Loading…
Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands
•We compared field- and image-measured changes in vegetation cover and bare ground.•Image-interpretation slightly overestimated woody vegetation and bare ground cover.•Estimates of litter and herbaceous vegetation from image interpretation were poor.•Image interpretation is useful to monitor woody v...
Saved in:
| Published in: | Ecological indicators 2014-10, Vol.45, p.570-578 |
|---|---|
| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites Items that cite this one |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | cdi_FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3 |
|---|---|
| cites | cdi_FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3 |
| container_end_page | 578 |
| container_issue | |
| container_start_page | 570 |
| container_title | Ecological indicators |
| container_volume | 45 |
| creator | Karl, Jason W. Gillan, Jeffrey K. Barger, Nichole N. Herrick, Jeffrey E. Duniway, Michael C. |
| description | •We compared field- and image-measured changes in vegetation cover and bare ground.•Image-interpretation slightly overestimated woody vegetation and bare ground cover.•Estimates of litter and herbaceous vegetation from image interpretation were poor.•Image interpretation is useful to monitor woody vegetation for fuels reduction.•Benefits of image interpretation are objectivity, repeatability, and simplicity.
The use of very high resolution (VHR; ground sampling distances |
| doi_str_mv | 10.1016/j.ecolind.2014.05.017 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1642263125</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1470160X14002192</els_id><sourcerecordid>1627957641</sourcerecordid><originalsourceid>FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3</originalsourceid><addsrcrecordid>eNqNkc1u1DAUhSMEEqX0ERDeILFJsJ3EPyuEKkorVWIBlbqzHOc641HGHmxnUB-hb42nGbqFjW1df-fcq3uq6h3BDcGEfdo2YMLs_NhQTLoG9w0m_EV1RgSnNcdt97K8O45rwvD96-pNSltcdFKys-rxxmeI-whZZxc8ChZt3LSpI6QwL08lt9MTxAdkQ0QjZDDZ-QkdYPqrMeEAsZy7fUhurWy0nwBpW7yRXWBOKMK4mKfPHEHnHfickPPodwjjrP2Y3lavrJ4TXJzu8-ru6uvPy-v69vu3m8svt7XpqMz1wCmzDFOhpW4HLsEKANoPkoPQtpSpNtowKQaBjWzlSI0QghnLB405Htvz6uPqu4_h1wIpq51LBuYyBIQlKcI6SllLaP8fKOWy56wjBe1X1MSQUgSr9rEsLj4ogtUxJbVVp5TUMSWFe1VSKroPpxY6GT3bqL1x6VlMBWMdZm3h3q-c1UHpKRbm7sfRqCRJWdceJ_i8EmXbcHAQVTIOvIHRxZKZGoP7xyx_ACf3uEc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1627957641</pqid></control><display><type>article</type><title>Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands</title><source>ScienceDirect Freedom Collection 2022-2024</source><creator>Karl, Jason W. ; Gillan, Jeffrey K. ; Barger, Nichole N. ; Herrick, Jeffrey E. ; Duniway, Michael C.</creator><creatorcontrib>Karl, Jason W. ; Gillan, Jeffrey K. ; Barger, Nichole N. ; Herrick, Jeffrey E. ; Duniway, Michael C.</creatorcontrib><description>•We compared field- and image-measured changes in vegetation cover and bare ground.•Image-interpretation slightly overestimated woody vegetation and bare ground cover.•Estimates of litter and herbaceous vegetation from image interpretation were poor.•Image interpretation is useful to monitor woody vegetation for fuels reduction.•Benefits of image interpretation are objectivity, repeatability, and simplicity.
The use of very high resolution (VHR; ground sampling distances<∼5cm) aerial imagery to estimate site vegetation cover and to detect changes from management has been well documented. However, as the purpose of monitoring is to document change over time, the ability to detect changes from imagery at the same or better level of accuracy and precision as those measured in situ must be assessed for image-based techniques to become reliable tools for ecosystem monitoring. Our objective with this study was to quantify the relationship between field-measured and image-interpreted changes in vegetation and ground cover measured one year apart in a Piñon and Juniper (P–J) woodland in southern Utah, USA. The study area was subject to a variety of fuel removal treatments between 2009 and 2010. We measured changes in plant community composition and ground cover along transects in a control area and three different treatments prior to and following P–J removal. We compared these measurements to vegetation composition and change based on photo-interpretation of ∼4cm ground sampling distance imagery along similar transects. Estimates of cover were similar between field-based and image-interpreted methods in 2009 and 2010 for woody vegetation, no vegetation, herbaceous vegetation, and litter (including woody litter). Image-interpretation slightly overestimated cover for woody vegetation and no-vegetation classes (average difference between methods of 1.34% and 5.85%) and tended to underestimate cover for herbaceous vegetation and litter (average difference of −5.18% and 0.27%), but the differences were significant only for litter cover in 2009. Level of agreement between the field-measurements and image-interpretation was good for woody vegetation and no-vegetation classes (r between 0.47 and 0.89), but generally poorer for herbaceous vegetation and litter (r between 0.18 and 0.81) likely due to differences in image quality by year and the difficulty in discriminating fine vegetation and litter in imagery. Our results show that image interpretation to detect vegetation changes has utility for monitoring fuels reduction treatments in terms of woody vegetation and no-vegetation classes. The benefits of this technique are that it provides objective and repeatable measurements of site conditions that could be implemented relatively inexpensively and easily without the need for highly specialized software or technical expertise. Perhaps the biggest limitations of image interpretation to monitoring fuels treatments are challenges in estimating litter and herbaceous vegetation cover and the sensitivity of herbaceous cover estimates to image quality and shadowing.</description><identifier>ISSN: 1470-160X</identifier><identifier>EISSN: 1872-7034</identifier><identifier>DOI: 10.1016/j.ecolind.2014.05.017</identifier><language>eng</language><publisher>Amsterdam: Elsevier Ltd</publisher><subject>Animal and plant ecology ; Animal, plant and microbial ecology ; Applied ecology ; Biological and medical sciences ; botanical composition ; Change detection ; computer software ; Conservation, protection and management of environment and wildlife ; ecosystems ; Estimates ; Fuels ; fuels (fire ecology) ; Fundamental and applied biological sciences. Psychology ; General aspects ; General aspects. Techniques ; ground vegetation ; High-resolution ; image analysis ; Image detection ; Image interpretation ; Image quality ; Imagery ; Land cover ; Litter ; Monitoring ; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking ; pinyon-juniper ; plant litter ; Rangeland monitoring ; Remote sensing ; Synecology ; Teledetection and vegetation maps ; Vegetation ; vegetation cover ; woodlands</subject><ispartof>Ecological indicators, 2014-10, Vol.45, p.570-578</ispartof><rights>2014</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3</citedby><cites>FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3</cites><orcidid>0000-0002-3326-3806</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28664063$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Karl, Jason W.</creatorcontrib><creatorcontrib>Gillan, Jeffrey K.</creatorcontrib><creatorcontrib>Barger, Nichole N.</creatorcontrib><creatorcontrib>Herrick, Jeffrey E.</creatorcontrib><creatorcontrib>Duniway, Michael C.</creatorcontrib><title>Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands</title><title>Ecological indicators</title><description>•We compared field- and image-measured changes in vegetation cover and bare ground.•Image-interpretation slightly overestimated woody vegetation and bare ground cover.•Estimates of litter and herbaceous vegetation from image interpretation were poor.•Image interpretation is useful to monitor woody vegetation for fuels reduction.•Benefits of image interpretation are objectivity, repeatability, and simplicity.
The use of very high resolution (VHR; ground sampling distances<∼5cm) aerial imagery to estimate site vegetation cover and to detect changes from management has been well documented. However, as the purpose of monitoring is to document change over time, the ability to detect changes from imagery at the same or better level of accuracy and precision as those measured in situ must be assessed for image-based techniques to become reliable tools for ecosystem monitoring. Our objective with this study was to quantify the relationship between field-measured and image-interpreted changes in vegetation and ground cover measured one year apart in a Piñon and Juniper (P–J) woodland in southern Utah, USA. The study area was subject to a variety of fuel removal treatments between 2009 and 2010. We measured changes in plant community composition and ground cover along transects in a control area and three different treatments prior to and following P–J removal. We compared these measurements to vegetation composition and change based on photo-interpretation of ∼4cm ground sampling distance imagery along similar transects. Estimates of cover were similar between field-based and image-interpreted methods in 2009 and 2010 for woody vegetation, no vegetation, herbaceous vegetation, and litter (including woody litter). Image-interpretation slightly overestimated cover for woody vegetation and no-vegetation classes (average difference between methods of 1.34% and 5.85%) and tended to underestimate cover for herbaceous vegetation and litter (average difference of −5.18% and 0.27%), but the differences were significant only for litter cover in 2009. Level of agreement between the field-measurements and image-interpretation was good for woody vegetation and no-vegetation classes (r between 0.47 and 0.89), but generally poorer for herbaceous vegetation and litter (r between 0.18 and 0.81) likely due to differences in image quality by year and the difficulty in discriminating fine vegetation and litter in imagery. Our results show that image interpretation to detect vegetation changes has utility for monitoring fuels reduction treatments in terms of woody vegetation and no-vegetation classes. The benefits of this technique are that it provides objective and repeatable measurements of site conditions that could be implemented relatively inexpensively and easily without the need for highly specialized software or technical expertise. Perhaps the biggest limitations of image interpretation to monitoring fuels treatments are challenges in estimating litter and herbaceous vegetation cover and the sensitivity of herbaceous cover estimates to image quality and shadowing.</description><subject>Animal and plant ecology</subject><subject>Animal, plant and microbial ecology</subject><subject>Applied ecology</subject><subject>Biological and medical sciences</subject><subject>botanical composition</subject><subject>Change detection</subject><subject>computer software</subject><subject>Conservation, protection and management of environment and wildlife</subject><subject>ecosystems</subject><subject>Estimates</subject><subject>Fuels</subject><subject>fuels (fire ecology)</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>General aspects. Techniques</subject><subject>ground vegetation</subject><subject>High-resolution</subject><subject>image analysis</subject><subject>Image detection</subject><subject>Image interpretation</subject><subject>Image quality</subject><subject>Imagery</subject><subject>Land cover</subject><subject>Litter</subject><subject>Monitoring</subject><subject>Parks, reserves, wildlife conservation. Endangered species: population survey and restocking</subject><subject>pinyon-juniper</subject><subject>plant litter</subject><subject>Rangeland monitoring</subject><subject>Remote sensing</subject><subject>Synecology</subject><subject>Teledetection and vegetation maps</subject><subject>Vegetation</subject><subject>vegetation cover</subject><subject>woodlands</subject><issn>1470-160X</issn><issn>1872-7034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqNkc1u1DAUhSMEEqX0ERDeILFJsJ3EPyuEKkorVWIBlbqzHOc641HGHmxnUB-hb42nGbqFjW1df-fcq3uq6h3BDcGEfdo2YMLs_NhQTLoG9w0m_EV1RgSnNcdt97K8O45rwvD96-pNSltcdFKys-rxxmeI-whZZxc8ChZt3LSpI6QwL08lt9MTxAdkQ0QjZDDZ-QkdYPqrMeEAsZy7fUhurWy0nwBpW7yRXWBOKMK4mKfPHEHnHfickPPodwjjrP2Y3lavrJ4TXJzu8-ru6uvPy-v69vu3m8svt7XpqMz1wCmzDFOhpW4HLsEKANoPkoPQtpSpNtowKQaBjWzlSI0QghnLB405Htvz6uPqu4_h1wIpq51LBuYyBIQlKcI6SllLaP8fKOWy56wjBe1X1MSQUgSr9rEsLj4ogtUxJbVVp5TUMSWFe1VSKroPpxY6GT3bqL1x6VlMBWMdZm3h3q-c1UHpKRbm7sfRqCRJWdceJ_i8EmXbcHAQVTIOvIHRxZKZGoP7xyx_ACf3uEc</recordid><startdate>20141001</startdate><enddate>20141001</enddate><creator>Karl, Jason W.</creator><creator>Gillan, Jeffrey K.</creator><creator>Barger, Nichole N.</creator><creator>Herrick, Jeffrey E.</creator><creator>Duniway, Michael C.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-3326-3806</orcidid></search><sort><creationdate>20141001</creationdate><title>Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands</title><author>Karl, Jason W. ; Gillan, Jeffrey K. ; Barger, Nichole N. ; Herrick, Jeffrey E. ; Duniway, Michael C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Animal and plant ecology</topic><topic>Animal, plant and microbial ecology</topic><topic>Applied ecology</topic><topic>Biological and medical sciences</topic><topic>botanical composition</topic><topic>Change detection</topic><topic>computer software</topic><topic>Conservation, protection and management of environment and wildlife</topic><topic>ecosystems</topic><topic>Estimates</topic><topic>Fuels</topic><topic>fuels (fire ecology)</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>General aspects. Techniques</topic><topic>ground vegetation</topic><topic>High-resolution</topic><topic>image analysis</topic><topic>Image detection</topic><topic>Image interpretation</topic><topic>Image quality</topic><topic>Imagery</topic><topic>Land cover</topic><topic>Litter</topic><topic>Monitoring</topic><topic>Parks, reserves, wildlife conservation. Endangered species: population survey and restocking</topic><topic>pinyon-juniper</topic><topic>plant litter</topic><topic>Rangeland monitoring</topic><topic>Remote sensing</topic><topic>Synecology</topic><topic>Teledetection and vegetation maps</topic><topic>Vegetation</topic><topic>vegetation cover</topic><topic>woodlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Karl, Jason W.</creatorcontrib><creatorcontrib>Gillan, Jeffrey K.</creatorcontrib><creatorcontrib>Barger, Nichole N.</creatorcontrib><creatorcontrib>Herrick, Jeffrey E.</creatorcontrib><creatorcontrib>Duniway, Michael C.</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Ecological indicators</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Karl, Jason W.</au><au>Gillan, Jeffrey K.</au><au>Barger, Nichole N.</au><au>Herrick, Jeffrey E.</au><au>Duniway, Michael C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands</atitle><jtitle>Ecological indicators</jtitle><date>2014-10-01</date><risdate>2014</risdate><volume>45</volume><spage>570</spage><epage>578</epage><pages>570-578</pages><issn>1470-160X</issn><eissn>1872-7034</eissn><abstract>•We compared field- and image-measured changes in vegetation cover and bare ground.•Image-interpretation slightly overestimated woody vegetation and bare ground cover.•Estimates of litter and herbaceous vegetation from image interpretation were poor.•Image interpretation is useful to monitor woody vegetation for fuels reduction.•Benefits of image interpretation are objectivity, repeatability, and simplicity.
The use of very high resolution (VHR; ground sampling distances<∼5cm) aerial imagery to estimate site vegetation cover and to detect changes from management has been well documented. However, as the purpose of monitoring is to document change over time, the ability to detect changes from imagery at the same or better level of accuracy and precision as those measured in situ must be assessed for image-based techniques to become reliable tools for ecosystem monitoring. Our objective with this study was to quantify the relationship between field-measured and image-interpreted changes in vegetation and ground cover measured one year apart in a Piñon and Juniper (P–J) woodland in southern Utah, USA. The study area was subject to a variety of fuel removal treatments between 2009 and 2010. We measured changes in plant community composition and ground cover along transects in a control area and three different treatments prior to and following P–J removal. We compared these measurements to vegetation composition and change based on photo-interpretation of ∼4cm ground sampling distance imagery along similar transects. Estimates of cover were similar between field-based and image-interpreted methods in 2009 and 2010 for woody vegetation, no vegetation, herbaceous vegetation, and litter (including woody litter). Image-interpretation slightly overestimated cover for woody vegetation and no-vegetation classes (average difference between methods of 1.34% and 5.85%) and tended to underestimate cover for herbaceous vegetation and litter (average difference of −5.18% and 0.27%), but the differences were significant only for litter cover in 2009. Level of agreement between the field-measurements and image-interpretation was good for woody vegetation and no-vegetation classes (r between 0.47 and 0.89), but generally poorer for herbaceous vegetation and litter (r between 0.18 and 0.81) likely due to differences in image quality by year and the difficulty in discriminating fine vegetation and litter in imagery. Our results show that image interpretation to detect vegetation changes has utility for monitoring fuels reduction treatments in terms of woody vegetation and no-vegetation classes. The benefits of this technique are that it provides objective and repeatable measurements of site conditions that could be implemented relatively inexpensively and easily without the need for highly specialized software or technical expertise. Perhaps the biggest limitations of image interpretation to monitoring fuels treatments are challenges in estimating litter and herbaceous vegetation cover and the sensitivity of herbaceous cover estimates to image quality and shadowing.</abstract><cop>Amsterdam</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ecolind.2014.05.017</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-3326-3806</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1470-160X |
| ispartof | Ecological indicators, 2014-10, Vol.45, p.570-578 |
| issn | 1470-160X 1872-7034 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1642263125 |
| source | ScienceDirect Freedom Collection 2022-2024 |
| subjects | Animal and plant ecology Animal, plant and microbial ecology Applied ecology Biological and medical sciences botanical composition Change detection computer software Conservation, protection and management of environment and wildlife ecosystems Estimates Fuels fuels (fire ecology) Fundamental and applied biological sciences. Psychology General aspects General aspects. Techniques ground vegetation High-resolution image analysis Image detection Image interpretation Image quality Imagery Land cover Litter Monitoring Parks, reserves, wildlife conservation. Endangered species: population survey and restocking pinyon-juniper plant litter Rangeland monitoring Remote sensing Synecology Teledetection and vegetation maps Vegetation vegetation cover woodlands |
| title | Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T03%3A11%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Interpretation%20of%20high-resolution%20imagery%20for%20detecting%20vegetation%20cover%20composition%20change%20after%20fuels%20reduction%20treatments%20in%20woodlands&rft.jtitle=Ecological%20indicators&rft.au=Karl,%20Jason%20W.&rft.date=2014-10-01&rft.volume=45&rft.spage=570&rft.epage=578&rft.pages=570-578&rft.issn=1470-160X&rft.eissn=1872-7034&rft_id=info:doi/10.1016/j.ecolind.2014.05.017&rft_dat=%3Cproquest_cross%3E1627957641%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c429t-b726f6028a9a3b79ef8ee25b97e8af28a2acac698b80c939d2c8886cf7ba070d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1627957641&rft_id=info:pmid/&rfr_iscdi=true |