Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing 100094, China.
J Environ Manage. 2018 Jul 15;218:280-290. doi: 10.1016/j.jenvman.2018.04.028. Epub 2018 Apr 21.
Landscape structure and vegetation coverage are important habitat conditions for Oriental Migratory Locust infestation in East Asia. Characterizing the landscape's dynamics of locust habitat is meaningful for reducing the occupation of locusts and limiting potential risks. To better understand causes and consequences of landscape pattern and locust habitat, it is not enough to simply detect locust habitat of each year. Rather, landcover transitions causing the change of locust habitat area must also be explored. This paper proposes an integrated implement to quantify the influence of landscape's dynamics on locust habitat changes based on three tenets: 1) temporal context can provide insight into the land cover transitions, 2) the detection of locust habitat area is operated on patches rather than pixels with full consideration of landscape's ecology, 3) the modeling must be flexible and unsupervised. These ideas have not been previously explored in demonstrating the possible role of changes in landscape characteristics to drive locust habitat transitions. The case study focuses on the Dagang district, a hot spot of locust infestation of China, from 2000 to 2015. Firstly, the seasonal characteristics of typical landcovers in NDVI, TVI, and LST were extracted from fused Landsat-MODIS surface reflectance imagery. Subsequently, a landscape membership-based random forest (LMRF) algorithm was proposed to quantify the landscape structure and hydrological regimen of locust habitat at the patch level. Finally, we investigated the correlations between the specific landcover transitions and habitat changes. Within the 16 years observations, our findings suggest that the sparse reeds and weeds in the vicinity of beach land, riverbanks, and wetlands are the dominant landscape structure associated with locust habitat change (R > 0.68), and the fluctuation in the water level is a key ecological factor to facilitate the locust habitat change (R > 0.61). These results are instrumental for developing precision pesticide use to reduce environmental degradation, and providing positive perspectives for ecological management and transformation of locust habitats.
景观结构和植被覆盖是东亚东方蝗灾发生的重要生境条件。描述蝗区景观动态对于减少蝗虫的占据和限制潜在风险具有重要意义。为了更好地理解景观格局和蝗虫生境变化的原因和后果,仅仅检测每年的蝗虫生境是不够的。相反,必须探索导致蝗虫生境面积变化的土地覆盖变化。本文提出了一种综合方法,基于三个原则来量化景观动态对蝗虫生境变化的影响:1)时间背景可以提供土地覆盖变化的洞察力;2)基于斑块而不是像素检测蝗虫生境面积,充分考虑景观生态学;3)模型必须灵活且无监督。这些想法在展示景观特征变化可能对驱动蝗虫生境转变的作用方面尚未得到探索。案例研究以中国蝗灾热点的大港地区为研究对象,研究时段为 2000 年至 2015 年。首先,从融合的 Landsat-MODIS 地表反射率图像中提取典型土地覆盖物在 NDVI、TVI 和 LST 中的季节性特征。随后,提出了一种基于景观成员的随机森林(LMRF)算法,以量化斑块水平上蝗虫生境的景观结构和水文状况。最后,我们研究了特定土地覆盖变化与生境变化之间的相关性。在 16 年的观测中,我们的研究结果表明,海滩、河岸和湿地附近稀疏的芦苇和杂草是与蝗虫生境变化相关的主要景观结构(R>0.68),水位波动是促进蝗虫生境变化的关键生态因素(R>0.61)。这些结果有助于开发精准农药使用,减少环境退化,为生态管理和蝗虫生境转变提供积极视角。