A major challenge in landscape modeling is to effectively visualize and analyze a massive amount of simulation outputs, which usually are in various raster and vector geospatial data formats. Because the task is often time-consuming and costly, available handy data viewers are limited. Yet, it is a useful tool for land managers to prepare and deploy their management plan in a landscape scale. Here, we upgraded our previous LANDISVIEW (version 1.0) to significantly enhance both visualizing and analyzing four major raster and vector geospatial data formats: ERDAS GIS/ASCII Raster (gis/.asc), ERDAS IMAGINE (.img) and Tagged Image (.tiff), which are the images formats widely used in remote sensing and landscape models (e.g., LANDIS). In addition, the version 2.0 software can serve as a converter for linking spatial data to other widely used landscape spatial analysis tools, including FRAGSTATS. Using this updated version 2.0, we were able to effectively assess a wildfire effect on forest structure and predict forest growth dynamics in responses to future wildfire and drought in northeastern California.

景观建模的主要挑战是如何有效地可视化和分析大量的模拟输出，这些输出通常采用各种栅格和矢量地理空间数据格式。由于该任务通常很耗时且昂贵，因此可用的方便数据查看器受到限制。但是，它对于土地管理人员来说是一个有用的工具，可以在景观范围内准备和部署其管理计划。在这里，我们升级了以前的LANDISVIEW（1.0版），以显着增强可视化和分析四种主要栅格和矢量地理空间数据格式：ERDAS GIS / ASCII栅格（gis / .asc），ERDAS IMAGINE（.img）和标记图像（。 tiff），这是在遥感和景观模型（例如LANDIS）中广泛使用的图像格式。此外，版本2。0软件可以用作将空间数据链接到其他广泛使用的景观空间分析工具（包括FRAGSTATS）的转换器。使用此更新的版本2.0，我们能够有效地评估野火对森林结构的影响，并预测森林的动态变化，以应对加利福尼亚州东北部未来的野火和干旱。