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1.
Assessing changes in the above ground biomass and carbon stocks of Lidder valley,Kashmir Himalaya,India 总被引：1，自引：0，他引：1
The changes in the land use and land cover (LULC), above ground biomass (AGB) and the associated above ground carbon (AGC) stocks were assessed in Lidder Valley, Kashmir Himalaya using satellite data (1980–2013), allometric equations and phytosociological data. Change detection analysis of LULC, comprising of eight vegetation and five non-vegetation types, indicated that 6% (74.5 km2) of the dense evergreen forest has degraded. Degraded forest and settlement increased by 20 and 52.8 km2, respectively. Normalized difference vegetation index was assessed and correlated with the field-based biomass estimates to arrive at best-fit models for remotely sensed AGB estimates for 2005 and 2013. Total loss of 1.018 Megatons of AGB and 0.5 Megatons of AGC was estimated from the area during 33-year period which would have an adverse effect on the carbon sequestration potential of the area which is already facing the brunt of climate change. 相似文献
2.
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
3.
Global warming associated with climate change is one of the greatest challenges of today’s world. Increasing emissions of the greenhouse gas CO2 are considered as a major contributing factor to global warming. One regulating factor of CO2 exchange between atmosphere and land surface is vegetation. Measurements of land cover changes in combination with modelling the Gross Primary Productivity (GPP) can contribute to determine important sources and sinks of CO2.The aim of this study is to accurately model the GPP for a region in West Africa with a spatial resolution of 250 m, and the differentiation of GPP based on woody and herbaceous vegetation. For this purpose, the Regional Biomass Model (RBM) was applied, which is based on a Light Use Efficiency (LUE) approach. The focus was on the spatial enhancement of the RBM from the original 1000–250 m spatial resolution (RBM+). The adaptation to the 250 m scale included the modification of two main input parameters: (1) the fraction of absorbed Photosynthetically Active Radiation (FPAR) based on the 1000 m MODIS MOD15A2 FPAR product which was downscaled to 250 m using MODIS NDVI time series; (2) the fractional cover of woody and herbaceous vegetation, which was improved by using a multi-scale approach. For validation and regional adjustments of GPP and the input parameters, in situ data from a climate station and eddy covariance measurements were integrated.The results of this approach show that the input parameters could be improved significantly: downscaling considerably reduces data gaps of the original FPAR product and the improved dataset differed less than 5.0% from the original data for cloud free regions. The RMSE of the fractional vegetation cover varied between 5.1 and 12.7%. Modelled GPP showed a slight overestimation in comparison to eddy covariance measurements. The in situ data was exceeded by 8.8% for 2005 and by 2.0% for 2006. The model results were converted to NPP and also agreed well with previous NPP measurements reported from different studies. Altogether a high accuracy and suitability of the regionally adjusted and downscaled model RBM+ can be concluded. The differentiation between vegetation growth forms allows a separation of long-term and short-term carbon storage based on woody and herbaceous vegetation, respectively. 相似文献
4.
In this study, we explored the capacity of vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products to characterize global savannas in Australia, Africa and South America. The savannas were spatially defined and subdivided using the World Wildlife Fund (WWF) global ecoregions and MODIS land cover classes. Average annual profiles of Normalized Difference Vegetation Index, shortwave infrared ratio (SWIR32), White Sky Albedo (WSA) and the Structural Scattering Index (SSI) were created. Metrics derived from average annual profiles of vegetation indices were used to classify savanna ecoregions. The response spaces between vegetation indices were used to examine the potential to derive structural and fractional cover measures. The ecoregions showed distinct temporal profiles and formed groups with similar structural properties, including higher levels of woody vegetation, similar forest–savanna mixtures and similar grassland predominance. The potential benefits from the use of combinations of indices to characterize savannas are discussed. 相似文献
5.
《地理信息系统科学与遥感》2013,50(3):371-393
This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982-2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northeast Asia. In combination with climate zones, NDVI changes that are influenced by climate factors and land cover changes were also evaluated. This study revealed that the vegetation cover in the arid, western regions of northeast Asia is strongly influenced by precipitation, and with increasing precipitation, NDVI values become less influenced by precipitation. Spatial changes in the NDVI as influenced by temperature in this region are less obvious. Land cover dynamics also influence NDVI changes in different climate zones, especially for bare ground, cropland, and grassland. Future research should also incorporate higher-spatial-resolution data as well as other data types (such as greenhouse gas data) to further evaluate the mechanisms through which these factors interact. 相似文献
6.
Cenk Donmez Suha Berberoglu Paul J. Curran 《International Journal of Applied Earth Observation and Geoinformation》2011
The aim of this study is to use full spatial resolution Envisat MERIS data to drive an ecosystem productivity model for pine forests along the Mediterranean coast of Turkey. The Carnegie, Ames, Stanford Approach (CASA) terrestrial biogeochemical model, designed to simulate the terrestrial carbon cycle using satellite sensor and meteorological data, was used to estimate annual regional fluxes in terrestrial net primary productivity (NPP). At its core this model is based on light-use efficiency, influenced by temperature, rainfall and solar radiation. Present climate data was generated from 50 climate stations within the watershed using co-kriging. Regional scale pseudo-warming data for year 2070 were derived using a Regional Climate Model (RCM) these data were used to downscale the GCM General Circulation Model for the research area as part of an international research project called Impact of Climate Changes on Agricultural Production Systems in Arid Areas (ICCAP). Outputs of climate data can be moderated using the four variables of percent tree cover, land cover, soil texture and NDVI. This study employed 47 MERIS images recorded between March 2003 and September 2005 to derive percent tree cover, land cover and NDVI. Envisat MERIS data hold great potential for estimating NPP with the CASA model because of the appropriateness of both its spatial and its spectral resolution. 相似文献
7.
Baozhang Chen Guang Xu Nicholas C. Coops Philippe Ciais Ranga B. Myneni 《International Journal of Digital Earth》2016,9(11):1055-1076
The Asia-Pacific (AP) region has experienced faster warming than the global average in recent decades and has experienced more climate extremes, however little is known about the response of vegetation growth to these changes. The updated Global Inventory Modeling and Mapping Studies third-generation global satellite Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index dataset and gridded reanalysis climate data were used to investigate the spatiotemporal changes in both trends of vegetation dynamic indicators and climatic variables. We then further analyzed their relations associated with land cover across the AP region. The main findings are threefold: (1) at continental scales the AP region overall experienced a gradual and significant increasing trend in vegetation growth during the last three decades, and this NDVI trend corresponded with an insignificant increasing trend in temperature; (2) vegetation growth was negatively and significantly correlated with the Pacific Decadal Oscillation index and the El Niño/Southern Oscillation (ENSO) in AP; and (3) at pixel scales, except for Australia, both vegetation growth and air temperature significantly increased in the majority of study regions and vegetation growth spatially correlated with temperature; In Australia and other water-limited regions vegetation growth positively correlated with precipitation. 相似文献
8.
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
9.
Carlos Muñoz-Robles Paul FrazierMatthew Tighe Nick ReidSue V. Briggs Brian Wilson 《International Journal of Applied Earth Observation and Geoinformation》2012,14(1):94-102
The amount and distribution of vegetation and ground cover are important factors that influence resource transfer (e.g. runoff, sediment) in patterned semi-arid landscapes. Identifying and describing these features in detail is an essential part of measuring and understanding ecohydrological processes at hillslope scales that can then be applied at broader scales. The aim of this study was to develop a comprehensive methodology to map ground cover using high resolution Quickbird imagery in woody and non-woody (pasture) vegetation. The specific goals were to: (1) investigate the use of several techniques of image fusion, namely principal components analysis (PCA), Brovey transform, modified intensity-hue-saturation (MIHS) and wavelet transform to increase the spatial detail of multispectral Quickbird data; (2) evaluate the performance of the red and near-infra-red bands (NIR), the difference vegetation index (DVI), and the normalised difference vegetation index (NDVI) in estimating ground cover, and (3) map and assess spatial and temporal changes in ground cover at hillslope scale using the most appropriate method or combination of methods. Estimates of ground cover from the imagery were compared with a subset of observed ground cover estimates to determine map accuracy. The MIHS algorithm produced images that best preserved spectral and spatial integrity, while the red band fused with the panchromatic band produced the most accurate ground cover maps. The patch size of the ground cover beneath canopies was similar to canopy size, and percent ground cover (mainly litter) increased with canopy size. Ground cover was mapped with relative accuracies of 84% in the woody vegetation and 86% in the pasture. From 2008 to 2009, ground cover increased from 55% to 65% in the woody vegetation and from 40% to 45% in the pasture. These ground cover maps can be used to explore the spatial ecohydrological interactions between areas of different ground cover at hillslope scale with application to management at broader scales. 相似文献
10.
Mengmeng Wang Natarajan Ishwaran Tianhua Hong Andy Bell Zhaoming Zhang 《International Journal of Digital Earth》2020,13(3):393-409
ABSTRACTEast Rennell of Solomon Island is the first natural site under customary law to be inscribed on UNESCO’s World Heritage List. Potential threats due to logging, mining and agriculture led to the site being declared a World Heritage in Danger in 2013. For East Rennell World Heritage Site (ERWHS) to ‘shed’ its ‘Danger’ status the management must monitor forest cover both within and outside of ERWHS. We used satellite data from multiple sources to track forest cover changes for the entire East Rennell island since 1998. 95% of the island is still covered by undisturbed forests; annual average normalized difference vegetation index (NDVI) for the whole island was above 0.91 in 2015. However, vegetation cover in the island has been slowly decreasing, at a rate of –0.0011 NDVI per year between 2000 and 2015. This decrease less pronounced inside ERWHS compared to areas outside. While potential threats due to forest clearing outside ERWHS remain the forest cover change from 2000 to 2015 has been below 15%. We suggest ways in which the Government of Solomon Islands could use our data as well as unmanned air vehicles and field surveys to monitor forest cover change and ensure the future conservation of ERWHS. 相似文献
11.
Urbanization is a natural and social process involving simultaneous changes to the Earth’s land systems, energy flow, demographics, and the economy. Understanding the spatiotemporal pattern of urbanization is increasingly important for policy formulation, decision making, and natural resource management. A combination of satellite remote sensing and patch-based models has been widely adopted to characterize landscape changes at various spatial and temporal scales. Nevertheless, the validity of this type of framework in identifying long-term changes, especially subtle or gradual land modifications is seriously challenged. In this paper, we integrate annual image time series, continuous spatial indices, and non-parametric trend analysis into a spatiotemporal study of landscape dynamics over the Phoenix metropolitan area from 1991 to 2010. We harness local indicators of spatial dependence and modified Mann-Kendall test to describe the monotonic trends in the quantity and spatial arrangement of two important land use land cover types: vegetation and built-up areas. Results suggest that declines in vegetation and increases in built-up areas are the two prevalent types of changes across the region. Vegetation increases mostly occur at the outskirts where new residential areas are developed from natural desert. A sizable proportion of vegetation declines and built-up increases are seen in the central and southeast part. Extensive land conversion from agricultural fields into urban land use is one important driver of vegetation declines. The xeriscaping practice also contributes to part of vegetation loss and an increasingly heterogeneous landscape. The quantitative framework proposed in this study provides a pathway to effective landscape mapping and change monitoring from a spatial statistical perspective. 相似文献
12.
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial–temporal variability is a challenging task.We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain.The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes. 相似文献
13.
Resolution vs. image quality in pre-tsunami imagery used for tsunami impact models in Aceh,Indonesia
Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Aceh, Indonesia. Previously, a Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30 m) images as well as a combination of 2003 and 2004 higher spatial resolution SPOT (10 m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualties and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using the new LCRs did not perform better than the original one. Particularly casualties models using 2002 LCRs performed better (δAIC > 2) than the more recent Landsat and SPOT counterparts. Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations). Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited. 相似文献
14.
Biomass burning from vegetation fires is an important source of greenhouse gas emissions. In this study, we quantify biomass burning emissions from grasslands from the highly sensitive Kaziranga National Park, Assam, Northeast India. Most of the fires in the park are ‘controlled burning fires’ set by the park officials for management purposes. We evaluated the short-term impacts of fires and the resulting air pollution through integrating biomass burnt information from satellite remote sensing datasets. IRS-P6 Advanced Wide Field Sensor (AWiFS) data during March and April corresponding to dry season were evaluated to delineate the burnt areas. These burnt area estimates were then integrated with biomass data and emission factors for quantifying the greenhouse gas emissions. Results suggested that of the total study area of 37,822 ha, nearly 3163.282 ha has been burnt during March, 2005. Within one month, the burnt area increased to 7443.92 ha by April, i.e., from 8.36% to 19.68%. In total, biomass burning from the grasslands contributed to 29.65 Tg CO2, 1.19 Tg CO, 0.071 Tg NOx, 0.042 Tg CH4, 0.0625 Tg total non-methane hydrocarbons, 0.152 Tg of particulate matter, and 0.062 Tg of organic carbon and 0.008 Tg of black carbon during April. The importance of ‘fire’ as a management tool for maintaining the wildlife habitat has been highlighted in addition to some of the adverse affects of air pollution resulting from such management practices. The results from this study will be useful to forest officials as well as policy makers to undertake some sustainable forest management practices to maintain an ideal habitat for Kaziranga's wildlife. 相似文献
15.
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
16.
我国森林植被遥感调查及建库研究 总被引：1，自引：0，他引：1
我国森林植被的覆盖程度受到土壤、气候、海拔、人为等各种因素的互相影响,为了能够遵循＂适地适树＂原则而更加精确在不同地区栽种适宜的树种从而提高我国森林覆被率,利用遥感技术对全国森林植被及其所生长的条件进行调查是重中之重。本文以全国范围为研究区域,利用MODIS数据对土壤、植被及气候数据进行提取,引入梯形网格,对全国进行等经纬度的网格划分,利用ArcGIS,ENVI等软件绘出我国土壤类型、N、P元素及有机质含量、年降雨量、年最高温度及最低温度的温度等值线,再利用数据挖掘技术提取与森林植被覆盖率相关的影响因子得出我国现阶段森林植被覆盖图,计算出我国现有林地面积并对影响森林植被覆盖的因子进行数据库的录入。 相似文献
17.
Monitoring changes in land use intensity of grazing systems in the Amazon is an important prerequisite to study the complex political and socio-economic forces driving Amazonian deforestation. Remote sensing offers the potential to map pasture vegetation over large areas, but mapping pasture conditions consistently through time is not a trivial task because of seasonal changes associated with phenology and data gaps from clouds and cloud shadows. In this study, we tested spectral-temporal metrics derived from intra-annual Landsat time series to distinguish between grass-dominated and woody pastures. The abundance of woody vegetation on pastures is an indicator for management intensity, since the duration and intensity of land use steer secondary succession rates, apart from climate and soil conditions. We used the developed Landsat-based metrics to analyze pasture intensity trajectories between 1985 and 2012 in Novo Progresso, Brazil, finding that woody vegetation cover generally decreased after four to ten years of grazing activity. Pastures established in the 80s and early 90s showed a higher fraction of woody vegetation during their initial land use history than pastures established in the early 2000s. Historic intensity trajectories suggested a trend towards more intensive land use in the last decade, which aligns well with regional environmental policies and market dynamics. This study demonstrates the potential of dense Landsat time series to monitor land-use intensification on Amazonian pastures. 相似文献
18.
Seasonal global mean sea level change from satellite altimeter, GRACE, and geophysical models 总被引：2，自引：1，他引：2
J. L. Chen C. R. Wilson B. D. Tapley J. S. Famiglietti Matt Rodell 《Journal of Geodesy》2005,79(9):532-539
We estimate seasonal global mean sea level changes using different data resources, including sea level anomalies from satellite
radar altimetry, ocean temperature and salinity from the World Ocean Atlas 2001, time-variable gravity observations from the
Gravity Recovery and Climate Experiment (GRACE) mission, and terrestrial water storage and atmospheric water vapor changes
from the NASA global land data assimilation system and National Centers for Environmental Prediction reanalysis atmospheric
model. The results from all estimates are consistent in amplitude and phase at the annual period, in some cases with remarkably
good agreement. The results provide a good measure of average annual variation of water stored within atmospheric, land, and
ocean reservoirs. We examine how varied treatments of degree-2 and degree-1 spherical harmonics from GRACE, laser ranging,
and Earth rotation variations affect GRACE mean sea level change estimates. We also show that correcting the standard equilibrium
ocean pole tide correction for mass conservation is needed when using satellite altimeter data in global mean sea level studies.
These encouraging results indicate that is reasonable to consider estimating longer-term time series of water storage in these
reservoirs, as a way of tracking climate change. 相似文献
19.
Christopher Potter Peggy Gross Vanessa Genovese Marie-Louise Smith 《Carbon balance and management》2007,2(1):1-11