3 resultados para crop
Resumo:
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Resumo:
Modification of natural areas by human activities mostly has a negative impact on wildlife by increasing the geographical and ecological overlap between people and animals. This can result in escalating levels of competition and conflict between humans and wildlife, for example over crops. However, data on specific crops and crop parts that are unattractive to wildlife yet important for human livelihoods are surprisingly scarce, especially considering their potential application to reducing crop damage by wildlife. Here we examine the co-utilization of a nationally important and spatially abundant cash crop, cashew Anacardium occidentalis, by people and chimpanzees Pan troglodytes verus inhabiting a forested–agricultural matrix in Cantanhez National Park in Guinea-Bissau. In this Park people predominantly harvest the marketable cashew nut and discard the unprofitable fruit whereas chimpanzees only consume the fruit. Local farmers generally perceive a benefit of raiding by chimpanzees as they reportedly pile the nuts, making harvesting easier. By ensuring that conflict levels over crops, especially those with high economic importance, remain low, the costs of living in proximity to wildlife can potentially be reduced. Despite high levels of deforestation associated with cashew farming, these findings point to the importance of cashew as a low-conflict crop in this area.
Resumo:
Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.