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trying to understand how data is collected using various technologies

November 24, 2009 Leave a comment

Using technology to measure different levels of the forest structure


“Measurements of forest structure are important for wildlife habitat management. An optimal strategy for mapping forest structure would include detailed measurements of the vertical dimension, which are traditionally provided by field sampling, together with the broad spatial coverage afforded by remote sensing. While no single sensor is capable of delivering this at the present time, it should be possible to combine information from multiple sensors to achieve a reasonable approximation. In this study, we compare estimates of forest structural metrics derived from remote sensing to measurements obtained in the field (large tree maximum canopy height, mean canopy height, standard deviation canopy height, and biomass). We then statistically combine structural information from LiDAR, RaDAR, and passive optical sensors in an attempt to improve accuracy of our estimates. The results of this study indicate that LiDAR is the best single sensor for estimating canopy height and biomass. The addition of ETM+ metrics significantly improved LiDAR estimates of large tree structure, while Quickbird and InSAR/SAR improved estimates either marginally or not at all. The combination of all sensors was more accurate than LiDAR alone, but only marginally better than the combination of LiDAR and ETM+. Structure metrics from LiDAR and RaDAR are essentially redundant, as are ETM+ and Quickbird.”

Application of LiDAR’s to biology and conservation

Using acoustic sensors to measure wildlife abundance


Overview of remote sensing

“Present applications of remote sensing are numerous and varied. They include land cover mapping and analysis, land use mapping, agricultural plant health monitoring and harvest forecast, water resources, wildlife ecology, archeological investigations, snow and ice monitoring, disaster management, geologic and soil mapping, mineral exploration, coastal resource management, military surveillance, and many more.

One main advantage of a remote sensing system is its ability to provide a synoptic view of a wide area in a single frame. The width of a single frame, or swath width, could be 37 mi x 37 mi (60 km x 60 km) in the case of the European SPOT satellite, or as wide as 115 mi x 115 mi (185 km x 185 km) in the case of Landsat. Remote sensing systems can provide data and information in areas where access is difficult as rendered by terrain, weather, or military security. The towering Himalayas and the bitterly cold Antarctic regions provide good examples of these harsh environments. Active remote sensing systems provide cloud-free images that are available in all weather conditions, day or night. Such systems are particularly useful in tropical countries where constant cloud cover may obscure the target area. In 2002, the United States military initiatives in Afghanistan used remote sensing systems to monitor troops and vehicle convoy movements at spatial resolutions of less than one meter to a few meters. Spatial resolution or ground resolution is a measure of how small an object on Earth’s surface can be measured by a sensor as separate from its surroundings.

The greater advantage of remote sensing systems is the capability of integrating multiple, interrelated data sources and analysis procedures. This could be a multistage sensing wherein data on a particular site is collected from the multiple sources at different altitudes like from a low altitude aircraft, a high altitude craft, a space shuttle and a satellite. It could also be a multispectral sensing wherein data on the same site are acquired in different spectral bands. Landsat-5, for example, acquires data simultaneously in seven wavelength ranges of the electromagnetic spectrum. Or, it could be a multitemporal sensing whereby data are collected on the same site at different dates. For example, data may be collected on rice-growing land at various stages of the crop’s growth, or on a volcano before and after a volcanic eruption.”

More on remote sensing

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