Forest cover and its change in Unguja Island, Zanzibar

Tropical forests are sources of many ecosystem services, but these forests are vanishing rapidly. The situation is severe in Sub-Saharan Africa and especially in Tanzania. The causes of change are multidimensional and strongly interdependent, and only understanding them comprehensively helps to change the ongoing unsustainable trends of forest decline. Ongoing forest changes, their spatiality and connection to humans and environment can be studied with the methods of Land Change Science. The knowledge produced with these methods helps to make arguments about the actors, actions and causes that are behind the forest decline. In this study of Unguja Island in Zanzibar the focus is in the current forest cover and its changes between 1996 and 2009. The cover and changes are measured with often used remote sensing methods of automated land cover classification and post-classification comparison from medium resolution satellite images. Kernel Density Estimation is used to determine the clusters of change, sub-area –analysis provides information about the differences between regions, while distance and regression analyses connect changes to environmental factors. These analyses do not only explain the happened changes, but also allow building quantitative and spatial future scenarios. Similar study has not been made for Unguja and therefore it provides new information, which is beneficial for the whole society. The results show that 572 km2 of Unguja is still forested, but 0,82–1,19% of these forests are disappearing annually. Besides deforestation also vertical degradation and spatial changes are significant problems. Deforestation is most severe in the communal indigenous forests, but also agroforests are decreasing. Spatially deforestation concentrates to the areas close to the coastline, population and Zanzibar Town. Biophysical factors on the other hand do not seem to influence the ongoing deforestation process. If the current trend continues there should be approximately 485 km2 of forests remaining in 2025. Solutions to these deforestation problems should be looked from sustainable land use management, surveying and protection of the forests in risk areas and spatially targeted self-sustainable tree planting schemes.

Determinants of Polylepis (Rosaceae) Forest Distribution and Treeline Formation in the High Andes

High elevation treelines are formed under common temperature conditions worldwide, but the functional mechanisms that ultimately constrain tree growth are poorly known. In addition to environmental constraints, the distribution of high elevation forests is largely affected by human influence. Andean Polylepis (Rosaceae) forests are an example of such a case, forests commonly growing in isolated stands disconnected from the lower elevation montane forests. There has been ample discussion as to the role of environmental versus anthropogenic causes of this fragmented distribution of Polylepis forests, but the importance of different factors is still unclear. In this thesis, I studied functional, environmental and anthropogenic aspects determining Polylepis forest distribution. Specifically, I assessed the degree of genetic determinism in the functional traits that enable Polylepis species to grow in cold and dry conditions. I also studied the role of environment and human influence constraining Polylepis forest distribution. I found evidence of genetically determined climatic adaptations in the functional traits of Polylepis. High elevation species had reduced leaf size and increased root tip abundance compared to low elevation species. Thus these traits have potentially played an important role in species evolution and adaptation to high elevation habitats, especially to low temperatures. I also found reduced photosynthesis rate among high elevation tree species compared to low elevation species, supporting carbon source limitation at treelines. At low elevations, Polylepis forest distribution appeared to be largely defined by human influence. This suggests that the absence of Polylepis forests in large areas in the Andes is the result of several environmental and anthropogenic constraints, the role of environment becoming stronger towards high elevations. I also show that Polylepis trees grow at remarkably low air and soil temperatures near treelines, and present new evidence of the role of air temperatures in constraining tree growth at high elevations. I further show that easily measurable indices of accessibility are related to the degree of degradation of Polylepis forest, and can therefore be used in the rapid identification of potentially degraded Polylepis forests. This is of great importance for the conservation and restoration planning of Polylepis forests in the Andes. In a global context, the results of this thesis add to our scientific knowledge concerning high elevation adaptations in trees, and increase our understanding of the factors constraining tree growth and forest distribution at high-­elevation treelines worldwide.

Forest insects and environmental variation in stand edges

Summary

Generating a raster map presentation of a forest resource by solving a transportation problem

Abstract

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Forest contractors entrepreneurial skills development in Finland by Forest Expertise and Innovation Network : project in 2009 - 2013

Julkaisumaa: 578 NO NOR Norja