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1.
The widespread changes in forest cover caused by climatological and anthropogenic factors can influence the forest ecosystem and climate system to a great extent. With the increasing availability of remote sensing data, monitoring of forest changes at high temporal resolution and on various scales is becoming more realistic. Though several methods based on time series data have been used to detect forest disturbance, there are few studies paying attention to boreal areas where the forest is significant in regulating the global carbon cycle and biogeophysical processes. In this paper, we present a robust method of Breaks Detection Based On Polynomial Model (BDPM) to track boreal (e.g. Lesser Khingan Mountains) deforestation and forest fires based on the MODIS and Landsat TM time series data. Compared with the previous methods, the BDPM offers the following advantages: (1) Fitting of the polynomial model using the seasonal variation of forests in the whole region instead of a single pixel to avoid error accumulation; (2) to avoid confusion between vegetation change due to climate changes and abrupt forest disturbances, we segmented the long-time NDVI series data into 12 seasonal cycles and simulated the temporal variations in each seasonal cycle.  相似文献   

2.
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  
马明国  王建  王雪梅 《遥感学报》2006,10(3):421-431
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   

3.
中国北方地区地域辽阔,干旱面积分布较广,风沙危害、水土流失等问题严重,是典型的气候敏感区及生态环境脆弱区。然而,该区域近几十年来生态环境质量演变及其对气候变化与人类活动响应的规律还不清晰,研究这些规律对加强北方地区生态文明建设及维护生物多样性具有重要意义。本文基于中国历史高分辨率生态环境质量数据(CHEQ),以及气候指标、夜间灯光等遥感数据,利用趋势分析、变异系数、偏相关分析、多元回归分析、重标极差分析等方法,探究了北方地区2001—2018年生态环境质量时空变化特征及其对气候变化与人类活动的响应。结果表明:①2001—2018年CHEQ指数总体呈小幅下降趋势,空间上呈东高西低、南北高中部低的分布特征;②近18年来,北方地区生态环境质量改善的区域仅为18.66%,而退化面积比例为40%;③生态环境质量与气温和人类活动呈显著负相关关系(P<0.05),而与降水呈显著正相关关系(P<0.05);④气候变化对生态环境质量变化起主导作用的区域占研究区面积的90%。本文在弥补现有研究不足的同时,可以为快速掌握北方地区绿色经济发展下生态环境质量的变化规律和提高生态文明建设的效果提供科学依据,为“绿水青山就是金山银山”的科学政策提供理论支撑。  相似文献   

4.
干旱区生态系统极易受到气候及土地利用变化的影响,其生物多样性格局及其形成机制是重要的生态学问题。基于新疆地区鸟类及哺乳动物物种多样性数据,结合气候、地形和长时间序列的植被遥感参数产品FAPAR数据等,主要在不同的土地利用类型及海拔带上采用单因子相关分析方法探讨了物种丰富度格局的形成机制。总体来说,不同生境类型中,植被遥感参数因子(DHI、NDVI等)与两种类群物种丰富度分布的相关性强于与气候因子(温度、降水)的相关性。具体而言,植被遥感参数因子中,基于FAPAR的生境指数因子与丰富度的相关性大于基于植被指数的因子(DHI_cumNDVI_cumEVI_cum);气候因子中,在草地生境或者较低的海拔上,年均降水因子对于丰富度分布的解释力强于年均温度因子。这表明在新疆地区,影响鸟类与哺乳类动物物种丰富度分布的主导理论是生境异质性假说与环境稳定性假说,其解释力在多种生境内均强于生产力与环境热量。  相似文献   

5.
Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau   总被引：1，自引：0，他引：1  
Understanding the relationships between snow and vegetation is important for interpretation of the responses of alpine ecosystems to climate changes. The Qinghai-Tibetan Plateau is regarded as an ideal area due to its undisturbed features with low population and relatively high snow cover. We used 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) datasets during 2001–2010 to examine the snow–vegetation relationships, specifically, (1) the influence of snow melting date on vegetation green-up date and (2) the effects of snow cover duration on vegetation greenness. The results showed that the alpine vegetation responded strongly to snow phenology (i.e., snow melting date and snow cover duration) over large areas of the Qinghai-Tibetan Plateau. Snow melting date and vegetation green-up date were significantly correlated (p < 0.1) in 39.9% of meadow areas (accounting for 26.2% of vegetated areas) and 36.7% of steppe areas (28.1% of vegetated areas). Vegetation growth was influenced by different seasonal snow cover durations (SCDs) in different regions. Generally, the December–February and March–May SCDs played a significantly role in vegetation growth, both positively and negatively, depending on different water source regions. Snow's positive impact on vegetation was larger than the negative impact.  相似文献   

6.
Alpine lakes on the Tibetan Plateau (TP) are key indicators of climate change and climate variability. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring lake changes on the TP and surroundings and understanding climate change impacts, particularly in remote and inaccessible areas where there are lack of in situ observations. This paper firstly introduces characteristics of Tibetan lakes, and outlines available satellite observation platforms and different remote sensing water-body extraction algorithms. Then, this paper reviews advances in applying remote sensing methods for various lake environment monitoring, including lake surface extent and water level, glacial lake and potential outburst floods, lake ice phenology, geological or geomorphologic evidences of lake basins, with a focus on the trends and magnitudes of lake area and water-level change and their spatially and temporally heterogeneous patterns. Finally we discuss current uncertainties or accuracy of detecting lake area and water-level changes from multi-source satellite data and on-going challenges in mapping characteristics of glacial lakes using remote sensing. Based on previous studies on the relationship between lake variation and climate change, it is inferred that the climate-driven mechanisms of lake variations on the TP still remain unclear and require further research.  相似文献   

7.
Species richness, or simply the number of species in a given area, is commonly used as an important indicator of biological diversity. Spatial variability in species richness has been postulated to depend upon environmental factors such as climate and climatic variability, which in turn may affect net primary productivity. The Advanced Very High Resolution Radiometer (AVHRR) derived Normalized Difference Vegetation Index (NDVI) has been shown to be correlated with climatic variables including rainfall, actual evapotranspiration and net primary productivity. To determine factors favoring high species richness, we examined the relationship between interannual NDVI variables and species richness of birds at a quarter degree scale (55 × 55 km). Results revealed a strong positive correlation between species richness and maximum average NDVI. Conversely, species richness showed negative correlation with standard deviation of maximum NDVI and the coefficient of variation. Though these relationships are indirect, they apparently operate through the green vegetation cover. Understanding such relationships can help in mapping and monitoring biological diversity, as well as in estimating changes in species richness in response to global climatic change.  相似文献   

8.
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   

9.
Abstract

High-latitude ecosystems are exposed to more pronounced warming effects than other parts of the globe. We develop a technique to monitor ecological changes in a way that distinguishes climate influences from disturbances. In this study, we account for climatic influences on Alaskan boreal forest performance with a data-driven model. We defined ecosystem performance anomalies (EPA) using the residuals of the model and made annual maps of EPA. Most areas (88%) did not have anomalous ecosystem performance for at least 6 of 8 years between 1996 and 2004. Areas with underperforming EPA (10%) often indicate areas associated with recent fires and areas of possible insect infestation or drying soil related to permafrost degradation. Overperforming areas (2%) occurred in older fire recovery areas where increased deciduous vegetation components are expected. The EPA measure was validated with composite burn index data and Landsat vegetation indices near and within burned areas.  相似文献   

10.
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   

11.
ABSTRACT

Mangroves are critical in the ecological, economic and social development of coastal rural and urban communities. However, they are under threat by climate change and anthropogenic activities. The Sunda Banda Seascape (SBS), Indonesia, is among the world’s richest regions of mangrove biomass and biodiversity. To inform current and future management strategies, it is critical to provide estimates of how mangroves will respond to climate change in this region. Therefore, this paper utilized spatial analysis with model-based climatic indicators (temperature and precipitation) and mangrove distribution maps to estimate a benchmark for the mangrove biomass of the SBS in six scenarios, namely the Last Inter-glacial Period, the current scenario (1950–2000) and all four projected Representative Concentration Pathways in 2070 due to climate change. Despite mangroves gaining more biomass with climate change (the increase in CO2 concentration), this paper highlighted the great proportion of below-ground biomass in mangrove forests. It also showed that the changes in spatial distribution of mangrove biomass became more variable in the context of climate change. As mangroves have been proposed as an essential component of climate change strategies, this study can serve as a baseline for future studies and resource management strategies.  相似文献   

12.
Satellite-based measurements of aerosols are one of the most effective ways to understand the role of aerosols in climate in terms of spatial and temporal variability. In the present study, we attempted to analyse spatial and temporal variations of satellite derived aerosol optical depth (AOD) over Indian region using moderate resolution imaging spectrometer over a period of 2001–2011. Due to its vast spatial extent, Indian region and adjacent oceanic regions are divided into different zones for analysis. The land mass is sub divided into five different zones such as Indo Gangetic Plain (IGP), Indian mainland, North Eastern India (NE), South India-1 (SI-1), South India-2 (SI-2). Oceanic areas are divided into Arabian Sea and Bay of Bengal. Arabian Sea is further divided as three zones viz. Northern AS (NAS), Central AS (CAS) and Eastern AS (EAS) zones. Bay of Bengal is divided as North BoB (NBoB), West BoB (WBoB), Central BoB (CBoB), and East BoB (EBoB). The study revealed that among all the land regions, IGP showed the highest peak AOD value (0.52 ± 0.17) while SI-2 showed the lower values of AOD in all the months compared to all India average. The maximum AOD is observed during premonsoon season for all regions. During the winter, average AOD levels were substantially lower than the summer averages. Peak of aerosol loading (0.35 ± 0.159) is observed in March over NE region, whereas in all other regions, peak is observed during May. Frequency distribution of long term AOD (<0.2, 0.3–0.5, >0.5) shows a shift of frequency distribution of AOD from <0.3 to 0.3–0.5 during the study period in all regions except IGP. In IGP shift of frequency of AOD values occurs from 0.3–0.5 to >0.5. Oceanic areas also shows seasonal variation of AOD. Over Arabian Sea, high AOD values with greater variations were observed in summer monsoon season while in Bay of Bengal it is observed during winter monsoon. This is due to the high wind speed prevailing in Arabian Sea during monsoon season which results in production of more sea salt aerosol. Highest AOD values are observed over NAS during monsoon season and over NBOB during winter season. Lowest AOD values with its lower variations observed in both the central region of Arabian Sea and Bay of Bengal.  相似文献   

13.
Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of “optical types” (OT), meaning “optically distinguishable functional types”, as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation.This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MODIS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found.Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability.  相似文献   

14.
This paper is a comprehensive review of the potential for remote sensing in exploring for geothermal resources. Temperature gradients in the earth crust are typically 25–30 °C per kilometer depth, however in active volcanic areas situated in subduction or rift zones gradients of up to 150 °C per kilometer depth can be reached. In such volcanic areas, meteoric water in permeable and porous rocks is heated and hot water is trapped to form a geothermal reservoir. At the Earth's surface hot springs and fumaroles are evidence of hot geothermal water. In low enthalpy systems the heat can be used for heating/cooling and drying while in high enthalpy systems energy is generated using hot water or steam. In this paper we review the potential of remote sensing in the exploration for geothermal resources. We embark from the traditional suite of geophysical and geochemical prospecting techniques to arrive at parameters at the Earth surface that can be measured by earth observing satellites. Next, we summarize direct and indirect detection of geothermal potential using alteration mineralogy, temperature anomalies and heat fluxes, geobotanical anomalies and Earth surface deformation. A section of this paper is dedicated to published remote sensing studies illustrating the principles of mapping: surface deformation, gaseous emissions, mineral mapping, heat flux measurements, temperature mapping and geobotany. In a case study from the La Pacana caldera (Chili) geothermal field we illustrate the cross cutting relationships between various surface manifestations of geothermal reservoirs and how remotely sensed indicators can contribute to exploration. We conclude that although remote sensing of geothermal systems has not reached full maturity, there is great potential for integrating these surface measurements in a exploration framework. A number of recommendations for future research result from our analysis of geothermal systems and the present contributions of remote sensing to studying these systems. These are grouped along a number of question lines: ‘how reproducible are remote sensing products’, ‘can long term monitoring of geothermal systems be achieved’ and ‘do surface manifestations link to subsurface features’?  相似文献   

15.
Increased atmospheric temperatures during the high-pressure which characterise the Mediterranean climate in the dry summer time, coupled with an increase in the intensity of storms in the following wet season over recent years, increase the risk of summer fires as well as debris flows and floods in the autumn and/or in the following years. In addition, the diffuse urbanization of Italy requires a rapid and reliable tool be available in order to obtain preliminary information, at the end of the summer season, that identifies newly fired areas that present a significant hazard to human populations. In such burned zones, soil instability may be more severe favouring debris flows which may impact on populated zones. Thus, in this paper we discuss a rapid methodology to: (i) identify burned areas using band ratio's using multitemporal LANDSAT ETM images; (ii) evaluate the potential of the burned areas as the source of debris flows based on morphometric parameters (slope and hill slope curvature); (iii) evaluate the structures, such as houses and roads, exposed to potential damage by debris flows. Hazardous areas were evaluated using a stochastical model coupled with an empirical relationship which accounts for the mobility of the debris flows. The methodology provides a classification of the most “dangerous” burned areas and the potentially maximum inundated downslope areas. This has been applied to Sicily for the period autumn 2001–autumn 2002. The total burned area was 76.37 km2. According to the classification proposed 6.4% of the burned areas were consider of very high to high hazard potential, 54.4% of medium hazard and 43.2% of low hazard potential.  相似文献   

16.
Efficient water-resource management is essential with regard to food security, growing populations and climate change. This is especially important for low- and middle-income (LMC) countries where food is often locally produced by traditional smallholder farming. Detailed knowledge of the spatio-temporal distribution of irrigation-water consumption provides valuable information to anticipate local food shortages and water scarcity as a result of climate variability. Yet, adequate techniques to quantify irrigation-water consumption at field level over large areas are lacking. Irrigation estimates generally have a coarse resolution making them inadequate for field-level assessments.This study developed a remote-sensing-based approach to quantify spatio-temporal patterns of irrigation-water consumption at field level using the MODIS evapotranspiration product (MOD16A2) and existing land-use maps on the spatio-temporal distribution of irrigated agriculture. Object-based image analysis was used to establish local evapotranspiration differences between irrigated and rainfed fields on a monthly basis, which are the irrigation-water consumption rates of the irrigated fields. This novel method was applied to a study area in the Central Rift Valley in Ethiopia where smallholder farming is dominant and only a few large-scale farms are present. Comparison with irrigation-water-consumption values of a local irrigation scheme showed that the monthly temporal dynamics were captured quite well, but lower values were calculated compared to the scheme's field data. Comparison with two validated remote-sensing based studies in Africa showed good agreement as irrigation-water-consumption estimates were in the same order of magnitude. Irrigation-water consumption follows the temporal rainfall pattern, i.e. irrigation practices intensify with increased water availability. Surface water is commonly used for irrigation in the study area.Our study shows that smallholder practices have a lower irrigation-water consumption compared to modern large-scale farms by approximately a factor 3. Irrigation-water consumption in the area is considerable, especially during the dry season. On average 32 % of excess water (precipitation – evapotranspiration) is consumed for irrigation. For smallholder irrigation and large-scale irrigation specifically this is 28 % and 63 % respectively.The object-based approach presented here is an operational mapping method for field-level irrigation-water-consumption over large areas. MOD16A2 is a global open-source readily-available evapotranspiration product used here although an evapotranspiration product with a higher spatial resolution might be preferred. Our approach can provide irrigation-water-consumption estimates over large areas in data-poor regions, which will increase the understanding of spatio-temporal patterns of smallholder irrigation and provide information to optimize water use.  相似文献   

17.
The Amazon landscape spatial variability and anisotropic trends in the Uatumã and Urubu River regions are evaluated using geomorphometric techniques such as fractal dimension, drainage network density and semivariogram. These procedures were applied to the digital elevation model (DEM) of the Shuttle Radar Topography Mission (SRTM). This evaluation facilitated the definition of geomorphometric domains with different degrees of roughness (fractal dimension) and elevation (semivariogram). These areas are consistent with known qualitative relief types. Furthermore, known geological structures in the subsurface and surface apparently influence the spatial variability of these geomorphometric variables. This is the Silves area case, where the hilly topography exhibits several annular and radial rivers, denoting subsurface control due to faults and folds that were mapped by seismic surveys. Another possible influence example is the spatial coincidence between structures mapped by magnetic data with low dissection zones delineated as a result of drainage network density analysis. In addition to the spatial distribution, the anisotropic trends of these geomorphometric variables were analyzed and compared with geological and geophysical information. Results indicate that the predominant directions for topographic semivariance anisotropy are NNE–SSW and NE–SW for the interfluvial regions, as well as NW–SE for the alluvial plains. The highest agglomeration direction in the drainage network, as shown by its anisotropy, coincides with the studied region’s current maximum horizontal stress direction, except in the floodplains. The direction with the most pronounced roughness, NNE–SSW, coincides with the direction of waterfalls and rapids. This study demonstrates that spatial variability knowledge and anisotropic trends of geomorphometric parameters is useful to understand the geology and geomorphology of the Central Amazon region.  相似文献   

18.
This paper investigated spatiotemporal dynamic pattern of vegetation, climate factor, and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets. First, most vegetation canopies demonstrated obvious seasonality, increasing with latitudinal gradient. Second, obvious dynamic trends were observed in both vegetation and climate change, especially the positive trends. Over 70% areas were observed with obvious vegetation greening up, with vegetation degradation principally in the Pearl River Delta, Yangtze River Delta, and desert. Overall warming trend was observed across the whole country (>98% area), stronger in Northern China. Although over half of area (58.2%) obtained increasing rainfall trend, around a quarter of area (24.5%), especially the Central China and most northern portion of China, exhibited significantly negative rainfall trend. Third, significantly positive normalized difference vegetation index (NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions, corresponding to their synchronous stronger seasonal pattern. Finally, at inter-annual level, the NDVI–climate relationship differed with climatic regions and their long-term trends: in humid regions, positive coefficients were observed except in regions with vegetation degradation; in arid, semiarid, and semihumid regions, positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature. This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process.  相似文献   

19.
We use a linear unmixing approach to test how land use and forestry maps, in combination with the MODIS BRDF/albedo product, can be used to estimate land cover type albedos in boreal regions. Operational land use maps from three test areas in Finland and Canada were used to test the method. The resulting endmember albedo estimates had low standard errors of the mean and were realistic for the main land cover types. The estimated albedos were fairly consistent with albedo measurements conducted with a telescope mast and pure pixel albedos. Problems with the method are the possible errors in the land cover maps, lack of good quality winter MODIS albedo composites and the mismatch between the MODIS pixels and the true observation area. The results emphasize the role of tree species as determinant of forest albedo. Comprehensive spatial and temporal measurements of land cover albedo are usually not possible with in situ mast measurements, and the spatial resolution of MODIS albedo product is often too low to allow direct comparison of pixel albedos and land cover types in areas with heterogeneous vegetation. Hence, and since local forestry maps exist for most temperate and boreal regions, we believe that the proposed method will be useful in estimating average regional land cover type albedos as well as in tracking changes in them.  相似文献   

20.
齐丹宁  胡政军  赵尚民 《测绘通报》2021,(9):98-102,107
研究采矿扰动区内植被变化规律,能够为矿区生态修复提供理论依据。本文以山西省西山煤田为研究区,通过设立对比试验区,利用MODIS/NDVI（2001-2019年）结合同期的气温、降水气候因子,分别从植被指数的时空变化及与气象因子之间的关系等方面展开对比,用于探究采矿扰动区内植被变化情况。研究结果表明：①19年来西山煤田与间接影响区及校验区的植被均呈增加趋势,但西山煤田相比于校验区NDVI均值低11.42%。②西山煤田相较于自然生态条件下植被增长率为-5.53%。③西山煤田与校验区的NDVI值均受到气温、降水两种气象因子的影响,但是与降水的相关性更高,即受降水影响更大。  相似文献   

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