APPENDIX E2. Vernal Pool Watershed Mapping

Transcription

1 APPENDIX E2 Vernal Pool Watershed Mapping

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3 MEMORANDUM To: U.S. Fish and Wildlife Service From: Tyler Friesen, Dudek Subject: SSHCP Vernal Pool Watershed Analysis Using LIDAR Data Date: February 6, 2014 cc: Sherri Miller, Terry Adelsbach, Richard Radmacher, Bill Ziebron Attachment(s): Figures 1 4; Attachment A, ArcGIS Glossary LIDAR OVERVIEW FROM ARCGIS ONLINE RESOURCE CENTER What Is LIDAR? Light detection and ranging (LIDAR) is an optical remote-sensing technique that uses laser light to densely sample the surface of the Earth, producing highly accurate x, y, z measurements. LIDAR, primarily used in airborne laser mapping applications, is emerging as a cost-effective alternative to traditional surveying techniques such as photogrammetry. LIDAR produces mass point cloud datasets that can be managed, visualized, analyzed, and shared using ArcGIS. The major hardware components of a LIDAR system include a collection vehicle (aircraft, helicopter, vehicle, and tripod), laser scanner system, Global Positioning System (GPS), and inertial navigation system (INS). An INS system measures roll, pitch, and heading of the LIDAR system. LIDAR is an active optical sensor that transmits laser beams toward a target while moving through specific survey routes. The reflection of the laser from the target is detected and analyzed by receivers in the LIDAR sensor. These receivers record the precise time from when the laser pulse left the system to when it is returned to calculate the range distance between the sensor and the target. Combined with the positional information (GPS and INS), these distance measurements are transformed to measurements of actual three-dimensional points of the reflective target in object space. LIDAR Laser Returns Laser pulses emitted from a LIDAR system reflect from objects both on and above the ground surface: for instance, vegetation, buildings, and bridges. One emitted laser pulse can

4 Memorandum Subject: SSHCP Vernal Pool Watershed Analysis Using LIDAR Data return to the LIDAR sensor as one or many returns. Any emitted laser pulse that encounters multiple reflection surfaces as it travels toward the ground is split into as many returns as there are reflective surfaces. The first returned laser pulse is the most significant return and will be associated with the highest feature in the landscape like a treetop or the top of a building. The first return can also represent the ground, in which case only one return will be detected by the LIDAR system. Multiple returns are capable of detecting the elevations of several objects within the laser footprint of an outgoing laser pulse. The intermediate returns, in general, are used for vegetation structure, and the last return for bare-earth terrain models. Post-Processing LIDAR Data The point data is post-processed after the LIDAR data collection survey into highly accurate geo-referenced x, y, z coordinates by analyzing the laser time range, laser scan angle, GPS position, and INS information. Additional information is stored along with every x, y, and z positional value. The following LIDAR point attributes are maintained for each laser pulse recorded: intensity, return number, number of returns, point classification values, points that are at the edge of the flight line, RGB (red, green, and blue) values, GPS time, scan angle, and scan direction. These data are typically stored as LAS files. LAS is an industry format created and maintained by the American Society for Photogrammetry and Remote Sensing. LAS is a published standard file format for the interchange of LIDAR data. It maintains specific information related to LIDAR data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. LIDAR Point Classification Every LIDAR point can have a classification assigned to it that defines the type of object that has reflected the laser pulse. LIDAR points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. SSHCP VERNAL POOL WATERSHED ANALYSIS USING LIDAR DATA Purpose: To identify individual vernal pool watershed boundaries in order to assess potential direct and indirect impacts to aquatic resources contained in existing and planned preserves within the South Sacramento Habitat Conservation Plan (SSHCP) Urban Development Area (UDA) February 2014

5 Memorandum Subject: SSHCP Vernal Pool Watershed Analysis Using LIDAR Data This analysis uses a similar approach implemented by ECORP Environmental Consulting, conducted for the Cordova Hills development in Process 1. Acquire high resolution classified LIDAR data 2. Develop a Digital Terrain Model (DTM) of the UDA 3. Utilize industry standard hydrologic assessment tools to determine hydrologic characteristics of the UDA 4. Divide UDA into sub-areas to facilitate a faster model run time 5. Identify hydrologic boundaries between individual vernal pool features and their watersheds. Acquire High-Resolution Classified LIDAR Data LIDAR surveys were conducted for Sacramento County during 2004 and The County of Sacramento provided Dudek with classified LIDAR data from these surveys. Figure 1 shows the extent of these surveys in relation to the SSHCP plan area boundary and the UDA. Develop a DTM of the UDA Using LAS files from both the 2004 and 2007 surveys, Dudek selected all the LAS files that fell within 1,000 feet for the UDA. The distance of 1,000 feet was chosen to incorporate vernal pool feature watersheds that may extend beyond the UDA boundary. Dudek then created a master LAS dataset filtering the classified LAS files to isolate only bare earth returns. These bare earth points were converted in ArcGIS into a raster dataset using 5-foot by 5-foot cell sizes (see Attachment A for a description of raster datasets). A cell size of 5 feet by 5 feet was chosen to capture the maximum amount of vernal pool features with the least amount of interpolation of the LIDAR data. Dudek then created a hydrologically corrected model by filling all sinks in the resulting raster (see Attachment A for a description of the ArcGIS Fill tool). The final product was a hydrologically corrected DTM of the UDA. Utilize Industry Standard Hydrologic Assessment Tools to Determine Hydrologic Characteristics of the UDA In order to identify watersheds from the hydrologically corrected DTM, the direction of flow across the DTM was assessed using the flow direction tool in ArcGIS (see Attachment A for a description of the ArcGIS flow direction tool). The result was a master flow direction raster dataset of the UDA. By assessing direction of flow, it is possible to identify the boundaries between watershed (ridges) using previously mapped vernal pool features as pour points February 2014

6 Memorandum Subject: SSHCP Vernal Pool Watershed Analysis Using LIDAR Data Divide UDA into Sub-Areas to Facilitate a Faster Model Run Time The UDA was broken into seven sub areas to facilitate a faster run time of the model. These sub-areas were defined by the boundaries of planned preserves and the entire project boundary of the five major development projects currently proposed within the UDA. These areas are defined as follows: 1. Cordova Hills development and adjacent planned preserves 2. Jackson and Newbridge developments and adjacent planned preserves 3. Sun Creek and Arboretum development and adjacent planned preserves 4. Regional Planning Unit (RPU) 1 planned preserves not captured in the above sub-areas 5. RPU 3 planned preserves not captured in the above sub-areas 6. The western portion of Laguna Creek Wildlife Corridor and adjacent planned preserves not captured in the above sub-areas 7. RPU 4 planned preserves not captured in the above sub-areas. See Figure 2 for a map showing the sub-areas. All vernal pool features within the boundaries and up to 250 feet outside of these boundaries were analyzed. The flow direction raster was then clipped to within 1 mile of the above 250- foot buffered area. One mile was chosen to analyze vernal pool feature watersheds under the assumption that it would be difficult to near impossible for stakeholders to adjust existing planned conservation boundaries more than 1 mile in order to protect the watershed from indirect effects. See Figure 3 for an example of these areas. Identify Hydrologic Boundaries Between Individual Vernal Pool Features and Their Watersheds Once a master flow-direction raster dataset was established, the watershed of each individual vernal pool feature could be determined using the ArcGIS watershed tool (see Attachment A for a description of the ArcGIS watershed tool). Each vernal pool feature from the SSHCP land cover database was converted into its own raster dataset using the same cell size (5 feet by 5 feet) as the input flow direction, using a numeric code as the unique identifier. These data were used as the pour point inputs in the watershed tool. A pour point is defined as the cells above which the contributing area, or catchment, will be determined. A custom script was written using Python programming language to analyze the individual watershed of each pour point feature. The output of this analysis was a raster dataset identifying the February 2014

7 Memorandum Subject: SSHCP Vernal Pool Watershed Analysis Using LIDAR Data contributing area for each vernal pool feature. Each of these raster datasets were converted into polygons and combined to create a master watershed file for each of the sub-areas. With these datasets it is possible to identify the watershed of any given vernal pool feature and all contributing vernal pool watershed (see Figure 4 for an example) February 2014

8 Citrus Heights Folsom Fair Oaks 50 Rancho Cordova Sacramento 80 Florin Rancho Murrieta 84 Elk Grove 5 Galt 99 Path: Z:\Projects\Sacramento_County\j7384_SSHCP\MAPDOC\MAPS\LIDAR Analysis Maps\WriteUp_Maps\Figure_01_LidarSurveyArea.mxd Miles 7384 MONTH 2009 SOURCE: County of Sacramento 2013 SOUTH SACRAMENTO COUNTY HABITAT CONSERVATION PLAN 88 SSHCP Plan Area UDA Boundary Sacramento County Boundary Lidar Survey Year Copyright:' 2013 Esri FIGURE 1 Sacramento County Lidar Survey Areas

9 Path: Z:\Projects\Sacramento_County\j7384_SSHCP\MAPDOC\MAPS\LIDAR Analysis Maps\WriteUp_Maps\Figure_02_UDA_SubAreas.mxd I Miles 7384 MONTH 2009 SOURCE: County of Sacramento 2013 SSHCP Plan Area UDA Boundary RPU Boundary Sub Areas Cordova Hills and Adjacent Planned Preserves SOUTH SACRAMENTO COUNTY HABITAT CONSERVATION PLAN Jackson/Newbridge and Adjacent Planned Preserves Sun Creek/Arboretum and Adjacent Planned Preserves RPU1 Planned Preserves RPU 3 Planned Preserves Laguna Creek Wildlife Corridor and Adjacent Planned Preserves RPU 4 Planned Preserves FIGURE 2 Study Sub Areas

10 Path: Z:\Projects\Sacramento_County\j7384_SSHCP\MAPDOC\MAPS\LIDAR Analysis Maps\WriteUp_Maps\Figure_03_AnalysisAreas.mxd I 7384 MONTH ,000 4,000 Feet SOURCE: County of Sacramento 2013 SOUTH SACRAMENTO COUNTY HABITAT CONSERVATION PLAN Jackson/Newbridge and Adjacent Planned Preserves Area Sample Area Vernal Pools 250 ft Vernal Pool Sample 1 mi Radius - Vernal Pool Sample Area Flow Direction Raster Extent (Cell n=17,779,182) FIGURE 3 Watershed Analysis Areas - Jackson and Newbridge Developments and Adjacent Planned Preserves

11 Path: Z:\Projects\Sacramento_County\j7384_SSHCP\MAPDOC\MAPS\LIDAR Analysis Maps\WriteUp_Maps\Figure_04_ResultsExample.mxd I 7384 MONTH Feet SOURCE:Bing 2014, County of Sacramento 2013 FIGURE 4 Watershed Contribution Areas for Vernal Pool SOUTH SACRAMENTO COUNTY HABITAT CONSERVATION PLAN Vernal Pools Swales Watershed Boundaries Contributing Watersheds to VP Vernal Pool Contributing Watersheds

12 ATTACHMENT A ArcGIS Glossary

13 ATTACHMENT A ArcGIS Glossary All descriptions are adapted or copied directly from the ArcGIS Online Resource Center. RASTER DATA In its simplest form, a raster consists of a matrix of cells (or pixels) organized into rows and columns (or a grid) where each cell contains a value representing information, such as elevation. Rasters are digital aerial photographs, imagery from satellites, digital pictures, or even scanned maps. Rasters are well suited for representing data that changes continuously across a landscape (surface). They provide an effective method of storing the continuity as a surface. They also provide a regularly spaced representation of surfaces. Elevation values measured from the earth's surface are the most common application of surface maps, but other values, such as rainfall, concentration, and density, can also define surfaces that can be spatially analyzed. The raster below displays elevation using green to show lower elevation and red, pink, and white cells to show higher elevations. For more information on raster data please visit this link. en/help/main/10.2/index.html#//009t FILL (SPATIAL ANALYST) Summary: Fills sink in a surface raster to remove small imperfections in the data. Usage: A sink is a cell with an undefined drainage direction; no cells surrounding it are lower. The pour point is the boundary cell with the lowest elevation for the contributing area of a sink. If the sink were filled with water, this is the point where water would pour out. The output surface raster will have all sinks filled to the limit of the pour point A-1 February 2014

14 ATTACHMENT A (Continued) FLOW DIRECTION (SPATIAL ANALYST) Summary: Creates a raster of flow direction for each cell to its steepest downslope neighbor. Usage: The output of the Flow Direction tool is an integer raster whose values range from 1 to 255. The values for each direction from the center are: For example if the direction of the steepest drop was to the left of the current processing cell, its flow direction would be coded as 16. If a cell has the same change in z-value in multiple directions and is not part of a sink, the flow direction is assigned with a lookup table defining the most likely direction. A cell at the edge of the surface raster will flow toward the inner cell with the steepest drop in z-value. If the drop is less than or equal to zero, the cell will flow out of the surface raster. WATERSHED (SPATIAL ANALYST) Summary: Determines the contributing area above a set of cells in a Raster. Delineating Watersheds: Watersheds can be delineated from a DEM by computing the flow direction and using it in the watershed tool. To determine the contributing area, a raster representing the direction of flow must first be created with the Flow Direction tool A-2 February 2014

15 ATTACHMENT A (Continued) You will then need to provide the locations you wish to determine the catchment area for. Source locations may be features, such as vernal pools, dams, or stream gauges, for which you want to determine characteristics of the contributing area. The output is a raster of the watersheds. The above example shows the result when multiple pour points are defined in the analysis. Because the goal of the SSHCP analysis was to identify the entire vernal pool watersheds independent of all other vernal pool features watersheds were calculated individually with each vernal pool feature as its own pour point resulting in as many runs of the watershed tool as there were vernal pools. The value of each watershed was taken from the value of the feature pour point data. In the case of the vernal pool watershed analysis the resulting watersheds were coded with the unique vernal pool ID number it corresponds to A-3 February 2014

16 ATTACHMENT A (Continued) INTENTIONALLY LEFT BLANK A-4 February 2014