James Wickham

Dr. James Wickham


Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2020 in ISPRS Journal of Photogrammetry and Remote Sensing
Verified
Journal Article
Open access
CHCollin Homer
Collin Homer
JDJon Dewitz
Jon Dewitz
SJSuming Jin
Suming Jin
GXGeorge Xian
George Xian
CCCatherine Costello
Catherine Costello
Kurt  RiittersKurt Riitters
Kurt Riitters
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 to 2016. For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error (SE) was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001 and 2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this period. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001–2006 at twice the rate of 2011–2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database.

1 June 1996 in Landscape Ecology
Verified
Journal Article
Closed access
PDF file
ROR. V. O'Neill
R. V. O'Neill
CHC. T. Hunsaker
C. T. Hunsaker
STS. P. Timmins
S. P. Timmins
BJB. L. Jackson
B. L. Jackson
KJK. B. Jones
K. B. Jones
JWJames Wickham
James Wickham

1 January 2000 in Conservation Ecology
Verified
Journal Article
Closed access
Kurt  RiittersKurt Riitters
Kurt Riitters
JWJames Wickham
James Wickham
RORobert O'NEill
Robert O'NEill
KJK. Bruce Jones
K. Bruce Jones
ESElizabeth Smith
Elizabeth Smith
Riitters, K., J. Wickham, R. O'Neill, B. Jones, and E. Smith. 2000. Global-scale patterns of forest fragmentation. Conservation Ecology 4(2): 3.

1 May 2021 in Remote Sensing of Environment
Verified
Journal Article
Closed access
JWJames Wickham
James Wickham
SSStephen V. Stehman
Stephen V. Stehman
DSDaniel G. Sorenson
Daniel G. Sorenson
LGLeila Gass
Leila Gass
JDJon A. Dewitz
Jon A. Dewitz

11 August 2014 in Remote Sensing
Verified
Journal Article
Open access
PDF file
JWJames Wickham
James Wickham
CHCollin Homer
Collin Homer
JVJames Vogelmann
James Vogelmann
AMAlexa Mckerrow
Alexa Mckerrow
RMRick Mueller
Rick Mueller
JCJohn W. Coulston
John W. Coulston
The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s as a small group with the straightforward goal of compiling a comprehensive national Landsat dataset that could be used to meet agencies’ needs, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five different products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Program (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). As a set, the products include almost every aspect of land cover from impervious surface to detailed crop and vegetation types to fire fuel classes. Some products can be used for land cover change assessments because they cover multiple time periods. The MRLC Consortium has become a collaborative forum, where members share research, methodological approaches, and data to produce products using established protocols, and we believe it is a model for the production of integrated land cover products at national to continental scales. We provide a brief overview of each of the main products produced by MRLC and examples of how each product has been used. We follow that with a discussion of the impact of the MRLC program and a brief overview of future plans.

1 March 2023 in GIScience & Remote Sensing
Verified
Journal Article
Closed access
JWJames Wickham
James Wickham
SSStephen V. Stehman
Stephen V. Stehman
DSDaniel G. Sorenson
Daniel G. Sorenson
LGLeila Gass
Leila Gass
JDJon A. Dewitz
Jon A. Dewitz
The National Land Cover Database (NLCD), a product suite produced through the MultiResolution Land Characteristics (MRLC) consortium, is an operational land cover monitoring program. Starting from a base year of 2001, NLCD releases a land cover database every 2–3-years. The recent release of NLCD2019 extends the database to 18 years. We implemented a stratified random sample to collect land cover reference data for the 2016 and 2019 components of the NLCD2019 database at Level II and Level I of the classification hierarchy. For both dates, Level II land cover overall accuracies (OA) were 77.5% ± 1% (± value is the standard error) when agreement was defined as a match between the map label and primary reference label only, and increased to 87.1% ± 0.7% when agreement was defined as a match between the map label and either the primary or alternate reference label. At Level I of the classification hierarchy, land cover OA was 83.1% ± 0.9% for both 2016 and 2019 when agreement was defined as a match between the map label and primary reference label only, and increased to 90.3% ± 0.7% when agreement also included the alternate reference label. The Level II and Level I OA for the 2016 land cover in the NLCD2019 database were 5% higher compared to the 2016 land cover component of the NLCD2016 database when agreement was defined as a match between the map label and primary reference label only. No improvement was realized by the NLCD2019 database when agreement also included the alternate reference label. User’s accuracies (UA) for forest loss and grass gain were>70% when agreement included either the primary or alternate label, and UA was generally70% for grass loss and gain and water gain and generally<50% for the other change themes. We conducted a post-analysis review for map-reference agreement to identify patterns of disagreement, and these findings are discussed in the context of potential adjustments to mapping and reference data collection procedures that may lead to improved map accuracy going forward.