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Suming Jin, Ph.D.

(her/she)

Dr. Suming Jin is a Physical Scientist with the U.S. Geological Survey at the Earth Resources Observation and Science Center (EROS) in Sioux Falls, SD.

Dr. Suming Jin is a Physical Scientist with the U.S. Geological Survey at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD. Dr. Jin received her Ph.D. degree in Forest Resources from the University of Maine in 2005. She was a postdoctoral researcher with the University of Wisconsin-Madison for three years.  Her work has focused on the development of algorithms that make it possible to automate the analysis of satellite imagery for the purpose of large-scale mapping of disturbance. She has developed methodologies and tools for land cover mapping and land cover change monitoring using remote sensing technologies from multiple satellite platforms. Her developed methods have been applied to operational production of NLCD 2006, NLCD 2011, NLCD 2011 for Alaska, CONUS annual land cover mapping from 2006-2011, NLCD 2016 and NLCD 2016 for Alaska, NLCD 2019, NLCD 2021 and NLCD 2021 for Alaska. She co-leads the change detection research team and training and classification research team for LCNext project (i.e. USGS’s premier land cover programs—NLCD and Land Cover Monitoring Assessment and Projection (LCMAP)).

Professional Experience

  • 2021-present Physical Scientist, U.S. Geological Survey Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD

  • 2019-2021 Principal Scientist, ASRC Federal Data Solutions, contractor to USGS EROS Center, Sioux Falls, SD

  • 2013-2018 Senior Scientist, ASRC Federal InuTeq, contractor to USGS EROS Center, Sioux Falls, SD

  • 2010-2013 Scientist, ASRC Research and Technology Solutions, USGS EROS Center, Sioux Falls, SD

Education and Certifications

  • 2005   Ph.D. Forest Resources, University of Maine, Orono, Maine

  • 2001   M.S. Forest Management, Chinese Academy of Forestry, Beijing, China

  • 1998   B.S. Forest Protection, Minor in Computer Science, Beijing Forestry University, Beijing, China

Affiliations and Memberships*

  • American Geophysical Union

  • American Association of Geographers

Abstracts and Presentations

  • Jin, S., J. Detwiz, 2022. CONUS Forest Annual Disturbance Product 1984-2019. USGS EROS Center.

  • Jin, S., J. Detwiz, 2022. NLCD Change Detection Using CCDC Synthetic and Composite Imagery. USGS EROS Center.

  • Jin, S., J. Detwiz, P. Danielson, B. Granneman, C. Costello, and Z. Zhu. 2021. National Land Cover Database 2019: A new strategy for creating clean Landsat composite images. AGU 2021 Fall meeting, December 13-17, New Orleans, LA.

  • Jin, S., J. Detwiz, C. Li, D. Sorenson, Z. Zhu, R. Shogib, P. Danielson, B. Granneman, C. Costello, A. Case, L. Gass. 2021. National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance date product. AGU 2021 Fall meeting, December 13-17, New Orleans, LA.

  • Jin, S., Homer, C.G., Dewitz, J., Danielson, P., and Howard, D.M., 2019, National Land Cover Database (NLCD) 2016 science research products [poster], in Fall Meeting, San Francisco, Calif., 9–13 December 2019, Proceedings: Washington, D.C., American Geophysical Union, pap. B11I-2301, at https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/500104.

  • Homer, C.G., Dewitz, J., Jin, S., and Xian, G., 2019, Completion of the 2016 National Land Cover Database, revealing patterns of conterminous U.S. land cover change from 2001 to 2016 [abs.], in Fall Meeting, San Francisco, Calif., 9–13 December 2019, Proceedings: Washington, D.C., American Geophysical Union, pap. B24A-03, at https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/502981.

  • Danielson, P., Yang, L., Jin, S., and Homer, C.G., 2019, Overview of the new National Land Cover Database (NLCD) 2016 land cover and land cover change products [abs.], in Annual Meeting, Washington, D.C., 3–7 April 2019, Proceedings: Washington, D.C., American Association of Geographers.

  • Jin, S., L. Yang, P. Danielson, J. Detwiz, C. Homer and G. Xian. 2018. Overall Method Design for NLCD 2016: 2001-2016 Land Cover and Land Cover Change. AGU 2018 Fall meeting, December 10-14, Washington DC.

  • Jin, S., L. Yang, P. Danielson, J. Detwiz, C. Homer and G. Xian. 2017. Overall Method Design for NLCD 2016: 2001-2016 Land Cover and Land Cover Change. The 2017 Silk Road Innovation Forum on Surveying, Remote Sensing, and Geographical Information Sciences (IFSRG), December 18-21, Xi’an, China.

  • Jin, S., L. Yang, P. Danielson, J. Detwiz, C. Homer and G. Xian. 2017. Overall Method Design for NLCD 2016: 2001-2016 Land Cover and Land Cover Change. Pecora 20, November 13-16, Sioux Falls, SD.

  • Jin, S., L. Yang, Z. Zhu, and C. Homer. 2017. Water and Ice/Snow Change Mapping between NLCD circa 2001 and 2011 in Alaska. AAG 2017 annual meeting, April 5-9, Boston, MA.

  • Jin, S., L. Yang, and C. Homer. 2016. Multi-Date National Land Cover Database 2016 Wetlands Mapping in the Conterminous United States. AAG 2016 annual meeting, March 29-April 2, San Francisco, CA.

  • Jin, S., L. Yang, and C. Homer. 2013. Alaska vegetated land cover change detection and classification from 2001 and 2011. 2013 AGU Fall Meeting, Dec. 9-13, San Francisco, California, USA. (Poster).

  • Huang, S., Liu, H., Dahal, D., Jin, S., Welp, L.R., Liu, J., and Liu, S., 2013, Integrating satellite images and flux tower measurements to model spatially explicit fire impact on vegetation production in interior Alaska [abs.], in The next decade of carbon cycle research—from understanding to application, NACP All-Investigators Meeting, 4th, Albuquerque, N. Mex., 4-7 February 2013, (Poster).

  • Jin, S., L. Yang, P. Danielson, C. Homer, and J. Fry. 2012. A simple and effective method for detecting forest disturbances and regeneration using two-date Landsat images. 2012 AGU Fall Meeting, Dec. 3-7, San Francisco, California, USA. (Poster).

  • Danielson, P., L. Yang, S. Jin, and C. Homer. 2012. A method for improving classification accuracy of crop classes for the National Land Cover Database 2006. 2012Association of American Geographers (AAG) Annual Meeting, February 24-28, New York.

  • Jin, S., L. Yang, J.E. Vogelmann, and C. Homer. 2011. Applicability of Landsat ETM+ SLC-off imagery filled using the Neighborhood Similar Pixel Interpolator for change detection. 2011 AGU Fall Meeting, Dec. 5-9, San Francisco, California, USA. (Poster).

  • Yang, L., S. Jin, C. Homer, P. Danielson, J. Fry, and G. Xian. 2011. NLCD 2011: A new generation of land cover characterization and monitoring. 2011 18th William T. Pecora Memorial Remote Sensing symposium, Nov. 14-17, Herndon, Virginia.

  • Danielson, P., L. Yang, S. Jin, and C. Homer. 2011. Development of a new protocol for mapping crop and hay/pasture areas for the National Land Cover Database 2011 (NLCD2011). 2011Association of American Geographers (AAG) Annual Meeting, April 12-15, Seattle, Washington.

  • Jin, S., L. Yang, G. Xian, P. Danielson, and C. Homer. 2010. A multi-index integrated change detection method for updating the National Land Cover Database. 2010 AGU Fall Meeting, December 13-17, San Francisco, California, USA. (Poster)

Science and Products

Filter Total Items: 20

A "Region-Specific Model Adaptation (RSMA)" based training data method in large-scale land cover mapping

An accurate and historical land cover monitoring dataset for Alaska could provide fundamental information for a range of studies, such as conservation habitats, biogeochemical cycles, and climate systems, in this distinctive region. This research addresses challenges associated with the extraction of training data for timely and accurate land cover classifications in Alaska over longer time period
Authors
Congcong Li, George Z. Xian, Suming Jin
By
Earth Resources Observation and Science (EROS) Center

Evaluation of Landsat image compositing algorithms

We proposed a new image compositing algorithm (MAX-RNB) based on the maximum ratio of Near Infrared (NIR) to Blue band (RNB), and evaluated it together with nine other compositing algorithms: MAX-NDVI (maximum Normalized Difference Vegetation Index), MED-NIR (median NIR band), WELD (conterminous United States Web-Enabled Landsat Data), BAP (Best Available Pixel), PAC (Phenology Adaptive Composite)
Authors
Shi Qiu, Zhe Zhu, Pontus Olofsson, Curtis Woodcock, Suming Jin
By
Earth Resources Observation and Science (EROS) Center

Where forest may not return in the western United States

Droughts that are hotter, more frequent, and last longer; pest outbreaks that are more extensive and more common; and fires that are more frequent, more extensive, and perhaps more severe have raised concern that forests in the western United States may not return once disturbed by one or more of these agents. Numerous field-based studies have been undertaken to better understand forest response t
Authors
James Wickham, Anne Neale, Kurt H. Riitters, Maliha Nash, Jon Dewitz, Suming Jin, Megan van Fossen, D Rosenbaum
By
Earth Resources Observation and Science (EROS) Center

National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance product

The National Land Cover Database (NLCD) 2016 products show that, between 2001 and 2016, nearly half of the land cover change in the conterminous United States (CONUS) involved forested areas. To ensure the quality of NLCD land cover and land cover change products, it is important to accurately detect the location and time of forest disturbance. We designed a comprehensive strategy to integrate a c
Authors
Suming Jin, Jon Dewitz, Congcong Li, Daniel G. Sorenson, Zhe Zhu, Rakibul Shogib, Patrick Danielson, Brian Granneman, Catherine Costello, Adam Case, Leila Gass
By
Earth Resources Observation and Science (EROS) Center

National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images

National Land Cover Database (NLCD) 2019 is a new epoch of national land cover products for the conterminous United States. Image quality is fundamental to the quality of any land cover product. Image preprocessing has often taken a considerable proportion of overall time and effort for this kind of national project. An approach to prepare image inputs for NLCD 2019 production was developed to ens
Authors
Suming Jin, Jon Dewitz, Patrick Danielson, Brian Granneman, Catherine Costello, Zhe Zhu
By
Science Synthesis, Analysis and Research Program, Earth Resources Observation and Science (EROS) Center , Advanced Research Computing (ARC)

Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database

The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001
Authors
Collin G. Homer, Jon Dewitz, Suming Jin, George Z. Xian, Catherine Costello, Patrick Danielson, Leila Gass, Michelle Funk, James Wickham, Steven Stehman, Roger F. Auch, Kurt H. Riitters
By
Earth Resources Observation and Science (EROS) Center

Overall methodology design for the United States National Land Cover Database 2016 products

The National Land Cover Database (NLCD) 2016 provides a suite of data products, including land cover and land cover change of the conterminous United States from 2001 to 2016, at two- to three-year intervals. The development of this product is part of an effort to meet the growing demand for longer temporal duration and more frequent, accurate, and consistent land cover and change information. To
Authors
Suming Jin, Collin Homer, Limin Yang, Patrick Danielson, Jon Dewitz, Congcong Li, Zhe Zhu, George Z. Xian, Danny Howard
By
Earth Resources Observation and Science (EROS) Center

A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term
Authors
Limin Yang, Suming Jin, Patrick Danielson, Collin Homer, Leila Gass, Stacie M Bender, Adam Case, Catherine Costello, Jon Dewitz, Joyce Fry, Michelle Funk, Brian J. Granneman, Greg C Liknes, Matthew B. Rigge, George Z. Xian
By
Earth Resources Observation and Science (EROS) Center

A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD
Authors
Suming Jin, Limin Yang, Zhe Zhu, Collin G. Homer
By
Earth Resources Observation and Science (EROS) Center

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the
Authors
Zhe Zhu, Alisa L. Gallant, Curtis Woodcock, Bruce Pengra, Pontus Olofsson, Thomas R. Loveland, Suming Jin, Devendra Dahal, Limin Yang, Roger F. Auch
By
Earth Resources Observation and Science (EROS) Center , Land Change Monitoring, Assessment, and Projection

Spatial variations in immediate greenhouse gases and aerosol emissions and resulting radiative forcing from wildfires in interior Alaska

Boreal fires can cool the climate; however, this conclusion came from individual fires and may not represent the whole story. We hypothesize that the climatic impact of boreal fires depends on local landscape heterogeneity such as burn severity, prefire vegetation type, and soil properties. To test this hypothesis, spatially explicit emission of greenhouse gases (GHGs) and aerosols and their resul
Authors
Shengli Huang, Heping Liu, Devendra Dahal, Suming Jin, Shuang Li, Shu-Guang Liu
By
Earth Resources Observation and Science (EROS) Center

An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach

We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for t
Authors
Patrick Danielson, Limin Yang, Suming Jin, Collin G. Homer, Darrell Napton
By
Earth Resources Observation and Science (EROS) Center

Non-USGS Publications**

Jin, S. and S.A. Sader. 2006. Effects of ownership and change on forest harvest rates, types and trends in northern Maine. Forest Ecology and Management 228: 177-186.
Jin, S., and S.A. Sader. 2005. MODIS time-series imagery for forest disturbance detection and quantification of patch size effects. Remote Sensing of Environment 99(4): 462-470.
Jin, S., and S.A. Sader. 2005. Comparison of time-series tasseled cap wetness and the normalized difference moisture index in detecting forest disturbances. Remote Sensing of Environment 94(3): 364-372.
Sader, S.A., S. Jin, J.W. Metzler, and M. Hoppus. 2006. Exploratory analysis of forest harvest and regeneration pattern among multiple landowners. Forestry Chronicle 82(2): 203-210.
Sader, S.A., M. Hoppus, J. Metzler, and S. Jin. 2005. Perspectives of Maine forest cover change from Landsat imagery and forest inventory analysis (FIA). Journal of Forestry 103(6): 299-303.
Sader, S.A, S. Jin., J. Metzler. and M. Hoppus. 2005. The effect of sensor resolution and image acquisition gaps on forest change detection errors. International Forestry Review, v.7(4) p. 285.

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

Science and Products

Filter Total Items: 20

A "Region-Specific Model Adaptation (RSMA)" based training data method in large-scale land cover mapping

An accurate and historical land cover monitoring dataset for Alaska could provide fundamental information for a range of studies, such as conservation habitats, biogeochemical cycles, and climate systems, in this distinctive region. This research addresses challenges associated with the extraction of training data for timely and accurate land cover classifications in Alaska over longer time period
Authors
Congcong Li, George Z. Xian, Suming Jin
By
Earth Resources Observation and Science (EROS) Center

Evaluation of Landsat image compositing algorithms

We proposed a new image compositing algorithm (MAX-RNB) based on the maximum ratio of Near Infrared (NIR) to Blue band (RNB), and evaluated it together with nine other compositing algorithms: MAX-NDVI (maximum Normalized Difference Vegetation Index), MED-NIR (median NIR band), WELD (conterminous United States Web-Enabled Landsat Data), BAP (Best Available Pixel), PAC (Phenology Adaptive Composite)
Authors
Shi Qiu, Zhe Zhu, Pontus Olofsson, Curtis Woodcock, Suming Jin
By
Earth Resources Observation and Science (EROS) Center

Where forest may not return in the western United States

Droughts that are hotter, more frequent, and last longer; pest outbreaks that are more extensive and more common; and fires that are more frequent, more extensive, and perhaps more severe have raised concern that forests in the western United States may not return once disturbed by one or more of these agents. Numerous field-based studies have been undertaken to better understand forest response t
Authors
James Wickham, Anne Neale, Kurt H. Riitters, Maliha Nash, Jon Dewitz, Suming Jin, Megan van Fossen, D Rosenbaum
By
Earth Resources Observation and Science (EROS) Center

National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance product

The National Land Cover Database (NLCD) 2016 products show that, between 2001 and 2016, nearly half of the land cover change in the conterminous United States (CONUS) involved forested areas. To ensure the quality of NLCD land cover and land cover change products, it is important to accurately detect the location and time of forest disturbance. We designed a comprehensive strategy to integrate a c
Authors
Suming Jin, Jon Dewitz, Congcong Li, Daniel G. Sorenson, Zhe Zhu, Rakibul Shogib, Patrick Danielson, Brian Granneman, Catherine Costello, Adam Case, Leila Gass
By
Earth Resources Observation and Science (EROS) Center

National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images

National Land Cover Database (NLCD) 2019 is a new epoch of national land cover products for the conterminous United States. Image quality is fundamental to the quality of any land cover product. Image preprocessing has often taken a considerable proportion of overall time and effort for this kind of national project. An approach to prepare image inputs for NLCD 2019 production was developed to ens
Authors
Suming Jin, Jon Dewitz, Patrick Danielson, Brian Granneman, Catherine Costello, Zhe Zhu
By
Science Synthesis, Analysis and Research Program, Earth Resources Observation and Science (EROS) Center , Advanced Research Computing (ARC)

Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database

The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001
Authors
Collin G. Homer, Jon Dewitz, Suming Jin, George Z. Xian, Catherine Costello, Patrick Danielson, Leila Gass, Michelle Funk, James Wickham, Steven Stehman, Roger F. Auch, Kurt H. Riitters
By
Earth Resources Observation and Science (EROS) Center

Overall methodology design for the United States National Land Cover Database 2016 products

The National Land Cover Database (NLCD) 2016 provides a suite of data products, including land cover and land cover change of the conterminous United States from 2001 to 2016, at two- to three-year intervals. The development of this product is part of an effort to meet the growing demand for longer temporal duration and more frequent, accurate, and consistent land cover and change information. To
Authors
Suming Jin, Collin Homer, Limin Yang, Patrick Danielson, Jon Dewitz, Congcong Li, Zhe Zhu, George Z. Xian, Danny Howard
By
Earth Resources Observation and Science (EROS) Center

A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term
Authors
Limin Yang, Suming Jin, Patrick Danielson, Collin Homer, Leila Gass, Stacie M Bender, Adam Case, Catherine Costello, Jon Dewitz, Joyce Fry, Michelle Funk, Brian J. Granneman, Greg C Liknes, Matthew B. Rigge, George Z. Xian
By
Earth Resources Observation and Science (EROS) Center

A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD
Authors
Suming Jin, Limin Yang, Zhe Zhu, Collin G. Homer
By
Earth Resources Observation and Science (EROS) Center

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the
Authors
Zhe Zhu, Alisa L. Gallant, Curtis Woodcock, Bruce Pengra, Pontus Olofsson, Thomas R. Loveland, Suming Jin, Devendra Dahal, Limin Yang, Roger F. Auch
By
Earth Resources Observation and Science (EROS) Center , Land Change Monitoring, Assessment, and Projection

Spatial variations in immediate greenhouse gases and aerosol emissions and resulting radiative forcing from wildfires in interior Alaska

Boreal fires can cool the climate; however, this conclusion came from individual fires and may not represent the whole story. We hypothesize that the climatic impact of boreal fires depends on local landscape heterogeneity such as burn severity, prefire vegetation type, and soil properties. To test this hypothesis, spatially explicit emission of greenhouse gases (GHGs) and aerosols and their resul
Authors
Shengli Huang, Heping Liu, Devendra Dahal, Suming Jin, Shuang Li, Shu-Guang Liu
By
Earth Resources Observation and Science (EROS) Center

An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach

We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for t
Authors
Patrick Danielson, Limin Yang, Suming Jin, Collin G. Homer, Darrell Napton
By
Earth Resources Observation and Science (EROS) Center

Non-USGS Publications**

Jin, S. and S.A. Sader. 2006. Effects of ownership and change on forest harvest rates, types and trends in northern Maine. Forest Ecology and Management 228: 177-186.
Jin, S., and S.A. Sader. 2005. MODIS time-series imagery for forest disturbance detection and quantification of patch size effects. Remote Sensing of Environment 99(4): 462-470.
Jin, S., and S.A. Sader. 2005. Comparison of time-series tasseled cap wetness and the normalized difference moisture index in detecting forest disturbances. Remote Sensing of Environment 94(3): 364-372.
Sader, S.A., S. Jin, J.W. Metzler, and M. Hoppus. 2006. Exploratory analysis of forest harvest and regeneration pattern among multiple landowners. Forestry Chronicle 82(2): 203-210.
Sader, S.A., M. Hoppus, J. Metzler, and S. Jin. 2005. Perspectives of Maine forest cover change from Landsat imagery and forest inventory analysis (FIA). Journal of Forestry 103(6): 299-303.
Sader, S.A, S. Jin., J. Metzler. and M. Hoppus. 2005. The effect of sensor resolution and image acquisition gaps on forest change detection errors. International Forestry Review, v.7(4) p. 285.

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

*Disclaimer: Listing outside positions with professional scientific organizations on this Staff Profile are for informational purposes only and do not constitute an endorsement of those professional scientific organizations or their activities by the USGS, Department of the Interior, or U.S. Government

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