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Estimation of urban tree carbon storage using multispectral and multitemporal imagery.

机译：使用多光谱和多时相影像估算城市树木的碳储量。

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摘要

Quantifying urban forest carbon storage, distribution, and change is important to understand the roles of urban vegetation in global climate change. Two different approaches were used to quantify carbon storage of urban trees in Syracuse, NY. The first approach to estimate urban carbon storage used a regression equation derived from the relationship between existing carbon storage data and the Normalized Difference Vegetation Index (NDVI) derived from multi-spectral images. The regression equation was developed to predict carbon storage of urban trees from NDVI, computed from Landsat ETM+ image, and from the carbon storage field data of 1999 for Syracuse, NY. The total carbon storage estimation based on NDVI data was 0.2% different from the estimation by the results of the field-based UFORE model.; The second approach was to compute tree heights from stereo pair imagery, and then to estimate tree carbon storage from this data. The results from these two methods were compared with the estimate from the UFORE (Urban Forest Effects) model. The carbon storage of past years was estimated using the first approach and changes in vegetation abundance were detected using image differencing. The second approach was performed on three subset areas of the city. The results showed some variations on each area due to its land cover characteristics. For these three subset areas, estimated carbon storage values from the tree height approach were 87% to 115% as computed to the values from the NDVI approach. The results from both NDVI and height methods were 67 to 106 and 77 to 107% of UFORE estimation, respectively. Therefore, the relatively simple and straightforward NDVI approach may be preferable in order to acquire urban carbon storage, respectively. Therefore, the relatively simple and straightforward NDVI approach may be preferable in order to acquire urban carbon storage.; Changes in total urban tree carbon storage in Syracuse were estimated using the imagery from 1985, 1992 and 1999. Using a modified pseudo-invariant feature method the images of 1985 and 1992 were radiometrically corrected through normalizing the imagery to the 1999 data. After image normalization, the total carbon storage by trees in Syracuse was estimated to be 148,660 metric tons of carbon for 1999, 149,430 metric tons of carbon for 1992, 146,800 metric tons of carbon for 1985. Comparisons of NDVI images through image differencing showed that about 75% of the study areas did not change. Suburban areas outside of Syracuse showed increases in carbon storage, while the city lost carbon most likely due to a severe localized storm in 1998. Study results demonstrate the potential ability of a remote sensing-based quantitative change detection system to support estimation of urban carbon storage, urban forest management, and assessment of damage from natural disasters.
机译：量化城市森林碳储量，分布和变化对于了解城市植被在全球气候变化中的作用非常重要。使用两种不同的方法来量化纽约州锡拉丘兹市城市树木的碳存储量。估算城市碳储量的第一种方法是使用从现有碳储量数据与多光谱图像中的归一化植被指数（NDVI）之间的关系得出的回归方程。建立了回归方程，以根据NDVI预测城市树木的碳储量，该NDVI是由Landsat ETM +图像和1999年纽约州锡拉丘兹的碳储量田地数据计算得出的。基于NDVI数据的总碳储量估算与基于现场UFORE模型的结果的估算相差0.2％。第二种方法是根据立体对图像计算树木的高度，然后根据此数据估算树木的碳储量。将这两种方法的结果与UFORE（城市森林效应）模型的估计值进行了比较。使用第一种方法估算了过去几年的碳储量，并使用图像差分法检测了植被丰度的变化。第二种方法是在城市的三个子区域进行的。结果显示，由于其土地覆盖特征，每个区域都有一些变化。对于这三个子区域，根据NDVI方法的估算值，根据树高方法估算的碳储量值为87％至115％。 NDVI和高度方法的结果分别为UFORE估计的67至106和77至107％。因此，相对简单和直接的NDVI方法可能更可取，以便分别获取城市碳储存。因此，相对简单和直接的NDVI方法可能更可取，以获得城市碳存储。使用1985、1992和1999年的图像估算了锡拉丘兹市城市树木总碳储量的变化。使用改进的伪不变特征方法，通过将图像标准化为1999年的数据，对1985年和1992年的图像进行了辐射校正。图像归一化后，锡拉丘兹树木的总碳储量估计为1999年为148,660公吨，1992年为149,430公吨，1985年为146,800公吨。通过图像差分的NDVI图像比较表明，大约75％的研究领域没有变化。锡拉丘兹（Syracuse）以外的郊区显示出碳存储量的增加，而该城市最有可能由于1998年的局部暴风雨而损失了碳。研究结果表明，基于遥感的定量变化检测系统具有支持估算城市碳存储量的潜在能力。 ，城市森林管理以及自然灾害造成的损失评估。

著录项

  • 作者

    Myeong, Soojeong.;

  • 作者单位

    State University of New York College of Environmental Science and Forestry.;

  • 授予单位 State University of New York College of Environmental Science and Forestry.;
  • 学科 Environmental Sciences.; Remote Sensing.; Biogeochemistry.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 110 p.
  • 总页数 110
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境科学基础理论;遥感技术;生物地球化学、气体地球化学;
  • 关键词

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