Description: ELUs are derived from soil and elevation data using a GIS. It was important that we used readily available data and we kept the derivation of ELUs as simple as possible. After consulting the published literature and conferring with expert soil scientists and plant ecologists, we focused on two aspects of soils, soil drainage class and soil texture. Soil drainage class is very good at distinguishing wet versus dry habitats. Soil texture (sandy, silty, loamy, etc.) is an important habitat component for plants. Using USDA SSURGO (State Soil Survey Geographic Database) data that is readily available from RIGIS, we created a raster dataset (50 feet cell size) of the different soil drainage classes and another raster dataset of the soil texture classes. There are many properties of soils that are available to use for analyses such as this, for example stoniness, depth to bedrock, etc. The two factors we chose are extremely important soil properties in supporting different plant communities.Landform represents where a location is with respect to elevation, slope, and aspect (direction a hillside is facing). Landform distinguishes hilltops, hill sides, valley bottoms, etc. We used the RIGIS digital terrain model as our source of elevation data to measure landform. Landform classes were identified using GIS modeling of slope, aspect, and elevation. A description of landform categories and the technical methods to obtain them can be found here.The final ELU map is made by adding together the raster datasets for landform, drainage class, and soil texture. Because we were careful with our encoding system, the sum of the three rasters provides us a composite of the individual datasets. For example, a location that is a well-drained (code value 2000) and consists of gravelly sand (code value 100) a sits on a hilltop (code value 21) and would combine to be ELU 2121 (2000+100+21). This process yielded 204 unique ELUs for the state of Rhode Island. Examination of a cumulative distribution function (CDF) of the ELUs showed that most of the ELUs were small and did not occur very often. Conversely, 20 ELUs were quite common and encompassed almost 85% of the land area of RI.
Copyright Text: URI EDC, URI NRS, URI CRC, Sea Grant RI, TNC
Name: Unfragmented Forest Blocks 2020 (250 to 500 acres)
Display Field: Forest
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 14 0;"><SPAN>410...Deciduous Forest (>80% hardwood) (Formerly Brushland in 1995) </SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN><SPAN>420...Coniferous Forest (>80% softwood) </SPAN></SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN><SPAN>430...Mixed Forest </SPAN></SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN>DESCRIPTION: Trees are classified as forests when the tree canopy covers at least 50% of the space when viewed from above on an aerial photograph. The three different categories depend upon the composition of deciduous vs. coniferous trees. On an aerial photograph, most coniferous trees have conical shapes (except for pines) with dense needles and tight branching with dark spectral signatures whereas deciduous trees have a more open or freeform shape with leaves (during the growing season) that give the tree a coarser texture or pattern and a looser or more open branching arrangement. Deciduous spectral signatures are generally lighter than coniferous signatures.</SPAN></P></DIV></DIV></DIV>
Name: Unfragmented Forest Blocks 2020 (500 acres or more)
Display Field: Forest
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 14 0;"><SPAN>410...Deciduous Forest (>80% hardwood) (Formerly Brushland in 1995) </SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN><SPAN>420...Coniferous Forest (>80% softwood) </SPAN></SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN><SPAN>430...Mixed Forest </SPAN></SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN>DESCRIPTION: Trees are classified as forests when the tree canopy covers at least 50% of the space when viewed from above on an aerial photograph. The three different categories depend upon the composition of deciduous vs. coniferous trees. On an aerial photograph, most coniferous trees have conical shapes (except for pines) with dense needles and tight branching with dark spectral signatures whereas deciduous trees have a more open or freeform shape with leaves (during the growing season) that give the tree a coarser texture or pattern and a looser or more open branching arrangement. Deciduous spectral signatures are generally lighter than coniferous signatures.</SPAN></P></DIV></DIV></DIV>
Description: This is a statewide, seamless digital dataset of the ecological communities for the State of Rhode Island, which was derived using automated and semi-automated methods and based on imagery captured in 2011. The project area encompasses the State of Rhode Island and also extends 1/2 mile into the neighboring states of Connecticut and Massachusetts or to the limits of source orthophotography. Geographic feature accuracy meets the National Mapping Standards for 1:5000 scale mapping with respect to base level data (roads, hydrography, and orthos). The minimum mapping unit for this dataset is .5 acre. The ecological communities classification scheme used for these data was based on the Rhode Island Ecological Communities Classification document created by Richard W. Enser on October 4, 2011.
Copyright Text: This dataset was created by Photo Science Inc., a Quantum Spatial Company