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Raymond L. Czaplewski, Ph.D.

Former Employee
Raymond L. Czaplewski, Ph.D.
Inventory and Monitoring
US Forest Service, Rocky Mountain Research Station
240 W Prospect Road
Fort Collins, CO 80526
United States
Current Research

I use a numerically-robust version of the Kalman filter to combine complex time-series of multivariate environmental monitoring data (e.g., annual NFI sample survey, remote sensing) with predictions from deterministic models (e.g., growth and yield). The number of variables is large, while the number of time-steps is small.

Past Research

Accuracy Assessment of Geospatial Databases

I have conducted extensive technology transfer in sample-survey statistics and design-based estimation related to accuracy assessment of geospatial databases. The most common type of database is based on pixel-level predictions of categorical and continuous land-cover variables with multispectral data from earth-observing orbital satellites, such as Landsat.

Expert Consultant during Adjudication Related to Mathematical Models and Statistical Estimators

I served as principal statistician for the US Forest Service (USFS) during 8 years of litigation related to timber appraisals in the appeal by Lance Logging Co., AGBCA No. 98-137-1, 01-1 BCA. Appellants challenged applications of my stem-profile models (taper equations) and their inherent uncertainty. The USFS uses these and many other types of mathematical and statistical models to aid in strategic and tactical decision-making. On March 20, 2001, Judge Keith R Szeliga ruled in favor of the US Forest Service. This outcome set precedence for use of all such models by the US Government.

In separate adjudication, I served a similar role during defense of the Lolo National Forest, publishing "Application of Forest Inventory and Analysis data to Estimate the Amount of Old Growth Forest and Snag Density in the Northern Region of the National Forest System." US District Judge Donald W. Molloy ruled in favor of the USFS.

Monitoring Natural Resources at National and Global Scales

I have extensive experience in mathematical-statistics for longitudinal sample-surveys, which is an essential component of any scientifically-credible broad-scale monitoring system. For most of my career, I served within the United States Forest Service Forest Inventory and Analysis (FIA) Program, which has a budget exceeding $81-million per year. FIA uses over 150,000 field plots across the USA that are re-measured every 5 to 10 years. This time-series of field-data is the foundation for annual statistical estimates of numerous indicators of forest conditions at the national- to county-scales. During the past 10-years, FIA has incorporated additional monitoring information from multi-temporal remote sensing. I have been one of FIA's leading scientists in use of multivariate remotely sensed data with multivariate field data to improve timeliness and reliablity of FIA information.

In addition, I was the lead consulting statistician for the 1990 Global Forest Resource Assessment conducted by the Food and Agriclutural Organization (FAO) of the United Nations. As a member of a small FAO team, I helped design and implement a global monitoring system that quantified the rates of tropical deforestation between 1980 and 1990 at sub-continental to global scales. This system used a probablity sample of satellite data from the Landsat program, which was pre-stratified with a deterministic mathematical model that predicted rates of deforestation based on socioeconomic and climatic data.

Other related projects include member of inter-agency teams for design of the monitoring program to implement the President's Northwest Forest Plan (1995-1997); identification of conceptual requirements for an extensive national wildlife monitoring program (2005); and a monitoring system for rural lands is the States of Jalisco and Colima, Mexico (2000-2005).

Research Interest

I have extensive experience in complex sample-surveys related to environmental monitoring. My research and development focuses on the national Forest Inventory and Analysis (FIA) program within the United States Forest Service (USFS), which is a large agency in the US Department of Agriculture (USDA). I am partially retired, with Scientist Emeritus status at the USFS Rocky Mountain Research Station. I seek innovative applications of multivariate time-series methods to better monitor the condition of natural resources

Why This Research Is Important

My research improves relevancy, timeliness and efficiency of the Forest Inventory and Analysis (FIA) program as articulated its 2007 Strategic Plan. The resulting mathematical statistics methods directly respond to recommendations from the National FIA User Group.

This research applies concepts from state-space and elementary systems-ecology to analyze time-series from annual FIA panels. This R&D also includes the static Kalman, which improves population estimates with auxiliary census data (e.g., remotely sensed Landsat pixels, administrative records) and independent sample survey estimates (e.g., sample of observations with high-resolution aerial photography or LiDAR). In these multivariate applications, the state-vector can have dimensions of 10 to 1000 or more state-variables, which represent time-series for areas of different forest conditions, numbers of trees by different species and size classes, and wood volumes categorized into different conditions. Such large dimensions suffer from ill-conditioned covariance matrices and serious numerical round-off errors, which are endemic to numerical computations with digital computers. I use numerical mitigation methods that are well-developed in the engineering literatures (e.g., avionics, astronomics, GPS/INS). These employ the LDL' square-root filter and pivots/partitioning suitable for singular and ill-conditioned covariance matrices. Details are partially documented in my past publications on the Kalman filter

  • Colorado State University, Ph.D. Quantitative Range Ecologhy, Annual monitoring of big game populations with management data, demographic models, and a demographic model-based statistical estimator (Kalman filter)., 1986
  • University of Wyoming, M.S. System Ecology, Mathematical theoretics of group selection, 1972
  • Northwestern University, B.A., Biology, 1970
Professional Experience
  • Emeritus Scientist, Research Mathematical Statistician,  |US Forest Service, Rocky Mountain Research Station,  2010 - Current
    I develop data-synthesis methods for the USDA national Forest Inventory and Analysis (FIA) Program. Methods combine time-series of sample-surveys with field plots and samples of high-resolution aerial imagery; full-coverage satellite data (Landsat, MODIS); and simple deterministic demographic-models. I implement methods with numerically-robust algorithms and statistical-software. These multivariate techniques reliably accommodate thousands of estimates (statistical tables) across a small number of annual time-steps.
  • Research Mathematical Statistician,  US Forest Service, Rocky Mountain Research Station,  1989 - 2010
    I developed methods in mathematical statistics that combine multivariate time-series of sample-survey estimates from field plots, remotely sensed data (full-coverage Landsat, sample-surveys with aerial photography), and predictions from deterministic (demographic) models. I use the multivariate Kalman filter and associated numerical methods that were perfected in electrical engineering. The multivariate state-space has large dimensions (numerous statistical tables), while the number of time-steps is small (annual). The application is the national US Forest Service, Forest Inventory and Analysis (FIA) Program.
  • Acting Assistant Director for Research,  US Forest Service, Rocky Mountain Research Station,  2007 - 2007
    I was a member of the executive team that managed research programs, including prioritization of research programs and professional staffing during budget reduction.
  • Project Leader,  US Forest Service, Rocky Mountain Research Station,  1996 - 2004
    I supervised a small team of Research Mathematical Statisticians. We conducted research and development to improve the cost-effectiveness of the national Forest Inventory and Analysis (FIA) Program, US Forest Service. This included leadership in shaping direction of our research priorities, budget allocation, and service as a member of the Management Teams for the Rocky Mountain Research Station and the national FIA program.
  • Acting National Budget Coordinator for Research and Development Deputy Area,  US Forest Service, Research and Development Deputy Area, Washington Office,  2003 - 2003
    I managed process for formulation of the national budget for Research and Development. This included support to the Deputy Chief for Research and Development during Congressional testimony and requests for information from the Office of Management and Budget and Congressional staffs.
  • Senior Consulting Statistician,  Food and Agricultural Organization (FAO) of the United Nations,  1992 - 1996
    As an adjunct member of a small and dedicated team, we designed and implemented a global monitoring system for tropical deforestation between 1980 and 1990. I designed the sampling-frame based on probability sample of scenes from the space-borne Landsat earth-observing satellite.
  • Program Analyst,  US Forest Service, Bighorn National Forest,  1979 - 1982
    I was a member of the core team that supported development of the first strategic plan for the Bighorn National Forest under the National Forest Management Act of 1976. I built upon previous work on the Forest's Timber Management Plan. My work was primarily on data and development of numerical tools for a geographic information system (GIS) known as R2MAP. This effort is among the first few examples in use of GIS in land and resource management.
Awards & Recognition
  • USDA Group Honor Award for Excellence, 2003
    For combining pixel based remote sensing technology and geospatial statistics to create a low cost, efficient, scaleable monitoring system tested over 22 million hectares of agricultural and forest land in Jalesco and Colima, Mexico
  • Best Scientific Paper Published in the Open Literature of Remote Sensing, , 2003
    Awarded by the Remote Sensing and Photogrammetry Society for the paper: Czaplewski, R.L. 2003. Can a sample of Landsat sensor scenes reliably estimate the global extent of tropical deforestation? International Journal of Remote Sensing 24(6):1409-141
  • USDA Certificate of Merit, Rocky Mountain Research Station, 2003
    Awarded for creativity and leadership in helping build an unprecedented partnership between the Forest Service and the US Geological Service to map the nation’s forest cover
  • USDA Certificate of Merit from Regional Forester, Rocky Mountain Region, US Forest Service, 2001
    Awarded for “Outstanding and long-term support to the Lance Logging Company Timber Sale Contract Case that resulted in a March 2001 precedent-setting decision in favor of the Forest Service and substantial future monetary savings for the agency."
  • Honorary Member of the Finnish Society of Forest Science, 1999
    For service on the Editorial Board of Silva Fennica
Featured Publications
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