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1.
Anirban Mukhopadhyay Arun Mondal Sandip Mukherjee Dipam Khatua Subhajit Ghosh Debasish Mitra Tuhin Ghosh 《Journal of Earth System Science》2014,123(6):1349-1360
In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020. 相似文献
2.
基于NDVI变化的三江源生态环境演变分区研究 总被引：2，自引：0，他引：2
在对1 km分辨率的1993年NOAA/AVHRR、2000年和2006年MODIS NDVI数据进行归一化处理的基础上,通过变化强度参量分析三江源地区NDVI的空间变化规律,结合源区内温度、降水、湖泊和湿地变化等调查资料,利用GIS空间分析技术综合研究三江源地区生态环境变化.结果表明:在1993-12000年和2000-2006年,三江源地区NDVI下降区域面积分别占源区总面积的50.73%和23.85%.三江源地区在20世纪90年代环境恶化严重,NDVI下降强烈,随着2000年8月三江源自然保护区的建立,该区环境治理取得良好效果,源区NDVI呈现稳定、轻微增加趋势,但局部地区仍存在NDVI下降趋势.综合分析温度、降水、湖泊、湿地和NDVI的变化状况表明,三江源环境变化存在显著区域特征. 相似文献
3.
As drought occurs in different climates, assessment of drought impacts on parameters such as vegetation cover is of utmost importance. Satellite remote sensing images with various spectral and spatial resolutions represent information about different land covers such as vegetation cover. Hence, the purpose of this study was to investigate the performance of satellite vegetation indices to monitor the agricultural drought on a local scale. In this regard, satellite images including Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) data were used to evaluate vegetation cover and their gradual changes effects on agricultural drought. Fars province in Iran with relatively low precipitation values was selected as the study area. Modified Perpendicular Drought Index (MPDI), MPDI1, Vegetation Condition Index (VCI), Normalized Difference Vegetation Index Anomalies (NDVIA), and Standardized Vegetation Index (SVI), were evaluated to select the remote sensing based index with the best performance in drought monitoring. The performance of such indices were investigated during 13 years (2000–2013) for MODIS and 29 years (1985–2013) for AVHRR. To assess the efficiency of the satellite indices in drought investigation, Standardized Precipitation Index (SPI) data of five selected stations were used for 3, 6, and 9 month periods on August. The results showed that NDVI-based vegetation indices had the highest correlation with SPI in cold climate and long-term timescale (6 and 9 month). The highest correlation values between remote sensing based indices and SPI were acquired, respectively, in 9-month and 6-month time-scales, with the values of 43.5% and 40%. Moreover, VCI showed the highest capability for agricultural drought investigating in different climate regions of the study area. Overall, the results proved that NDVI-based indices can be used for drought monitoring and assessment in a long-term timescale on a local time-scale.
相似文献4.
Identifying effective vegetation biophysical and spectral parameters for investigating light to moderate grazing effects on grasslands improves management practices on grasslands. Using mixed grasslands as a case study, this paper compares responses of vegetation biophysical properties and spectral parameters derived from satellite images to grazing intensity, and identifies the suitable biophysical and spectral parameters to detect grazing effects in these areas. Biophysical properties including cover, canopy height and Leaf area index (LAI) were measured in three sites with different grazing managements and one benchmark site in 2008 and 2009 in Grasslands PlaceTypeNational Park and surrounding provincial pastures, Canada. Thirteen vegetation spectral indices, calculated by statistically combining different spectral information, were evaluated. The results indicate that canopy height and the ratio of photosynthetically active vegetation cover to non-photosynthetically active vegetation cover (PV/NPV) showed significant differences between ungrazed and grazed sites. All spectral vegetation indices except the canopy index (CI) show significant differences between grazing treatments. Red-Near infrared (Red-NIR) based vegetation indices, such as Modified Triangular Vegetation Index 1 (MTVI1), Soil-adjusted Vegetation Index (SAVI), are significantly correlated to the PV/NPV. Green/Mid-infrared (Green/MIR) related vegetation indices, i.e. Plant Senescence Reflectance Index (PRSI) and Normalized Canopy Index (NCI), show significant correlation with canopy height. Models based on a linear combination of MTVI1 and SAVI were developed for PV/NPV and PRSI and NCI for canopy height. Models that simulated PV/NPV and canopy height show significant correlations with grazing intensity, suggesting the feasibility of remote sensing to quantify light to moderate grazing effects in mixed grasslands. 相似文献
5.
Wetlands play an important role in water conservation, environmental protection, and biodiversity conservation. Remote sensing is an economical and efficient technique for wetland monitoring which can limit disturbance in sensitive areas and support wetland conservation. In this paper, we used three phases of Thematic Mapper/Enhanced Thematic Mapper plus (TM/ETM+) remote sensing images from October 1989, October 1999, and October 2009 to study wetlands in Xingzi County. The images were segmented using the object-oriented remote sensing image interpretation software eCognition Developer 8.64, then segmented images were classified by slope, digital elevation model (DEM) data, Normalized Difference Vegetation Index (NDVI), Specific Leaf Area Vegetation Index (SLAVI), and Land and Water Masks (LWM) index to produce land type classification maps. Land use change information was obtained by analyzing the superposition of two classification maps of the wetland area from different years. The results showed that landscape patches in Xingzi County displayed fragmentation in their spatial distribution over time. Based on an index of changes in landscape patches, the fastest growing landscape type is grassland, while the fastest decreasing type is irrigated land. Dominant driving factors of changes in Xingzi County’s wetland landscape are population growth and policy changes. 相似文献
6.
An urban area comprises a complex mix of diverse land cover types and materials. Urban ecology and environment is significantly influenced by the proportion of impervious cover that is increasing considerably with time due to the continuous influx of people into urban areas. Therefore, it is of vital importance to determine the spatiotemporal pattern and magnitude of urbanization. In the present study, we have employed a supervised backpropagation neural network in order to extract the impervious features using five spectral indices, such as one vegetation index—Soil-Adjusted Vegetation Index (SAVI), one water index—Modified Normalized Water Index (MNDWI), and three urban indices—Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Index-Based Built-up Index (IBI). The study has been performed using Landsat Thematic Mapper data of November, 2011, of the rapidly urbanizing city of Ranchi, capital of Jharkhand state, India. Using different combinations of these spectral indices while keeping SAVI and MNDWI constant, seven composite images were built, and from each of these composites, impervious features were classified and its accuracy assessed with reference to high-resolution images provided by Microsoft Bing Imagery and adequate ground truthing. It was observed that along with SAVI and MNDWI, whenever IBI was used in any combination, it decreased the classification efficiency. On the other hand, NDBI and BUI, individually or when used together, discriminated the impervious features from the others with high accuracy with the combination of SAVI, MNDWI, and BUI achieving the highest accuracy of 90.14 %. 相似文献
7.
Vegetation is a natural source of Volatile Organic Compounds (VOC) that plays an important role in atmospheric chemistry. The main objective of the current study is to implement a model to quantify process-based VOC emissions from plants that focuses on the relationship between the sensitivity of VOC emission estimates to spatial resolution data, based on scientific knowledge and vegetation dynamics derived from satellite observations. The Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) were elected to examine this issue using different resolutions of satellite-derived products: 22m from the DEIMOS-1 satellite, and 250m and 1000m provided by MODIS. The study is focused on an area of 80×80km2 in Portugal for 2011. Detailed land cover and meteorological data are also included in the emission quantification algorithm. The primary outcomes were determined using a multi-scale analysis showing spatial and temporal variations in the vegetation parameters and modeling results. The results confirm that the emissions model is highly sensitive to the spatial resolution of the satellite-derived data, resulting in about a 30% difference in total isoprene emissions for the study area. 相似文献
8.
Ajman is a rapidly urbanizing emirate with land development succeeding at a fast pace. This study aims to monitor land use/land cover changes and assesses the impact of these changes on groundwater quality and quantity of the shallow aquifer using multitemporal remote sensing data and geographic information system (GIS). To monitor the land use/land cover changes, the Spectral Angle Mapper (SAM) and the Normalized Difference Vegetation Index (NDVI) algorithms were utilized. The obtained maps were correlated against a set of total dissolved solid (TDS); Mg, Cl, and NO3 groundwater quality index; and depth to the groundwater table maps constructed from groundwater data. The spatial analysis revealed a sharp depletion in groundwater quality and quantity related to the increase in the land use/land cover classes. The mean total TDS is from 21,971 to 26,450 mg/L and depth to groundwater level from ?12.33 to ?17.2 m over a period of 15 years. Maps of normalized difference and groundwater quality sustainability showed that the eastern side of the study area has a high value of groundwater quality sustainability and normalized difference, while the western side of the study area has a minimal value of groundwater quality sustainability and normalized difference. This study is of great assistance for decision makers and land developers to relate to municipal land allotment in rapidly developing regions such as Ajman. 相似文献
9.
内蒙古中部地区土地荒漠化遥感调查及环境质量评价 总被引：6，自引：2，他引：4
选择内蒙古中部地区作为典型荒漠化区域,根据荒漠化土地分类体系,确定决策树的结构以及各类地物在树形中的位置。基于各类地物的光谱反射特性和图像数据反映的综合特征,采取相应的识别和提取方法,以最大限度地利用遥感数据源。在研究过程中,采用从多光谱及多时相TM和ETM+遥感数据中提取出的光谱反射特性、土壤调节植被指数、土壤亮度指数以及土壤湿度指数等复合指数进行不同地物的分类和提取。结果表明:利用决策树分层提取法可以有效地排除和避免提取地物时多余信息的干扰及影响,目标明确。然后,通过图像代数检测法及目视解译法确定1990-2000年土地荒漠化的变化信息,对内蒙古中部地区的荒漠化演变规律做出分析。最后,结合研究区气候数据,在GIS支持下,通过对研究区生态环境质量变化和气候因子变化的相关性分析,表明研究区影响环境变化的主要因子是降水量与蒸发量(干燥度)。 相似文献
10.
The relationship between land surface temperature and land use/land cover in Guangzhou,China 总被引：1，自引：1，他引：0
The integration of remote sensing, geographic information system, landscape ecology and statistical analysis methods was applied
to study the urban thermal environment in Guangzhou. Normalized Difference Vegetation Index (NDVI), Normalized Difference
Build-up Index (NDBI), Normalized Difference Barren Index (NDBaI) and Modified Normalized Difference Water Index (MNDWI) were
used to analyze the relationships between land surface temperature (LST) and land use/land cover (LULC) qualitatively. The
result revealed that, most urban built-up lands were located in the middle part, and high LST areas mostly and were in the
middle and southern parts. Therefore, the urbanization and thermal environment in the middle and southern parts need to be
determined. Land surface temperature increased with the density of urban built-up and barren land, but decreased with vegetation
cover. The relationship between MNDWI and LST was found to be negative, which implied that pure water would decrease the surface
temperature and the polluted water would increase the surface temperature. A multiple regression between LST and each indices
as well as the elevation was created to elevate the urban thermal environment, which showed that NDVI, NDBI, NDBaI, MNDWI
were effective indicators for quantifying LULC impacts on LST. 相似文献
11.
文章应用EOS-MODIS数据对松嫩平原的荒漠化问题进行了研究。首先计算出标准化植被指数(NDVI)和植被覆盖指数(VCI),反演求得荒漠化指数(DI),得到荒漠化面积;采用多种方法和复杂步骤,首次获得了松嫩平原碱质荒漠化、沙质荒漠化的面积,分别为160.30×104hm2和50.56×104hm2,分别占该区面积的24.35 ％ 和7.84 ％ ;应用数字高程模型(DEM)对荒漠化的分布规律和成因进行了分析和讨论,指出松嫩平原以碱质荒漠化为主, 当前荒漠化的发展程度已处于临界状态,对区域可持续发展构成了严重威胁,亟需采取行之有效的防治措施。 相似文献
12.
Apple orchard phenology response to desiccation and temperature changes in Urmia Lake region 总被引：1，自引：1，他引：0
V. Eisavi S. Homayouni E. Rezaei-Chiyaneh 《International Journal of Environmental Science and Technology》2017,14(9):1865-1878
Agricultural production activities, such as those for various fruits and cereals, play a significant role in the local economy and food security of the Urmia Lake region. In particular, this region has thousands of hectares of apple orchards, which have an important socioeconomic impact on the life of people. Climate and land cover changes over the past several decades threaten the apple orchards phenology (AOP). Recent studies have emphasized the effect of temperature on plant phenology; however, they have overlooked the influence of land cover changes, such as Lake Desiccation, on plant phenology. Meanwhile, how climate change and Lake Desiccation will affect the AOP is still not very well understood. Therefore, in this study, we used the Enhanced Vegetation Index (EVI) extracted from remote sensing images acquired by the MODIS sensor spanning from 2003 to 2014, in order to extract the AOP events. Furthermore, we used a random forest regression (RFR) for analyzing the relationship between temperature changes/Lake Desiccation and AOP. The results revealed that EVI is a very useful tool for estimating the AOP with a mean root-mean-square error of 6.25 days. Moreover, there is a linear trend toward the early start of season in this region. The end of season (EOS) and the growing season length have also increased in the areas closer to the lake until 2008. This seems that the delayed EOS in the area closest to Urmia Lake has been associated with the lake microclimate since 2008. 相似文献
13.
2001-2018年石羊河流域植被变化及其对流域管理的启示 总被引：1，自引：0，他引：1
植被是流域生态系统的重要指标,植被景观管理也是流域综合管理的重要内容。综合利用长时间序列MODIS反射率和归一化差值植被指数（NDVI）产品及Landsat卫星遥感影像,基于谷歌地球引擎（GEE）平台,利用计算机自动分类的方法,监测了2001-2018年间石羊河流域的植被（包括灌溉土地）的逐年变化,结合降水、径流量和地下水位地面监测数据,分析了全流域植被指数、植被面积、灌溉土地范围的变化特征及其与水循环之间的互馈关系。研究发现,2001-2018年间,石羊河流域的植被面积以每年约135 km2的速率增加,其中,自然植被和灌溉土地分别以每年60.5 km2和74.6 km2的速率增加。除了金昌区的植被增加以灌溉土地为主外,其他区域都以自然植被的增加为主。特别是民勤地区,由于十多年的持续调水和有效退耕,地下水位近年来开始抬升,自然植被开始恢复。但与此同时,中游凉州区和永昌县的生态风险加大。未来可从灌溉规模控制、地表与地下水统一调度、景观分级和配置技术发展、优化产业结构、强化与流域外的连通性等方面加强流域综合管理,提高流域社会系统弹性,增强可持续发展能力。 相似文献
14.
As the characterization of primary productivity of wetland ecosystem, the Normalized Difference Vegetation Index (NDVI) plays an important role in local ecosystem conservation for environmental management. In this paper, the correlations of NDVI and hydro-meteorological variables were studied in a water scarce area with emphasis on different land use types, namely water, wetland, residential land and farmland, during the growing seasons of 1999 and 2000. The significant NDVI changes were detected between spring and summer for all land use types. The correlation analysis revealed that the NDVI-temperature correlation (P?P?P?farmland > Rwetland > Rresidential land > Rwater for NDVI and precipitation correlations (P?water > Rwetland > Rresidential land > Rfarmland for NDVI and temperature correlations (P?相似文献
15.
The Hanjiang River Basin is the source area of the Middle Route Project of the South-to-North Water Diversion Project, and the vegetation coverage in this basin directly affects the quality of the ecological environment. This study is based on long time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data synthesized over 16 days from 2000 to 2016 in the Hanjiang River Basin. Major climatic data (temperature and rainfall) and topographic data (elevation, slope, and aspect) are employed to analyze the driving forces of NDVI changes. The results demonstrate the following: for the 2000–2016 period, the average annual NDVI is 0.823, with a change trend of 0.025 year?1. The overall NDVI upstream is higher than that downstream. The average annual value of NDVI upstream is 0.844, with a change trend of 0.036 year?1, and that of downstream is 0.799, with a change trend of 0.022 year?1. The spatial distribution of NDVI was significantly increased in the area around the upstream section of the river and near the Danjiangkou Reservoir, and the distribution of NDVI around the central city was significantly reduced. The NDVI was positively correlated with temperature and rainfall, and the impacts differed among different regions. At elevations below 2000 m, the NDVI shows an increasing trend with increasing elevation, and at elevations exceeding 2000 m, the NDVI is negatively correlated with elevation. Slope is positively correlated with the NDVI. The influence of aspect on the NDVI was small. 相似文献
16.
基于时间序列建模的城市热岛时间尺度成分分离方法与应用 总被引：1，自引：0，他引：1
城市热岛效应是全球与区域气候变化研究中的焦点问题。基于2001—2012年较长时间序列的北京市MODIS地表温度产品及相关NDVI和反射率产品,给出地表温度时间序列构建方法。基于站点气象观测资料进行的精度验证表明地表温度时间序列构建方法可行,并最终给出城市热岛强度的量化方案。研究选取统计学中X-11-ARIMA时间序列建模方法,分离并分析城市热岛强度时间序列的结构性成分。分析发现,以平均城乡温差为指标的北京城市热岛强度季节性特征明显,与城乡土地利用状况、季节性地表覆盖、地物热特性以及气候因子等联系密切。趋势—循环特征与城市扩张速度及入选城市区域面积相关。以已发生城市热岛区域城乡平均温差为指标的北京城市热岛强度趋势—循环特性在12年间表现平稳。时间序列建模分析提取出不规则变动成分,为定量研究偶然因素对城市热岛的影响提供了可能。 相似文献
17.
From early November 2008 to February 2009, lack of rainfall led to severe drought in northern China. More than 9.3 million ha of wheat in six major crop production provinces, including Henan, Anhui, Shandong, Shanxi, Gansu, and Shaanxi, were hit by drought. Supported by Chinese HJ-1 satellite images together with NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data, dynamic monitoring of the drought was conducted. HJ-1 CCD data with 30-m resolution were used to identify cropland information. Spatial–temporal variation of drought was detected using Vegetation Index and Water Index time series data derived from MODIS visible, infrared, and short-wave infrared bands. The influences of drought were classified into five levels based on MODIS-derived 8-day composite Anomaly Water Index (AWI) and field survey data. The results indicated that the drought deteriorated beginning in November 2008 and became most serious in late January 2009. HJ-1 data together with MODIS data proved to be valuable data sources for monitoring soil moisture and drought at a both regional and national scale. 相似文献
18.
《地学前缘(英文版)》2022,13(2):101312
Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha?1 year?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion. 相似文献
19.
Based on GIMMS NDVI data of Qilian Mountains region during 1982-2006, using the maximum synthesis, mean method, slope analysis and correlation analysis, the spatial and temporal changes of vegetation cover and its correlations with climatic factors were studied in Qilian Mountains. The results showed that: ①Vegetation NDVI of Qilian Mountains increases from west to east in general, showing the distribution pattern of much more vegetation in east regions than in west regions; ②Vegetation NDVI of Qilian Mountains has generally increased in the past twenty five years, but there are obvious spatial differences, especially vegetation NDVI of middle and east regions increase obviously; ③There have been obvious differences on spatial variation of seasonal NDVI in the past twenty five years in Qilian Mountains, and the increased area of vegetation NDVI is the largest in summer, followed by autumn, spring, but the most reduced area of vegetation NDVI is in winter. The regions of increased vegetation NDVI concentrate on southern mountain of Qinghai Province and in Buha River Basin, while the regions of reduced vegetation NDVI concentrate on Wushaoling, Lenglongling and Daban mountain in each season; ④The correlations between monthly average vegetation NDVI and temperature and precipitation are very significant, which indicates that temperature and precipitation are the main factors affecting the change of vegetation NDVI in Qilian Mountains, but intensive human activities are also important factors affecting the change of vegetation NDVI in some areas. 相似文献