Search for dissertations about: "morphometric"

Showing result 1 - 5 of 54 swedish dissertations containing the word morphometric.

2. 1. Morphometric and Landscape Feature Analysis with Artificial Neural Networks and SRTM data : Applications in Humid and Arid Environments

   Author : Amir Houshang Ehsani; Friedrich Quiel; Wolfgang Wagner; KTH; []
   Keywords : Self Organizing Map; Neural Network; Morphometric Feature; Landscape; Yardang; Lut Desert; Potential natural vegetation; geoecosystem; Landform; Landsat ETM ; Morphometric Parameters; SRTM; Resolution; Curvatures; DEM.; TECHNOLOGY; TEKNIKVETENSKAP;

   Abstract : This thesis presents a semi-automatic method to analyze morphometric features and landscape elements based on Self Organizing Map (SOM) as an unsupervised Artificial Neural Network algorithm in two completely different environments: 1) the Man and Biosphere Reserve “Eastern Carpathians” (Central Europe) as a complex mountainous humid area and 2) Lut Desert, Iran, a hyper arid region characterized by repetition of wind-eroded features. In 2003, the National Aeronautics and Space Administration (NASA) released the SRTM/ SIR-C band data with 3 arc seconds (approx. READ MORE

4. 2. Morphometric differentiation in Papaver radicatum (Papaveraceae) : Geographic pattern and significance for refugial survival theory

   Author : Eva Selin; Uppsala universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Ecology; Capsule morphology; Geographic pattern; Leaf morphology; Morphometric variation; Papaver radicatum; Refugial survival; Seed shape; Ekologi; Terrestrial; freshwater and marine ecology; Terrestisk; limnisk och marin ekologi; ekologisk botanik; Ecological Botany;

   Abstract : The morphometric pattern of variation among and within Scandinavian populations of the alpine species Papaver radicatum was studied. Results from analyses (including multivariate techniques) of capsule and leaf traits of wild-collected and cultivated plants as well as wild-collected seeds show correlated patterns of variation in capsule traits and partly corresponding patterns of variation between capsule and seed traits. READ MORE

5. 3. The spatial structure of genetic and morphometric variation in Corylus avellana (Betulaceae): pattern and scale

   Author : Helena Persson; Biologiska institutionen; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; phytogeography; chemotaxonomy. Physiology of nonvascular plants; Systematisk botanik; taxonomi; morfologi; kemotaxonomi. Växters fysiologi inte kärlväxter .; taxonomy; morphology; Systematic botany; Öland; clonal structure; marginal and central populations; image analysis; aerial photographs; morphometric variation; allozymes; Corylus avellana; genetic variation;

   Abstract : In the present thesis, I investigated the spatial structure of genetic and morphometric variation in the widespread wind-pollinated shrub Corylus avellana (L.) Betulaceae, hazel, and related the variation to geographic distribution and different spatial scales. READ MORE

6. 4. Cell adhesion proteins in different invasive patterns of colon carcinomas : a morphometric and molecular genetic study

   Author : Victoria Hahn-Strömberg; Lennart Franzén; Richard Palmqvist; Örebro universitet; []
   Keywords : LANTBRUKSVETENSKAPER; AGRICULTURAL SCIENCES; colon carcinoma; growth pattern; tight junction; Complexity Index; cell adhesion; E-cadherin; Beta-catenin; Occludin; Claudin.; Medicine; Medicin; Biomedicin; Biomedicine;

   Abstract : Colorectal carcinoma is the second most common type of cancer in both men and women in Sweden. Cancer of the colon and rectum are often considered together and their ten year survival rate is approximately 50 – 60 % depending on sex and location. READ MORE

7. 5. Artificial neural networks : applications in morphometric and landscape features analysis

   Author : Amir Houshang Ehsani; Fredrich Quiel; Wolter Arnberg; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Environmental engineering; Miljöteknik;

   Abstract : In this thesis a semi-automatic method is developed to analyze morphometric features and landscape elements based on Self Organizing Map (SOM) as a unsupervised Artificial Neural Network algorithm. Analysis and parameterization of topography into simple and homogenous land elements (landform) can play an important role as basic information in planning processes and environmental modeling. READ MORE