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卢旺达植被和湿地监测
NDAYISABA FELIX
学位类型硕士
导师包安明(ANMING BAO)
2017-05-01
学位授予单位中国科学院大学
学位授予地点新疆乌鲁木齐
学位专业理学硕士
关键词植被动态 湿地监测 赫斯特指数 遥感 Modis Ndvi Gis Vegetation Dynamics Wetland Monitoring Hurst Exponent Remote Sensing
摘要准确地认识和预测植被动态变化对于最大限度地解决发展中国家粮食短缺问题至关重要。植被的动态变化趋势与可持续发展紧密相连,例如可以通过观测植被动态变化趋势来制定相应的政策,便于野生动物保护区和栖息地管理。因气候变化、不合理的土地利用加剧了土地的退化,其评估研究是近年来的研究热点。关于植被和土地资源退化的评估研究可以为政府决策提供依据,为全国生态环境保护工作做出针对性的调整,可以大大提高政府管理部门的工作效率。本研究主要是在全球气候变化背景下,对 1990~2015 年卢旺达最大的湿地—Akagera 湿地资源进行分析并对本国的植被退化的状况进行评估。研究内容的第一部分是监测卢旺达 Akagera 湿地并制图,具体方法和结果参见本文第三章, 采用的数据有 Landsat TM,ETM +和 OLI 卫星影像,和 SRTM 数字高程模型(30m 分辨率)。湿地位于卢旺达 -坦桑尼亚边界,沿 Akagera 河由北向南延伸,总面积约为 100,229.76 公顷。水体占到湿地总面积的 30%,河马草和莎草面积分别占 29.8%和29%,还有小部分洪泛平原和沼泽的森林。虽然近些年湿地面积趋于稳定,但由于物种入侵给湿地生态系统带来了很大的不稳定性。通过分析近年来的影像数据,结果表明 Mihindi 湖,Ihema 湖,Hago 湖和Kivumba 湖面积减少,而 Rwanyakizinga 湖面积略微增加。研究内容的第二部分,文章根据 NDVI 和网格气象数据调查了植被的时空特征和植被绿度与降水之间的相互关系,具体方法和结果参见本文第四章。在这项研究中,利用 AVHRR 和 MODIS NDVI 数据集,并结合降雨趋势,对卢旺达植被 1990~2014 年的第一个生长季的时空动态变化进行评估。基于回归分析和赫斯特指数方法,利用 NDVI 和网格气象数据,研究了植被绿度和降水时空分布特征的相互关系。通过研究发现,植被覆盖总体呈上升趋势,年最大变化率为 0.043。在整个研究期间,全国 81.3%的植被有所改善,另外中轻微度退化占到7.5%,大幅度恶化占到 6.6%,其中 Kigali 市和东部省的退化现象严重。对植被类型变化的分析表明,五种植被受到严重威胁:“马赛克草原/森林或灌丛”严重退化,其次是稀疏的植被、草地或木本植被,人工植被和洪泛区阔叶林。通过计算 Hurst 指数,发现指数变化趋势与植被生长态势相一致,可持续的植被面积为 40.16%,不可持续面积为1.67%,不可预测面积为 58.17%。这项研究能够为政府和地方管理部门提供了有关生态保护的信息,为全国环境保护和可持续发展做出有针对性的意见。
其他摘要The knowledge of the current vegetation dynamics and the ability to make accurate predictions of ecological changes is essential to minimize times of food scarcity in developing countries. Vegetation trends are also closely related to sustainability issues, such as management of conservation areas and wildlife habitats. Land degradation assessment has been a crucial subject of research in recent years, mostly because of the concomitant ecological concerns in the context of climate variability. Information on vegetation and land resources degradation is paramount in a sense that it provides governments and local authorities with valuable information to elaborate and implement scientifically informed policies to enhance environmental protection.Specifically, the purpose of this thesis was to evaluate the status of Vegetation degradation in Rwanda,in the context of changing climate and weather patterns, from 1990-2015. It also purposed to monitor wetland resources, taking the Akagera wetland, the largest wetland resource in Rwanda, as a case study.The first part of this work, whose methodology and results are presented in Chapter 3, deals with mapping and monitoring the Akagera wetland in Rwanda. Landsat TM, ETM+ and OLI were used in conjunction with the Shuttle Radar Topographic Mission (SRTM) Digital Elevation model (30m resolution). The mapping and delineation results showed that the wetland narrowly extends along the Rwanda-Tanzania border from North to South, following the course of Akagera River and the total area can be estimated at 100,229.76ha. After water bodies that occupy an equivalent of 30% of the wetland‘s surface area, Hippo grass and Cyperus Papyrus are also predominant, representing 29.8 and 29% respectively. Flood plains and swamp forest were also inventoried in smaller proportions. While the wetland extent has apparently remained stable, the inhabiting water bodies have been subjected to enormous instability due to invasive species. Lake Mihindi, Ihema, Hago and Kivumba have been shrinking in extent, while Lake Rwanyakizinga has experienced a certain degree of expansion. In the second part, whose methodology and results are elaborated in chapter 4, we investigated the spatial temporal characteristics of vegetation and the interrelationships between vegetation greenness and precipitation in light of NDVI and gridded meteorological datasets. AVHRR and MODIS NDVI datasets were used to assess the spatial temporal dynamics of vegetation greenness in Rwanda under the contrasting trends of precipitation, for the period starting from 1990 to 2014, and for the first growing season (season A). Based on Regression Analysis and the Hurst exponent index methods, we have investigated the spatial temporal characteristics and the interrelationships between vegetation greenness and precipitation in light of NDVI and gridded meteorological datasets. The findings revealed that the vegetation cover was characterized by an increasing trend; with the maximum annual change rate of 0.043. The results also suggest that 81.3% of the country‘s vegetation has improved throughout the study period, while 14.1% of the country‘s vegetation degraded, from slight (7.5%) to substantial (6.6%) deterioration. Most pixels with severe degradation were found in Kigali city and the Eastern Province. The analysis of changes per vegetation type highlighted that five types of vegetation are seriously endangered: The ‗Mosaic grassland/ forest or shrubland‘ was severely degraded, followed by ‗Sparse vegetation‘, ‗grassland or woody vegetation regularly flooded on water logged soil‘, ‗artificial surfaces‘ and ‗broadleaved forest regularly flooded‘. The Hurst Exponent results indicated that the vegetation trend was consistent, with a sustainable area percentage of 40.16%, unsustainable area of 1.67% and an unpredictable area of 58.17%. This study will provide government and local authorities with valuable information to improve efficiency in the recently targeted efforts of environmental protection and regeneration throughout the country.
学科领域地图学与地理信息系统
语种英语
文献类型学位论文
条目标识符http://ir.xjlas.org/handle/365004/14802
专题研究系统_荒漠环境研究室
作者单位中国科学院新疆生态与地理研究所
推荐引用方式
GB/T 7714
NDAYISABA FELIX. 卢旺达植被和湿地监测[D]. 新疆乌鲁木齐. 中国科学院大学,2017.
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