Journal Article10.1016/J.RSE.2008.10.001
A two-step nearest neighbors algorithm using satellite imagery for predicting forest structure within species composition classes
TL;DR: In this article, a two-step algorithm is proposed in which the class of a relevant categorical variable such as land cover is predicted in the first step, and continuous variables such as volume are predicted by the second step subject to the constraint that all nearest neighbors must come from the predicted class of the categorical variables.
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About: This article is published in Remote Sensing of Environment. The article was published on 16 Mar 2009. The article focuses on the topics: Forest inventory & Categorical variable.
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Citations
Probability- and model-based approaches to inference for proportion forest using satellite imagery as ancillary data
TL;DR: Four conclusions were drawn: the logistic regression model exhibited no serious lack of fit to the data; all the estimators produced comparable estimates for mean proportion forest, except for small areas; probability-based inferences enhanced using maps produced increased precision; and the computational intensity associated with estimating variances for model-based estimators can be greatly reduced with no detrimental effects.
147
Using remotely sensed data to construct and assess forest attribute maps and related spatial products
TL;DR: This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses five topic areas: statistical classification and prediction techniques used to construct maps and related spatial products, accuracy assessment methods, map-based statistical inference, and two emerging topics, change detection and use of lidar data.
142
Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data
TL;DR: In this paper, the authors employ neighborhood statistics (standard deviation, variance, sill variance, and ratios of these metrics at 5 and 10m) calculated from SPOT-5 sensor data and derivatives to estimate and map tree canopy diameter (CDIA), bole diameter at breast height (DBH), tree height (HT), crown closure (CC), vertical length of live crown (LC), and basal area (BA).
142
A review of methods for mapping and prediction of inventory attributes for operational forest management
TL;DR: This article reviews the most commonly used prediction techniques for predicting forest inventory attributes in the context of a comprehensive modeling framework that includes a discussion of methods, data sources, variable selection, and model validation.
140
Satellite image-based maps: Scientific inference or pretty pictures?
TL;DR: Probability- and model-based approaches are explained, illustrated, and compared for producing inferences for population parameters using a map depicting three land cover classes: non-forest, coniferous forest, and deciduous forest.
138
References
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An introduction to categorical data analysis
Alan Agresti
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TL;DR: In this paper, the authors present a tour of categorical data analysis for Contingency Tables and Logit and Loglinear models for contingency tables, as well as generalized linear models for Matched Pairs.
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Monitoring Vegetation Systems in the Great Plains with Erts
J. W. Rouse,R. H. Haas,J. A. Schell,D. W. Deering +3 more
- 01 Jan 1974
TL;DR: In this paper, a method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 spectral bands 5 and 7, corrected for sun angle, which is shown to be correlated with aboveground green biomass on rangelands.
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A review of assessing the accuracy of classifications of remotely sensed data
TL;DR: This paper reviews the necessary considerations and available techniques for assessing the accuracy of remotely sensed data including the classification system, the sampling scheme, the sample size, spatial autocorrelation, and the assessment techniques.
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