticultural crops

Published: 17 January 2020With increasingly advanced remote sensing systems, more accurate retrievals of crop water status are being made at the individual crop level to aid in precision irrigation. This paper summarises the use of remote sensing for the estimation of water status in horticultural crops. The remote measurements of the water potential, soil moisture, evapotranspiration, canopy 3D structure, and vigour for water status estimation are presented in this comprehensive review. These parameters directly or indirectly provide estimates of crop water status, which is critically important for irrigation management in farms. The review is organised into four main sections: (i) remote sensing platforms; (ii) the remote sensor suite; (iii) techniques adopted for horticultural applications and indicators of water status; and, (iv) case studies of the use of remote sensing in horticultural crops. Finally, the authors’ view is presented with regard to future prospects and research gaps in the estimation of the crop water status for precision irrigation.Deepak Gautam and Vinay Paga

On the Use of Unmanned Aerial Systems for Environmental Monitoring

[EN] Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.The present work has been funded by the COST Action CA16219 "HARMONIOUS-Harmonization of UAS techniques for agricultural and natural ecosystems monitoring". B. Toth acknowledges financial support by the Hungarian National Research, Development and Innovation Office (NRDI) under grant KH124765. J. Millerovd was supported by projects GA17-13998S and RVO67985939. Isabel and Jodo de Lima were supported by project HIRT (PTDC/ECM-HID/4259/2014-POCI-0145-FEDER016668).Manfreda, S.; Mccabe, MF.; Miller, PE.; Lucas, R.; Pajuelo Madrigal, V.; Mallinis, G.; Ben Dor, E.... (2018). On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sensing. 10(4):1-28. https://doi.org/10.3390/rs10040641S12810

Using a Remotely Piloted Aircraft System to Investigate the Relationship between Canopy Temperature Depression and American Beech Health in Southern Ontario

The unprecedented spread of invasive pest and pathogens, along with climate change and human activity/development is degrading forest system health. American beech trees are a principal tree species that dominates Ontario’s hardwood forests, yet are declining in numbers, primarily due to diseases such as beech bark disease and beech leaf disease, but also because of human development in environmentally sensitive forests. To better monitor American beech (Fagus grandifolia) health and identify severely deteriorated trees, innovative technologies such as Remotely Piloted Aircrafts (RPAs) can be utilized to complement the data collected by mid-altitude aerial aircrafts and ground-based surveys. Existing research has demonstrated the potential for RPA based thermography, which measure individual canopy temperature readings, to identify trees that are under water stress because of factors such as drought and foliar, stem and/or root diseases. However, whether American beech trees displaying noticeable signs in decline in health, due to factors such as foliar, stem and/or root diseases, can be differentiated from trees showing little to no sign in decline is yet to be determined by RPA-borne thermal imaging. This paper investigates whether RPA-borne thermal imaging can be a useful tool to monitor American beech tree health in Southern Ontario forests. The study was located at rare Charitable Research Reserve in Cambridge, Ontario, in semi-naturalized forests. A total of 29 American beech trees across eight different plots were included in the sample for the study and were given a health level of either “healthy”, “fair” or “poor” based on the presence/severity of beech bark disease, severity of bark deterioration and limb loss, and canopy coverage estimated as a percentage based on RPA visual imagery. In August of 2020, thermal imagery was collected on five different days: August 6th, 7th, 15th, 19th, and 26th, and in the following year was collected on three different days: August 2nd, 3rd, and 4th. Canopy temperatures of each individual beech tree was retrieved, normalized based on air temperature (canopy temperature depression) and analyzed to determine whether canopy temperature readings significantly differed based on health level. This study found that increasing American beech tree canopy temperatures were not correlated with deteriorating health. The one-way ANOVA performed for most flights showed that canopy temperature readings did not significantly change based on the recorded tree health level

Infrared Imagery Scanning Systems For Censusing Big Game

The primary objective of this study was to explore the potential of an airborne infrared scanner for the census of mule deer (Odocoileus hemionus) and elk (Cervus canadensis) in the Intermountain West. Flight altitude was varied in hopes of achieving species separation, and ground studies were conducted, using a hand-held radiometer and captive deer, to find the optimum time of morning to census. The problems and potentialities of infrared imagery scanning systems for censusing big game are discussed and compared to visual aerial census methods

NASA Thesaurus. Volume 1: Hierarchical listing

There are 16,713 postable terms and 3,716 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary