The American Society for Photogrammetry and Remote Sensing (ASPRS) has released a call for posters for the fast-approaching UAS MAPPING 2015 RENO symposium which will be held at the Reno Ballroom in downtown Reno on September 29-30. The symposium is focused on education and collaboration on UAS technology and its application to the survey, mapping and remote sensing field. Industry experts from the private sector, academia and the government will present practical information on flight planning, mission control, acquisition and data processing for data analysis and production of mapping products. View Conference Program.
A poster session is currently being organized which will provide another means of information exchange in addition to the general sessions, exhibitions, networking sessions and live demonstrations already organized. Poster sessions will be held concurrently with blocks of time allocated for networking and exhibition. A committee will review the applications and select poster session presenters from the pool of applicants. Poster presenters will receive a discounted registration!
Posters are to follow guidelines for standard technical/research format. The poster space is 48” height x 96” width with a recommended poster size of 42”x90”.
Please email poster applications to firstname.lastname@example.org. This is an excellent opportunity to highlight your UAS technologies, applications, research and development, and real-life project experiences!
Igno Breukers, Quest Innovations
Igno Breukers CCO of Quest Group with a personal focus on and interest for UAV multi-spectral and hyperspectral imaging applications.
Abstract – Prism Based Multi-Sensor Multispectral Imaging in UAVs
Quest Innovations has been the leading company since 1998 in the market for 3-CCD and 5-CCD Multi-/Hyperspectral prism-based camera technology for multiple 100% aligned images in various bandwidths (RGB, IR and Thermal a.o.) generated from the same area. In this field Quest has also developed UAV camera’s with on-board storage for applications such as remote sensing, precision agriculture, oil detection and aerial cartography. With the release of the Condor3 UAV camera Quest Innovations has opened the door to the masses looking for an uncompromising, ultra-lightweight, smart data-gathering 3-CCD HD Multispectral Imager at an unprecedented price level. Recently Quest performed a PoC project for FKMCD (Florida Keys Mosquito Control Department), in need of a solution capable of detecting water (mosquito breeding habitat) below a canopy of vegetation to be flown by UAVs. With usage of our NDVI filtered VisNirNir Multispectral UAV camera with extra thermal sensor our aim was to deduce the presence of waterpools/breeding habitats by differentiating between vegetation standing in water as opposed to those standing on dry soil. Our aim is to present the results with our Condor3-UAVcamera.
Duke Bulanon, Northwest Nazarene University
Dr. Duke M Bulanon is an assistant professor of Physics and Engineering Department at Northwest Nazarene University (Nampa, Idaho).
Abstract – Automatic Detection of Individual Trees in an Apple Orchard Using Modified Watershed Algorithm
Evolving precision agriculture techniques are complicated by the tight spacing of many crops which are cultivated in rows. Since the need for closely grown plants is dictated by the need to conserve resources and is a preexisting condition in current fields and orchards the development of computer-vision algorithms to identifying and analyzing individual plants in crowded growing environments is necessary. One such algorithm has been developed to work with aerial apple orchard images in order to identify and analyze individual trees with respect to published vegetation health indices. Working with multispectral images (NIR band, green band, blue band) taken one-hundred meters above the orchard, the algorithm slices the image into individual rows for subroutine analysis. Working with each row separately the algorithm utilizes a variety of methods to develop a matrix of favorable tree intersection points. The methods include: canopy profile matching, threshold concavity measurements, and maximum intensity values in vegetation health indices. Once the intersection points are determined markers are created to be used in a gradient modified, marker-controlled watershed segmentation algorithm in order to divide each row into individual tree canopy profiles. This data is then available to measure the vegetation health indices and trends plant coloration for each individual tree in the orchard. These algorithms provide novel and innovated methods for target crop analysis that will help enable precision agriculture’s expansion and broader application.
Sharon Dulava, Humboldt State University
Sharon Dulava is a master’s student in the Department of Wildlife at Humboldt State University.
Abstract – Fine scale change detection using unmanned aircraft systems (UAS) to inform reproductive biology in nesting birds
In May 2015, U.S. Fish and Wildlife Service collaborated with the U.S. Geological Survey National Unmanned Aircraft Systems Project Office, the Pyramid Lake Paiute Tribe and researchers from Humboldt State University to conduct a series of flights over nesting bird colonies at Anaho Island National Wildlife Refuge. We used UAS imagery to detect fine scale changes in bird movement that were used to differentiate active nests from non-nesting birds, a critical first step to assessing reproductive success.
Grzegorz Jozkow, The Ohio State University
Grzegorz Jozkow received his PhD in Photogrammetry and Remote Sensing from the Wroclaw University of Environmental and Life Sciences (Poland) in 2010, and is a post-doctoral researcher at The Ohio State University.
Abstract – Analysis of point cloud generated from LiDAR UAS data
Mapping with the UAS is typically performed with consumer grade cameras. Acquired data allows to create very dense point clouds and subsequent products. Besides many advantages, UAS imagery meets limitations, such as lack of vegetation penetration, difficulty with matching on surfaces having insufficient texture, etc. In these cases, the alternative is the LiDAR UAS data. It is getting more popular in UAS due to sensor miniaturization, lower costs, and availability of the sufficient grade navigation sensors that are necessary for LiDAR data georeferencing. This work reports about the experiences related to the processing of UAS acquired navigation and LiDAR data to obtain georeferenced point cloud. The test data was collected with the octocopter platform equipped with a Velodyne laser scanner, dual-frequency GPS receiver and MEMS IMU sensor. Due to more dynamic platform motion, the GPS/IMU data integration presented challenges to the trajectory reconstruction. The analysis of the georeferenced LiDAR point cloud was executed by comparing it to point clouds created by the dense image matching. Comparison showed that the LiDAR product, though more sparse and not containing RGB information, was more complete. LiDAR points were collected on objects having low texture, or even on the trees where the dense image matching failed due to movement of trees.
Karla King is a UAS practitioner.
Abstract –Ground Truthing Automated Change Detection in El Dorado National Forest Using UAS
This research project detects change in forest cover in El Dorado National Forest. The method analyzes Landsat 8 data in Google Earth Engine and employs a drone to perform ground truthing for the resulting map. My poster highlights the use of a DJI Phantom 3 Advanced in addition to traditional field data-collection methods to conduct the accuracy assessment of the study.
Omer Mian, Applanix
Omer Mian is Product Manager for Applanix’ DMS (Direct Mapping Solution for UAVs)
Abstract – Commercial Operations of UAS in Canada – 2015
Efficient mapping from unmanned aerial platforms cannot rely on aerial triangulation using known ground control points. The cost and time of setting ground control, added to the need for increased overlap within and between flightlines, severely limits the ability of small VTOL platforms, in particular, to handle mapping-grade missions of all but the very smallest survey areas. Applanix has brought its experience in manned photogrammetry applications to this challenge, setting out the requirements for increasing the efficiency of mapping operations from small UAVs, using survey-grade GNSS-inertial technology to accomplish direct georeferencing of the platform and/or the imaging payload.
Farid Navadnejad, Matthew N. Gillins, Daniel T. Gillins, PhD
Farid Javadnejad is a Doctoral Student in Geomatics Engineering also a Graduate Research Assistant in School of Civil and Construction Engineering at the Oregon State University.
Matthew N. Gillins is a Graduate Research Assistant at Oregon State University currently pursuing a Master’s degree in Civil and Construction Engineering within the Geomatics Engineering group.
Daniel Gillins in an Assistant Professor in the School of Civil and Construction Engineering at Oregon State University.
Abstract – UAS-based Photogrammetry for natural disasters damage mapping
Remote sensing is a valuable tool for mapping and assessing damage after a natural disaster. While satellite imagery is ideal for a large geographical scale and mobile terrestrial laser scanning (MTLS) is appropriate for a street-view scale, rapidly emerging Unmanned Aerial System (UAS) technology has great potential for bridging the scale gap between these two sources of data. The low altitude maneuvering capabilities of micro UAS make it possible to perform high spatio-temporal resolution imaging and mapping at a site scale. UAS data is even more favorable when the study area is not accessible for MTLS, or when the resolution of satellite imagery is too coarse. This study is an example of the application of UAS photogrammetry for mapping earthquake damage. The area of interest is the historic village of Bungamati in Nepal (an area of 0.14 km2), which was severely damaged due to the magnitude 7.8 Gorkha earthquake of 2015. In order to map the damaged buildings, the village was surveyed using a micro UAS that carried a consumer grade digital camera for acquiring aerial images. The images were processed using the Structure-from-Motion (SfM) technique, which resulted in a 3D reconstruction and an ortho-rectified aerial photograph of the study area. In order to geo-reference these products to a global coordinate system, ground control points were used as determined by a static differential GNSS survey using dual-frequency GNSS receivers. The products were then utilized to delineate structural failures in areas of interest with GIS tools. The results of this study show that UAS-based photogrammetry is a feasible, high resolution alternative for post-disaster mapping.
Kurtis Poettcker & Brian Mazurkewich, Abacus DataGraphics
Kurtis Poettcker GISP has an MSc in Geographical Information Science from the University of London. Brian Mazurkewich is a Civil Engineering Technologist graduate from SIAST and has worked at Abacus for 20 years.
Abstract – UAS for pipeline watercourse depth-of-cover inspections
Our poster details the procedure used by Abacus Datagraphics Ltd. for performing pipeline water course depth of cover inspections. This process involves determining the crossing location, locating the pipeline, tying in data with RTK GPS, capturing the site with a suav, compiling all collected data into a crossing map and delivering both digital and hard copies. The focus of the poster will be the role the suav data plays in enhancing the final product.
Dr. Balaji Ramachandran, Nicholls State University
Dr. Balaji Ramachandran is Head and Associate Professor, Department of Applied Sciences, at Nicholls State University in Thibodaux, Louisiana.
Abstract – Nicholls State University sUAS Program 2005-Present-Future
Nicholls Geomatics program started investigating the adoption of emerging UAS technology in the Post- Katrina era for monitoring and mapping the coast. Since its inception as a research endeavor in 2005, the sUAS program has grown into a mature component of Geomatics and Biological Sciences program instruction and research. The ongoing research projects include characterization of Louisiana barrier islands, offshore platform inspection, precision-agriculture, and infrastructure monitoring. A sUAS certification program is being designed to prepare students in UAS related careers.
Atena Haghighattalab, University of Kansas
Atena Haghighattalab is a PhD Candidate in the Geography Department, Graduate Research Assistant, Plant Pathology Department, Kansas State University.
Abstract – Review Different Types of UASs and Sensors and Compare Their Performance with Ground-Truth Reflectance Data
Applying emerging technologies in remote sensing field, such as UAS, can provide adequate resolution for phenotyping studies, offering higher resolution sensing, multiple view-angles, control illumination and the ability to regulate the distance from the target to the sensors. We developed a semi-automate pipeline for collecting UAS data and processing UAS’s imagery to extract plot level data from aerial images. We also examined the relationship between ground truth spectral data and NDVI from ultra-high spatial resolution multispectral imagery collected by different UAS systems. This study was conducted at International Maize and Wheat Improvement Center (CIMMYT) in Mexico.
Tiebiao Zhao, University of California at Merced
Tiebiao Zhao is with Mechatronics, Embedded Systems and Automation (MESA) Lab
Abstract – Low Cost Scientific Data Drones for Enhanced Melon Productivity and Security
Abstract: We propose a project in precision agriculture using unmanned aerial vehicle (UAV) to help manage melon production. A UAV platform capable of multispectral imaging serves the data collection purpose for making management decisions. Firstly, real-time imagery with high spatial resolution (centimeters) can be acquired for growing melon by red, green, blue(RGB), near infrared (NIR) and thermal infrared (TIR) cameras. Then information about water stress and status of crop can be extracted for irrigation, precision application of insecticide, fungicide and herbicide, respectively. In addition, pre-harvest and harvest yield estimation will be given for production decisions.