Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 34 for “"multispectral imagery"”.
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Cloud analysis using NOAA-7 AVHRR multispectral imagery
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric and Planetary Sciences, 1984.
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Site-Specific In-Season Nitrogen Management Using Drone Multispectral Imagery And Proximal Sensing
… While the research focused mainly on UAV-based multispectral sensing, we were able to use proximal sensing and hyperspectral sensing in a section of this study. This dissertation is organized in five independent chapters as follows:In the first chapter, we cover the research that took place in …
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Determining estuarine seagrass density measures from low altitude multispectral imagery flown by remotely piloted aircraft
… sensing methods using satellite and aircraft imagery enable mapping of seagrass populations at landscape scale. Aerial monitoring of a seagrass population can require imagery of high spatial and/or spectral resolution for successful feature extraction across all levels of seagrass density. …
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Phenotyping Canola (Brassica napus L.) Agronomic Traits and Estimating Seed Yield Using Unoccupied Aerial Vehicle (UAV)-based Multispectral Imagery
… such as unoccupied aerial vehicles (UAVs) and multispectral sensors, desirable phenotypic traits and seed yield can be estimated digitally. In this thesis, the main objective was to develop an efficient and non-destructive method to estimate canola flowering number, flowering layer depth, …
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Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario
… First, in my thesis the potential of UAV-based imagery was investigated to monitor spatial and temporal variation of crop status in comparison with RapidEye. The correlation between red-edge indices and LAI and biomass are higher for UAV-based imagery than that of RapidEye. Secondly, the …
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Intra-field Nitrogen Estimation for Wheat and Corn using Unmanned Aerial Vehicle-based and Satellite Multispectral Imagery, Plant Biophysical Variables, Field Properties, and Machine Learning Methods
… study is to use Unmanned Aerial Vehicle (UAV) multispectral imagery, PlanetScope satellite imagery, vegetation indices (VI), crop height, leaf area index (LAI), field topographic metrics, and soil properties to predict canopy nitrogen weight (g/m2) of corn and wheat fields in southwestern …
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Analysis of Multiresolution Data fusion Techniques
… years, as the availability of remote sensing imagery of varying resolution has increased, merging images of differing spatial resolution has become a significant operation in the field of digital remote sensing. This practice, known as data fusion, is designed to enhance the spatial resolution …
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Techniques for Processing Airborne Imagery for Multimodal Crop Health Monitoring and Early Insect Detection
… of UAV remote sensing using visible spectrum and multispectral imagery. An algorithm has been developed to work on a server for the remote processing of images acquired of a crop field with a UAV. This algorithm first enhances the images to adjust the contrast and then classifies areas of the …
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Airborne multispectral and hyperspectral remote sensing techniques in archaeology: a comparative study
… are to test to what extent hyperspectral and multispectral imagery can reveal otherwise invisible archaeological sites surviving as cropmarks; to assess the relative usefulness of the different sensors employed; and to investigate the potential of hyperspectral and multispectral imagery to …
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Fusion Approaches to Individual Tree Species Classification Using Multi-Source Remotely Sensed Data
… Random Forest (RF) algorithms to incorporating multispectral imagery (MSI), a very high spatial resolution panchromatic image (PAN), and Light Detection and Ranging (LiDAR) data for five object-based tree species classification in an urban environment. The results demonstrated that 3D structural …
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Multispectral Image Labeling for Unmanned Ground Vehicle Environments
Described is the development of a multispectral image labeling system with emphasis on Unmanned Ground Vehicles(UGVs). UGVs operating in unstructured environments face significant problems detecting viable paths when LIDAR is the sole source for perception. Promising advances in computer vision and …
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Assessment of the spatial variability of vegetative status in vineyards using non-destructive sensors: Application of remote and proximal sensing technologies in precision viticulture
… of a remotely piloted aerial system (RPAS) multispectral imagery was tested to assess the vegetative growth of a vineyard. A special focus was set on proximal sensing, especially on a fluorescence sensor used either manually and on-the-go, to determine chlorophyll, flavonol and nitrogen …
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Classification of Plot-Level Fire-Caused Tree Mortality in a Redwood Forest Using Digital Orthophotography and Lidar
… mortality resulting from the fire using digital multispectral imagery and LiDAR. The percent mortality of trees at least 25.4 cm (10”) DBH was aggregated to three classes (0-25, 25-50, and 50-100%). Three separate Classification Analysis and Regression Tree (CART) models were created to classify …
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Analyzing remote sensing-derived normal difference vegetation index to predict coastal protection by Spartina alterniflora
… Vegetation Index (NDVI) extracted from drone multispectral imagery was compared to measured stem count and estimated biomass. The study compared two different years and three time points within a growing season [August 2022; June, August, October 2023). In addition, at three plots the stem …
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Developing a Satellite-Based Methodology to Estimate Built-up Biocapacity for Use in the National Ecological Footprint and Biocapacity Accounts: A Comparative Study of Pléiades Neo and Sentinel-2 Imagery, Classification Algorithms, and Segmentation Approaches
… and segmentation technique on the results. Multispectral imagery from Pléiades Neo (1.2-meter resolution) and Sentinel-2 (10-meter resolution) provided the basis for classification into land cover categories. Identified land cover categories within the built-up fabric were transformed to …
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Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data
Landsat-7 ETM+ (SLC-off) multispectral satellite imagery was tested to identify and delineate natural stands of wild rice (Zizania palustris L.) from other aquatic vegetation growing on area lakes of the Leech Lake Native American reservation in northern Minnesota. Leech Lake is located within the …
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Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data
Landsat-7 ETM+ (SLC-off) multispectral satellite imagery was tested to identify and delineate natural stands of wild rice (Zizania palustris L.) from other aquatic vegetation growing on area lakes of the Leech Lake Native American reservation in northern Minnesota. Leech Lake is located within the …
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Terrain characterization for site selection and preparation
… ResNet, and MobileNet) were modified to include multispectral imagery and compared. Seven land cover classes were determined with an accuracy of 82.71% by model ResNet/SegNet. To determine soil moisture content (SMC), ten models were developed to predict soil moisture – two machine learning …
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Airborne monitoring system for in-season agriculture : operational considerations and image processing for wide-area sensing
Remote sensing, in particular multispectral imagery, can measure crop health and detect in-season disturbances such as pests and diseases before they are visible to the naked eye, but it is inaccessible to small-plot farmers, especially in developing countries. So-called eExtension services provide …
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