Our mission is to help you make better decisions every day when operating in complex environments.

We achieve our mission by developing software that provides easy access to critical data; developing models that help reduce complex environments to manageable proportions; assisting our clients -- via training and mentoring -- in using data and models to make more effective decisions.

 

 
Who we are and how Harmeny came to be
Harmeny developed from a group of foresters and researchers working on large monitoring and management programs for companies in N. British Columbia in the mid 1990's. The company's efforts were initially silviculture based, on the development of Integrated Pest Management, Planting Management, Silviculture Treatment (Response) Monitoring and Operational Planning.

This work has been extended more recently into Inventory Management Systems focussing on data access, modeling and forecasting, and decision support systems. Ian Moss, and Mishtu Banerjee developed Harmeny Systems Ltd. to further develop the software tools, analyses, and forest management ideas that originated out of this group. As evidenced in the time line below we have constantly innovated to develop the tools and concepts needed to allow our clients to make better decision every day when operating in complex environments.


Harmeny Time Line: A Decade of Innovation
1995: An Adaptive Management perspective for analysis of Silviculture Monitoring data is developed, based on the concept that there is: (1) a management scenario, (2) a target outcome that is desired and (3) an opportunity to use monitoring (repeated measure) data to identify the likelihood of achieving a targeted outcome. The Adaptive Management perspective is integrated into a risk-management framework similar to invoking the use of Actuary Tables as commonly applied within the insurance industry.

1995 - 1998: The Adaptive Management Approach is refined and applied to various silviculture treatment monitoring programs. Analysis tools are used to summarize the likelihood of achieving desired outcomes based on repeated observations of trees and plots through time, and then combined with Survey data to predict the likelihood of producing desired outcomes within a specified period of time in recently established plantations. Software is developed to generate new Actuary Tables and to enable the Survey based Forecasting System.

1998: The Analysis Tools are incorporated into a new database framework: LifeLine ACT98. The database framework includes a unique data model, scenario based query process, a methodology for loading data into the model, and incorporates the actuary table generator.

1998 - 2000: LifeLine ACT98 is used to house various monitoring and field experiment-based datasets and the survey system is rebuilt into Survey 2000. Survey 2000 works directly with LifeLine ACT98 to create an Integrated Database and Forecasting System. The Forest Stand Financial Analyst is developed and used to evaluate economic returns for alternate silviculture strategies.

2000: LifeLine ACT98 is refined and rebuilt as LifeLine 2000 with (1) a simpler user interface enabling managers to query a wide array of data through the process of defining Management Scenarios. Other refinements include (2) an improved data model, (3) automated Scenario Based Query Process. The LifeLine 2000 system is applied to several inventory-monitoring programs.

2001. LifeLine 2000 is used to integrate a wide range of inventory data: growth and yield, air-photo, plot-based, habitat and ecological monitoring into an inventory warehouse, where all the data is accessible to managers. LifeLine 2000 Developers Tools are built to automate and speed data-model construction, data examination, and data load methodology. A GIS Spatial Link is designed allowing inventory summaries across monitoring programs. In late 2001, LifeLine 2000 went through a complete re-design of all its parts, so that it can form the basis of a new Inventory Management System, LifeLine (Adaptive Inventory) that takes our Adaptive Management principles to a new level, integrating the data-warehouse, spatial analysis, updating and forecasting capabilities required for inventory management.

2002. LifeLine 2.1 is built atop the LifeLine AI 2000 base. Itl allows clients to (1) house all their inventory data, (2) search and summarize data across inventory types, (3) update inventories, and (4) forecast inventories. The Stand Structure Classification methodology is developed. The ForesTree growth model Version 1.0 is developed.

2003. Support is added for querying spatial data in LifeLine via the PostGIS database resulting in LifeLine 3.1. Stand Structure Classification is used with LifeLine modeling techniques to design the Forest Inventory Warehouse which consolidates data with Stand level, plot level and tree level detail and provides stand and stock tables.

2004. LifeLine's spatial querying is extended via support for MapServer so the results of a query on spatial data can be viewed in a map, resulting in LifeLine 3.2 . XAYA, a generalization of the original LifeLine Query engine is developed, to allow developers to rapidly build their own custom applications with LifeLine-like capabilities. The ForesTree Growth Model version 1.0 is integrated with the Forest Inventory Warehouse. Work begins on the ForesTree Growth Model version 2.0

2005. XAYA is being used to develop a new web-centric version of LifeLine -- LifeLine 4.0. The Stand Structure Classification and ForesTree growth model is being used to develop a model for forecasting the effects of natural disturbances such as the bark beetle on the forest inventory.


Mishtu Banerjee has worked in the forest industry for over 15 years, and focussed primarily on building monitoring based decision support systems in various aspects of forestry: nursery, silviculture, woodlands inventory.

Mishtu's scientific interests focus on the analysis of complex developing systems, ecosystem dynamics, and population and quantitative genetics.

His scientific and practical interests combine in the development of the LifeLine software that captures the complexity of our natural world in silico.



Ian Moss has worked in the forest industry for over 20 years, and spanned a diverse range of issues from silviculture, forest policy, forest economics, forest inventory and growth and yield.

Ian's scientific interests are in developing mathematical models that simulate complex biological dynamics such as stand development and succession.

Ian's scientific and practical interests combine in integrating his mathematical models of biological processes fundamental to forestry with econometric models of the pay-offs and costs associated with growing forests.