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1.
Abstract Wildfire is a major disturbance agent in Mediterranean Type Ecosystems (MTEs). Providing reliable, quantitative information on the area of burns and the level of damage caused is therefore important both for guiding resource management and global change monitoring. Previous studies have successfully mapped burn severity using remote sensing, but reliable accuracy has yet to be gained using standard methods over different vegetation types. The objective of this research was to classify burn severity across several vegetation types using Landsat ETM imagery in two areas affected by wildfire in southern California in June 1999. Spectral mixture analysis (SMA) using four reference endmembers (vegetation, soil, shade, non‐photosynthetic vegetation) and a single (charcoal‐ash) image endmember were used to enhance imagery prior to burn severity classification using decision trees. SMA provided a robust technique for enhancing fire‐affected areas due to its ability to extract sub‐pixel information and minimize the effects of topography on single date satellite data. Overall kappa classification accuracy results were high (0.71 and 0.85, respectively) for the burned areas, using five canopy consumption classes. Individual severity class accuracies ranged from 0.5 to 0.94. 相似文献
2.
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
3.
Vegetation phenology has a great impact on land-atmosphere interactions like carbon cycling, albedo, and water and energy exchanges. To understand and predict these critical land-atmosphere feedbacks, it is crucial to measure and quantify phenological responses to climate variability, and ultimately climate change. Coarse-resolution sensors such as MODIS and AVHRR have been useful to study vegetation phenology from regional to global scales. These sensors are, however, not capable of discerning phenological variation at moderate spatial scales. By offering increased observation density and higher spatial resolution, the combination of Landsat and Sentinel-2 time series might provide the opportunity to overcome this limitation.In this study, we analyzed the potential of combined Sentinel-2 and Landsat time series for estimating start of season (SOS) of broadleaf forests across Germany for the year 2018. We tested two common statistical modeling approaches (logistic and generalized additive models using thin plate splines) and the two most commonly used vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI).We found strong agreement between SOS estimates from logistic and spline models (rEVI = 0.86; rNDVI = 0.65), whereas agreement was higher for EVI than for NDVI (RMSDEVI = 3.07, RMSDNDVI = 5.26 days). The choice of vegetation index thus had a higher impact on the results than the fitting method. The EVI-based SOS also showed higher correlation with ground observations compared to NDVI (rEVI = 0.51, rNDVI = 0.42). Data density played an important role in estimating land surface phenology. Models combining Sentinel-2A/B, with an average cloud-free observation frequency of 12 days, were largely consistent with the combined Landsat and Sentinel-2 models, suggesting that Sentinel-2A/B may be sufficient to capture SOS for most areas in Germany in 2018. However, in non-overlapping swath areas and mountain areas, observation frequency was significantly lower, underlining the need to combine Landsat and Sentinel-2 for consistent SOS estimates over large areas. Our study demonstrates that estimating SOS of temperate broadleaf forests at medium spatial resolution has become feasible with combined Landsat and Sentinel-2 time series. 相似文献
4.
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
5.
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
6.
Abstract This paper describes the first stage of an experiment aiming to evaluate the potential and limitations of MIVIS data for mapping the degradational state of soils in a sub‐scene of a southern Apennines study area (Italy). After radiometric rectification of the image data and the collection of a field/laboratory spectral library, linear spectral mixture modelling (SMA) was used to decompose image spectra into fractions of spectrally distinct mixing components. Spectral endmember selection was based upon a principal component analysis (PCA) applied to a set of soil spectra, collected from the spectral library. The resulting abundance estimates (fractions) trough SMA were then analysed to identify soil conditions and to obtain an improved measure of dry and green vegetation cover. A map of soil conditions and dry‐green vegetation abundance, based upon MIVIS data was then derived from normalised fractions of soil‐vegetation endmembers obtained from SMA. 相似文献
7.
The vegetation fraction is a key factor used in many research fields, including soil and water conservation, and ecological evaluation. In this paper, based on the traditional dimidiated pixel model, NDVI soil extraction is modified to improve the accuracy of the vegetation fraction obtained, thus also providing an improved method for obtaining vegetation factors in other areas of research. Due to the unique regional location of the Yarlung Zangbo River basin, terrain factors are critical for the stability of vegetation change. The improved model is here applied to inverse the vegetation coverage of the study region; the spatial patterns of change intensity during the past 15 years (1998–2012) are then analyzed. Considering the area’s alpine climate, results show that terrain factors have a significant effect on the distribution of vegetation coverage change intensity. Before specific thresholds are reached, terrain factors such as elevation, topographic relief, and slope exhibit a positive correlation with change in the vegetation fraction. In areas with the same longitude, the higher the latitude the greater the change intensity, while vegetation change intensity also increases with an increasing variety among the upper, middle, and lower reaches of the Yarlung Zangbo River. In the river’s middle-upper and lower reaches, vegetation coverage is prone to increase and decrease, respectively. The results presented here could greatly enhance the inversion precision of vegetation coverage and reveal the spatial and temporal heterogeneity between vegetation coverage, which are of great ecological significance and practical value for the protection of eco-environment in the Yarlung Zangbo River basin. 相似文献
8.
Climate dominantly controls vegetation over most regions at most times, and vegetation responses to climate change are often asymmetric with temporal effects. However, systematic analysis of the time-lag and time-accumulation effects of climate on vegetation growth, has rarely been conducted, in particular for different vegetation growing phases. Thus, this study aimed to leverage normalized difference vegetation index (NDVI) to determine the spatiotemporal patterns of climatic effects on global vegetation growth considering various scenarios of time-lag and/or accumulation effects. The results showed that (i) climatic factors have time-lag and -accumulation effects as well as their combined effects on global vegetation growth for the whole growing season and its subphases (i.e., the growing and senescent phases). However, these effects vary with climatic factors, vegetation types, and regions. Compared with those of temperature, both precipitation and solar radiation display more significant time-accumulation effects in the whole growing season worldwide, but behave differently in the growing and senescent phases in the middle-high latitudes of the Northern Hemisphere; (ii) compared to the scenario without time effects, considering time-lag and -accumulation effects as well as their combined effects increased by 17 %, 15 %, and 19 % the overall explanatory power of vegetation growth by climate change for the whole growing season, the growing phase, and senescent phase, respectively; (iii) considering the time-lag and -accumulation effects as well as their combined effects, climate change controls 70 % of areas with a significant NDVI variation from 1982 to 2015, and the primary driving factor was temperature, followed by solar radiation and precipitation. This study highlights the significant time-lag and -accumulation effects of climatic factors on global vegetation growth. We suggest that these effects need to be incorporated into dynamic vegetation models to better understand vegetation growth under accelerating climate change. 相似文献
9.
Tagel Gebrehiwot Anne van der Veen Ben Maathuis 《International Journal of Applied Earth Observation and Geoinformation》2011
With the development of global changes, researchers from all over the world increasingly pay attention to drought detection, and severe droughts that may have resulted from climate change. In this paper, spatial and temporal variability of drought is evaluated based on precipitation data and remotely sensed images. The standard precipitation index (SPI) and vegetation condition index (VCI) are used to evaluate the spatial and temporal characteristics of meteorological and vegetative drought in Tigray, Northern Ethiopia. Based on the drought critical values of SPI and VCI defining drought, the spatial and temporal extent of droughts in the study area is established. We processed 396 decadal images in order to produce the multi-temporal VCI drought maps. The results of the SPI and VCI analysis reveal that the eastern and southern zones of the study region suffered a recurrent cycle of drought over the last decade. Results further show that there is a time lag between the period of the peak VCI and precipitation values obtained from the meteorological stations across the study area. A significant agreement was observed between VCI values with the current plus last two-months of precipitation. The study demonstrates the utility of the vegetation condition index in semi-arid and arid regions. 相似文献
10.
A growing number of studies have focused on variations in vegetation phenology and their correlations with climatic factors. However, there has been little research on changes in spatial heterogeneity with respect to the end of the growing season (EGS) and on responses to climate change for alpine vegetation on the Qinghai–Tibetan Plateau (QTP). In this study, the satellite-derived normalized difference vegetation index (NDVI) and the meteorological record from 1982 to 2012 were used to characterize the spatial pattern of variations in the EGS and their relationship to temperature and precipitation on the QTP. Over the entire study period, the EGS displayed no statistically significant trend; however, there was a strong spatial heterogeneity throughout the plateau. Those areas showing a delaying trend in the EGS were mainly distributed in the eastern part of the plateau, whereas those showing an advancing trend were mostly scattered throughout the western part. Our results also showed that change in the vegetation EGS was more closely correlated with air temperature than with precipitation. Nonetheless, the temperature sensitivity of the vegetation EGS became lower as aridity increased, suggesting that precipitation is an important regulator of the response of the vegetation EGS to climate warming. These results indicate spatial differences in key environmental influences on the vegetation EGS that must be taken into account in current phenological models, which are largely driven by temperature. 相似文献
11.
Abstract The goal of this research was to explore the utility of very high spatial resolution, digital remotely sensed imagery for monitoring land‐cover changes in habitat preserves within southern California coastal shrublands. Changes were assessed for Los Penasquitos Canyon Preserve, a large open space in San Diego County, over the 1996 to 1999 period for which imagery was available. Multispectral, digital camera imagery from two summer dates, three years apart, was acquired using the Airborne Data Acquisition and Registration (ADAR) digital‐camera system. These very high resolution (VHR) image data (1m), composed of three visible and one near‐infrared wavebands (V/NIR), were the primary image input for assessing land cover change. Image‐derived datasets generated from georeferenced and registered ADAR imagery included multitemporal overlays and multitemporal band differencing with threshold selection. Two different multitemporal image classifications were generated from these datasets and compared. Single‐date imagery was analyzed interactively with image‐derived datasets and with information from field observations in an effort to discern change types. A ground sampling survey conducted soon after the 1999 image acquisition provided concurrent ground reference data. Most changes occurring within the three‐year interval were associated with transitional phenological states and differential precipitation effects on herbaceous cover. Variations in air temperatures and timing of rainfall contributed to differences that the seven‐week image acquisition offset may have caused. Disturbance factors of mechanical clearing, erosion, potentially invasive plants, and fire were evident and their influence on the presence, absence, and type of vegetation cover were likely sources of change signals. The multitemporal VHR, V/NIR image data enabled relatively fine‐scale land cover changes to be detected and identified. Band differencing followed by multitemporal classification provided an effective means for detecting vegetation increase or decrease. Detailed information on short‐term disturbance effects and long‐term vegetation type conversions can be extracted if image acquisitions are carefully planned and geometric and radiometric processing steps are implemented. 相似文献
12.
Spring greening in boreal forest ecosystems has been widely linked to increasing temperature, but few studies have attempted to unravel the relative effects of climate variables such as maximum temperature (TMX), minimum temperature (TMN), mean temperature (TMP), precipitation (PRE) and radiation (RAD) on vegetation growth at different stages of growing season. However, clarifying these effects is fundamental to better understand the relationship between vegetation and climate change. This study investigated spatio-temporal divergence in the responses of Finland’s boreal forests to climate variables using the plant phenology index (PPI) calculated based on the latest Collection V006 MODIS BRDF-corrected surface reflectance products (MCD43C4) from 2002 to 2018, and identified the dominant climate variables controlling vegetation change during the growing season (May–September) on a monthly basis. Partial least squares (PLS) regression was used to quantify the response of PPI to climate variables and distinguish the separate impacts of different variables. The study results show the dominant effects of temperature on the PPI in May and June, with TMX, TMN and TMP being the most important explanatory variables for the variation of PPI depending on the location, respectively. Meanwhile, drought had an unexpectedly positive impact on vegetation in few areas. More than 50 % of the variation of PPI could be explained by climate variables for 68.5 % of the entire forest area in May and 87.7 % in June, respectively. During July to September, the PPI variance explained by climate and corresponding spatial extent rapidly decreased. Nevertheless, the RAD was found be the most important explanatory variable to July PPI in some areas. In contrast, the PPI in August and September was insensitive to climate in almost all of the regions studied. Our study gives useful insights on quantifying and identifying the relative importance of climate variables to boreal forest, which can be used to predict the possible response of forest under future warming. 相似文献
13.
14.
以Landsat TM归一化植被指数(NDVI)为数据源,运用像元二分模型提取陕北黄土高原1990、2000、2010年夏季的植被覆盖度,分析陕北黄土高原植被覆盖度的空间变化情况。结果显示:研究区植被覆盖度呈波动上升趋势。不同等级植被覆盖度在数量和空间位置上的转移较为活跃。大于等于60%的植被覆盖度和小于等于40%的植被覆盖度在空间上呈西南—东北两个方向扩张的分布趋势。受气候和人为等因素的影响,陕北黄土高原植被改善良好。 相似文献
15.
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
16.
草原矿区长时序植被覆盖度变化趋势对比分析 总被引：8，自引：2，他引：6
呼伦贝尔草原区生态脆弱，在人类活动和气候等因素影响下草原生态变化备受关注。本文以宝日希勒矿区及周边为研究区，应用1985-2015年Landsat年度最大合成NDVI数据，采用像元二分模型反演植被覆盖度；分别利用一元线性回归法和Sen+Mann-Kendall法对研究区植被覆盖度趋势和空间差异进行了对比分析。结果表明：两种方法得到的植被变化趋势基本一致，Sen+Mann-Kendall方法相较于一元线性回归法对植被覆盖度改善和退化反应更为敏感。研究结果有助于科学评价长时序煤炭开发活动对地表生态的影响并为长时序植被变化监测提供方法参考。 相似文献
17.
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
18.
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
19.
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
20.
GIS支持的全球气候变化对中国Holdridge生命地带的可能影响研究 总被引：7，自引：0，他引：7
该文以地理信息系统为支持手段 ,根据Holdridge气候—植被生命地带的分类体系 ,首先研究了在目前气候条件下中国Holdridge生命地带空间分布的基本格局 ;然后采用GFDL、GISS、OSU3个GCMs模拟的 2×CO2 情景下的气温和降水作为未来气候条件 ,揭示了 2×CO2 情景下中国Holdridge生命地带在空间分、面积以及海拔高度等方面的变化 相似文献