Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA.
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA.
Sci Total Environ. 2017 Dec 15;605-606:721-734. doi: 10.1016/j.scitotenv.2017.06.245. Epub 2017 Jul 1.
Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observations (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9-14days) start-of-season (SOS) and a later (13-20days) end-of-season (EOS), resulting in an extended (5-30days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30day per year), and increasing EOS and GSL (0.50 and 0.90day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels.
植被的季节性物候在全球碳循环和生态系统生产力中起着重要作用。在城市环境中，由于其对公众健康（例如过敏）和能源需求（例如冷却效果）的影响，植被物候也很重要。在这项研究中，我们研究了利用遥感观测（即陆地卫星数据）来推导美国四个截然不同地区（华盛顿特区，华盛顿州金县，爱荷华州波尔克县以及马里兰州巴尔的摩市和县）城市核心区植被的一些物候指标的潜力在过去的三十年中。我们使用了 1982 年至 2015 年期间所有可用的陆地卫星观测（约 3000 个场景）和一个自适应的双逻辑模型来检测和量化植被物候期的年度变化，即植被季节性变化的指标。该模型不仅可以捕获和量化农村地区密集植被的物候期，还可以捕获和量化城市核心区混合植被的物候期。推导的物候指标与从中分辨率成像光谱仪（MODIS）和实地观测得出的类似指标吻合较好，表明所提出的模型所描绘的物候动态是可靠的。植被物候及其季节性和年际动态在城市地区表现出明显的空间格局，表现为季节开始较早（9-14 天），季节结束较晚（13-20 天），导致生长季节长度（GSL）延长（5-30 天）与四个研究区域的周围郊区和农村地区相比。在过去的三十年中，这些研究区域的季节开始（-0.30 天/年）呈下降趋势，季节结束和生长季节长度（0.50 和 0.90 天/年）呈上升趋势。由于其当地气候条件，植被类型和不同的城乡环境不同，这四个城市系统之间的这些趋势的幅度有所不同。与 MODIS 等粗分辨率数据集相比，陆地卫星提供的城市区域物候信息更为详细，从而提高了我们对城市区域人类-自然系统相互作用（或反馈）的理解。鉴于国家和全球范围内快速的城市化和大都市的扩张，此类信息对于城市规划非常有价值。
