Color: [0, 0, 0, 255] Background Color: N/A Outline Color: N/A Vertical Alignment: bottom Horizontal Alignment: left Right to Left: false Angle: 0 XOffset: 0 YOffset: 0 Size: 10 Font Family: Tahoma Font Style: normal Font Weight: normal Font Decoration: none
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>With the size of the study area measured at approximately 30.46 square miles, a cost-effective and accurate strategy for assessing the urban forest is the use of remotely sensed and semi-automated classification methods to inventory the current canopy cover and to analyze data for future planting goals.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Broad band based vegetation indices, based on sensors with broad wavelength region bands, are the most frequently used indicators for monitoring ecosystem dynamics and vegetation health. Many vegetation indices have been developed and applied in vegetation studies since the first vegetation index was introduced. Vegetation indices were created to evaluate cover, chlorophyll content, leaf area, phenology, and absorbed photo-synthetically active radiation. Since live green vegetation and tree canopy absorb solar radiation in the photosynthetically active radiation (PAR) spectral region, they scatter solar radiation in the near-infrared spectral region. When the two spectral regions are assessed in ratio-based indices, they contrast with cover that absorbs or reflects light similarly in both regions. This assessment used NDVI to calculate the health condition rating. </SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Broad band based vegetation indices, based on sensors with broad wavelength region bands, are the most frequently used indicators for monitoring ecosystem dynamics and vegetation health. Many vegetation indices have been developed and applied in vegetation studies since the first vegetation index was introduced. Vegetation indices were created to evaluate cover, chlorophyll content, leaf area, phenology, and absorbed photo-synthetically active radiation. Since live green vegetation and tree canopy absorb solar radiation in the photosynthetically active radiation (PAR) spectral region, they scatter solar radiation in the near-infrared spectral region. When the two spectral regions are assessed in ratio-based indices, they contrast with cover that absorbs or reflects light similarly in both regions. This assessment used NDVI to calculate the health condition rating. </SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Data produced in this raster yields the fragmentation type of the tree canopy. Values can range from Patch to Core Forest. Patch-like fragmentation canopies or ususally very small and provide very little in terms of wildlife function outside of small ecosystems. Decreasing the amount of patch forest will increase the overall health of the urban forest as a whole as it will become less susceptible to invasive species. </SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Using hyperspectral imagery, campgrounds, sawmills, nurseries, ash tree locations, road density, and major interstate on/off ramps as variables, a probalistic suitablility model was created. An overlay model was produced using rasterized information from these layers with each layer having a ranking of 1-5 based on the level of risk factors within each variable.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 0 0;"><SPAN>To help the city of Corinth, Mississippi increase its canopy coverage, an urban tree canopy assessment was conducted to determine the current land cover. This analysis makes it possible to identify the areas available to plant trees. Further analysis to identify the most suitable locations was also conducted. Each planting location was assigned a priority ranking for stormwater, urban heat island, and a composite overall ranking. </SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-size:10pt">With the size of the study area measured at approximately 30.46 square miles, a cost-effective and accurate strategy for assessing the urban forest is the use of remotely sensed and semi-automated classification methods to inventory the current canopy cover and to analyze data for future planting goals.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN><SPAN>With the size of the study area measured at approximately 30.46 square miles, a cost-effective and accurate strategy for assessing the urban forest is the use of remotely sensed and semi-automated classification methods to inventory the current canopy cover and to analyze data for future planting goals.</SPAN></SPAN></P></DIV></DIV></DIV>