1,184 research outputs found
Automated extraction of water bodies from NIR and RGB aerial imagery in northern Alaska using supervised and unsupervised machine learning techniques
Thawing and freezing of permafrost ground are affected by various reasons: air temperature,
vegetation, snow accumulation, subsurface physical properties, and moisture. Due to
the rising of air temperature, the permafrost temperature and the thermokarst activity increase.
Thermokarst instability causes an imbalance for the hydrology system, topography,
soils, sediment and nutrient cycle to lakes and streams. Hence the lakes and ponds are
ubiquitous in permafrost region. The plants and animals fulfil their nutrient needs from
water in the environment. Other animals acquire their needs from the plants and animals
that they consume. Therefore the influence of degradation of lakes and ponds strongly
affect biogeochemical cycles.
This research aims to implement an automated workflow to map the water bodies caused
by permafrost thawing. The scientific challenge is to test the machine learning techniques
adaptability to assist the observation and mapping of the water bodies using aerial imagery.
The study area is mainly located in northern Alaska and consists of five different locations:
Ikpikpuk, Teschekpuk Central, Teshekpuk East, Tesheckpuk West, Meade East, and Meade
West. To estimate the degradation of the high centred polygons distribution and potential
degradation of ice wedges, I mapped the polygonal terrain and ice-wedge melt ponds
using areal photogrammetry data of NIR and RGB bands captured by Thaw Trend Air
2019 flight campaign.
The techniques used are unsupervised K-mean classification, supervised segment mean
shift, and supervised random forest classification to model the water polygons from airborne
photogrammetry. There are two phases to perform the machine learning classification;
the first step is to test the accuracy of each technique and get to a conclusion about
the most adapted method. The second is to prepare the Orthomosaic data, run the chosen
workflow, and visualize the final results. The morphology filter with opening option application
and clean boundary filters are practical before classification as they sharpen the
image features. The conclusion is to use the Random forest classification as it was helpful
in all NIR Orthomosaics; however, the RGB images required downsampling to provide
adequate accuracy
Spectral Mixture Kernels with Time and Phase Delay Dependencies
Spectral Mixture (SM) kernels form a powerful class of kernels for Gaussian
processes, capable to discover patterns, extrapolate, and model negative
covariances. Being a linear superposition of quasi-periodical Gaussian
components, an SM kernel does not explicitly model dependencies between
components. In this paper we investigate the benefits of modeling explicitly
time and phase delay dependencies between components in an AM kernel. We
analyze the presence of statistical dependencies between components using
Gaussian conditionals and posterior covariance and use this framework to
motivate the proposed SM kernel extension, called Spectral Mixture kernel with
time and phase delay Dependencies (SMD). SMD is constructed in two steps:
first, time delay and phase delay are incorporated into each base component;
next, cross-convolution between a base component and the reversed complex
conjugate of another base component is performed which yields a complex-valued
and positive definite kernel representing correlations between base components.
The number of hyper-parameters of SMD, except the time and phase delay ones,
remains equal to that of the SM kernel. We perform a thorough comparative
experimental analysis of SMD on synthetic and real-life data sets. Results
indicate the beneficial effect of modeling time and phase delay dependencies
between base components, notably for natural phenomena involving little or no
influence from human activity.Comment: 28 page
Data Requirements for Oceanic Processes in the Open Ocean, Coastal Zone, and Cryosphere
The type of information system that is needed to meet the requirements of ocean, coastal, and polar region users was examined. The requisite qualities of the system are: (1) availability, (2) accessibility, (3) responsiveness, (4) utility, (5) continuity, and (6) NASA participation. The system would not displace existing capabilities, but would have to integrate and expand the capabilities of existing systems and resolve the deficiencies that currently exist in producer-to-user information delivery options
Third Earth Resources Technology Satellite Symposium. Volume 3: Discipline summary reports
Presentations at the conference covered the following disciplines: (1) agriculture, forestry, and range resources; (2) land use and mapping; (3) mineral resources, geological structure, and landform surveys; (4) water resources; (5) marine resources; (6) environment surveys; and (7) interpretation techniques
Literature review of the remote sensing of natural resources
Abstracts of 596 documents related to remote sensors or the remote sensing of natural resources by satellite, aircraft, or ground-based stations are presented. Topics covered include general theory, geology and hydrology, agriculture and forestry, marine sciences, urban land use, and instrumentation. Recent documents not yet cited in any of the seven information sources used for the compilation are summarized. An author/key word index is provided
Earth Resources, A Continuing Bibliography with Indexes
This bibliography lists 460 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1984. 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
Quarterly literature review of the remote sensing of natural resources
The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports
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