Windows VBS Coordinate Map URL Scripts

 Add a new download that contains Windows Visual Basic Scripts (VBS) that work from a pasted coordinate or a default coordinate in the folder called coordinates.txt.  The example files show 4 examples plus a command "Create_KML" that creates a Google Earth KML file from a coordinate. If a file exists it then adds a sequence.

1 - USGS_TNM_1m_DEM: Launches the USGS The National Map (TNM) site to a specific coordinate to check for the availability of 1-meter LiDAR DEMs across the USA.

2 - FEMA_MSC_DFIRM: Launches the FEMA Map Service center to a specific coordinate that has the current regulatory map as well as other links to Floodplain Management records and maps.

3 - FEMA-Map_Change: Launches the FEMA Map Change Viewer to a specific coordinate that contains three types of FEMA DFIRM data: Pending, Preliminary, and Available. 

4 - FEMA_FEMA_NFHL: Launches the FEMA National Flood Hazard Layer (NFHL) Viewer to a specific coordinate where you can also  print NFHL FIRMette or Full FIRM.

These are simple tools that put information at you fingertips. ENLOY!

DOWNLOAD

Took my recent task list that was performed in my recent collage class and entered into ChatGPT (free version) without prompting the output.

WK01 - Recommended folder structure & QGIS Setup/settings

WK02 - Using QGIS (location search, tool bars, plugins, projections, REST Services, and filter layers)

WK03 - USGS TNM Download and USGS StreamStats (download WV HYDRO, NSS Basin, and 30m DEM for Kanawha Basin) and merge and clip raster's (symbology and color ramps)

WK04 - Filtering and saving flowline layers, visual selections of Basins and dissolving

WK05 - Map Symbology, Measurement Review: Measure Tool (attributes Tool Bar), Add geometry Attributes (tool box), Attributes Table Field Calculator (geometry function), Transportation Data: Download Data, Merge, and dissolve (add unique ID), delete unneeded fields

WK06 - Create new seed file with all reference layers, Identify River Crossings and Count by Basin, Measure River Miles and Sum by Basin, and "Refactor Fields" and "Aggregate" Commands

WK07 - Series of table joins to Basin watersheds and wrap up of Kanawha Basin with transition Micro Basins

WK08 - Use Galax VA to create micro basin in USGS StreamStats, download DEM from USGS TNM and process data for sub-basin creation

WK09 - Use r.watershed on Galax and understand the raster math of accumulation - begin thinking of final project

WK10 - Introduction to Tool Box Models and the H&H Toolbox for Micro Watersheds

WK11 - Landcover, slope, and geomorphons measurements for Galax

WK12 - Small Watershed Selections / Precipitation Map

WK13 - Map creation with focus on final project

WK14 - Distance Map Project as project example

---

ChatGPT

This sequence appears to outline a structured curriculum for learning GIS concepts and applications using QGIS, with a focus on hydrological and watershed analysis. Here’s a breakdown of the recommended approach to each week:

### **WK01: Recommended Folder Structure & QGIS Setup/Settings**

- **Folder Structure:**

  - Create a top-level project folder with subfolders such as:
    - `Raw_Data`: Unprocessed datasets
    - `Processed_Data`: Cleaned or clipped datasets
    - `Outputs`: Final maps, reports, or figures
    - `Scripts`: Python, R, or model scripts
    - `Documentation`: Notes, metadata, or guidance documents

- **QGIS Setup/Settings:**

  - Customize QGIS interface (toolbars, panels)
  - Set project CRS (coordinate reference system) and on-the-fly projection
  - Install essential plugins (e.g., QuickMapServices, Processing Toolbox, etc.)
  - Configure snapping settings for precise editing

---

### **WK02: Using QGIS**

- **Key Tools & Features:**

  - Use **Locator** to search locations or layers
  - Enable and organize toolbars for navigation, measuring, and editing
  - Explore and install useful plugins such as **GRASS**, **SAGA**, or **OpenLayers**
  - Set up projections: Understand how to reproject layers
  - Access REST services for live GIS data (e.g., WMS/WFS services)
  - Learn filtering methods to display only relevant data in layers

---

### **WK03: USGS TNM Download and StreamStats**

- **Data Download & Processing:**
  - Access **USGS TNM** for 30m DEM and StreamStats for hydrology data
  - Download Kanawha Basin data (e.g., WV Hydro, NSS Basin)
  - **Merge and clip rasters:** Combine multiple rasters and trim to area of interest
  - Apply symbology and color ramps for visual clarity

---

### **WK04: Filtering & Saving Flowline Layers**

- **Processing Flowline Data:**
  - Filter flowline layers to isolate relevant streams or features
  - Use **selection tools** for visual basin delineation
  - Apply the **Dissolve** tool to combine basins or administrative units

---

### **WK05: Map Symbology & Transportation Data**

- **Data Enhancement & Analysis:**
  - Enhance maps with meaningful symbology (colors, classifications)
  - Review attributes with the **Measure Tool** or **Attributes Toolbar**
  - Use **Field Calculator** to add geometry attributes (e.g., area, perimeter)
  - Download transportation data, merge datasets, and dissolve redundant geometries
  - Assign unique IDs and delete unnecessary fields for cleaner data

---

### **WK06: Seed File & River Analysis**

- **Data Consolidation & River Metrics:**
  - Create a new seed file containing all key reference layers
  - Identify and count river crossings by basin
  - Measure river miles and calculate sums by basin
  - Use tools like **Refactor Fields** and **Aggregate** to streamline data

---

### **WK07: Table Joins & Micro Basins**

- **Advanced Table Management:**
  - Perform multiple table joins to enrich watershed data
  - Finalize the Kanawha Basin analysis
  - Transition focus to micro-basins for localized studies

---

### **WK08: Micro Basin Analysis (Galax, VA)**

- **Data Preparation:**
  - Use StreamStats to delineate micro-basin for Galax, VA
  - Download and process a DEM for sub-basin creation
  - Prepare for advanced watershed modeling

---

### **WK09: Raster Analysis with r.watershed**

- **Raster Operations:**
  - Use GRASS GIS tools like **r.watershed** to analyze flow accumulation
  - Explore raster math concepts for hydrological accumulation

---

### **WK10: Toolbox Models**

- **Automating Workflows:**
  - Introduction to the **Processing Toolbox**
  - Use pre-built H&H Toolbox models for micro-watershed analysis

---

### **WK11: Landcover, Slope & Geomorphons**

- **Landscape Analysis:**
  - Analyze landcover using raster data
  - Compute slope and geomorphons (landform classification) using terrain tools

---

### **WK12: Precipitation Map**

- **Hydrological Analysis:**
  - Select small watersheds for focused studies
  - Overlay precipitation data to visualize spatial distribution

---

### **WK13: Final Project Map**

- **Map Creation:**
  - Create maps for the final project, focusing on visual and analytical clarity
  - Incorporate key findings and annotations

---

### **WK14: Distance Map Project**

- **Project Example:**
  - Develop a distance-based map as a practical example for the final project
  - Demonstrate tools like cost-distance analysis or proximity calculations

---

### **Tips for Success:**

1. **Documentation:** Keep track of your processes, tools, and settings in a notebook or text file.
2. **Backup:** Frequently save and backup your work.
3. **Ask Questions:** Use forums or communities like GIS Stack Exchange if you face challenges.

---

Let me know if you’d like more details on any specific week!

QGIS in Watershed Class

The "Q" in QGIS stands for "Quantum." The name "Quantum GIS" was chosen by its founder, Gary Sherman, when he began developing the software in early 2002. The choice of "Quantum" doesn't have a special meaning beyond starting with a "Q," which indicates its use of the Qt library for its graphical user interface. Although the term "quantum" does have a rich history.

 ### Scientific Roots

Originally, "quantum" comes from the Latin word for "amount" or "how much." In the early 20th century, it became a fundamental concept in physics with the development of quantum mechanics. This field of study revolutionized our understanding of atomic and subatomic processes, introducing ideas like quantized energy levels and wave-particle duality.

### Cultural Influence in the Early 2000s

 By the early 2000s, "quantum" had permeated popular culture, often symbolizing cutting-edge technology and futuristic concepts. This was a time marked by rapid technological advancements and a growing fascination with the potential of science to transform everyday life. The term "quantum" was frequently used in media and entertainment to evoke a sense of mystery and advanced science, even if not always accurately.

### In QGIS

When Gary Sherman named QGIS in 2002, the choice of "Quantum" likely reflected this cultural zeitgeist. It suggested that the software was at the forefront of technology, leveraging the latest advancements to provide powerful tools for geospatial analysis. The name also hinted at the precision and complexity that users could expect from the software, aligning with the scientific connotations of the term.

### Broader Cultural Context

The integration of GRASS GIS (Geographic Resources Analysis Support System) into QGIS is a fascinating story that highlights the collaborative nature of open-source software development.

### History of GRASS GIS

GRASS GIS was originally developed by the U.S. Army Corps of Engineers in the early 1980s as a tool for land management and environmental planning. It quickly became one of the most powerful and versatile GIS applications, known for its extensive geospatial analysis capabilities. Over time, GRASS GIS evolved into an open-source project, maintained by a global community of developers and users. 

### Integration with QGIS

The integration of GRASS GIS into QGIS began as a way to leverage the powerful analytical tools of GRASS within the more user-friendly interface of QGIS. This integration allows users to access GRASS functionalities directly from QGIS, combining the strengths of both platforms.

#### Key Features of the Integration:

1. **GRASS Plugin**: To use GRASS functionalities in QGIS, users need to load the GRASS plugin via the Plugin Manager. This plugin provides access to GRASS databases and tools, enabling users to manage and visualize GRASS raster and vector layers.

2. **GRASS Toolbox**: The GRASS Toolbox in QGIS offers over 400 modules for various types of geospatial analysis, including raster and vector manipulation, 3D rendering, and temporal data analysis.

3. **Data Management**: Users can import data into GRASS locations and mapsets directly from QGIS, making it easier to manage and analyze large datasets. 4. **Seamless Workflow**: The integration supports a seamless workflow, allowing users to perform complex analyses without switching between different software environments.

### Impact on the GIS Community

The integration of GRASS GIS into QGIS has significantly enhanced the capabilities of QGIS, making it a more powerful tool for geospatial professionals. It has also fostered a collaborative environment where developers from both communities can contribute to the continuous improvement of the software.

Joe Trimboli with Microsoft Copilot   

FEMA Out-by-LiDAR

 

Using LiDAR For Map Amendments  

LiDAR data can replace the requirement to submit elevation information  

certified by a licensed land surveyor or professional engineer, which can create  

a cost savings for property owners. However, LiDAR data may be less accurate  

than certified elevations and may not capture the full risk for the building or  

lot.  

For more information on the standard LOMA process and requirements,  

please refer to How to Request a Map Amendment Guide.  

DOES MY COMMUNITY HAVE LIDAR?  

Not all communities have LiDAR data available. Talk to your floodplain administrator to find out if your  

community has LiDAR data.  

To be used in a LOMA request, LiDAR data must meet or exceed the U.S. Geological Survey (USGS)  

Quality Level 3 accuracy requirement. To learn more about this requirement, please use the USGS  

LiDAR Base Specification Guide.  

The USGS plans to collect high quality LiDAR data across the United States using a 3D Elevation  

Program (3DEP). For more information on the 3DEP program and current USGS LiDAR availability,  

please visit their 3DEP webpage.  

WHEN LIDAR CANNOT BE USED  

There are situations when LiDAR cannot be used in a LOMA request. These include applications involving  

the following:  

• Buildings or lots elevated using fill  

• Buildings or lots in the regulatory floodway  

• Buildings or lots in Coastal High Hazard Areas (Zone V, VE, or V1-V30)  

• Buildings or lots in Zone AO, AR, or A99  

• Buildings under construction. LiDAR would need to show that the lot or portion of the lot on which  

building will be located is above the Base Flood Elevation (BFE)  

• Conditional determinations  

• Electronic LOMAs (eLOMAs)  

• Potential violations identified through the LOMA process  

• Physical changes to the flooding source/Special Flood Hazard Area that require revisions to the  

Flood Insurance Rate Map  

• Requests to supersede previously issued LOMAs based on certified elevation data  

Additional information about LiDAR requirements for LOMAs is available in the  

MT-1 Technical Guidance document.  

WHAT NEEDS TO BE SUBMITTED WITH MY APPLICATION?  

When requesting a LOMA using LiDAR data, you must submit a paper map or digital PDF that displays:  

(1) an overlay of the LiDAR contours (lines of equal elevation), or  

(2) an overlay of the LiDAR points (points with specific elevations).  

Either overlay must include an aerial image of the building or lot with at least one street intersection  

shown on the map.  

The map must also have:  

• Scale and North arrow  

• Source of the LiDAR, including public website  

address. LiDAR must be provided by a Federal,  

State, or local government agency.  

• Address or Assessor’s Parcel Number (APN)  

for the building/lot  

• LiDAR accuracy information  

• Clearly identified building and/or lot boundaries  

• Name, organization, and contact information  

for the map overlay creator  

(Does it meet Quality Level 3 standards?)  

• Vertical Datum of elevation data (e.g., NAVD 88)  

• Location of the data archive or metadata file  

(must be available for independent verification  

through a publicly available website or metadata)  

• Aerial imagery that correctly represents the  

footprint of the building  

• Date the LiDAR was collected  

Your floodplain administrator or a mapping professional can help you develop the map for your  

application. For other requirements, please use the How to Request a Map Amendment Guide.  

|

DECEMBER 2018  

USING LIDAR FOR MAP AMENDMENTS  

2

CALCULATING ELEVATIONS USING LIDAR  

The lowest adjacent grade (LAG) for a building, or the lowest lot elevation (LLE) for a lot, will be compared  

to the effective Base Flood Elevation (BFE) to determine the flood zone. If LAG/LLE is at or above the BFE  

on the current flood map, FEMA can issue a removal determination. For buildings or lots that cannot be  

removed from the high-risk zone using LiDAR, certified elevation data will be required for a standard LOMA  

determination.  

Using LiDAR Contours  

For LOMA submittals that include LiDAR data contours, FEMA will subtract half the contour interval or  

1 foot, whichever is greater, from the lowest contour closest to (but not going through) the building (to  

determine the LAG) or the lot (to determine the LLE).  

CALCULATING THE LOWEST GRADE (LAG)  

1. Determine the closest contour lower than the building footprint.  

2. Subtract 1/2 the contour interval or 1 ft., whichever is greater to determine the applicable LAG or Lowest Lot Elevation (LLE).  

Elevation 802’  

This structure is Out as Shown (OAS)  

Requests where the FIRM data clearly  

LAG would be 797’  

(closest lower contour  

shows the property/structure to be Out as  

Shown are not eligible for LiDAR review.  

of 798’ - 1’)  

Elevation 800’  

LAG would be 797’  

(closest lower contour  

of 798’ - 1’)  

Elevation 798’  

LAG would be 795’  

(Will Need Field Survey) (closest  

lower contour of 796’ - 1’)  

Elevation 796’  

Zone AE  

Lake BFE = 796.2  

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DECEMBER 2018  

USING LIDAR FOR MAP AMENDMENTS  

3

Using LiDAR Point Data  

For submittals that include LiDAR point data, FEMA will subtract 2 feet from the lowest point closest to the  

building (to determine the LAG) or the lowest point on the lot (to determine the LLE). Multiple points must  

cover the building/lot for this method.  

•365.53  

Zone AE  

Lake BFE = 360.0  

•369.09  

•369.05  

•369.31  

LAG would be 360.77’  

(lowest adjacent  

point -2')  

•362.85  

•366.38  

•367.99  

•369.49  

•371.34  

•370.68  

363.62•  

364.94•  

362.77•  

•371.8  

•373.18  

367.68•  

•374.35  

•374.58  

•374.56  

•374.58  

•371.57  

•372.24  

•370.11  

WHERE DO I GO IF I NEED HELP?  

To speak with a Map Specialist about the amendment process, contact the FEMA Map Information  

eXchange (FMIX) at 877-FEMA-MAP (877-336-2627) or FEMAMapSpecialist@riskmapcds.com  

|

DECEMBER 2018  

USING LIDAR FOR MAP AMENDMENTS  

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