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|Resource type:||Composite Resource|
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|Created:||Jul 23, 2016 at 2:36 p.m.|
|Last updated:|| Feb 01, 2017 at 5:37 a.m.
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The most traditional way to examine land use change is to use a cross-tabulation matrix to identify the most important categorical land use transition from time 1 to time 2. However, such method does not necessarily capture or indicate the real changes on the landscape. For example, assuming that from 1986 to 2015, Utah’s total agricultural land loss (aka, net change) is 200 square miles, but this does not mean that only 200 square miles of agricultural land have experienced land use change in the last 30 years. It is highly possible that a given quantity of agricultural land loss at one location can be accompanied by another quantity of agricultural land gain at another location (aka, swapping). Thus, by purely using net change, we might fail to capture the swapping component of change, and fail to capture the intricate transitions of landscape. This dataset analyzed important categorical land use change while account for persistence and swaps. It provides additional information concerning what happened on the landscape.
This dataset includes a statistical table and a GIS raster file. The table summarizes the persistence and swaps, as well as gross gain and gross loss in the Wasatch Range Metropolitan Area (WRMA). The GIS file is the compiled spatial layer that represents the gain, loss, persistence, and swaps on the landscape. We used Water Related Land Use data of Year 1986 to Year 2015 for this analysis. Land use categories used in this dataset include urban (URB), irrigated agricultural land (IR), and non-irrigated agricultural land (NI), sub-irrigated agricultural land (SubIR), riparian (RIP), water, (WATER), and other (OTHER). We then examined the categorical land use changes with a transition matrix.
A categorical land use gain is determined as the conversion from other sources to this particular categorical land use, and a categorical land use loss is defined as conversion from this particular categorical land use to other uses. For example, the gain of irrigated agricultural (IR) land use will be the sum of areas of urban to IR, non-irrigated agricultural land to IR, sub-irrigated agricultural land to IR, riparian to IR, water to IR, and other to IR. The total change is calculated as the sum of gain and loss. The net change equals to |Gain|-|Loss|. The Swap =2* MIN(Gain,Loss).
Resource Level Coverage
|Variable Description||Land use categories|
|Data Collection Method||We used Water Related Land Use data of Year 1986 to Year 2015 for this analysis. Land use categories used in this dataset include urban (URB), irrigated agricultural land (IR), and non-irrigated agricultural land (NI), sub-irrigated agricultural land (SubIR), riparian (RIP), water, (WATER), and other (OTHER). We then examined the categorical land use changes with a transition matrix.|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||iUTAH-innovative Urban Transitions and Aridregion Hydro-sustainability||1208732|
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
|Shujuan Li||Utah State University|
|Joanna Endter-Wada||Dept. of Environmental & Society, Utah State University|
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/