共查询到20条相似文献，搜索用时 687 毫秒
1.
Zhiqiang Gao Wei Gao Ni-Bin Chang 《International Journal of Applied Earth Observation and Geoinformation》2011
This paper presents a new drought assessment method by spatially and temporally integrating temperature vegetation dryness index (TVDI) with regional water stress index (RWSI) based on a synergistic approach. With the aid of LANDSAT TM/ETM data, we were able to retrieve the land-use and land-cover (LULC), vegetation indices (VIs), and land surface temperature (LST), leading to the derivation of three types of modified TVDI, including TVDI_SAVI, TVDI_ANDVI and TVDI_MSAVI, for drought assessment in a fast growing coastal area, Northern China. The categorical classification of four drought impact levels associated with the RWSI values enables us to refine the spatiotemporal relationship between the LST and the VIs. Holistic drought impact assessment between 1987 and 2000 was carried out by linking RWSI with TVDIs group wise. Research findings indicate that: (1) LST and VIs were negatively correlated in most cases of low, medium, and high vegetation cover except the case of high density vegetation cover in 2000 due to the effect of urban heat island (UHI) effect; (2) the shortage of water in 1987 was more salient than that that in 2000 based on all indices of TVDI and RWSI; and (3) TVDIs are more suitable for monitoring mild drought, normal and wet conditions when RWSI is smaller than 0.752; but they are not suitable for monitoring moderate and severe drought conditions. 相似文献
2.
Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area. 相似文献
3.
基于指数分析法的西安市土地利用变化及驱动力研究 总被引：1，自引：0，他引：1
基于2000和2007年2期TM遥感影像,利用指数分析法,分别提取出归一化差异建筑指数(NDBI)、修正归一化差异水体指数(MNDWI)和归一化差异植被指数(NDVI)3种指数模型,分别代表西安市的3种最主要的土地利用类型--建筑用地、水体和植被.采用神经网络分类器进行监督分类,借助ERDAS Imagine 9.0、ENVI、ArcGIS 9.2和Matlab等软件平台,计算出西安市土地利用类型的动态转移矩阵,构建了土地利用变化动态度指数模型,定量分析西安市土地利用的时空变化.依据研究区土地利用变化的结果分析,变化的驱动力因子主要是人口增长、经济增长和政策变动. 相似文献
4.
Gohar Ghazaryan Olena Dubovyk Valerie Graw Nataliia Kussul Jürgen Schellberg 《地理信息系统科学与遥感》2020,57(5):704-718
ABSTRACT Globally, drought constitutes a serious threat to food and water security. The complexity and multivariate nature of drought challenges its assessment, especially at local scales. The study aimed to assess spatiotemporal patterns of crop condition and drought impact at the spatial scale of field management units with a combined use of time-series from optical (Landsat, MODIS, Sentinel-2) and Synthetic Aperture Radar (SAR) (Sentinel 1) data. Several indicators were derived such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Land Surface Temperature (LST), Tasseled cap indices and Sentinel-1 based backscattering intensity and relative surface moisture. We used logistic regression to evaluate the drought-induced variability of remotely sensed parameters estimated for different phases of crop growth. The parameters with the highest prediction rate were further used to estimate thresholds for drought/non-drought classification. The models were evaluated using the area under the receiver operating characteristic curve and validated with in-situ data. The results revealed that not all remotely sensed variables respond in the same manner to drought conditions. Growing season maximum NDVI and NDMI (70–75%) and SAR derived metrics (60%) reflect specifically the impact of agricultural drought. These metrics also depict stress affected areas with a larger spatial extent. LST was a useful indicator of crop condition especially for maize and sunflower with prediction rates of 86% and 71%, respectively. The developed approach can be further used to assess crop condition and to support decision-making in areas which are more susceptible and vulnerable to drought. 相似文献
5.
Monitoring agricultural drought effectively and timely is important to support drought management and food security. Effective drought monitoring requires a suite of drought indices to capture the evolution process of drought. Thermal infrared signals respond rapidly to vegetation water stress, thus being regarded useful for drought monitoring at the early stage. Several temperature-based drought indices have been developed considering the role of land surface temperature (LST) in surface energy and water balance. Here, we compared the recently proposed Temperature Rise Index (TRI) with several agricultural drought indices that also use thermal infrared observations, including Temperature Condition Index (TCI), Vegetation Health Index (VHI) and satellite-derived evapotranspiration ratio anomaly (ΔfRET) for a better understanding of these thermal infrared drought indices. To do so, we developed a new method for calculating TRI directly from the top-of-atmosphere brightness temperatures in the two split-window channels (centered around ∼11 and 12 μm) rather than from LST. TRI calculated using the Himawari-8 brightness temperatures (TRI_BT) and LST retrievals (TRI_LST), along with the other LST-based indices, were calculated for the growing season (July–October) of 2015−2019 over the Australian wheatbelt. An evaluation was conducted by spatiotemporally comparing the indices with the drought indices used by the Australian Bureau of Meteorology in the official drought reports: the Precipitation Condition Index (PCI) and the Soil Moisture Condition Index (SMCI). All the LST-based drought indices captured the wet conditions in 2016 and dry conditions in 2019 clearly. Ranking of Pearson correlations of the LST-based indices with regards to PCI and SMCI produced very similar results. TRI_BT and TRI_LST showed the best agreement with PCI and SMCI (r > 0.4). TCI and VHI presented lower consistency with PCI and SMCI compared with TRI_BT and TRI_LST. ΔfRET had weaker correlations than the other LST-based indices in this case study, possibly because of outliers affecting the scaling procedure. The capability of drought early warning for TRI was demonstrated by comparing with the monthly time series of the greenness index Vegetation Condition Index (VCI) in a case study of 2018 considering the relatively slow response of the greenness index to drought. TRI_BT and TRI_LST had a lead of one month in showing the changing dryness conditions compared with VCI. In addition, the LST-based indices were correlated with annual wheat yield. Compared to wheat yields, all LST-based indices had a peak correlation in September. TRI_BT and TRI_LST had strong peak and average correlations with wheat yield (r ≥ 0.8). We conclude that TRI has promise for agricultural drought early warning, and TRI_BT appears to be a good candidate for efficient operational drought early warning given the readily accessible inputs and simple calculation approach. 相似文献
6.
Weixin Xu Song Gu XinQuan Zhao Jianshe Xiao Yanhong Tang Jingyun Fang Juan Zhang Sha Jiang 《International Journal of Applied Earth Observation and Geoinformation》2011
Using satellite-observed Normalized Difference Vegetation Index (NDVI) data and Rotated Empirical Orthogonal Function (REOF) method, we analyzed the spatio-temporal variation of vegetation during growing seasons from May to September in the Three-River Source Region, alpine meadow in the Qinghai-Tibetan Plateau from 1982 to 2006. We found that NDVI in the centre and east of the region, where the vegetation cover is low, showed a consistent but slight increase before 2003 and remarkable increase in 2004 and 2005. Impact factors analysis indicted that among air temperature, precipitation, humid index, soil surface temperature, and soil temperature at 10 cm and 20 cm depth, annual variation of NDVI was highly positive correlated with the soil surface temperature of the period from March to July. Further analysis revealed that the correlation between the vegetation and temperature was insignificant before 1995, but statistically significant from 1995. The study indicates that temperature is the major controlling factor of vegetation change in the Three-River Source Region, and the currently increase of temperature may increase vegetation coverage and/or density in the area. In addition, ecological restoration project started from 2005 in Three-River Source Region has a certain role in promoting the recovery of vegetation. 相似文献
7.
Youshui Zhang Inakwu O.A. Odeh Chunfeng Han 《International Journal of Applied Earth Observation and Geoinformation》2009
As more than 50% of the human population are situated in cities of the world, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect has been linked to the regional climate, environment, and socio-economic development. In this study, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery, respectively acquired in 1989 and 2001, were utilized to assess urban area thermal characteristics in Fuzhou, the capital city of Fujian province in south-eastern China. As a key indicator for the assessment of urban environments, sub-pixel impervious surface area (ISA) was mapped to quantitatively determine urban land-use extents and urban surface thermal patterns. In order to accurately estimate urban surface types, high-resolution imagery was utilized to generate the proportion of impervious surface areas. Urban thermal characteristics was further analysed by investigating the relationships between the land surface temperature (LST), percent impervious surface area, and two indices, the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results show that correlations between NDVI and LST are rather weak, but there is a strong positive correlation between percent ISA, NDBI and LST. This suggests that percent ISA, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated land-use/land-cover (LULC) conditions. 相似文献
8.
微波植被指数在干旱监测中的应用 总被引：3，自引：0，他引：3
在植被覆盖区域,归一化植被指数(NDVI)被广泛地应用于干旱遥感监测。和基于光学遥感的植被指数相比,Shi等提出的微波植被指数MVI(Microwave Vegetation Index)被证实能够反映更多的植被生长信息。本文以MVI为基础,利用MVI代替目前比较成熟的温度植被指数TVDI(Temperature Vegetation Index)中的NDVI,构建温度微波植被干旱指数TMVDI(Temperature Microwave Vegetation Index),发展了一种新的干旱监测方法。本文以2006年夏季四川省发生的百年难遇的干旱为研究对象,将基于TMVDI与TVDI的干旱监测结果进行了对比分析。最后,为评估监测结果的准确性,将遥感监测的结果与基于气象站点降雨观测数据构建的标准降雨指数SPI(Standardized Precipitation Index)的计算结果进行了对比分析。结果表明,利用低频降轨微波辐射计数据计算的T MVDI最适合于进行植被覆盖区域的干旱监测。 相似文献
9.
Dušan Jovanović Miro Govedarica Filip Sabo Dubravka Sladić Aleksandar Ristić 《国际地球制图》2015,30(5):483-505
Main objective of this study was to establish a relationship between land cover and land surface temperature (LST) in urban and rural areas. The research was conducted using Landsat, WorldView-2 (WV-2) and Digital Mapping Camera. Normalised difference vegetation index and normalised difference built-up index were used for establishing the relation between built-up area, vegetation cover and LST for spatial resolution of 30 m. Impervious surface and vegetation area generated from Digital Mapping Camera from Intergraph and WV-2 were used to establish the relation between built-up area, vegetation cover and LST for spatial resolutions of 0.1, 0.5 and 30 m. Linear regression models were used to determine the relationship between LST and indicators. Main contribution of this research is to establish the use of combining remote sensing sensors with different spectral and spatial resolution for two typical settlements in Vojvodina. Correlation coefficients between LST and LST indicators ranged from 0.602 to 0.768. 相似文献
10.
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
11.
基于NDVI序列影像精化结果的植被覆盖变化研究 总被引：5，自引：0，他引：5
植被归一化指数(NDVI)是地表植被覆盖特征的重要指标之一。本文以三峡库区2001-2003年MODIS遥感数据反演的NDVI时间序列影像为例,研究NDVI影像序列的精化问题,包括降云及去噪处理的有效方法。在改进的BISE技术降云处理的基础上,采用小波软阈值降噪方法提取有效变化趋势。然后进行库区2001-2003年植被变化的变化矢量分析,采用阈值分割的方法将库区变化强度影像分为未变化、小变化、中等变化与剧烈变化四个类型。研究成果可为三峡库区宏观生态环境变化的掌握提供一定的依据。 相似文献
12.
Land cover changes associated with urbanisation modify microclimate, leading to urban heat islands, whereby cities are warmer than the surrounding countryside. Understanding the factors causing this phenomenon could help urban areas adapt to climate change and improve living conditions of inhabitants. In this study, land surface temperatures (LST) of Aarhus, a city in the high latitudes, are estimated from the reflectance of a thermal band (TIRS1; Band 10; 10.60–11.19 μm) of Landsat 8 on five dates in the summer months (one in 2015, and four in 2018). Spectral indices, modelled on the normalised difference vegetation index (NDVI), using all combinations of the first seven bands of Landsat 8 are calculated and their relationships with LST, analysed. Land cover characteristics, in terms of the percentages of tree cover, building cover and overall vegetation cover are estimated from airborne LiDAR data, building footprints and 4-band aerial imagery, respectively. The correlations between LST, the spectral indices and land cover are estimated.The difference in mean temperature between the rural and urban parts of Aarhus is up to 3.96 °C, while the difference between the warmer and colder zones (based on the mean and SD of LST) is up to 13.26 °C. The spectral index using the near infrared band (NIR; Band 5; 0.85-0.88 μm) and a short-wave infrared band (SWIR2; Band 7; 2.11–2.29 μm) has the strongest correlations (r: 0.62 to 0.89) with LST for the whole study area. This index is the inverse of normalised burn ratio (NBR), which has been used for mapping burnt areas. Spectral indices using different combinations of the infrared bands have stronger correlations with LST than the more widely used vegetation indices such as NDVI. The percentage of tree cover has a higher negative correlation (Pearson’s r: -0.68 to -0.75) with LST than overall vegetation cover (r: -0.45 to -0.63). Tree cover and building cover (r: 0.53 to 0.71) together explain up to 68 % of the variation in LST. Modification of tree and building cover may therefore have the potential to regulate urban LST. 相似文献
13.
Dheera Kalota 《国际地球制图》2017,32(10):1105-1119
In the present study, relationship between Land surface temperature and selected indices, vegetation index (VARI), built-up index (BUI) and elevation (DEM) is investigated. Ordinary least square method and geographically weighted regression are used to analyse the spatial correlation between the indices with surface temperature. Subsequently, temporal trends (2001–2015) in surface temperature and vegetation are explored after every two years of interval. LANDSAT image and ASTER DEM are used to extract LST and additional indices. The selected variables (Built-up, vegetation and topography) explain 69% of the variation in surface temperature. The OLS and GWR revealed that topography and vegetation are the significant factor of LST in Manipur State. Topography being a constant parameter, its effect is constant over time. The changing scenario of vegetation is significantly contributing to LST. The surface temperature over a period of 15 years show increasing trend and is negatively and strongly correlated to vegetation cover. 相似文献
14.
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
15.
Mehdi Hosseini Mohammad Reza Saradjian 《Journal of the Indian Society of Remote Sensing》2014,42(4):719-726
High difference between dielectric constant of water (dielectric constant about 80) and dielectric constant of dried soil (dielectric constant about 2–3) makes Synthetic Aperture Radar (SAR) highly capable in soil moisture estimation. However, there are other factors which affect on radar backscattering coefficient. The most important parameters are vegetation cover, surface roughness and sensor parameters (frequency, polarization and incidence angle). In this paper, the importance of considering the effects of these parameters on SAR backscatter coefficients is shown by comparing different soil moisture estimation models. Moreover, an experimental soil moisture estimation model is developed. It is shown that this model can be used to estimate soil moisture under a variety of vegetation cover densities. The new developed model is based on combination of different indices derived from Landsat5-Thematic Mapper and AIRSAR images. The AIRSAR image is used for extraction of backscattering coefficient and incidence angle while TM image is used for calculation of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Brightness Temperature. Then a soil moisture estimation model which is named as Hybrid model is developed based on integration of all of these parameters. The accuracies of this model are assessed in the NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7 by using SAR data in C band and L band frequencies and also in different polarizations of HH, HV, VV and TP. The results show that for instance in L band with HV polarization, R-square values of 0.728, 0.628 and 0.527 are obtained between ground measured soil moisture and estimated soil moisture values using the Hybrid model for NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7, respectively. 相似文献
16.
以成都市为研究区,定量分析了各地表特征参数与地表温度之间的线性关系。通过对地表温度与归一化植被指数(NDVI)、归一化建筑指数(NDBI)、归一化水汽指数(NDMI)进行局部区域逐像元分析和总体区域统计分析,结果表明NDVI,NDMI,NDBI与地表温度间都存在明显的线性关系,可用于说明地表温度的动态变化,在3月份,NDMI与地温的相关性更优于NDVI。对传统城市热现象研究中,NDMI与NDBI能够用来以NDVI作为分析地表温度随季节而变化的互补的度量标准。 相似文献
17.
Since soil moisture and vegetation index are direct and important indicators for surface drought status, a new drought monitoring method (MPDI1) is developed in NIR-Red reflectance space. It is a combination of two satellite-derived variables—a soil moisture component using the Perpendicular Drought Index (PDI), and a vegetation component using the Perpendicular Vegetation Index (PVI). Enhanced Thematic Mapper Plus (ETM+) image and in-situ ground observation are introduced to validate the accuracy of the proposed method. Results indicate that MPDI1 is highly consistent to the in-situ ground observation with the coefficient of determination (R2?=?0.49) between MPDI1 and 5–20 cm mean soil moisture, which is slightly higher than the coefficient of determination (R2?=?0.42) between MPDI1 and 10 cm soil moisture. Compared with drought indices such as PDI and the Modified Perpendicular Drought Index (MPDI), MPDI1 provides quite similar trends for bare soil or lower vegetated surface, but it demonstrates a better performance in measuring densely vegetated surface. This paper concludes that MPDI1 provides correct and sufficient information on surface drought status in soil-plant continuum, which appears to have robust available and great potential for surface drought estimation in China and other countries. 相似文献
18.
阜新地区植被覆盖度变化提取及分析 总被引：3，自引：0，他引：3
植被覆盖度是反应地区生态环境的重要指标,利用1995,2007年的两期TM遥感数据,以归一化植被指数(NDVI)像元二分法为植被覆盖度估算模型,计算阜新地区不同时期的植被覆盖度并得出阜新地区植被覆盖度等级图以及阜新地区植被覆盖度变化等级图。得出如下结论:1995年到2007年阜新地区植被覆盖度退化面积为64.817%,好转面积为6.547%,基本无变化区域为28.636%,阜新地区植被覆盖度退化严重。 相似文献
19.
Yogesh Kant B. D. Bharath Javed Mallick Clement Atzberger Norman Kerle 《Journal of the Indian Society of Remote Sensing》2009,37(2):201-214
The knowledge of the surface temperature is important to a range of issues and themes in earth sciences central to urban climatology,
global environmental change and human-environment interactions. The study analyses land surface temperature (LST) estimation
using temporal ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) datasets (day time and night time) over
National Capital Territory Delhi using the surface emissivity information at pixel level. The spatial variations of LST over
different land use/land cover (LU/LC) at day time and night time were analysed and relationship between the spatial distribution
of LU/LC and vegetation density with LST was developed. Minimum noise fraction (MNF) was used for LU/LC classification which
gave better accuracy than classification with original bands. The satellite derived emissivity values were found to be in
good agreement with literature and field measured values. It was observed that fallow land, waste land/bare soil, commercial/industrial
and high dense built-up area have high surface temperature values during day time, compared to those over water bodies, agricultural
cropland, and dense vegetation. During night time high surface temperature values are found over high dense built-up, water
bodies, commercial/industrial and low dense built-up than over fallow land, dense vegetation and agricultural cropland. It
was found that there is a strong negative correlation between surface temperature and NDVI over dense vegetation, sparse vegetation
and low dense built-up area while with fraction vegetation cover, it indicates a moderate negative correlation. The results
suggest that the methodology is feasible to estimate NDVI, surface emissivity and surface temperature with reasonable accuracy
over heterogeneous urban area. The analysis also indicates that the relationship between the spatial distribution of LU/LC
and vegetation density is closely related to the development of urban heat islands (UHI). 相似文献
20.
B. K. Bhattacharya V. K. Dadhwal 《Journal of the Indian Society of Remote Sensing》2005,33(2):331-338
The retrieval of land (soil-vegetation complex) surface temperature (LST) was carried out over semi-arid mixed agriculture
landscape of Gujarat using thermal bands (channel 4 and 5) and ground emissivity from atmospherically corrected NDVI of NOAA
AVHRR LAC images. The atmospheric correction of Visible and NIR band reflectance was done using SMAC model. The LST computed
from split-window method and subsequently corrected with fractional vegetation cover were then compared with near synchronous
ground observations of soil and air temperatures made during 13–17 January and April, 1997 at five Land Surface Processes
Experiment (LASPEX) sites of Anand, Sanand, Derol, Arnej and Khandha covering 100 km x 100 km. The fractional vegetation cover
corrected LST at noon hrs. varied from 301.6 – 311.9K in January and from 315.8 – 325.6K in April. The LSTcorr were found to lie in the mid way between AT and ST during January. But in April, LST were found to be more close to ST which
may be due to relatively poor vegetation growth as indicated by lower NDVI values in April indicating more contribution to
LST from exposed soil surface. 相似文献