Qual o melhor método para exportar um raster georreferenciado para o Google Earth? Enquanto buscamos a resposta, conheça os recursos do ENVI 5.1 para exportar um raster para o aplicativo do Google. Fiz um teste com uma imagem Landsat-8.
Como utilizar corretamente as Ferramentas para Geoprocessamento no QGIS 2.2? Em quais situações essas ferramentas devem ser utilizadas? Estas são algumas perguntas que pairam na mente de muitas pessoas durante a utilização de um aplicativo SIG.
An international group of seventy scientists hailing from more than eighteen countries have created the first global datasets of the world’s glaciers (not including the ice sheets of Greenland and Antarctica.
To make it easier and faster to access your frequently used ArcGIS Online items, we introduced “My Favorites” in the December 2013 release of ArcGIS Online. You can mark an item as a favorite and create a list of all your favorites.
Nigerian Observer The Man Who Mapped The World Nigerian Observer At the beginning of the 16th century, cartographers used heavy Gothier, or block-letter, type, which limited the space available for written information on maps.
Most imagery for use in GIS projects consist of satellite images or aerial photographs but it can also include, thermal images, digital elevation models (DEMs), scanned maps and land classification maps.
The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics. One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor, which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content, soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25 Member States of the European Union. The aim of this study is the generation of a harmonised high-resolution soil erodibility map (with a grid cell size of 500 m) for the 25 EU Member States. Soil erodibility was calculated for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated at 0.032 t ha h ha− 1 MJ− 1 mm− 1 with a standard deviation of 0.009 t ha h ha− 1 MJ− 1 mm− 1. The yielded soil erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation of the protective effect of surface stone cover, which is usually not considered for the soil erodibility calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where highest percentages of surface stone cover were observed.