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1.
Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r 2 = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area. 相似文献
2.
Human activities have affected the urban environment resulting in a drastic change in the surface temperature. The impact of urban heat islands is noticeable in urban areas than in rural areas. The thermal band of Landsat 8 data is used to retrieve the spatial distribution of land surface temperature (LST) over Kohima Sadar for the years 2009, 2015 and 2020 with the Mono-window algorithm. Urban Thermal Field Variance Index (UTFVI) is used to assess the ecological condition in the area impacted by LST. Cartosat-1 Digital Elevation Model (Carto DEM) is used to understand the variations of LST and indices values with reference to the elevation profile located at different random points. The variations in the land cover are categorized as per the values of normalized difference vegetation index (NDVI) and built-up density index (BUI). This work estimates the influence of elevation over LST, vegetation, and the built-up area. Results implies a negative correlation between LST and NDVI whereas a positive correlation between LST and BUI. Likewise, NDVI and BUI show a strong negative correlation. It is observed that LST is independent of elevation profile but the variation of LST depends on the impact of change in topography urbanization, deforestation, and afforestation. There is no significant relationship of elevation with the variations in NDVI and BUI values. It is observed that the impact of emissivity influences the estimation of LST values. For the locations having the highest and lowest LST, NDVI, and BUI values, 50 random points are generated for the entire region, and validation is executed with the google earth historical image. 相似文献
3.
Land surface temperature (LST) plays an important role in local, regional and global climate studies. LST controls the distribution
of the budget for radiation heat between the atmosphere and the earth’s surface. Therefore, it is important to evaluate abrupt
changes in land use/land cover (LULC). Penang Island, Malaysia has been experiencing a rapid and drastic change in urban expansion
over the past two decades due to growth in industrial and residential areas. The aim of this study was to investigate and
evaluate the impact of LST with respect to land use changes in Penang Island, Malaysia. Three supervised classification techniques
known as maximum likelihood, minimum distance-to-mean and parallelepiped were applied to the images to extract thematic information
from the acquired scene by using PCI Geomatica 10.1 image processing software. These remote sensing classification techniques
help to examine land-use changes in Penang Island using multi-temporal Landsat data for the period of 1999–2007. Training
sites were selected within each scene and seven land cover classes were assigned to each classifier. The relative performance
of each technique was evaluated. The accuracy of each classification map was assessed using a reference data set consisting
of a large number of samples collected per category. Two Landsat satellite images captured in 1999 and 2007 were chosen to
classify the LULC types using the maximum likelihood classification method, determined from visible and near-infrared bands.
The study revealed that the maximum likelihood classifier produced superior results and achieved a high degree of accuracy.
The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC. The results showed that
the urban (highly built-up) area increased dramatically, and grassland area increased moderately. Inversely, barren land decreased
obviously, and forest area decreased moderately. While urban (minimally built-up) area decreased slightly. These changes in
LULC caused at significant difference in LST between urban and rural areas. Strong correlation values were observed between
LST and NDVI for all LULC classes. The remote sensing technique used in this study was found to be efficient; it reduced the
time for the analysis of the urban expansion, and it was found to be a useful tool to evaluate the impact of urbanisation
with LST. 相似文献
4.
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
5.
Land use and land cover (LULC) changes caused by human activities have strong influences on regional environment. Land surface temperate plays an important role in studying the impact of LULC changes on regional environment. In this paper, remotely sensed thermal infrared data were used to assess land surface temperature (LST) in the Weigan and Kuqa river oasis, Xingjiang, one of the important agricultural areas in the northwestern China. The present study deals with the extraction of LST and the relationship between LULC changes using Landsat 5 TM acquired on September 25, 1989, and September 6, 2011. The results indicate that the surface temperature of water body, bare land, and desert changed significantly between 1989 and 2011. In general, the LST was lower in 1989 than in 2011. There were no lower, higher, and highest temperature zones in 1989. However, the minimum temperature was 10.7 °C in 1989 and 15.8 °C in 2011. The maximum temperature was 29.3 °C in 1989 and 41.8 °C in 2011. Regarding the LULC types, the desert features in the Gobi Desert warmed more quickly than the oasis. So, the temperature of the oasis was lower than the surrounded areas, resulting in a so-called “cold island” phenomenon. Oasis cold island effect index (OCIEI) shows that stability of oasis had rising trend from 1989 to 2011. In addition, the impact of LULC changes on LST was analyzed and the driving forces were also analyzed from 1977 to 2011. This study is significant for further understanding of the energy exchange status of soil-plant-atmospheric system and the regional heat distribution in arid and semi-arid areas of the northwest China. 相似文献
6.
It is axiomatically true that urbanization in India's metropolises and large cities has been exacerbated since the beginning of the millennium, consuming the natural and semi-natural ecosystem on the outskirts of the city, resulting in a zone with a distinct climate known as urban climate. Such a climate—the result of a built-up environment is distinctly different from the natural climate as the paved surface and concrete skyscrapers not only destroy the natural ecosystem, it peculiarly induce a different kind of insolation, cooling and air drainage were lacking in green space, water bodies and open space cannot accommodate with environmental rhythm properly, resulting into the accumulation of heat, ecological derangement of subsurface soil which can easily be predicted by GIS analysis. This paper is an attempt to measure urban growth and its impact on the environment in the metropolitan city Kolkata. The use of satellite data and GIS techniques to detect urban expansion is a highly scientific strategy. Using geospatial techniques, the current study attempts to examine major urban changes in Kolkata and its surroundings from 1988 to 2021. Landsat 5 TM and Landsat 8 OLI temporal data are used to identify land-use change through unsupervised classification; Spectral Radiance Model and Split Window Algorithm method are used for identifying land surface temperature change. SRTM DEM (30 m) has been used to identify flood risk zones and several spectral indices like Normalized Difference Vegetation Index and Modified Normalized Difference Water Index are a further extension for environmental assessment. By all such suitable methods, a clearer change in an urban environment is detected within the period of 33 years (1988–2021). The result shows that the population changes, vegetation cover and built-up area, and accessibility are at a rapid rate. These changes are causing major environmental degradation in the city. The classification result indicates that appropriate land use planning and environmental monitoring are required for the long-term exploitation of these resources. 相似文献
7.
Remote sensing data can be used as the basis for meteorological data. Due to the limitations of meteorological stations on the Earth, derivation of land surface temperature is one of the most important aspects of the remote sensing application in climatology studies. In the present study, Landsat-8 thermal infrared sensor data of the scene located over Khuzestan province with row/path of 165/38 were used to derive land surface temperature (LST). Normalized difference vegetation index (NDVI), fraction of vegetation cover, satellite brightness temperature, and land surface emissivity were calculated as the vital criteria to derive LSTs using the split window algorithms. LST determination was performed by nine different split window algorithms. Eventually, LST products were evaluated using ground-based measurements at the meteorological stations of the study area. The results showed that algorithm of Coll and Casselles had a highest accuracy with RMSE 1.97 °C, and Vidal’s method presented the lowest accuracy to derive LST with RMSE 4.11 °C. According to the results, regions with high density of vegetation and water resources have lowest diurnal temperature and regions with bare soils and low density of vegetation have a highest diurnal temperature. Results of the study indicated that LST algorithm accuracy is an important factor in the environmental and climate change studies. 相似文献
8.
This paper describes the spatiotemporal changes pertaining to land use land cover (LULC) and the driving forces behind these changes in Doodhganga watershed of Jhelum Basin. An integrated approach utilizing remote sensing and geographic information system (GIS) was used to extract information pertaining to LULC change. Multi-date LULC maps were generated by analyzing remotely sensed images of three dates which include LandSat TM 1992, LandSat ETM+ 2001 and IRS LISS-III 2005. The LULC information was extracted by adopting on-screen image interpretation technique in a GIS environment at 1:25,000 scale. Based on the analysis, changes were observed in the spatial extent of different LULC types over a period of 13 years. Significant changes were observed in the spatial extent of forest, horticulture, built-up and agriculture. Forest cover in the watershed has decreased by 1.47 %, Agricultural by 0.93 % while as built-up area has increased by 0.92 %. The net decrease in forest cover and agriculture land indicate the anthropogenic interference into surrounding natural ecosystems. From the study it was found that the major driving forces for these changes were population growth and changes in the stream discharge. The changes in the stream discharge were found responsible for the conversion of agricultural land into horticulture, as horticulture has increased by 1.14 % in spatial extent. It has been found that increasing human population together with decreasing stream discharge account for LULC changes in the watershed. Therefore, the existing policy framework needs to focus upon mitigating the impacts of forces responsible for LULC change so as to ensure sustainable development of land resources. 相似文献
9.
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
10.
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
11.
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
12.
干旱是一种周期性发生的自然现象,其发生过程中有关参数如地表覆盖度、温度和土壤表层含水量等可以通过遥感的途径进行定量反演,而这些参数客观地反映了地表的综合特征。综述了运用遥感反演产品---土地表面温度和归一化植被指数在干旱监测中的应用前景和进展,分析了距平植被指数、条件植被指数、条件温度指数和归一化温度指数等干旱监测方法的优缺点,在前人研究的基础上,提出了条件植被温度指数的干旱监测模型,探讨了其应用前景。 相似文献
13.
Land cover and vegetation in Lake Baikal basin (LBB) are considered to be highly susceptible to climate change. However, there is less information on the change trends in both climate and land cover in LBB and thus less understanding of the watershed sensitivity and adaptability to climate change. Here we identified the spatial and temporal patterns of changes in climate (from 1979 to 2016), land cover, and vegetation (from 2000 to 2010) in the LBB. During the past 40 years, there was a little increase in precipitation while air temperature has increased by 1.4 °C. During the past 10 years, land cover has changed significantly. Herein grassland, water bodies, permanent snow, and ice decreased by 485.40 km 2, 161.55 km 2 and 2.83 km 2, respectively. However, forest and wetland increased by 111.40 km 2 and 202.90 km 2, respectively. About 83.67 km 2 area of water bodies has been converted into the wetland. Also, there was a significant change in Normalized Difference Vegetation Index (NDVI), the NDVI maximum value was 1 in 2000, decreased to 0.9 in 2010. Evidently, it was in the mountainous areas and in the river basin that the vegetation shifted. Our findings have implications for predicting the safety of water resources and water eco-environment in LBB under global change. 相似文献
14.
利用MODIS植被指数和陆地表面温度产品建立全国3个农业气候区NDVI-Ts、NDVI-ΔT和NDVI-ATI空间,并由NDVI-Ts、NDVI-ΔT和NDVI-ATI空间分别建立温度植被干旱指数(TVDI)、温差植被干旱指数(DTVDI)和表观热惯量植被干旱指数(AVDI)3个干旱评价指标研究全国干旱分布,利用实测土壤含水量对3个干旱指标进行检验评价.NDVI-ΔT空间中的湿边基本与横坐标平行,表明当土壤水分处于饱和状态或植被完全无水分胁迫条件下,植被和土壤对缓冲环境温度变化的能力大体相当;由NDVI-ATI空间看出,随着植被覆盖增加,表观热惯量有增加的趋势.对比3个干旱评价指标表明:当监测范围较大,区域内地形复杂时,由NDVI-Ts空间计算的TVDI评价干旱最合理,由NDVI-ΔT空间计算的DTVDI在干旱监测中也具有一定的价值,而由NDVI-ATI空间计算的AVDI已经不能合理评价干旱. 相似文献
15.
The Multan district is mainly prone to riverine floods but has remained understudied. Chenab flood-2014 was the worst flood that this district experienced in recorded history. This study applies remote sensing (RS) techniques to estimate the extent, calculate duration, assess the major causes and resulting impacts of the flood-2014, using Landsat-8 OLI images. These images were obtained for pre-flood, during-flood and post-flood instances. Secondary data of flood causing factors were obtained for comprehensive analysis. Spatially trained and validated datasets were obtained through Google Earth platform and Global positioning system. The supervised classification with maximum likelihood algorithm was used to classify land use and land cover of the study area. The Modified Normalized Difference Water Index was utilized to detect flood inundation extent and duration, and Normalized Difference Vegetation Index was utilized to monitor vegetation coverage and changes. The analysis allowed us to assess flood causes, and calculate the extent of the flooded areas with duration and recession, as well as damages to standing crops and built-up areas. The results revealed that the flood-2014 occurred due to heavy rains in early September in upper Chenab catchment. The flood inundation continued for around two months, which heavily affected agriculture and built-up areas. The present study introduces practical use of RS techniques to provide basis for effective flood inundation mapping and impact assessment, as an application for early flood response and recovery in the world. 相似文献
16.
地表特征参数与下垫面特征密切相关,它是研究地表物质平衡和能量平衡的基础,因而应用遥感方法反演区域地表特征参数日益受到重视。本文主要应用现有的地表特征参数遥感反演模型,利用AVHRR和TM数据反演了黄河三角洲的地表特征参数:地表反照率、地面温度和植被指数等,并根据反演结果研究了地表特征参数及其合理组合所反映的地表特征。农田植被和天然植被的植被指数变化规律不同;在植被全覆盖区域,植被指数与反照率成幂函数关系,在极干或极湿情况下,地表温度与反照率成线性关系;地表特征参数的合理组合反映出黄河三角洲下垫面覆盖度低,裸地较多,地表较湿润,蒸发量较大。 相似文献
17.
以我国高纬度多年冻土区漠河县城区及郊区862 km 2的区域为研究对象,基于RS和GIS技术对该区地表覆被变化和地表温度进行研究。结果表明：地表类型和地表温度反演结果与现场比对结果一致;从1988年到2015年,经过火灾后重建和城镇化发展,建设用地面积增加了11.33 km 2;以2015年为例,冬季由于积雪覆盖,有79.02%的区域无植被覆盖,夏季有80.91%的区域为高植被覆盖。冬季地表温度和高程具有高度相关性,高程每升高100 m,地表温度平均升高2.27℃,表明该区地表温度也存在显著的逆温现象。该区城镇热岛效应全年存在,城镇区域地表温度高于全区平均值,夏季最显著,最高温差可达6.37℃。地表温度与 NDVI具有明显的负相关关系;不同土地利用类型地表温度由低到高的顺序为水体-林地-草地-裸地-建筑用地。 相似文献
18.
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 NO 3 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
19.
利用1998-2007年SPOT VGT归一化植被指数(NDVI)数据对新疆植被覆盖的年际和空间变化进行了动态监测,并从气候变化和人类活动双重角度分析了植被覆盖演变的原因.1998-2007年新疆植被覆盖变化经历了2个阶段:1998-2001年植被覆盖严重退化时期;2002-2007年植被覆盖由急剧上升到缓慢下降再到持续升高时期,NDVI明显高于20世纪末期水平.新疆植被覆盖变化存在显著的空间差异,阿尔泰山地森林、巴音布鲁克草原等自然植被NDVI明显退化,农业灌溉区和生态建设地区的植被覆盖明显提高.从不同的土地利用类型来看,沙地和耕地的NDVI上升趋势显著,林地和草地植被的NDVI退化严重.研究表明,新疆植被覆盖变化是气候变化和人类活动共同作用的结果.温度对植被覆盖变化的影响表现为对植被生长年内韵律的控制和春季植被生长期的延长,年降水量的波动式下降是导致新疆植被覆盖变化呈现2个阶段的主导冈素.农业生产水平的提高是新疆农业灌溉区NDVI不断上升的重要原因,同时,近年来大规模实施的生态建设工程所带来的生态效应正在呈现. 相似文献
20.
基于GIMMS NDVI3g（the third generation of Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index）数据,结合趋势分析、Mann-Kendall检验和Pearson相关分析等方法,识别了渭河流域19822015年不同时间尺度（年、月及季节）植被NDVI的动态变化特征及气候因素影响。结果表明,近34年渭河流域NDVI呈现增长趋势,且20002015年NDVI较19821999年显著增长,趋势线斜率分别为0.003和0.001,退耕还林后植被覆盖状况明显改善;年均NDVI与气温呈显著正相关,与降水的正相关性较弱;月均NDVI与气温和降水都表现为显著正相关,相关系数分别为0.926,0.743;春秋季NDVI与气温呈现显著正相关,夏季NDVI与气温、降水的相关性不明显,冬季NDVI与前期气温存在滞后相关。 相似文献
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