Fractional coverage rather than green chromatic coordinate is a robust indicator to track grassland phenology using smartphone photography

2021 ◽  
pp. 101544
Author(s):  
Zunchi Liu ◽  
Kai Liu ◽  
Jingjing Zhang ◽  
Chuang Yan ◽  
T. Ryan Lock ◽  
...  
Keyword(s):  
Fractional Coverage

scholarly journals Construction of a Landscape Ecological Network for a Large-Scale Energy and Chemical Industrial Base: A Case Study of Ningdong, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 344
Author(s):  
Haochen Yu ◽  
Jiu Huang ◽  
Chuning Ji ◽  
Zi’ao Li
Keyword(s):  
Ecological Restoration ◽  
Large Scale ◽  
Ecological Environment ◽  
Ecological Network ◽  
High Importance ◽  
Fractional Coverage ◽  
Industrial Base ◽  
Ecological Corridors ◽  
Vegetation Fractional Coverage

A large-scale energy and chemical industry base is an important step in the promotion of the integrated and coordinated development of coal and its downstream coal-based industry. A number of large-scale energy and chemical industrial bases have been built in the Yellow River Basin that rely on its rich coal resources. However, the ecological environment is fragile in this region. Once the eco-environment is destroyed, the wildlife would lose its habitat. Therefore, this area has attracted wide attention regarding the development of the coal-based industry while also protecting the ecological environment. An ecological network could improve landscape connectivity and provide ideas for ecological restoration. This study took the Ningdong Energy and Chemical Industrial Base as a case study. Morphological spatial pattern analysis was applied to extract core patches. The connectivity of the core patches was evaluated, and then the ecological source patches were recognized. The minimum cumulative resistance model, hydrologic analysis and circuit theory were used to simulate the ecological network. Then, ecological corridors and ecological nodes were classified. The results were as follows: (1) The vegetation fractional coverage has recently been significantly improved. The area of core patches was 22,433.30 ha. In addition, 18 patches were extracted as source patches, with a total area of 9455.88 ha; (2) Fifty-eight potential ecological corridors were simulated. In addition, it was difficult to form a natural ecological corridor because of the area’s great resistance. Moreover, the connectivity was poor between the east and west; (3) A total of 52 potential ecological nodes were simulated and classified. The high-importance nodes were concentrated in the western grassland and Gobi Desert. This analysis indicated that restoration would be conducive to the ecological landscape in this area. Furthermore, five nodes with high importance but low vegetation fractional coverage should be given priority in later construction. In summary, optimizing the ecological network to achieve ecological restoration was suggested in the study area. The severe eco-environmental challenges urgently need more appropriate policy guidance in the large energy and chemical bases. Thus, the ecological restoration and ecological network construction should be combined, the effectiveness of ecological restoration could be effectively achieved, and the cost could also be reduced.

An asperity-based fractional coverage model for transfer films on a tribological surface

Wear ◽  
2011 ◽  
Vol 270 (3-4) ◽  
pp. 127-139 ◽  
Author(s):  
E.Y.A. Wornyoh ◽  
C.F. Higgs
Keyword(s):  
Fractional Coverage ◽  
Transfer Films ◽  
Coverage Model

scholarly journals Vegetation fractional coverage change in a typical oasis region in Tarim River Watershed based on remote sensing

2012 ◽  
Vol 5 (1) ◽  
pp. 89-101 ◽  
Author(s):  
Fei Zhang ◽  
Tashpolat Tiyip ◽  
JianLi Ding ◽  
Mamat Sawut ◽  
Verner Carl Johnson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Tarim River ◽  
Fractional Coverage ◽  
River Watershed ◽  
Vegetation Fractional Coverage

scholarly journals A map of global peatland distribution created using machine learning for use in terrestrial ecosystem and earth system models

2017 ◽  
Author(s):  
Yuanqiao Wu ◽  
Ed Chan ◽  
Joe R. Melton ◽  
Diana L. Verseghy
Keyword(s):  
Machine Learning ◽  
Statistical Model ◽  
Machine Learning Method ◽  
Learning Method ◽  
Earth System ◽  
Geophysical Field ◽  
Fractional Coverage ◽  
System Models ◽  
Earth System Models ◽  
Global Carbon

Abstract. Peatlands store large amounts of soil carbon and constitute an important component of the global carbon cycle. Accurate information on the global extent and distribution of peatlands is presently lacking but it important for earth system models (ESMs) to be able to simulate the effects of climate change on the global carbon balance. The most comprehensive peatland map produced to date is a qualitative presence/absence product. Here, we present a spatially continuous global map of peatland fractional coverage using the extremely randomized tree machine learning method suitable for use as a prescribed geophysical field in an ESM. Inputs to our statistical model include spatially distributed climate data, soil data and topographical slopes. Available maps of peatland fractional coverage for Canada and West Siberia were used along with a proxy for non-peatland areas to train and test the statistical model. Regions where the peatland fraction is expected to be zero were estimated from a map of topsoil organic carbon content below a threshold value of 13 kg/m2. The modelled coverage of peatlands yields a root mean square error of 4 % and a coefficient of determination of 0.91 for the 10,978 tested 0.5 degree grid cells. We then generated a complete global peatland fractional coverage map. In comparison with earlier qualitative estimates, our global modelled peatland map is able to reproduce peatland distributions in places remote from the training areas and capture peatland hot spots in both boreal and tropical regions, as well as in the southern hemisphere. Additionally we demonstrate that our machine-learning method has greater skill than solely setting peatland areas based on histosols from a soil database.

An Asperity-Based Fractional Coverage Model for Solid Lubricant Film Transfer on a 3D Surface

2007 ◽  
Author(s):  
E. Y. A. Wornyoh ◽  
C. F. Higgs
Keyword(s):  
Friction Coefficient ◽  
Control Volume ◽  
Lubricant Film ◽  
Wear Factor ◽  
Fractional Coverage ◽  
Disk Interface ◽  
Coverage Model ◽  
Powder Lubrication ◽  
Topography Data ◽  
Tribological Parameters

Topography data was obtained from an aluminum thin film deposited unto a substrate. Using this 20 μm × 20 μm specimen, an asperity-based fractional coverage model was used to predict (1) the friction coefficient at a pad/disk interface (2) the thickness of deposited lubricant film and (3) the wear factor for a compacted lubricant pellet in sliding contact. The fractional coverage varies with time and is a useful modeling parameter for quantifying the amount of third body film covering the disk asperities. The model was based on a previous 1-D control volume fractional coverage model which was used to glean tribological parameters including friction coefficient and wear factor. In this model, the wear rate of the pellet, pad friction coefficient, and lubricant thickness can be determined as a function of the pellet load, slider pad load, disk speed, and material properties. Steady-state results from the model adequately predict the self-repairing and self-replenishing nature of powder lubrication as a function of topography.

scholarly journals Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

2016 ◽  
Vol 9 (1) ◽  
pp. 323-361 ◽  
Author(s):  
J. R. Melton ◽  
V. K. Arora
Keyword(s):  
Spatial Distribution ◽  
Large Scale ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Plant Functional Types ◽  
Atmospheric Composition ◽  
Climate Modelling ◽  
Fractional Coverage ◽  
Terrestrial Ecosystem Model ◽  
Functional Types

Abstract. The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land–atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka–Volterra (L–V) predator–prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L–V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L–V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Fractional Coverage of Rainfall Over a Grid: Analyses of NEXRAD Data Over the Southern Plains

1996 ◽  
Vol 32 (9) ◽  
pp. 2787-2802 ◽  
Author(s):  
Ying Fan ◽  
Eric E. Wood ◽  
Mary Lynn Baeck ◽  
James A. Smith
Keyword(s):  
Southern Plains ◽  
Fractional Coverage

scholarly journals Neighborhood Verification: A Strategy for Rewarding Close Forecasts

2009 ◽  
Vol 24 (6) ◽  
pp. 1498-1510 ◽  
Author(s):  
Elizabeth E. Ebert
Keyword(s):  
High Resolution ◽  
Rainfall Intensity ◽  
Mean Value ◽  
Forecast Performance ◽  
Fractional Coverage ◽  
Optimal Scale ◽  
Verification Methods ◽  
Intercomparison Project ◽  
The Mean ◽  
Spatial Verification

Abstract High-resolution forecasts may be quite useful even when they do not match the observations exactly. Neighborhood verification is a strategy for evaluating the “closeness” of the forecast to the observations within space–time neighborhoods rather than at the grid scale. Various properties of the forecast within a neighborhood can be assessed for similarity to the observations, including the mean value, fractional coverage, occurrence of a forecast event sufficiently near an observed event, and so on. By varying the sizes of the neighborhoods, it is possible to determine the scales for which the forecast has sufficient skill for a particular application. Several neighborhood verification methods have been proposed in the literature in the last decade. This paper examines four such methods in detail for idealized and real high-resolution precipitation forecasts, highlighting what can be learned from each of the methods. When applied to idealized and real precipitation forecasts from the Spatial Verification Methods Intercomparison Project, all four methods showed improved forecast performance for neighborhood sizes larger than grid scale, with the optimal scale for each method varying as a function of rainfall intensity.

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