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101.
Based on a total of 519 images,the composite images with the lowest possible cloud cover were generated at pixel level with image synthesis method on Google Earth En-gine(GEE)platform.The Remote Sensing Ecological Index(RSEI)was adopted,and calcu-lated in an efficient way with the assistance of parallel cloud computing of the GEE platform.The RSEI was used in this paper to evaluate and monitor the eco-environmental quality of the Lhasa Metropolitan Area.Results show that:(1)The ecological quality is better in the west than in the east of Lhasa Metropolitan Area,with Lhasa as an approximate dividing point.The ecological quality improved and then deteriorated dramatically before 2000,with the mean RSEI value dropping from 0.51 to 0.46;the trend was followed by a gradual increase up until 2017,with the mean RSEI value increased from 0.46 to 0.55.(2)The RSEI is weakly and positively correlated with socioeconomic indicators.This indicates that the population growth and economic development did not negatively influence the ecological quality,but actually boosted it.(3)The GEE can serve as an efficient computing platform for the assessment and monitoring of eco-environmental quality in vast regions. 相似文献
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HE Yuchuan XIONG Junnan CHENG Weiming YE Chongchong HE Wen YONG Zhiwei TIAN Jie 《资源与生态学报(英文版)》2021,12(6):729-742
Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development. In the past 20 years, the ecological environment in Altay Prefecture has changed significantly due to global warming. Meanwhile, with increasing human activities, the spatiotemporal pattern and driving forces of vegetation variation in the area are uncertain and difficult to accurately assess. Hence, we quantified the vegetation growth by using the Normalized Difference Vegetation Index (NDVI) on the Google Earth Engine (GEE). Then, the spatiotemporal patterns of vegetation from 2000 to 2019 were analyzed at the pixel scale. Finally, significance threshold segmentation was performed using meteorological data based on the correlation analysis results, and the contributions of climate change and human activities to vegetation variation were quantified. The results demonstrated that the vegetation coverage in Altay Prefecture is mainly concentrated in the north. The vegetation areas representing significant restoration and degradation from 2000 to 2019 accounted for 24.08% and 1.24% of Altay Prefecture, respectively. Moreover, spatial correlation analysis showed that the areas with significant correlations between NDVI and temperature, precipitation and sunlight hours accounted for 3.3%, 6.9% and 20.3% of Altay Prefecture, respectively. In the significant restoration area, 18.94% was dominated by multiple factors, while 3.4% was dominated by human activities, and 1.74% was dominated by climate change. Within the significant degradation area, abnormal degradation and climate change controlled 1.07% and 0.17%, respectively. This study revealed the dynamic changes of vegetation and their driving mechanisms in Altay Prefecture, and can provide scientific support for further research on life community mechanism theory and key remediation technology of mountain-water-forest-farmland-lake-grass in Altay Prefecture. 相似文献
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WebGIS开发方法的研究与实现 总被引：5，自引：2，他引：3
概述了传统WebGIS的特点和实现技术,在此基础上提出了以Google Maps API为WebGIS功能核心,结合恰当的地图发布平台和Web开发平台的WebGIS系统的新方案,阐述了新方案的原理及优势,并以长株潭地图浏览系统为例完成系统设计和功能实现。 相似文献
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介绍了基于浏览器的Google Earth交互式系统、开发技术、Struts框架和Ajax技术,描述了系统架构及开发途径。基于浏览器的Google Earth交互式系统具有广泛的商业应用前景。 相似文献
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Teaching high-school geomorphological concepts and topographic map reading entails many challenges. This research reports the applicability and effectiveness of Google Earth in teaching topographic map skills and geomorphological concepts, by a single teacher, in a one-computer classroom. Compared to learning via a conventional instructional method, students learning with Google Earth do not have different geomorphological concepts development because both settings enable students to learn with similar static representation. However, students learning with Google Earth improve topographic map skills significantly compared to the conventional instructional method. This is because of the 3D landscape visualization and prior knowledge connections available with Google Earth. 相似文献
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利用Google Earth Engine遥感大数据云平台,以若尔盖县的弯曲河流为研究对象,以空间分辨率为10 m的Sentinel-2多光谱卫星遥感影像为数据源,选用归一化差分水体指数(NDWI)、改进型归一化差分水体指数(MNDWI)和自动水体提取指数(AWEI)相组合的方式,建立支持向量机模型,进行弯曲河流信息的提取;利用归一化差分水体指数、改进型归一化差分水体指数和自动水体提取指数,提取出弯曲河流信息,并与支持向量机模型提取的结果进行了比较。研究结果表明,利用归一化差分水体指数提取的弯曲河流的整体性和连续性最优;利用改进型归一化差分水体指数提取的地势复杂区域细小河流的精度较高;利用支持向量机模型提取的弯曲河流更为准确,并消除了山体和植物阴影对弯曲河流提取的影响;与利用3种指数提取的结果相比,支持向量机模型提取的弯曲河流的总体精度和用户精度都相对最高。 相似文献
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红树林作为热带和亚热带海岸带上特有的森林群落,具有独特的生态功能以及重大的社会、经济价值。中国红树林经历了反复的破坏与保护,遥感监测手段可以为实施大规模的红树林生态系统保护和恢复行动提供科学技术支撑。本研究依托Google Earth Engine平台提出一种时空概率阈值法对中国红树林范围进行提取。研究选取2015年516景Landsat 8数据,首先使用非监督分类法进行水陆分离,其次通过生成缓冲区确定红树林潜在生长区,然后协同多种指数与光谱信息构建多特征决策树提取红树林粗略的生长范围,最后基于长时序的红树林粗略范围数据计算红树林生长概率,并通过实验确定概率阈值对红树林进行精细提取。通过实验对比发现时空概率阈值法的红树林生产者精度达90.36%,且能较好地提取幼小、分散的红树林。研究得到了2015年中国红树林分布结果,全国红树林面积为21932 ha,广西和广东两省红树林面积占中国红树林总面积的73.22%,为中国红树林主要分布区域。 相似文献
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作为典型的干旱区内陆湖泊,博斯腾湖的面积变化趋势与当地自然和人文环境的变迁密不可分。本文结合GIS与RS技术,利用Landsat影像和MODIS数据共2289景及JRC GSW水体掩膜产品,基于Google Earth Engine（GEE）平台采用指数法得出2000—2019年博斯腾湖面积年际和年内变化趋势,并采用2019年Sentinel-2影像进行结果对比分析,同时通过2000—2018年焉耆、库尔勒和巴音布鲁克气象站日值数据和人类活动分析其变化原因。得出如下结论：① 本结果中基于海量遥感数据提取面积的结果表明,GEE可以充分应用高时间分辨率遥感数据进行湖泊年际尤其是年内面积变化分析。相比于Landsat-5/7/8影像与MOD09GQ数据,由于Sentinel-2影像的时空分辨率优势,基于其所得的湖岸线可显示出较多细节。② 2000—2013年博斯腾湖面积共减少181.66 km2,变化速率为13.98 km/a;2013—2019年,湖泊共增加133.13 km2,变化速率为22.19 km2/a;③ 博斯腾湖面积一般在每年的3—6月呈上升趋势,且在当年6—9月保持峰值,面积在10—12月减小;④ 博斯腾湖面积年际变化与其流域内焉耆、库尔勒、巴音布鲁克气象站的降水、蒸发及积温因素变化的相关性未达到显著水平,而年内变化与上述气候要素相关性较高。 相似文献