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Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

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Logistic regression

In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).

Transformer (machine learning model)

A transformer is a deep learning architecture that relies on the parallel multi-head attention mechanism. The modern transformer was proposed in the 2017 paper titled 'Attention Is All You Need' by Ashish Vaswani et al., Google Brain team. It is notable for requiring less training time than previous recurrent neural architectures, such as long short-term memory (LSTM), and its later variation has been prevalently adopted for training large language models on large (language) datasets, such as the Wikipedia corpus and Common Crawl, by virtue of the parallelized processing of input sequence.

Boreal forest of Canada

Canada's boreal forest is a vast region comprising about one third of the circumpolar boreal forest that rings the Northern Hemisphere, mostly north of the 50th parallel. Other countries with boreal forest include Russia, which contains the majority; the United States in its northernmost state of Alaska; and the Scandinavian or Northern European countries (e.g. Sweden, Finland, Norway and small regions of Scotland). In Europe, the entire boreal forest is referred to as taiga, not just the northern fringe where it thins out near the tree line.

Nonlinear regression

In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables. The data are fitted by a method of successive approximations. In nonlinear regression, a statistical model of the form, relates a vector of independent variables, , and its associated observed dependent variables, . The function is nonlinear in the components of the vector of parameters , but otherwise arbitrary.

Landsat program

The Landsat program is the longest-running enterprise for acquisition of of Earth. It is a joint NASA / USGS program. On 23 July 1972, the Earth Resources Technology Satellite was launched. This was eventually renamed to Landsat 1 in 1975. The most recent, Landsat 9, was launched on 27 September 2021. The instruments on the Landsat satellites have acquired millions of images.

Diffusion model

In machine learning, diffusion models, also known as diffusion probabilistic models or score-based generative models, are a class of latent variable models. They are Markov chains trained using variational inference. The goal of diffusion models is to learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space. In computer vision, this means that a neural network is trained to denoise images blurred with Gaussian noise by learning to reverse the diffusion process.

Tropical forest

Tropical forests (a.k.a. jungle) are forested landscapes in tropical regions: i.e. land areas approximately bounded by the tropic of Cancer and Capricorn, but possibly affected by other factors such as prevailing winds. Some tropical forest types are difficult to categorize. While forests in temperate areas are readily categorized on the basis of tree canopy density, such schemes do not work well in tropical forests. There is no single scheme that defines what a forest is, in tropical regions or elsewhere.

Reinforcement learning

Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.

Multinomial logistic regression

In statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems, i.e. with more than two possible discrete outcomes. That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which may be real-valued, binary-valued, categorical-valued, etc.).

Secondary forest

A secondary forest (or second-growth forest) is a forest or woodland area which has regenerated through largely natural processes after human-caused disturbances, such as timber harvest or agriculture clearing, or equivalently disruptive natural phenomena. It is distinguished from an old-growth forest (primary or primeval forest), which has not recently undergone such disruption, and complex early seral forest, as well as third-growth forests that result from harvest in second growth forests.