How to Download and Use Land Change Modeler for ArcGIS
Land Change Modeler (LCM) for ArcGIS is a powerful extension that allows you to analyze, model and predict land cover change and its impacts on ecological sustainability. LCM for ArcGIS offers a user-friendly workflow that simplifies the complexities of change analysis and provides a start-to-finish solution for your land change analysis needs.
In this article, we will show you how to download and use LCM for ArcGIS, as well as some of its key features and benefits.
How to Download LCM for ArcGIS
LCM for ArcGIS is available from two sources: Harvard University and Clark Labs. Depending on your affiliation and ArcGIS version, you can choose the most suitable option for you.
If you are a Harvard affiliate, you can download LCM 2.0 for ArcGIS from the Center for Geographic Analysis website[^1^]. This extension works with ArcGIS 10.2 and requires a login with your HUID/HarvardKey. You will also need to follow the installation instructions and run a license file to activate it.
If you are not a Harvard affiliate, or if you have a different ArcGIS version, you can download LCM for ArcGIS from the Clark Labs website[^2^]. This extension is fully integrated into the TerrSet software, which is a geospatial monitoring and modeling system that includes other tools such as IDRISI and GeOSIRIS. You will need to purchase a license for TerrSet and install it on your computer.
How to Use LCM for ArcGIS
Once you have installed LCM for ArcGIS, you can access it from the ArcToolbox window in ArcMap. You will see a folder called Land Change Modeler that contains several tools grouped into four categories: Land Change Analysis, Transition Potential Modeling, Change Prediction, and REDD Analysis.
Each tool has its own interface that guides you through the steps of performing a specific task. You can also refer to the user manual or the online help for more details and examples. Here are some of the main tasks that you can do with LCM for ArcGIS:
Analyze land cover change by generating graphs and maps of gains, losses, net change, persistence, and transitions. You can also abstract complex land change patterns into simpler trends using a change abstraction tool.
Model land cover transition potentials using one of several methods, such as neural network, logistic regression, decision forest, support vector machine, weighted normalized likelihood, or SimWeight. You can also incorporate dynamic variables that drive or explain change.
Predict future land cover scenarios by incorporating planning interventions, incentives and constraints, such as reserve areas and infrastructural changes. You can also create hard or soft prediction maps based on a multi-objective land competition model or a vulnerability map.
Evaluate REDD related forest conservation strategies and carbon impact scenarios with full GHG emission impact accounting. You can also assess additionality of REDD projects and business-as-usual projection scenarios.
Key Features and Benefits of LCM for ArcGIS
LCM for ArcGIS is a comprehensive and innovative tool that helps you to understand the causes and consequences of land cover change and to plan for a more sustainable future. Some of the key features and benefits of LCM for ArcGIS are:
It supports data in IDRISI raster (.rst) and IDRISI vector (.vct) format, as well as any raster file supported by ArcGIS that can be automatically converted to IDRISI format.
It provides an automated workflow that guides you through the steps of land change analysis, modeling and prediction.
It offers a variety of methods and options to suit different data types, objectives and preferences.
It allows you to incorporate spatially explicit planning interventions, incentives and constraints into your future scenarios.
It includes special tools for assessing REDD related forest conservation strategies and carbon impact scenarios.
It produces high-quality graphs and maps that can be exported to other formats or applications.
Land Change Modeler for ArcGIS is a powerful extension that allows you to 29c81ba772