Influence of Quality of Remote Sensing Data on Vegetation Passability by Terrain Vehicles

Abstract

The article studied databases of vegetation created from remote sensors, outcome of analyses of Cross-Country Movement in forests, and quality of utilized data. The aim was to combine various databases of forests and get statistics of best data by using different methods of evaluation. Passability in forests is mainly conducted with analysis of driving between trees. The most suitable datasets in the Czech Republic are Forest Economic Plan and Digital Elevation Model 5th generation combined with Digital Surface Model 1st generation. Accuracy and usability of databases were compared with digital model of surface created from orthophoto images. Processing of data is the most important part that influences quality of statistical and map results. Studied characteristics of input databases and applied methods also have considerable influence on results of analysis of forest passability. The outcome substantially varies for personnel armored vehicles and wheeled vehicles mostly due to their movement capabilities.

GNSS Signal Quality in Forest Stands for Off-Road Vehicle Navigation

“…In cases when drivers are not able to use some segments of roads (damaged or destroyed objects, traffic jam, etc. ), they have to be provided with complete cross-country mobility (CCM) analyses considering all main geographical factors to solve transportation problems [1,2]. The cross-country movement of off-road vehicles is affected by various terrain features such as slope, terrain roughness, soil type, vegetation, seasonal changes to the ground surface, rivers, etc.…”

The Influence of the Quality of Digital Elevation Data on the Modelling of Terrain Vehicle Movement

“…Their analyses and implementations defining soil impact are in [19,20], refs. [21][22][23] focused on forest passability, refs. [24,25] describing problematics of microrelief obstacles and [26][27][28][29] consist of all environmental elements in one complex study.…”