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Measuring continuous landscape patterns with Gray-Level Co-Occurrence Matrix (GLCM) indices: An alternative to patch metrics?

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Scale Effects on Spatially Varying Relationships Between Urban Landscape Patterns and Water Quality
inferredcites →https://doi.org/10.1007/s10980-006-9010-5openalex-snapshot
Effects of thematic resolution on landscape pattern analysis
inferredcites →https://doi.org/10.1007/s10980-009-9327-yopenalex-snapshot
Surface metrics: an alternative to patch metrics for the quantification of landscape structure
inferredcites →https://doi.org/10.1016/j.apgeog.2016.10.008openalex-snapshot
Urban green infrastructure and local flooding: The impact of landscape patterns on peak runoff in four Texas MSAs
inferredcites →https://doi.org/10.1016/j.atmosenv.2008.02.043openalex-snapshot
Spatial interpolation of air pollution measurements using CORINE land cover data
inferredcites →https://doi.org/10.1016/j.ecolind.2007.12.002openalex-snapshot
Parsimony in landscape metrics: Strength, universality, and consistency
inferredcites →https://doi.org/10.1016/j.ecolind.2012.07.018openalex-snapshot
Trends in the use of landscape spatial metrics as landscape indicators: A review
inferredcites →https://doi.org/10.1016/j.ecolind.2017.10.029openalex-snapshot
Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing
inferredcites →https://doi.org/10.1016/j.ecolind.2018.09.058openalex-snapshot
Multi-city comparison of the relationships between spatial pattern and cooling effect of urban green spaces in four major Asian cities
inferredcites →https://doi.org/10.1016/j.ecolmodel.2014.08.018openalex-snapshot
Understanding and quantifying landscape structure – A review on relevant process characteristics, data models and landscape metrics
inferredcites →https://doi.org/10.1016/j.isprsjprs.2013.09.009openalex-snapshot
An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD
inferredcites →https://doi.org/10.1016/j.landurbplan.2009.08.006openalex-snapshot
Monitoring loss of biodiversity in cultural landscapes. New methodology based on satellite data
inferredcites →https://doi.org/10.1016/j.landurbplan.2011.03.017openalex-snapshot
Mapping form and function in urban areas: An approach based on urban metrics and continuous impervious surface data
inferredcites →https://doi.org/10.1016/j.landurbplan.2011.11.024openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.landurbplan.2013.10.002openalex-snapshot
A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation
inferredcites →https://doi.org/10.1016/j.rse.2006.09.005openalex-snapshot
Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil
inferredcites →https://doi.org/10.1016/j.rse.2009.02.014openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.rse.2011.11.004openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.rse.2012.01.003openalex-snapshot
Image texture as a remotely sensed measure of vegetation structure
inferredcites →https://doi.org/10.1016/j.rse.2015.12.027openalex-snapshot
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inferredcites →https://doi.org/10.1023/b:land.0000030441.15628.d6openalex-snapshot
Use and misuse of landscape indices
inferredcites →https://doi.org/10.1109/jstars.2012.2190383openalex-snapshot
Image Based Characterization of Formal and Informal Neighborhoods in an Urban Landscape
inferredcites →https://doi.org/10.1109/proc.1979.11328openalex-snapshot
Statistical and structural approaches to texture
inferredcites →https://doi.org/10.1109/tsmc.1973.4309314openalex-snapshot
Textural Features for Image Classification
inferredcites →https://doi.org/10.1177/0265813516663932openalex-snapshot
The influence of urban landscape spatial patterns on single-family housing prices
inferredcites →https://doi.org/10.1177/0309133312439594openalex-snapshot
Landscape ecology and biogeography
inferredcites →https://doi.org/10.14358/pers.69.9.991openalex-snapshot
Spatial Metrics and Image Texture for Mapping Urban Land Use
inferredcites →https://doi.org/10.14358/pers.72.2.187openalex-snapshot
Population Density and Image Texture

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Identifying Spatial Variation of Carbon Stock in a Warm Temperate Forest in Central Japan Using Sentinel-2 and Digital Elevation Model Data
inferred← citeshttps://doi.org/10.3390/rs15194676openalex-snapshot
GF-2 Data for Lithological Classification Using Texture Features and PCA/ICA Methods in Jixi, Heilongjiang, China
inferred← citeshttps://doi.org/10.3390/rs15235550openalex-snapshot
Automatic Crop Classification Based on Optimized Spectral and Textural Indexes Considering Spatial Heterogeneity
inferred← citeshttps://doi.org/10.3390/rs16203906openalex-snapshot
Accurate Estimation of Gross Primary Production of Paddy Rice Cropland with UAV Imagery-Driven Leaf Biochemical Model
inferred← citeshttps://doi.org/10.3390/rs18183177openalex-snapshot
Spatially Constrained Grassland Aboveground Biomass Estimation by Identifying and Masking Achnatherum splendens: Integrating UAV Remote Sensing and Deep Learning
inferred← citeshttps://doi.org/10.3390/s20247175openalex-snapshot
Development and Application of a Vehicle-Mounted Soil Texture Detector
inferred← citeshttps://doi.org/10.3390/su15076067openalex-snapshot
Machine Learning-Based Classification of Asbestos-Containing Roofs Using Airborne RGB and Thermal Imagery
inferred← citeshttps://doi.org/10.3390/urbansci8040183openalex-snapshot
The Effect of War on Spatial Differentiation of Real Estate Values and Urban Disorder in the Damascus Metropolitan Area
inferred← citeshttps://doi.org/10.3832/ifor4982-019openalex-snapshot
Assessing forest resilience after windthrow: linking deadwood, regeneration, and landscape-scale susceptibility - A case study in a Pre-Alpine forest in Italy
inferred← citeshttps://doi.org/10.4028/p-zhzxt4openalex-snapshot
Machine Learning-Based Prediction of Forming-Induced Defects in Flax Woven Fabrics Using 3D Scanning and Haralick Texture Features
inferred← citeshttps://doi.org/10.5772/intechopen.99532openalex-snapshot
Thoughts for Foods: Imaging Technology Opportunities for Monitoring and Measuring Food Quality
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