利用无人机图像估算地上生物量和碳储量

Sandesh Upadhyaya, Prabin Gyawali, Sambhav Sapkota, Nishan Neupane, Manoj Neupane
{"title":"利用无人机图像估算地上生物量和碳储量","authors":"Sandesh Upadhyaya, Prabin Gyawali, Sambhav Sapkota, Nishan Neupane, Manoj Neupane","doi":"10.3126/njg.v22i1.55123","DOIUrl":null,"url":null,"abstract":"Forests have a vital role in maintaining global climate stability by removing greenhouse gases like carbon dioxide from environment. Estimation of carbon stock is crucial in quantifying the amount of carbon that is present in the forest. The estimation of forest biomass and carbon stock through field measurements is a challenging and timeconsuming task. Here in this scenario, our study aims to estimate carbon stock in a forest area using the hybrid technique i.e., aerial survey and ground survey. We used low-altitude remote sensing data acquired by UAV to estimate biomass and carbon stock in an efficient way compared to the traditional techniques. We developed an orthomosaic from the collected aerial imageries and manually delineated tree crowns to obtain crown projection area (CPA) for the entire study area using GIS tools. Our study area contained a mixed species with Pinus Wallichiana to be the dominant species while other species are negligible. Using field-measured tree height and diameter at breast height (DBH) as input, we estimated above-ground biomass (AGB) with an allometric equation and then used a factor value to estimate carbon stock or aboveground carbon (AGC) for six sample plots. Next, we developed a relationship between CPA and carbon stock and validated it by comparing the carbon stock values obtained from the allometric equation for the remaining four sample plots. Among the various developed model, 4th order Polynomial model was chosen due to its highest coefficient of correlation. After the model validation was done the AGC of whole study area was obtained by using the CPA delineated manually from the orthomosaic image. The total AGC and AGB obtained for our study area which was about 7 hectare was 210.7480 tons and 448.4 tons respectively.","PeriodicalId":489906,"journal":{"name":"Nepalese journal of geoinformatics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of Above Ground Biomass and Carbon Stock using UAV images\",\"authors\":\"Sandesh Upadhyaya, Prabin Gyawali, Sambhav Sapkota, Nishan Neupane, Manoj Neupane\",\"doi\":\"10.3126/njg.v22i1.55123\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forests have a vital role in maintaining global climate stability by removing greenhouse gases like carbon dioxide from environment. Estimation of carbon stock is crucial in quantifying the amount of carbon that is present in the forest. The estimation of forest biomass and carbon stock through field measurements is a challenging and timeconsuming task. Here in this scenario, our study aims to estimate carbon stock in a forest area using the hybrid technique i.e., aerial survey and ground survey. We used low-altitude remote sensing data acquired by UAV to estimate biomass and carbon stock in an efficient way compared to the traditional techniques. We developed an orthomosaic from the collected aerial imageries and manually delineated tree crowns to obtain crown projection area (CPA) for the entire study area using GIS tools. Our study area contained a mixed species with Pinus Wallichiana to be the dominant species while other species are negligible. Using field-measured tree height and diameter at breast height (DBH) as input, we estimated above-ground biomass (AGB) with an allometric equation and then used a factor value to estimate carbon stock or aboveground carbon (AGC) for six sample plots. Next, we developed a relationship between CPA and carbon stock and validated it by comparing the carbon stock values obtained from the allometric equation for the remaining four sample plots. Among the various developed model, 4th order Polynomial model was chosen due to its highest coefficient of correlation. After the model validation was done the AGC of whole study area was obtained by using the CPA delineated manually from the orthomosaic image. The total AGC and AGB obtained for our study area which was about 7 hectare was 210.7480 tons and 448.4 tons respectively.\",\"PeriodicalId\":489906,\"journal\":{\"name\":\"Nepalese journal of geoinformatics\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nepalese journal of geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3126/njg.v22i1.55123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nepalese journal of geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3126/njg.v22i1.55123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

森林通过从环境中清除二氧化碳等温室气体,在维持全球气候稳定方面发挥着至关重要的作用。碳储量的估算对于量化森林中存在的碳量至关重要。通过野外测量估算森林生物量和碳储量是一项具有挑战性和耗时的任务。在这种情况下,我们的研究旨在使用混合技术,即航空调查和地面调查来估计森林地区的碳储量。与传统方法相比,利用无人机获取的低空遥感数据对生物量和碳储量进行了有效估算。我们利用地理信息系统(GIS)工具,从收集的航空图像和人工圈定的树冠中开发了一个正射影图,以获得整个研究区的树冠投影面积(CPA)。本研究区为一种混合种,优势种为Wallichiana松,其他种可忽略不计。以野外测量的树高和胸径(DBH)为输入,利用异速生长方程估算了6个样地的地上生物量(AGB),并利用因子值估算了碳储量或地上碳(AGC)。接下来,我们建立了CPA与碳储量之间的关系,并通过比较剩余四个样地的异速生长方程获得的碳储量值来验证它。在各种已开发的模型中,选择了四阶多项式模型,因为它的相关系数最高。模型验证完成后,利用人工圈定的正射影CPA获得整个研究区的AGC。研究区面积约7公顷,总AGC为210.7480吨,总AGB为448.4吨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Above Ground Biomass and Carbon Stock using UAV images
Forests have a vital role in maintaining global climate stability by removing greenhouse gases like carbon dioxide from environment. Estimation of carbon stock is crucial in quantifying the amount of carbon that is present in the forest. The estimation of forest biomass and carbon stock through field measurements is a challenging and timeconsuming task. Here in this scenario, our study aims to estimate carbon stock in a forest area using the hybrid technique i.e., aerial survey and ground survey. We used low-altitude remote sensing data acquired by UAV to estimate biomass and carbon stock in an efficient way compared to the traditional techniques. We developed an orthomosaic from the collected aerial imageries and manually delineated tree crowns to obtain crown projection area (CPA) for the entire study area using GIS tools. Our study area contained a mixed species with Pinus Wallichiana to be the dominant species while other species are negligible. Using field-measured tree height and diameter at breast height (DBH) as input, we estimated above-ground biomass (AGB) with an allometric equation and then used a factor value to estimate carbon stock or aboveground carbon (AGC) for six sample plots. Next, we developed a relationship between CPA and carbon stock and validated it by comparing the carbon stock values obtained from the allometric equation for the remaining four sample plots. Among the various developed model, 4th order Polynomial model was chosen due to its highest coefficient of correlation. After the model validation was done the AGC of whole study area was obtained by using the CPA delineated manually from the orthomosaic image. The total AGC and AGB obtained for our study area which was about 7 hectare was 210.7480 tons and 448.4 tons respectively.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信