115 research outputs found
Remote Sensing in Agriculture: State-of-the-Art
The Special Issue on “Remote Sensing in Agriculture: State-of-the-Art” gives an exhaustive overview of the ongoing remote sensing technology transfer into the agricultural sector. It consists of 10 high-quality papers focusing on a wide range of remote sensing models and techniques to forecast crop production and yield, to map agricultural landscape and to evaluate plant and soil biophysical features. Satellite, RPAS, and SAR data were involved. This preface describes shortly each contribution published in such Special Issue
Earth Observatory Satellite (EOS) Definition Phase Report, Volume 1
System definition studies were conducted of the Earth Observatory Satellite (EOS). The studies show that the concept of an Earth Observatory Satellite in a near-earth, sun-synchronous orbit would make a unique contribution to the goals of a coordinated program for acquisition of data for environmental research with applications to earth resource inventory and management. The technical details for the proposed development of sensors, spacecraft, and a ground data processing system are presented
Earth Resources: A continuing bibliography with indexes (Issue 37)
This bibliography lists 512 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1983. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis
Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis
Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters
Earth resources: A continuing bibliography with indexes
This bibliography lists 579 reports, articles, and other documents introduced into the NASA scientific and technical information system. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis
Earth resources: A continuing bibliography with indexes (issue 62)
This bibliography lists 544 reports, articles, and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1989. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis
The Use of Hyperspectral Imaging for Remote Sensing, and the Development of a Novel Hyperspectral Imager
This thesis determines the potential uses of a novel technology in hyperspectral remote sensing, by
testing the capabilities of a prototype imaging spectrometer that was built using microslice technology.
These capabilities are compared to those of current hyperspectral remote sensing instruments in the
context of the requirements for various remote sensing applications. Due to the wide variety of potential
applications for hyperspectral imaging, any unique capability of a new instrument is likely to improve
a current application, or even develop a new one.
The use of microslice technology allows a 2-dimensional eld of view (FoV) to be imaged simultane
ously with a wide spectral range. Modelling of the remote sensing performance of the spectrometer
shows that this enables it to achieve a signal to noise ratio (SNR) an order of magnitude higher than
conventional hyperspectral instruments. The prototype microslice spectrometer images in the 475-650
nm wavelength range at 7 nm spectral resolution. It also images an instantaneous eld of view (IFoV)
of 260 x 52 mrad, at a spatial resolution of 2.6 mrad. Classication techniques are used on ground
based laboratory and eld test data from the instrument to demonstrate that it can accurately identify
some mineral, vegetation, and water pollutant samples.
Various trade-os can theoretically be performed on the prototype specications to develop an instru
ment with particular capabilities for a specic application. This novel design means that a greater
detector area is required than for conventional designs; but the 2-dimentsional FoV gives greater
trade-o exibility, in particular allowing the SNR to enter into the trade-o equation. This unique
capability was found to lend itself to two applications in particular: detecting water pollutants in
rivers, and detecting hydrocarbons contamination of ecosystems
Exploring Hyperspectral Imaging and 3D Convolutional Neural Network for Stress Classification in Plants
Hyperspectral imaging (HSI) has emerged as a transformative technology in imaging, characterized by its ability to capture a wide spectrum of light, including wavelengths beyond the visible range. This approach significantly differs from traditional imaging methods such as RGB imaging, which uses three color channels, and multispectral imaging, which captures several discrete spectral bands. Through this approach, HSI offers detailed spectral signatures for each pixel, facilitating a more nuanced analysis of the imaged subjects. This capability is particularly beneficial in applications like agricultural practices, where it can detect changes in physiological and structural characteristics of crops. Moreover, the ability of HSI to monitor these changes over time is advantageous for observing how subjects respond to different environmental conditions or treatments. However, the high-dimensional nature of hyperspectral data presents challenges in data processing and feature extraction. Traditional machine learning algorithms often struggle to handle such complexity. This is where 3D Convolutional Neural Networks (CNNs) become valuable. Unlike 1D-CNNs, which extract features from spectral dimensions, and 2D-CNNs, which focus on spatial dimensions, 3D CNNs have the capability to process data across both spectral and spatial dimensions. This makes them adept at extracting complex features from hyperspectral data. In this thesis, we explored the potency of HSI combined with 3D-CNN in agriculture domain where plant health and vitality are paramount. To evaluate this, we subjected lettuce plants to varying stress levels to assess the performance of this method in classifying the stressed lettuce at the early stages of growth into their respective stress-level groups. For this study, we created a dataset comprising 88 hyperspectral image samples of stressed lettuce. Utilizing Bayesian optimization, we developed 350 distinct 3D-CNN models to assess the method. The top-performing model achieved a 75.00\% test accuracy. Additionally, we addressed the challenge of generating valid 3D-CNN models in the Keras Tuner library through meticulous hyperparameter configuration. Our investigation also extends to the role of individual channels and channel groups within the color and near-infrared spectrum in predicting results for each stress-level group. We observed that the red and green spectra have a higher influence on the prediction results. Furthermore, we conducted a comprehensive review of 3D-CNN-based classification techniques for diseased and defective crops using non-UAV-based hyperspectral images.MITACSMaster of Science in Applied Computer Scienc
Earth Resources. A continuing bibliography with indexes, issue 34, July 1982
This bibliography lists 567 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System between April 1, and June 30, 1982. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis
The Multispectral Imaging Science Working Group. Volume 3: Appendices
The status and technology requirements for using multispectral sensor imagery in geographic, hydrologic, and geologic applications are examined. Critical issues in image and information science are identified
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