{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T13:30:15Z","timestamp":1774445415455,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2009,8,31]],"date-time":"2009-08-31T00:00:00Z","timestamp":1251676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this study, we tested the Maximum Entropy model (Maxent) for its application and performance in remotely sensing invasive Tamarix sp. Six Landsat 7 ETM+ satellite scenes and a suite of vegetation indices at different times of the growing season were selected for our study area along the Arkansas River in Colorado. Satellite scenes were selected for April, May, June, August, September, and October and tested in single-scene and time-series analyses. The best model was a time-series analysis fit with all spectral variables, which had an AUC = 0.96, overall accuracy = 0.90, and Kappa = 0.79. The top predictor variables were June tasselled cap wetness, September tasselled cap wetness, and October band 3. A second time-series analysis, where the variables that were highly correlated and demonstrated low predictive strengths were removed, was the second best model. The third best model was the October single-scene analysis. Our results may prove to be an effective approach for mapping Tamarix sp., which has been a challenge for resource managers. Of equal importance is the positive performance of the Maxent model in handling remotely sensed datasets.<\/jats:p>","DOI":"10.3390\/rs1030519","type":"journal-article","created":{"date-parts":[[2009,8,31]],"date-time":"2009-08-31T10:06:01Z","timestamp":1251713161000},"page":"519-533","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":95,"title":["Mapping Invasive Tamarisk (Tamarix): A Comparison of Single-Scene and Time-Series Analyses of Remotely Sensed Data"],"prefix":"10.3390","volume":"1","author":[{"given":"Paul  H.","family":"Evangelista","sequence":"first","affiliation":[{"name":"Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado 80523- 499, USA"}]},{"given":"Thomas  J.","family":"Stohlgren","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado 80526, USA"}]},{"given":"Jeffrey  T.","family":"Morisette","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado 80526, USA"}]},{"given":"Sunil","family":"Kumar","sequence":"additional","affiliation":[{"name":"Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado 80523- 499, USA"}]}],"member":"1968","published-online":{"date-parts":[[2009,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1614\/0890-037X(2004)018[1441:IBKWDS]2.0.CO;2","article-title":"Improving biodiversity knowledge with data set synergy: a case study of nonnative plants in Colorado","volume":"18","author":"Crosier","year":"2004","journal-title":"Weed Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.1614\/0890-037X(2004)018[1449:DROSIA]2.0.CO;2","article-title":"Distinct roles of surveys, inventories, and monitoring in adaptive weed management","volume":"18","author":"Dewey","year":"2004","journal-title":"Weed Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1017\/S0890037X00037908","article-title":"Using satellite data to map false broomweed (Ericameria austrotexana) infestations on south Texas rangelands","volume":"7","author":"Anderson","year":"1993","journal-title":"Weed Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1017\/S0890037X00023915","article-title":"Use of remote sensing for detecting and mapping leafy spurge (Euphorbia esula)","volume":"9","author":"Everitt","year":"1995","journal-title":"Weed Technol."},{"key":"ref_5","first-page":"497","article-title":"Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones","volume":"25","author":"Rowlinson","year":"1999","journal-title":"Water SA"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1614\/0043-1745(2000)048[0393:URSTDW]2.0.CO;2","article-title":"Using remote sensing to detect weed infestations in Glycine max","volume":"48","author":"Medlin","year":"2000","journal-title":"Weed Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1614\/WS-05-54.2.346","article-title":"Using remote sensing for identification of late-season grass weed patches in wheat","volume":"54","year":"2006","journal-title":"Weed Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1614\/WS-04-044R2","article-title":"A review of remote sensing of invasive weeds and example of the early detection of spotted knapweed (Centaurea maculosa) and babysbreath (Gypsophila paniculata) with a hyperspectral sensor","volume":"53","author":"Lass","year":"2005","journal-title":"Weed Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"603","DOI":"10.14358\/PERS.71.5.603","article-title":"Field determination of optimal dates for the discrimination of invasive wetland plant species using derivative spectral analysis","volume":"71","author":"Laba","year":"2005","journal-title":"Photogramm. 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