Esri World Elevation Layers are enhanced with more detailed void-free 1 arc second (~ 30 meters) SRTM data for Asia and Australia. The Australian DEM (DEM-S), which is a cleaned and smoothed version of SRTM 1 arc sec, is courtesy … Continue reading
In a country like Netherlands, where about half of its land is less than 1 meter (3.3 ft) above sea level, having detailed and precise elevation data is vital for applications like flood management, climate change, 3D visualization and terrain analysis. … Continue reading
Esri World Elevation Layers are enhanced with more detailed void-free 1 arc-second (~ 30 meters) SRTM data (Version 3.0) from NASA for South America, Western Europe, Central America and Caribbean Islands. With this update, there is now 3 times more … Continue reading
On September 23, 2014, the White House announced that the highest possible resolution elevation data generated from NASA’s Shuttle Radar Topography Mission (SRTM) in 2000 will be released globally over the next year. The announcement was made at the United Nations … Continue reading
Recently, we released an update to the Esri global collection of multi-scale, multi-resolution and multi-source World Elevation services. These global elevation services enable you to create stunning visualizations, calculate aspect or slope, and provide a baseline for analysis and other … Continue reading
Elevation data supports numerous GIS applications ranging from deriving slope and aspect, stream delineation, cut and fill analysis, viewshed analysis, orthorectification of aerial photography or satellite imagery, rendering 3D visualizations, creating relief maps, and for various types of analysis and … Continue reading
In the previous blog post, I discussed several of the attribute checks you could use to validate attribute updates made on the source parcel data before loading into the fabric. As a continuation, in this post I’ll discuss how to use the geometry and topology checks included in ArcGIS Data Reviewer.
Several checks exist that can help with examining the geometry of the lines and polygons. The first, Invalid Geometry check, looks for features with empty or null geometries as well as non-simple geometries. This check can be run on both the Parcel_Lines and Parcel_Polygons feature classes.
In preparation for loading your parcel data into the parcel fabric there are a number of criteria you have to meet. A critical step in the process is to match your source data to the Local Government Information Model, with all its domains and specific attributes. In this blog I’d like to highlight some of the automated checks in ArcGIS Data Reviewer that can help you validate your data prior to migrating it into this new schema, as it is better to identify any errors before you move to the fabric.
Let’s say you’re a farmer or farm real estate broker, and you are evaluating whether or not to buy a piece of land. Your business and your livelihood depends completely on the land and its capability to produce income.
How do you tell the difference between a bad piece of land and a piece of land that has good potential but hasn’t been managed well or has otherwise been neglected? What can the piece of land do, and what is it really worth?
In a time of great uncertainty and volatility in financial markets and real estate valuation, the inherent capability of a piece of land’s soil asset has just become a lot easier to estimate. Image credit: USDA
To help answer these questions, esri has produced two new maps and map layers on arcgis.com. Both are planning-level maps of the economic capability of the United States’ soils. One map shows the economic capability when the soil is irrigated and the other when the soil is not irrigated. These maps are entitled Irrigated Land Capability Class and Non-Irrigated Land Capability Class, respectively.
Both maps are made directly from the SSURGO planning level soil dataset from NRCS. For the more technical among us, we used the MUAGGATT table fields ICCDCD and NICCDCD from SSURGO. Both maps cover the entire USA including Hawaii, Alaska, and Puerto Rico.
At 1:24,000 scale, each part of the United States falls into one of eight broad land capability classes.
The first four classes (1-4) are useful for growing crops, where each class from one to four needs more management or treatment, and has more limitations than the previous class. For example, classes 3 and 4 require more management or treatment than classes 1 and 2.
The last four land capability classes (5-8) are not useful for crops. NRCS recommends these lands be used for things other than crops, like rangeland, forestland, or wildlife habitat. Class eight isn’t even good for forestry, pasture or rangeland, and so instead NRCS recommends those lands be used for recreation, wildlife habitat, watershed, or aesthetic purposes.
These maps feature a color scheme (shown here in 50% transparency) that matches an image of a sample landscape that you see when you click on each soil map unit. This graphic may then be used like a second legend, displaying the eight classes for you on a replica landscape.
Land Capability Class is one of the most important concepts in the US soil dataset SSURGO. Land Capability Class is even used in some states for property tax assessment. In the State of Ohio, for example, the tax code prescribes specifically how to use this map to determine property tax.
Esri plans to release more land capability maps, specifically Land Capability Subclass. We will let you know as soon as these maps are complete and online, and rest assured that the subclasses will be in a format that is easily mashed up with either the Irrigated or Non-Irrigated Capability Class maps.
Special thanks to Michael Dangermond for providing this post. Questions for Michael: firstname.lastname@example.org