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1.
Land cover change analysis was undertaken in semi-arid southeastern Botswana. The aim was to determine how remotely sensed data could be applied over time and under different rainfall regimes to help assess the relative significance of biophysical and human factors in causing land cover change in a rapidly evolving developing world context. To this purpose, land cover changes were studied along an east (hardveld)-west (sandveld) gradient of decreasing rainfall and decreasing population density. Three years of Thematic Mapper imagery from 1984, 1994 and 1996, covering the period from the 1980s drought to the 1990s ‘normal’ rainfall regime were analysed using supervised classification techniques. Land cover change analysis revealed that over a large part of the study area the dry and more biophysically vulnerable western sandveld showed greater vegetation recovery than the eastern hardveld with its more productive soils and higher rainfall. Underlying causes behind this apparent reversal of trends are inferred to be mainly socioeconomic in nature and particularly related to higher population density due to the rise of salaried urban occupation opportunities in the hardveld. This work concludes that, while biophysical causes of change are important, the human dimension is regarded as being more significant especially where human factors negate otherwise positive biophysical effects in an agrarian developing country. 相似文献
2.
In perennial and natural vegetation systems, monitoring changes in vegetation over time is of fundamental interest for identifying and quantifying impacts of management and natural processes. Subtle changes in vegetation cover can be identified by calculating the trends of a vegetation density index over time. In this paper, we apply such an index-trends approach, which has been developed and applied to time series Landsat imagery in rangeland and woodland environments, to continental-scale monitoring of disturbances within forested regions of Australia. This paper describes the operational methods used for the generation of National Forest Trend (NFT) information, which is a time-series summary providing visual indication of within-forest vegetation changes (disturbance and recovery) over time at 25 m resolution. This result is based on a national archive of calibrated Landsat TM/ETM+ data from 1989 to 2006 produced for Australia's National Carbon Accounting System (NCAS). The NCAS was designed in 1999 initially to provide consistent fine-scale classifications for monitoring forest cover extent and changes (i.e. land use change) over the Australian continent using time series Landsat imagery. NFT information identifies more subtle changes within forested areas and provides a capacity to identify processes affecting forests which are of primary interest to ecologists and land managers. The NFT product relies on the identification of an appropriate Landsat-based vegetation cover index (defined as a linear combination of spectral image bands) that is sensitive to changes in forest density. The time series of index values at a location, derived from calibrated imagery, represents a consistent surrogate to track density changes. To produce the trends summary information, statistical summaries of the index response over time (such as slope and quadratic curvature) are calculated. These calculated index responses of woody vegetation cover are then displayed as maps where the different colours indicate the approximate timing, direction (decline or increase), magnitude and spatial extent of the changes in vegetation cover. These trend images provide a self-contained and easily interpretable summary of vegetation change at scales that are relevant for natural resource management (NRM) and environmental reporting. 相似文献
3.
In the past 50 years, the Sahel has experienced significant tree- and land cover changes accelerated by human expansion and prolonged droughts during the 1970s and 1980s. This study uses remote sensing techniques, supplemented by ground-truth data to compare pre-drought woody vegetation and land cover with the situation in 2011. High resolution panchromatic Corona imagery of 1967 and multi-spectral RapidEye imagery of 2011 form the basis of this regional scaled study, which is focused on the Dogon Plateau and the Seno Plain in the Sahel zone of Mali. Object-based feature extraction and classifications are used to analyze the datasets and map land cover and woody vegetation changes over 44 years. Interviews add information about changes in species compositions. Results show a significant increase of cultivated land, a reduction of dense natural vegetation as well as an increase of trees on farmer's fields. Mean woody cover decreased in the plains (−4%) but is stable on the plateau (+1%) although stark spatial discrepancies exist. Species decline and encroachment of degraded land are observed. However, the direction of change is not always negative and a variety of spatial variations are shown. Although the impact of climate is obvious, we demonstrate that anthropogenic activities have been the main drivers of change. 相似文献
4.
Studies of the impact of human activity on vegetation dynamics of the Sahelian belt of Africa have been recently re-invigorated by new scientific findings that highlighted the primary role of climate in the drought crises of the 1970s–1980s. Time series of satellite observations revealed a re-greening of the Sahelian belt that indicates no noteworthy human effect on vegetation dynamics at sub continental scale from the 1980s to late 1990s. However, several regional/local crises related to natural resources occurred in the last decades despite the re-greening thus underlying that more detailed studies are needed. In this study we used time-series (1998–2010) of SPOT–VGT NDVI and FEWS–RFE rainfall estimates to analyse vegetation – rainfall correlation and to map areas of local environmental anomalies where significant vegetation variations (increase/decrease) are not fully explained by seasonal changes of rainfall. Some of these anomalous zones (hot spots) were further analysed with higher resolution images Landsat TM/ETM+ to evaluate the reliability of the identified anomalous behaviour and to provide an interpretation of some example hot spots. The frequency distribution of the hot spots among the land cover classes of the GlobCover map shows that increase in vegetation greenness is mainly located in the more humid southern part and close to inland water bodies where it is likely to be related to the expansion/intensification of irrigated agricultural activities. On the contrary, a decrease in vegetation greenness occurs mainly in the northern part (12°–15°N) in correspondence with herbaceous vegetation covers where pastoral and cropping practices are often critical due to low and very unpredictable rainfall. The results of this study show that even if a general positive re-greening due to increased rainfall is evident for the entire Sahel, some local anomalous hot spots exist and can be explained by human factors such as population growth whose level reaches the ecosystem carrying capacity as well as population displacement leading to vegetation recovery. 相似文献
5.
本文借助Google Earth Engine(GEE)云平台,以Landsat影像、气温降水和土地利用类型为基础,利用Theil-Sen Median趋势分析、Mann-Kendall检验、偏相关性和多元回归残差分析法,分析了1999—2018年陕北黄土高原植被覆盖时空特征、变化趋势及气候变化与人类活动对于不同土地利用类型的影响,得出以下结论:(1)1999—2018年陕北黄土高原年际FVC呈改善趋势,其平均增速为0.004 9/a(P<0.01),植被覆盖度呈增加趋势的面积占总面积的74.43%;(2)植被覆盖度与降水和气温的偏相关系数具有明显的空间差异,植被生长对降水变化较敏感;(3)气候变化和人类活动的共同作用是植被生长的主要原因,其中气候变化对植被FVC的影响范围为-0.001 0/a~0.003 6/a,而人类活动对植被FVC的影响范围为-0.046 1/a~0.049 0/a;(4)在不同土地利用类型中,气候变化对水体增幅影响最大,对针叶林和阔叶林增幅影响最小,而人类活动变化对人类占用地增幅影响最大,对阔叶林增幅影响最小。 相似文献
6.
ABSTRACT Inner Mongolia is an important ecological zone of northern China and 67% of its land area is grassland. This ecologically fragile region has experienced significant vegetation degradation during the last decades. Although the spatial extents and rates of vegetation change have previously been characterized through various remote sensing and GIS studies, the underlying driving factors of vegetation changes are still not well understood. In this study, we first used time-series MODIS NDVI data from 2000 to 2016 to characterize the temporal trend of vegetation changes. These vegetation change trends were compared with climate and socioeconomic variables to determine the potential drivers. We used a set of statistical methods, including multiple linear regression (MLR), spatial correlation analysis, and partial least squares (PLS) regression analyzes, to quantify the spatial distribution of the driving forces and their relative importance to vegetation changes. Results show that the main driving factors and their impact magnitude (weight) are in the order of human activities (r = -0.785, p < 0.01, VIP = 1.37), precipitation (r = 0.541, p < 0.05, VIP = 0.89), temperature (r = -0.319, p > 0.05 VIP = 0.59). The area affected by human activities was 10.57%. Specific human activities, such as coal mining and grazing were negatively associated with vegetation cover, while eco-engineering projects had positive impacts. This study provided thorough quantification of driving forces of vegetation change and enhanced our understanding of their interactions. Our integrated geospatial-statistical approach is particularly important for sustainable development of ecosystem balance in Chen Barag Banner and other areas facing similar challenges. 相似文献
7.
Global climate change has led to significant vegetation changes in the past half century. North China Plain, the most important grain production base of china, is undergoing a process of prominent warming and drying. The vegetation coverage, which is used to monitor vegetation change, can respond to climate change (temperature and precipitation). In this study, GIMMS (Global Inventory Modelling and Mapping Studies)-NDVI (Normalized Difference Vegetation Index) data, MODIS (Moderate-resolution Imaging Spectroradiometer) – NDVI data and climate data, during 1981–2013, were used to investigate the spatial distribution and changes of vegetation. The relationship between climate and vegetation on different spatial (agriculture, forest and grassland) and temporal (yearly, decadal and monthly) scales were also analyzed in North China Plain. (1) It was found that temperature exhibiting a slight increase trend (0.20 °C/10a, P < 0.01). This may be due to the disappearance of 0 °C isotherm, the rise of spring temperature. At the same time, precipitation showed a significant reduction trend (−1.75 mm/10a, P > 0.05). The climate mutation period was during 1991–1994. (2) Vegetation coverage slight increase was observed in the 55% of total study area, with a change rate of 0.00039/10a. Human activities may not only accelerate the changes of the vegetation coverage, but also c effect to the rate of these changes. (3) Overall, the correlation between the vegetation coverage and climatic factor is higher in monthly scale than yearly scale. The correlation analysis between vegetation coverage and climate changes showed that annual vegetation coverage was better correlatend with precipitation in grassland biome; but it showed a better correlated with temperature i the agriculture biome and forest biome. In addition, the vegetation coverage had sensitive time-effect respond to precipitation. (4) The vegetation coverage showed the same increasing trend before and after the climatic variations, but the rate of increase slowed down. From the vegetation coverage point of view, the grassland ecological zone had an obvious response to the climatic variations, but the agricultural ecological zones showed a significant response from the vegetation coverage change rate point of view. The effect of human activity in degradation region was higher than that in improvement area. But after the climate abruptly changing, the effect of human activity in improvement area was higher than that in degradation region, and the influence of human activity will continue in the future. 相似文献
8.
Kamleshan Pillay Naeem Hoosen Agjee Srinivasan Pillay 《Journal of the Indian Society of Remote Sensing》2014,42(1):51-60
Land is the basic resource that is needed by man in order to survive: It provides humans with living space, nutrition and energy resources. The rapid growth of the human population, climate change and pollution on a catastrophic scale has caused the quality of land resources to be compromised. Remote sensing is a useful tool in land cover change detection providing information to decision makers. The aim of this study was to evaluate land cover changes in the Mtunzini area in South Africa over the past 18 years; determine why changes have occurred and predict land cover patterns for future years. In this study a supervised classification was used to detect land cover classes of the Mtunzini area from 1992 to 2009 using four Landsat images in the time series analysis. The supervised classification had an accuracy of 80.80 % which was used to model land cover changes. Commercial sugar cane and forest plantation classes increased throughout the time series. It was estimated in the modelling procedure that bushland (42.11 %) and bare soil (35 %) would be changed to commercial sugar cane. This is indicative of the expanding agriculture sector in Mtunzini. Natural vegetation is predicted to be disturbed: 18 % of bushland and 15.07 % of dense bush are expected to be replaced by rural dwellings. This is owing to a potential increase in the rural population and a reduced local economic growth. This study highlights the need for increased vigilance of the forestry industry and commercial sugar cane farms which may be encroaching on natural vegetation and livelihoods of local residents. Strategic planning and proper management of natural vegetation types is needed as these land cover types are decreasing rapidly. 相似文献
9.
夏兰芳 《测绘与空间地理信息》2012,(8):5-7,12
建立了一套基于遥感信息和DSM的变化检测信息管理系统,该系统主要包括DSM数据管理模块、DSM变化检测模块和变化结果表达模块。系统利用多时相的数字表面模型(DSM),通过变化检测模块检测出城市地区人工建筑物、植被等的变化情况,检测结果可以应用在基本农田保护、土地利用变化监测以及违法用地查处等方面,为地理国(市)情监测提供技术支持。检测过程自动化程度高、快速、准确。 相似文献
10.
11.
Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover. 相似文献
12.
一种利用多时相TM影像分析地表植被变化的新方法--以敦煌地区绿洲植被变化分析为例 总被引：2，自引：0，他引：2
变化分析是多时相遥感影像的主要应用领域。以郭煌绿洲为例 ,探讨一种应用多时相TM影像进行地表植被变化分析的新方法。结果证明 ,用不同时相的NDVI影像进行彩色合成可以直观地反映地表植被的变化 ,而利用色彩变换得到的各分量可以对变化特点进行定量分析。其中色度反映变化类型 ,饱和度反映变化强度 ,而亮度图像则反映地表植被多年来的总体长势。除了直观和定量的特性之外 ,该方法还可以用于其它类型的变化分析 ,具有可扩展性 相似文献
13.
一种利用多时相TM影像分析地表植被变化的新方法：——以敦煌地区绿洲植 … 总被引：6，自引：0，他引：6
变化分析是多时相遥感影像的主要应用领域。以敦煌绿洲为例,探讨一种应用多时相ＴＭ影像进行地表植被变化分析的新方法。结果证明,用不同时相的ＮＤＶＩ影像进行彩色合成可以直观地反映地表植被的变化,而利用色彩变换得到的各分量可以对变化特点进行定量分析。其中色度反映变化类型,饱和度反映变化强度,而亮度图像则反映地表植被多年来的总体长势。除了直观和定量的特性之外,该方法还可以用于其它类型的变化分析,具有可扩展性 相似文献
14.
Climate change scenarios predict that Central Asia may experience an increase in the frequency and magnitude of temperature and precipitation extremes by the end of the 21st century, but the response regularity of different types of vegetation to climate extremes is uncertain. Based on remote-sensed vegetation index and in-situ meteorological data for the period of 2000–2012, we examined the diverse responses of vegetation to climate mean/extremes and differentiated climatic and anthropogenic influence on the vegetation in Central Asia. Our results showed that extensive vegetation degradation was related to summer water deficit as a result of the combined effect of decreased precipitation and increased potential evapotranspiration. Water was a primary climatic driver for vegetation changes regionally, and human-induced changes in vegetation confined mainly to local areas. Responses of vegetation to water stress varied in different vegetation types. Grasslands were most responsive to water deficit followed by forests and desert vegetation. Climate extremes caused significant vegetation changes, and different vegetation types had diverse responses to climate extremes. Grasslands represented a symmetric response to wet and dry periods. Desert vegetation was more responsive during wet years than in dry years. Forests responded more strongly to dry than to wet years due to a severe drought occurred in 2008. This study has important implications for predicting how vegetation ecosystems in drylands respond to climate mean/extremes under future scenarios of climate change. 相似文献
15.
Forested areas in the United States have been altered since the time of European settlement. There is increasing interest in comparing present day vegetation with that of the Pre-Euroamerican era to understand what changes have occurred in some of our more outstanding natural areas. Studies have been conducted using Government Land Office (GLO) notes to understand historic vegetation surveys, but past studies focused on species present/absent lists. The GLO surveys included information about tree species, tree diameter and other physical features. This study used indicator kriging to interpolate the probability of tree species on the landscape using the GLO data from 62 townships. Once continuous probability models were developed, vegetation spatial patterns were analyzed throughout the sub-basin. This technique provided insight into what the vegetation pattern (spatially) was like prior to Euroamerican settlement within the Buffalo River sub-basin. It provided the base information necessary to quantify vegetation change and the spatial extent of that change. Based on this research it appears that post-Euroamerican fire suppression and agricultural practices with other human activities have been major contributors to change. Eastern Redcedar ( Juniperious virginiana ) and hickory ( Carya sp .) have increased, while oak species ( Quercus sp .) have decreased. Additionally 19% of the sub-basin has changed to non-forest. 相似文献
16.
Abstract The objective of this study was to explore the utility of multi‐temporal, multi‐spectral image data acquired by the IKONOS satellite system for monitoring detailed land cover changes within shrubland habitat reserves. Sub‐pixel accuracy in date‐to‐date registration was achieved, in spite of the irregular relief of the study area and the high spatial resolution of the imagery. Change vector classification enabled features ranging in size from tens of square meters to several hectares to be detected and six general land cover change classes to be identified. Interpretation of the change vector classification product in conjunction with visual inspection of the multi‐temporal imagery enabled identification of specific change types such as: vegetation disturbance and associated increase in soil exposure, shrub removal, urban edge vegetation clearing and fire maintenance, increase in vegetation cover, spread of invasive plant species, fire scars and subsequent recovery, erosional scouring, trail and road development, and expansion of bicycle disturbances. 相似文献
17.
天津滨海新区土地利用变化及驱动因子分析 总被引：1，自引：0，他引：1
随着全球变化研究的深入,人们逐渐认识到人类活动所导致的土地利用/土地覆盖变化(Land Use and Cover Change)最终会反过来影响到人类自身的生存和发展。因此,土地利用与土地覆盖变化成为全球变化研究的热点问题。本文以天津滨海新区为研究区域,使用ENVI软件通过面向对象解译的方法分别对2005、2010、2014年的遥感图像进行处理,得到3期的解译数据;然后,运用土地利用动态度及土地利用转移矩阵的方法对土地利用的面积变化情况进行分析;最终得出结论:该区域土地利用类型面积变化以建筑用地、未利用地的大幅增加及水域的锐减为主。2005~2014年9年间建筑用地和未利用地面积增加量分别为13 638.15 hm~2、6 926.94 hm~2;植被和盐田的面积都是减少的,而植被减少的面积最多,减少的面积量为10 673.28 hm~2。同时,本文进一步分析了经济、人口、政策驱动因子对该区域土地利用变化的影响。 相似文献
18.
基于遥感的植被年际变化及其与气候关系研究进展 总被引：61，自引：0，他引：61
植被具有明显的年际变化和季节变化特点,对植被的动态监测可以从一定程度上反映气候变化的趋势,因此监测植被动态变化以及分析这种变化与气候的关系已经成为全球变化研究的一个重要领域.随着遥感卫星获得长时间系列逐日观测数据,许多国际组织和机构制定了全球卫星数据接收、处理和生成数据集计划,所产生的标准数据集则极大地促进了该项研究.大量研究在全球尺度、洲际尺度（北美洲和欧亚大陆）以及区域尺度上广泛开展.在阅读国内外大量文献的基础上,比较分析了常用于植被监测的卫星传感器和主要数据集,汇总了植被年际变化及其与气候关系研究的主要研究方法和研究结果.结果表明近20年来全球植被活动明显增强,表现为北半球普遍存在增加的趋势,南半球干旱半干旱区出现降低的植被光合作用,但这些变化因空间位置不同和研究尺度不一样体现出不同的动态变化特征.气温和降水是影响植被变化的最主要的因素. 相似文献
19.
1983—1992年中国陆地植被NDVI演变特征的变化矢量分析 总被引：32，自引：2，他引：32
以NDVI时序资料为基本数据源，综合应用变化矢量分析和主成分分析方法对1983年至1992年中国陆地植被NDVI的变化强度、变化类型及空间结构变化特征进行了分析。研究结果表明在此期间中国陆地植被NDVI变化有以下特点：（1）十年间NDVI变化东西分异明显，东部变化幅度远大于西部。NDVI变化整体表现为稳中略增，增加区主要分布在台湾、福建、四川、河南等地；减少区主要分布在云南省和新疆北部等地。（2）空间结构信息表现了景观异质性，其变化主要发生在南方，反映了植被的生长和衰老过程及地形（山脉走向）变化。 相似文献
20.
Seema Mehra Parihar Soma Sarkar Amitava Dutta Shilpi Sharma Tanushree Dutta 《国际地球制图》2013,28(3):273-287
The East Kolkata Wetlands is a unique resource recovery system. The Ramsar Convention recognized it as a ‘Wetland of International Importance’ in August 2002. However, the long-term resource exploitation and land use changes in the dynamic ecosystem have resulted in non-linear environmental responses. This is an attempt using open source remote sensing datasets to capture the spatio-temporal transformation of the wetland resulting from various anthropogenic activities. Landsat MSS and TM imageries of 1973, 1980, 1989, 2001 and 2010 were classified using Maximum Likelihood Classifier to monitor the wetland change; however, to study wetland dynamics, the post-classification wetland change detection maps have been generated for two temporal phases, i.e. 1973–1989 and 1989–2010. This study finds that the area under wetlands has reduced comprehensively in the past 40 years due to the conversion of wetlands into various other uses such as urban expansion of the Kolkata metropolitan city. 相似文献