Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High Dimensional Sparse Data

Chow and Liu introduced an algorithm for fitting a multivariate distribution with a tree (i.e. a density model that assumes that there are only pairwise dependencies between variables) and that the graph of these dependencies is a spanning tree. The original algorithm is quadratic in the dimesion of the domain, and linear in the number of data points that define the target distribution $P$. This paper shows that for sparse, discrete data, fitting a tree distribution can be done in time and memory that is jointly subquadratic in the number of variables and the size of the data set. The new algorithm, called the acCL algorithm, takes advantage of the sparsity of the data to accelerate the computation of pairwise marginals and the sorting of the resulting mutual informations, achieving speed ups of up to 2-3 orders of magnitude in the experiments.

Rapid Losses of Surface Elevation following Tree Girdling and Cutting in Tropical Mangroves.

Discussion Conclusions Materials and Methods Acknowledgments Author Contributions References Reader Comments (0) Figures Abstract The importance of mangrove forests in carbon sequestration and coastal protection has been widely acknowledged. Large-scale damage of these forests, caused by hurricanes or clear felling, can enhance vulnerability to erosion, subsidence and rapid carbon losses. However, it is unclear how small-scale logging might impact on mangrove functions and services. We experimentally investigated the impact of small-scale tree removal on surface elevation and carbon dynamics in a mangrove forest at Gazi bay, Kenya. The trees in five plots of a Rhizophora mucronata (Lam.) forest were first girdled and then cut. Another set of five plots at the same site served as controls. Treatment induced significant, rapid subsidence (−32.1±8.4 mm yr−1 compared with surface elevation changes of +4.2±1.4 mm yr−1 in controls). Subsidence in treated plots was likely due to collapse and decomposition of dying roots and sediment compaction as evidenced from increased sediment bulk density. Sediment effluxes of CO2 and CH4 increased significantly, especially their heterotrophic component, suggesting enhanced organic matter decomposition. Estimates of total excess fluxes from treated compared with control plots were 25.3±7.4 tCO2 ha−1 yr−1 (using surface carbon efflux) and 35.6±76.9 tCO2 ha−1 yr−1 (using surface elevation losses and sediment properties). Whilst such losses might not be permanent (provided cut areas recover), observed rapid subsidence and enhanced decomposition of soil sediment organic matter caused by small-scale harvesting offers important lessons for mangrove management. In particular mangrove managers need to carefully consider the trade-offs between extracting mangrove wood and losing other mangrove services, particularly shoreline stabilization, coastal protection and carbon storage.

Retrieval by Shape Population: An Index Tree Approach

Based on our previous work in deformable shape model-based object detection, a new method is proposed that uses index trees for organizing shape features to support content-based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

Scalable Overlay Multicast Tree Construction for QoS-Constrained Media Streaming

Overlay networks have become popular in recent times for content distribution and end-system multicasting of media streams. In the latter case, the motivation is based on the lack of widespread deployment of IP multicast and the ability to perform end-host processing. However, constructing routes between various end-hosts, so that data can be streamed from content publishers to many thousands of subscribers, each having their own QoS constraints, is still a challenging problem. First, any routes between end-hosts using trees built on top of overlay networks can increase stress on the underlying physical network, due to multiple instances of the same data traversing a given physical link. Second, because overlay routes between end-hosts may traverse physical network links more than once, they increase the end-to-end latency compared to IP-level routing. Third, algorithms for constructing efficient, large-scale trees that reduce link stress and latency are typically more complex. This paper therefore compares various methods to construct multicast trees between end-systems, that vary in terms of implementation costs and their ability to support per-subscriber QoS constraints. We describe several algorithms that make trade-offs between algorithmic complexity, physical link stress and latency. While no algorithm is best in all three cases we show how it is possible to efficiently build trees for several thousand subscribers with latencies within a factor of two of the optimal, and link stresses comparable to, or better than, existing technologies.

Nutrient enrichment effects on mangrove sediments from differing tree height zones in Bocas del Toro, Panama

Red mangrove (Rhizophora mangle L.) forests have distinct tree-height zones, with tall trees fringing the ocean and shorter trees in interior stands. A long-term nitrogen (N) and phosphorus (P) fertilization experiment in Almirante Bay, Bocas del Toro Province, Panama has shown that tree-height zonation is primarily related to nutrient limitation. This experiment was used to test the effects of in-situ nutrient additions and tree zonation on mangrove sediments. The sediments underlying the experimental R. mangle trees were sampled and N₂ fixation, ¹⁵N, chlorophyll a, percent N and P, and percent organic biomass were quantified. Both N and P additions significantly affected almost every parameter measured in both zones within this experiment. These results are likely to have implications for management since N and P inputs are predicted to increase throughout the tropics and subtropics worldwide.