LANDIS
General System description
System Name: LANDIS
Brief overview
LANDIS is a spatially explicit landscape simulation model. It models natural processes, such as fire, wind, and insect disturbance; succession, and seed dispersal, as well as forest management.
Contents
Scope of the system
The purpose of LANDIS is to predict forest landscape change over long time periods. LANDIS was developed because previous forest simulation models were not suited for larger areas. Spatially explicit computer simulation of entire landscapes requires simulation at appropriate spatial resolution and level of mechanisms and processes that are modelled.
LANDIS is a spatially explicit landscape simulation model. It models natural processes, such as fire, wind, and insect disturbance; succession, and seed dispersal, as well as forest management. LANDIS is raster-based and tracks only presence or absence of tree species in a given age class. Disturbance events are simulated stochastically based on mean return intervals and disturbance size.
System origin
LANDIS development began in the early 1990s under the direction of Dr. David Mladenoff, with partial funding from the Northern Research Station, Rhinelander, Wisconsin. Dr. Hong He joined the team in the late 1990s followed by Dr. Robert Scheller several years later. There are two currently supported versions of LANDIS which were developed with primary funding from the Northern Research Station of the USDA Forest Service.
LANDIS 4.0 is a fully modular software product with improved fire simulation and new capabilities for simulating fuel accumulation and decomposition and disturbance by biological agents such as insects and disease. Dr. He led the development of this version at the University of Missouri in collaboration with the Northern Research Station in Rhinelander, Wisconsin.
LANDIS-II is a completely re-engineered version developed at the Forest Landscape Ecology Laboratory, University of Wisconsin-Madison, in collaboration with the Northern Research Station in Rhinelander, Wisconsin. LANDIS-II was designed to advance forest landscape simulation modeling in many respects, including:
- allows for the incorporation of ecosystem processes and states (e.g., live biomass accumulation) at broad spatial scales
- has flexible time steps for every process,
- uses an advanced architecture that will significantly increase collaborative potential. [1]
Support for specific issues
- Landscape planning
Support for specific thematic areas of a problem type
- Silvicultural
Capability to support decision making phases
[Intelligence, Design, Choice, Monitoring [2]]
- Intelligence: LANDIS supportS understanding natural changes in ecosystem states
- Design: LANDIS allows creating various management simulations to understand how these affect ecosystems over time
Related systems
- LANDIS-II has taken an open source, modular design for which numerous extensions are available at http://www.landis-ii.org/exts
- Companion tools:[3]
- LANDISVIEW - A graphical tool for quickly examining and animating LANDIS-II outputs
- PnET for LANDIS-II - A tool for calculating maximum ANPP and/or species probability of establishment.
- APACK Tool for Landscape Metrics and Analysis
- IAN: Extensible Image Analysis Tool (Calculates Landscape Metrics):
Data and data models
Typical spatial extent of application
Typically applied to large landscapes from thousands to millions of hectares.
Forest data input
LANDIS represents landscapes as a grid of cells and tracks age cohorts of each species (presence/absence or biomass) rather than individual trees[4]. Spatial resolution is flexible, generally 10-500 m pixel sizes[5].
Required LANDIS-II data can be broken into three basic data types: species data, ecoregion data, and initialization data.[6]
Species data include the species life history attributes and species establishment probabilities. Life history attributes can be found in the literature and in the North American Silvic manual. They can also be determined from expert knowledge of the landscape of interest. Species establishment probabilities - the probability of survival after successful germination - are needed for each species and ecoregion combination. These can be estimated from expert knowledge, inventory data (how frequent is a species on each ecoregion?), or from multi-modeling (using a separate model to calculate species establishment probabilities).
Ecoregion definitions are highly dependent upon the landscape and the research or management question. In the midwest, ecoregions are often defined very broadly because of the low topography. Ecoregions are often defined using available landtype definitions: USDA Forest Service sub-sections, HUC, STATSGO polygons, etc. The extent of ecoregions also depends on the process of interest. If fine-scale fire behavior is being simulated, fine-scale ecoregions will be desirable.
Initialization data are the species and ages found on your landscape at the first time step. These data are often the most difficult and expensive to create. And again, the difficulty of creating these data will be dependent upon the data available. In the U.S., Forest Inventory and Analysis data is often summarized by ecoregion and cross-tabulated with satellite classification data. In some areas, more detailed stand cruise data is available for initialization. In general, the fewer species and the more even-aged the forest, the easier initialization will be. Boreal forests are easier, southern hardwoods more difficult.
Type of information input from user (via GUI)
- ???
Models
Forest models
- Succession/Dispersal
- Silvicultural
- Climate impacts
- Insects/Disease
- Fire
- Wind
Social models
Social and economic impacts must be inferred from spatially explicit estimates of biophysical change.
Decision Support
Definition of management interventions
[Define what is available for the manager to intervene in the forest: time of harvest, plantations, thinnings, reconversions...Existence of prescription writer, simple enumeration of all possibilities, scenario simulation , etc.]
Harvests are implemented by removing specific cohorts of specific species on sites selected for harvest. The sites selected for harvest are determined by one of eight “harvest regimes” from which the user may choose. These harvest regimes vary in the number of entries required to complete the silvicultural treatment, and in whether they are applied to 1) an entire stand (stand-filling), 2) a portion of a stand or to multiple stands (stand-spreading), and 3) multiple patches within a single stand (i.e., group selection). The regimes currently available are 1) one-entry, stand-filling, 2) periodic-entry, stand-resampling * , stand-filling, 3) two-entry, stand-filling, 4) one-entry, stand-spreading, 5) two-entry, stand-spreading, 6) periodic-entry, group selection, 7) periodic-entry-fixed stand, two-entry, stand-filling, and 8) periodic-entry-stand-resampling, two-entry, stand-filling. Stand resampling means that in each entry year, the stands within the management area will be ranked again using the initial ranking algorithm. Thus, the specific stands treated in each entry may vary, but the treatment applied will not.
These regimes allow simulation of multiple-entry silvicultural treatments such as shelterwood, seed-tree, and group selection. The periodic entry options allow for automatic harvesting of stands at some specified interval (e.g., rotation length). Stand-filling regimes are applied to every site in a single stand, while stand-spreading regimes begin at a focal site in a stand; harvest terminates when a certain harvest size is reached. This size may be reached before the stand is completely harvested, or the harvest may spill over into an adjacent stand. All eligible sites within a stand must be harvested before harvest can spill over into another stand, but the process may continue until the size has been reached. This feature allows timber management to be used to change the patch size distribution of the landscape, and to allow patterns to emerge that are less constrained by the underlying stand map than are the stand-filling harvest regimes.[7]
Typical temporal scale of application
- LANDIS is typically run for simulations from 10-1000 years.
- LANDIS-II has flexible time steps for every ecological process.
Types of decisions supported
LANDIS is generally used to support strategic planning decisions.
Decision-making processes and models
- Simulation (with stochasticity)
Output
Types of outputs
LANDIS outputs rasters of vegetation coverage consisting of species and age cohorts.
LANDIS-II has a number of companion programs for post-process (see Related Systems above).
Spatial analysis capabilities
- LANDIS simulates a number of processes spatially, including seed dispersal and succession, fire, insects and disease.
- LANDIS uses and outputs spatial data in the ERDAS 7.4 raster files (*.gis).
Abilities to address interdisciplinary, multi-scaled, and political issues
- LANDIS simulates ecosystem processes at multiple scales
System
System requirements
Operating systems: Windows 2000/XP
Development status: Fully operational
Architecture and major DSS components
[Describe the basic architecture of the system in software and hardware. Desktop client-server, web based, as well as the integration with available systems. Basic data flow, focusing on retrieval of required input and propagation and implementations of decisions. Mention its modular and scalability capabilities.]
LANDIS 4.0 is a 32-bit Windows application implemented with Visual C++. Conceptual and operation diagrams of data flow can be found here[8]
LANDIS-II a 32-bit Windows application implemented in version 2.0 of C#. Conceptual and operation diagrams of data flow can be found here[9]. For the upcoming version, the Spatial Modeling Library will become a separate open-source project.[10]
Usage
LANDIS was originally designed for use by researchers, but it has now been applied in a wide variety of management decisions. A number of specific applications are described here[11].
Computational limitations
[Describe the system limitations: e.g. number of management units, number of vehicles, time horizon.]
LANDIS 4 is can process up to 65,536 map classes.
User interface
User interface quality: LANDIS has a Windows-style graphical user interface.
Complexity of system / user interface: Using this program requires a substantial investment in learning the details of the software.
Documentation and support
LANDIS 4 documentation can be found here: http://web.missouri.edu/~umcsnrlandis/userguide.php
LANDIS-II documentation is here: http://www.landis-ii.org/documentation
Installation
Prerequisite knowledge needed: A fairly extensive list of inputs are needed, given the detail at which multiple processes are simulated. Application is probably best accomplished through a team that includes individuals with working knowledge of programming, GIS packages, forest vegetation dynamics, associated resource interactions, and forest planning.
Cost: Free
References
Cited references
- ↑ http://nrs.fs.fed.us/tools/landis/
- ↑ http://fp0804.emu.ee/wiki/index.php/Simon%27s_decision_making_model
- ↑ http://www.landis-ii.org/users
- ↑ http://nrs.fs.fed.us/tools/landis/
- ↑ http://web.missouri.edu/~umcsnrlandis/
- ↑ http://www.landis-ii.org/documentation/Gentle%20Introduction/WhatDataWillINeed
- ↑ http://web.missouri.edu/~umcsnrlandis/harvest.php
- ↑ http://web.missouri.edu/~umcsnrlandis/conceptualdesign.php
- ↑ http://www.landis-ii.org/documentation
- ↑ http://code.google.com/p/landis-spatial/
- ↑ http://www.landis-ii.org/documentation/ProjectsPage
External resources
LANDIS 4
LANDIS-II
- Website: http://www.landis-ii.org/
- Publications: http://www.landis-ii.org/documentation/PublicationsPage
BOTH
