{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:34:13Z","timestamp":1761896053927,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2015,4,23]],"date-time":"2015-04-23T00:00:00Z","timestamp":1429747200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study develops a modelling framework for utilizing very high-resolution (VHR) aerial imagery for monitoring stocks of above-ground biomass (AGB) in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM), Gabor wavelets and Fourier-based textural ordination (FOTO)) were used in conjunction with two different machine learning (ML)-based regression techniques (support vector regression (SVR) and random forest (RF) regression). These methods were implemented on both 50-cm resolution Digital Globe data extracted from Google Earth\u2122 (GE) and 8-cm commercially obtained VHR imagery. This study further examines the role of forest biophysical parameters, such as ground-measured canopy cover and vertical canopy height, in explaining AGB distribution. Three models were developed using: (i) horizontal canopy variables (i.e., canopy cover and texture variables) plus vertical canopy height; (ii) horizontal variables only; and (iii) texture variables only. AGB was variable across the site, ranging from 51.02 Mg\/ha to 356.34 Mg\/ha. GE-based AGB estimates were comparable to those derived from commercial aerial imagery. The findings demonstrate that novel use of this array of texture-based techniques with GE imagery can help promote the wider use of freely available imagery for low-cost, fine-resolution monitoring of forests parameters at the landscape scale.<\/jats:p>","DOI":"10.3390\/rs70505057","type":"journal-article","created":{"date-parts":[[2015,4,23]],"date-time":"2015-04-23T11:40:29Z","timestamp":1429789229000},"page":"5057-5076","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth"],"prefix":"10.3390","volume":"7","author":[{"given":"Minerva","family":"Singh","sequence":"first","affiliation":[{"name":"Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK"}]},{"given":"Damian","family":"Evans","sequence":"additional","affiliation":[{"name":"\u00c9cole fran\u00e7aise d\u2019Extr\u00eame-Orient, Siem Reap, Cambodia"}]},{"given":"Daniel","family":"Friess","sequence":"additional","affiliation":[{"name":"Department of Geography, National University of Singapore, 1 Arts Link, 117570 Singapore"}]},{"given":"Boun","family":"Tan","sequence":"additional","affiliation":[{"name":"APSARA National Authority, Angkor International Research and Documentation Centre,  Siem Reap, Cambodia"}]},{"given":"Chan","family":"Nin","sequence":"additional","affiliation":[{"name":"APSARA National Authority, Department of Forestry Management, Cultural Landscape and Environment, Siem Reap, Cambodia"}]}],"member":"1968","published-online":{"date-parts":[[2015,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1126\/science.1201609","article-title":"A large and persistent carbon sink in the world\u2019s forests","volume":"333","author":"Pan","year":"2011","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1016\/j.tree.2004.09.006","article-title":"Southeast Asian biodiversity: An impending disaster","volume":"19","author":"Sodhi","year":"2004","journal-title":"Trends Ecol. 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