Invasive species can be considered a threat to biodiversity, and remote sensing has been proposed as a tool for detection and monitoring of invasive species. In this study, we test the ability to discriminate between two tree species of the same genera, using data from Landsat 8 satellite imagery, aerial images, and airborne laser scanning. Ground observations from forest stands dominated by ei...

Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cov...

Urban areas are Earth’s fastest growing land use that impact hydrological and ecological systems and the surface energy balance. The identification and extraction of accurate spatial information relating to urban areas is essential for future sustainable city planning owing to its importance within global environmental change and human–environment interactions. However, monitoring urban expansi...

Accurate and timely maps of tree cover attributes are important tools for environmental research and natural resource management. We evaluate the utility of Landsat 8 for mapping tree canopy cover (TCC) and aboveground biomass (AGB) in a woodland landscape in Burkina Faso. Field data and WorldView-2 imagery were used to assemble the reference dataset. Spectral, texture, and phenology predictor ...

This work modelled the spatial distribution of the rodent species that act as hosts in the transmission cycle of the parasitic tapeworm Echinococcus multilocularis. The rodent distribution was modelled in relation to landscape characteristics in four ways, using (1) a Landsat ETM+ derived hard classification, (2) single-image Landsat ETM+ derived NDVI, (3) single-image MODIS 16-day composite ND...

Information on the structural complexity of forest stands is required to inform conservation priorities that guide the sustainable management of private native vegetation for multiple objectives of landowners. Whilst research into methods for the operational mapping of vegetation structure is expanding, the research is largely exploratory, and no methods have yet seen widespread acceptance. Thi...

The panchromatic bands of Landsat 7, SPOT, and IRS satellite imagery provide an opportunity to evaluate the effectiveness of texture analysis of satellite imagery for mapping of land uselcover, especially forest cover. A variety of texture algorithms, including standard deviation, Ryherd-Woodcock minimum variance adaptive window, low pass etc., were applied to moving 3x3 and 7x7 pixel windows. ...

Classifying roads in remotely sensed imagery has been addressed by a number of research efforts. Detecting these features is important for a variety of endeavors such as agricultural assessment and urban planning. This study investigates the viability of using a pulse-coupled neural network to recognize roads in Landsat-4 Thematic Mapper multispectral imagery.

Urban greenspace is important for the health of cities. Up-to-date databases and information are vital to maintain and monitor growth in cities. During the last decade, advances in spaceborne hyperspectral sensors have resulted in some advantages being gained over multispectral sensors for land cover monitoring (due to increased spectral resolution). The objective of this research was to compar...