Modeling Forest Above-Ground Biomass of Teak (Tectona grandis L. F.) Using Field Measurement and Sentinel-2 Imagery

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-05-11 DOI:10.1155/2024/9910094

Santosh Ghimire, Rajeev Joshi, Jeetendra Gautam, Binod Bhatta

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Abstract

Over the last few decades, remote sensing has emerged as a dependable and cost-effective method for collecting precise data on forest biophysical parameters, aiding in sustainable forest management and global initiatives to combat climate change. This research aimed to develop a model for estimating the above-ground biomass (AGB) of Teak (Tectona grandis L. F.) by combining field measurements with Sentinel-2 earth observation data. The study took place in 36-year-old teak plantation areas within the Sagarnath Forest Development Project in Nepal’s Sarlahi district. Field measurements were conducted using a destructive systematic sampling method, employing 10 × 10 m² sample plots, and the volume of logs was determined using Newton’s formula. A total of 30 sample plots were used for calibration, while 10 were utilized for validation purposes. The findings revealed that the average AGB per plot was 814 kg (equivalent to 81.4 t ha⁻¹), with a minimum value of 716 kg (71.6 t ha⁻¹) and a maximum value of 1,060 kg (106 t ha⁻¹). The study utilized five independent variables, namely, the Red band, Green band, Blue band, near-infrared (NIR), and normalized difference vegetation index (NDVI) values from Sentinel-2 imagery data, to develop estimation models. Among the 12 models examined, model M10 proved to be the best fit for accurate AGB estimation (adjusted R² = 0.9809, RMSE = 0.01269, AIC = −170, and p-value = < 8.39e−21). The equation of the best-fitted model was ln (AGB) = A + B × Red + C × Green + D × Blue² + E × ln (NIR) + F × ln (NDVI), providing an accurate estimate of AGB. Model validation involved a t-test comparing the observed and calculated AGB values for ten sample plots, demonstrating no significant difference (p-value = 0.3662 > 0.05). This model has the potential to facilitate AGB biomass calculations and carbon stock estimates for teak plantations of similar age groups.

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利用实地测量和哨兵-2 图像模拟柚木（Tectona grandis L. F.）的森林地上生物量

过去几十年来，遥感技术已成为收集森林生物物理参数精确数据的可靠且具有成本效益的方法，有助于可持续森林管理和应对气候变化的全球倡议。这项研究旨在通过将实地测量结果与哨兵-2 号地球观测数据相结合，建立一个估算柚木（Tectona grandis L. F.）地上生物量（AGB）的模型。研究在尼泊尔萨尔拉希县萨加纳特森林开发项目的 36 年柚木种植区进行。实地测量采用破坏性系统取样法，使用 10 × 10 平方米的样地，并使用牛顿公式确定原木的体积。共有 30 块样地用于校准，10 块样地用于验证。研究结果显示，每个样地的平均 AGB 为 814 千克（相当于 81.4 吨/公顷），最小值为 716 千克（71.6 吨/公顷），最大值为 1,060 千克（106 吨/公顷）。研究利用五个自变量，即哨兵-2 图像数据中的红波段、绿波段、蓝波段、近红外（NIR）和归一化差异植被指数（NDVI）值，建立了估算模型。在研究的 12 个模型中，模型 M10 被证明是最适合准确估算 AGB 的模型（调整 R2 = 0.9809，RMSE = 0.01269，AIC = -170 和 p 值 = <8.39e-21）。最佳拟合模型方程为 ln (AGB) = A + B × Red + C × Green + D × Blue2 + E × ln (NIR) + F × ln (NDVI)，提供了对 AGB 的准确估计。模型验证包括对十块样地的观测值和计算值进行 t 检验，结果显示两者无显著差异（p 值 = 0.3662 >0.05）。该模型可用于类似树龄组柚木种植园的 AGB 生物量计算和碳储量估算。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.