-Scant information exists about the spatial extent of human impact on forest resource supplies, i .e. , depreciative and nonforest uses. I used observations of ground-sampled land use and intrusions on forest land to map the probabil i ty of resource use and human impact for broad areas. Data came from a seven-state survey region (Alabama, Arkansas, Louisiana, Mississippi, east Oklahoma, Tennes...

In this paper, we address the problem of 3D human body pose estimation from depth images acquired by a stereo camera. Compared to the Kinect sensor, stereo cameras work outdoors having a much higher operational range, but produce noisier data. In order to deal with such data, we propose a framework for 3D human pose estimation that relies on random forests. The first contribution is a novel gri...

Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST) derived from infr...

In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images. The machine learned features from fully convolutional neural network (FCN) and hand-designed texton features are used to classify the MRI image voxels. The score map with pixelwise predictions is used as a feature map which is learned from multimodal MRI training dataset u...

C-band repeat-pass interferometry, in particular, the coherence, has been shown to be of great potential for stem volume retrieval. For boreal forests, we have investigated a stem volume retrieval method based on inversion of ERS-1/2 coherence measurements by means of a semiempirical model. A multitemporal combination of several stem volume estimates has been used in order to reduce errors in t...

Ambiguity between forest types on remote-sensing imagery is a major cause of errors found in accuracy assessments of forest inventorymaps. This paper presents amethodology, based on forest plot inventory, ground measurements and simulated imagery, for systematically quantifying these ambiguities in the sense of the minimum distance (MD), maximum likelihood (ML), and frequency-based (FB) classif...

A major goal of current research is to address temporal climatic variations that are related to CO2 emissions. A significant portion of these emissions are due to forest destruction and the resulting conversion of biomass to CO2. As 30% of the earth’s landmass is forest-covered, it is important to understand the biomass content with better estimates than are currently available. This research h...

Propagation of electromagnetic waves in forest environments is examined in which both the transmitting and receiving points are located in the trunk layer of a four-layered anisotropic forest model. This propagation model considers the forest as a horizontally stratified, anisotropic media of canopy and trunk, bounded by ground below and air above. The electromagnetic fields are obtained using ...

-The avian community of a mature residential area was studied and compared with an undisturbed climax beech-maple forest. Urbanization was presumed to be responsible for decreasing species richness and diversity, increasing biomass and density, and favoring dominance by a few species. Foraging guilds shifted from forest insectivores that were canopy foliage gleaners or bark drillers to urban gr...

Deforestation detection using satellite images can make an important contribution to forest management. Current approaches can be broadly divided into those that compare two images taken at similar periods of the year and those that monitor changes by using multiple images taken during the growing season. The CMFDA algorithm described in Zhu et al. (2012) is an algorithm that builds on the latt...