The use of remotely sensed data for forest biomass monitoring : a case of forest sites in north-eastern Armenia

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesIn recent years there has been an increasing interest in the use of synthetic aperture radar (SAR) data and geospatial technologies for environmental monitoring․ Particularly, forest biomass evaluation was of high importance, as forests have a crucial role in global carbon emission. Within this study we evaluate the use of Sentinel 1 C-band multitemporal SAR data with combination of Alos Palsar L-band SAR and Sentinel 2 multispectral remote sensing (RS) data for mapping forest aboveground biomass (AGB) of dry subtropical forests in mountainous areas. Field observation from National Forest Inventory was used as a ground truth data. As the SAR data suffers greatly by the complex topography, a simple approach of aspect and slope information as forestry ancillary data was implemented directly in the regression model for the first time to mitigate the topography effect on radar backscattering value․ Dense time-series analysis allowed us to overcome the SAR saturation by the forest phenology and select the optimal C-band scene. Image texture measures of SAR data has been strongly related to the biomass distribution and has robustly contributed to the prediction․ Multilinear Stepwise Regression allowed to select and evaluate the most relevant variables for AGB. The prediction model combining RS with ancillary data explained the 62 % of variance with root-mean-square error of 56.6 t ha¯¹. The study also reveals that C-band SAR data on forest biomass prediction is limited due to their short wavelength. Further, the mountainous condition is a major constraint for AGB estimation. Additionally, this research demonstrates a positive outcome in forest AGB prediction with freely accessible RS data

Some basic observations on Kelly's conjecture for graphs

AbstractP.J. Kelly first mentioned the possibility of determining a graph from subgraphs obtained by deleting several points. While such problems have received a great deal of attention in the case of deletions of single points, the problem for several points is virtually untouched. This paper contains some basic results on that problem, including the negative observation that for every k, there exist two non-isomorphic graphs with the same collection of k-point subgraphs

An automated model reduction method for biochemical reaction networks

We propose a new approach to the model reduction of biochemical reaction networks governed by various types of enzyme kinetics rate laws with non-autocatalytic reactions, each of which can be reversible or irreversible. This method extends the approach for model reduction previously proposed by Rao et al. which proceeds by the step-wise reduction in the number of complexes by Kron reduction of the weighted Laplacian corresponding to the complex graph of the network. The main idea in the current manuscript is based on rewriting the mathematical model of a reaction network as a model of a network consisting of linkage classes that contain more than one reaction. It is done by joining certain distinct linkage classes into a single linkage class by using the conservation laws of the network. We show that this adjustment improves the extent of applicability of the method proposed by Rao et al. We automate the entire reduction procedure using Matlab. We test our automated model reduction to two real-life reaction networks, namely, a model of neural stem cell regulation and a model of hedgehog signaling pathway. We apply our reduction approach to meaningfully reduce the number of complexes in the complex graph corresponding to these networks. When the number of species' concentrations in the model of neural stem cell regulation is reduced by 33.33%, the difference between the dynamics of the original model and the reduced model, quantified by an error integral, is only 4.85%. Likewise, when the number of species' concentrations is reduced by 33.33% in the model of hedgehog signaling pathway, the difference between the dynamics of the original model and the reduced model is only 6.59%

The Effects of Training and Practice in the Use of a Self-Monitoring Technique to Enhance the Reading Comprehension of Intermediate-Grade Students

The purpose of this study was to investigate the effectiveness of training and practice in using a self-monitoring technique to enhance the comprehension of intermediate-grade poor comprehenders. Subjects were 129 sixth grade low-average comprehenders from three middle schools, who scored from stanine three to stanine six on the reading comprehension subtest of the California Achievement Test. Subjects' treatment was based on the school they attended. Three comparable middle schools were randomly elected and assigned one of the following treatments: (1) training with practice, (2) training, or (3) neither training nor practice. Training in rating and hypothesis formation was conducted by the investigator over a three- day period. Materials used in training ranged from sentences to passages three to four paragraphs in length. Students were taught to rate pass ages on a 1-2-3 rating scale and to use hypothesis formation to enhance comprehension. Following training, the training with practice group used rating and hypothesis formation for three weeks during their regular reading lessons, under the guidance of the classroom reading teacher. After training and practice, all three groups were tested in two sessions. Three measures were used to test for differences among groups. These were a "global" comprehension test, a rating-with-response test requiring a match between perceived knowledge and demonstrated knowledge, and a test requiring the detection of embedded errors. Data were analyzed using a multivariate analysis of covariance. Scores were adjusted using a covariate of reading ability. No significant differences were found among groups. Implications for research and instruction included: training studies such as this may be most effective if done over an extended period of time in an ecologically valid setting; further study is needed to determine whether the Rating-with-Response and Embedded Error measures employed here give useful information about comprehension processing