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ASSESSING NATURAL RESOURCES WITH THE VISNIRMIR DIGITAL VIDEO IMAGING SYSTEM

机译:使用Visnirmir数字视频成像系统评估自然资源

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摘要

The visible/near-infrared/mid-infrared (VISNIRMIR) digital video imaging system acquires data in the blue (447-455 nm), green (555-565 nm), red (625-635 nm), red edge (704-716 nm), near-infrared (814-826 nm), and mid-infrared (1631-1676 nm) regions of the electromagnetic spectrum. This paper discusses application of the system as a tool for assessing natural resources. For this study, a rangeland area and a wetland area were used as test sites. Conventional color and false color images were created and were qualitatively assessed to determine their usefulness for separating various land-cover types within the areas of interest. The imagery was also subjected to an unsupervised classification to evaluate the potential of the system as tool for land-cover mapping. Composite imagery provided valuable information for qualitative assessment of the study sites. For the rangeland site, the best map accuracies were obtained using a broad land-cover mapping scheme. American lotus (Nelumbo lutea) was classified accurately for the wetland site (user's and producer's accuracies greater than 90%); the other land-cover types were mapped with low (<60%) to intermediate accuracies (60 to 84%). These preliminary results indicate that the mapping capabilities of this system are site and cover type specific.
机译:可见/近红外/中红外线(Visnirmir)数字视频成像系统获取蓝色(447-455 nm),绿色(555-565 nm),红色(625-635 nm),红色边缘(704- 716 nm),近红外(814-826nm)和中红外(1631-1676nm)电磁频谱区域。本文讨论了系统的应用作为评估自然资源的工具。对于这项研究,牧场地区和湿地面积用作试验场。创建了传统的颜色和假彩色图像,并定性评估,以确定其在利息区域内分离各种陆地类型的有用性。图像也经过无监督的分类,以评估系统的潜力作为陆地覆盖映射的工具。复合图像为研究网站的定性评估提供了有价值的信息。对于牧场网站,使用广泛的陆地覆盖映射方案获得了最佳地图精度。美国莲花(Nelumbo Lutea)被准确地归类为湿地部位(用户和生产者的准确性大于90%);将其他陆地覆盖物类型映射低(<60%)至中间精度(60至84%)。这些初步结果表明该系统的映射能力是特定于站点和覆盖类型。

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