Analysing transition of land surface temperature and derived indices with respect to elevation values in Kohima Saddar

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.

     

Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island,Malaysia

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.     

城市不透水面与地表温度定量关系的遥感分析

作为城市下垫面的最主要组成部分,城市不透水面是引发城市热岛效应的主要因素,但目前不透水面与地表温度之间的定量关系仍不明确,不同研究的结论也不尽相同。选取了上海、广州、北京、长沙、兰州、福州等6个代表我国不同区域的城市作为研究区来进一步研究城市不透水面与城市热环境的定量关系。采用Landsat ETM+影像和线性光谱混合分析法提取出各个研究区的不透水面,利用热红外波段反演出各研究区的地表温度,采用多种回归模型和大样本量对二者之间的相关关系进行定量分析;在此基础上讨论了不透水面对城市热环境的影响机制。结果表明：不透水面与地表温度呈明显的正相关关系,并且以指数函数为最佳拟合模型,回归方程的相关系数均为0.750以上,最高可达0.954 1;高不透水面盖度地区的升温幅度更大,比低不透水面盖度地区高出0.600~1.700 ℃,其原因主要是高不透水面盖度地区的植被覆盖率低,蒸腾蒸发作用小。     

Review of Methods for Simulating Land Surface Temperature at the Pixel Scale Based on Ground Measurements over Heterogeneous Surface

Remotely sensed Land Surface Temperature (LST) is a key parameter for studying the global climate changes and the exchanges of water and energy. Acquiring LST accurately is important to diagnose the change of environment on earth. Quantifying the uncertainty of remotely sensed LST is the first step of its application. However, due to the difficulties in obtaining the ground truth of LST at the pixel scale, it is difficult to validate the remotely sensed LST. Here, methods for simulating the LST at the pixel scale based on ground measurements over heterogeneous area were reviewed. From the way to construct the ground scene, these methods were classified into three types, including the Modified Geometric Projection model (MGP), realistic structural three-dimensional model, and other model. The advantages and disadvantages of these models were examined and compared. Finally, some issues in simulating LST at the pixel scale over heterogeneous area needed to be solved and on-going directions in the future were summarized.     

Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

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 (r² = 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.     

西藏地表温度时空演变特征及影响因子

地表温度（land surface temperature,LST）是反映生态环境状况的重要指标。西藏作为气候变化的敏感地区,掌握其LST的时空变化有利于深入了解西藏热环境演化过程,为长期监测高原基础生态变化提供帮助。研究基于谷歌地球引擎获取西藏2000—2020年的MODIS LST数据,采用归一化分级方法对LST进行5个等级的划分,利用趋势分析、热力空间分析以及重心迁移等方法分析了研究区近20年来的LST时空演变特征。同时,选取归一化植被指数（normalized difference vegetation index,NDVI）、裸土指数（bare soil index,BI）、垂直不透水面指数（perpendicular impervious surface index,PISI）、湿度（WET）以及高程（digital elevation model,DEM）等5个影响LST的地表参数,结合多尺度地理加权回归,探讨了LST影响因子的作用尺度与作用效力。结果表明：2000—2020年,西藏LST均值由18.72℃上升至20.28℃,年均增长0.09℃,LST呈现微弱上升态势。2...     

基于植被指数和土地表面温度的干旱监测模型

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。     

根据多时相夜间MODIS LST推断的腾冲地区新生代火山岩岩浆囊分布与活动特征

腾冲火山地热区位于印度板块与欧亚板块俯冲-碰撞带的弧后活动区,是我国新生代火山-地热最为活动的地区之一.本文利用MODIS夜间月平均地表温度(Land Surface Temperature,LST)数据,计算了研究区2001～2011年132个月的月平均地表温度,圈定了地温异常区;分析了异常区年内及年际间的平均地表温度变化趋势,推测了可能的地下岩浆囊分布位置及活动特征.研究结果表明,腾冲地区现今地下可能存在3个岩浆囊:第1个位于五合-新华-蒲川-团田一带,面积约为537km2,地温异常最明显;第2个位于朗蒲-热海-马鞍山地区,面积约为226km2,地温异常次之;第3个位于马站-曲石之间,面积约为28km2,地温异常较为明显.3个地温异常区在年内的地表温度变化趋势基本一致,而且周期性明显,均在5～6月份和8～9月份出现2个温度峰.其中朗蒲-热海-马鞍山异常区的地温变化波动最大,可能反映地下岩浆囊地热系统与地表地下水系统的对流交换活动性更强.MODIS夜间月平均地表温度数据得出的结果与测震、GPS形变、He同位素比值及最大相对地热梯度等方法推测的地温异常区范围具有很好的一致性,特别是地温异常区年内温度周期性变化的发现,表明卫星热红外遥感技术应用于地热异常实时监测与研究的巨大潜力.     

基于MODIS LST产品估算青藏高原地区的日平均地表温度

地表温度是衡量地-气界面热状况的重要指标,在冻土制图、城市热岛效应等研究领域有重要应用.MODIS数据只提供了每日4次过境的瞬时温度值,而实际应用中往往需要日平均地表温度.对实测0cm温度数据进行分析后,发现其日变化曲线呈分段函数特性,白天按正弦曲线变化,夜间则呈线性下降.据此提出对白天和晚上的数据进行分段拟合的方案,并与已有的两种拟合方法作对比验证.地面验证工作包括两个方面:一是模拟的验证,按卫星过境时间从逐小时的实测0cm数据中挑出4个瞬时值,将上述拟合方法应用于这4个瞬时值,得到拟合的日平均温度,再同24h的算术平均值比较.结果表明:Sin-Linear法精度最高,平均误差在1K以内;其二是地面对MODIS的验证,将3种方法应用于MODIS数据,再与地面平均值比较,3种方法中Sin-Linear法误差最小,且具有最好的线性相关,R2超过0.9.     

华北地块北缘中元古界几个重要不整合面的地质特征及构造意义

华北地块北缘中元古代沉积层序中出现多个沉积间断和不整合面。此次研究对其中5个不整合面进行了野外考察,分析了它们的地质特征和空间分布,认为它们与不同的地质过程有关。大红峪组底部不整合面是早期裂谷盆地演化为被动大陆边缘的记录,属于裂解不整合面性质;高于庄组底部和杨庄组底部的不整合面是海平面变化造成被动大陆边缘内部高地沉积间断和海岸超覆沉积的结果;铁岭组顶部不整合面可能与弧后环境发生挤压抬升有关;下马岭组沉积后的抬升可能是相邻大陆地块碰撞作用的产物。华北地块北缘中元古代层序中不整合面的形成与Columbia和Rodinia超大陆的形成和裂解过程密切相关。     

The relationship between land surface temperature and land use/land cover in Guangzhou,China

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.     

Heat wave risk assessment and mapping in urban areas: case study for a midsized Central European city,Novi Sad (Serbia)

Risk assessment and mapping methodologies for heat waves as frequently occurring hazards in central and southeastern Europe were applied in this study, and the impact of heat waves on the mortality of urban populations was determined as part of the assessment. The methodology for conducting the heat wave risk assessment is based on European Commission’s Guidelines for Risk Assessment and Mapping. The Novi Sad (Serbia) urban area was studied during summer 2015, which was one of the hottest summers in the last few decades. In situ air temperature measurements from urban stations and mortality of urban populations were used. Nocturnal urban heat island (UHI) intensity values between the various built-up zones and natural surrounding areas were used for the hazard level calculation. Temperature data from 9 p.m. to 5 a.m. were used because during the night, the UHI intensity reached its maximum values. The average daily number of deaths by LCZs was used to define the impact level of the vulnerability index. Calculations for both hazard levels were completed during two intensive heat waves (in July and August 2015) when it was expected that there may be a high level of risk. The results and maps show that the urban area is complex, and the heat wave risk on the population is not uniform. The most densely built-up areas (LCZs 2, 5 and 6) have very high or high risk values that are influenced by a higher rate of mortality. The obtained results and maps can be used by local authorities to prevent and mitigate climate-related hazards, for medical institutions as well as urban planners and for ancillary local, regional or national services. According to these results, the local authorities could define hot spots where they can place medical and rescue teams and install points with water supplies, etc.     

大陆地表温度场的时空变化与现今构造活动

试图利用地表温度场数据获取中国西部的构造活动信息。在建立热与应变关系的基础上,对中国西部MODIS/Terra地表温度产品进行分析处理。研究发现:(1)地表温度在一些地区发生偏离年变现象,这种年变偏离与一些活动构造带的活动有关;(2)在扣除年变基准场等主要气候因素后,年变残差(ΔT)中长周期成分(LSTLOW)更接近构造活动所引起的热信息,能为构造活动提供一定的指示信息。研究发现,一个地震的发生对周围不同构造区的影响不同,有的地区升温,有的地区降温。2004年印尼地震最大的影响是引起青藏高原中部巴颜喀拉—松潘地块的降温;(3)与前者相对应,发生在中国周边地区的不同地震引起的温度变化格局不同,对同一地区的影响也不同,例如2001年东昆仑8.1级地震引起龙门山断裂带升温,而2003年斋桑泊7.9级地震和2004年印尼9级地震却引起该带的降温;(4)不同地区地温变化的时间过程不同。这些现象均对构造变形过程有一定的启示。在上述现象的基础上,笔者结合GPS观测结果,不同深度的地温信息以及地震活动等资料,对地表温度场中包含构造活动信息进行了初步检验,并对地表温度场反映的区域构造变形模型进行了讨论。     

http://www.sciencedirect.com/science/article/pii/S1674987110000137

<正>This study attempts to acquire information on tectonic activity in western China from land surface temperature(LST) field data.On the basis of the established relationship between heat and strain,we analyzed the LST distribution in western China using the satellite data product MODIS/Terra.Our results show that:1. There are departures from annual changes of LST in some areas,and that these changes are associated with the activity of some active tectonic zones.2.When annual-change background values caused by climate factors are removed,the long-period component(LST_(LOW)) of temperature residual(△T) of the LST is able to serve as an indicator for tectonic activity.We have found that a major earthquake can produce different effects on the LST fields of surrounding areas.These effects are characterized by both rises and drops in temperature.For example, there was a noteworthy temperature decline associated with the Sumatran M9 earthquake of 2004 in the Bayan Har-Songpan block of central Tibetan Plateau.3.On the other hand,the LST field of a single area may respond differently to major shocks occurring in different areas in the regions surrounding China.For instance,the Kunlun M 8.1 event made the LST on the Longmen Mountains fault zone increase,whereas the Zaisan Lake M 7.9 quake of 2003,and the Sumatran M9 event of 2004.caused decreases in the same area's LST.4.The variations of land surface temperature(LST) over time are different in different tectonic areas.These phenomena may provide clues for the study of tectonic deformation processes.On the basis of these phenomena,we use a combination of temperature data obtained at varied depths,regional seismicity and strain results obtained with GPS measurements,to test the information related to tectonic activity derived from variations of the LST field,and discuss its implications to the creation of models of regional tectonic deformation.     

S patio-temporal pattern of land use and land cover and its effects on land surface temperature using remote sensing and GIS techniques: a case study of Bhubaneswar city,Eastern India (1991–2021)

Urbanization produces substantial land use changes by causing the construction of different urban infrastructures in the city region for habitation, transportation, industry, and other reasons. As a result, it has a significant impact on Land Surface Temperature (LST) by disrupting the surface energy balance. The objective of this paper is to assess the impact of land-use/land-cover (LU/LC) dynamics on urban land surface temperature (LST) of Bhubaneswar City in Eastern India during 30 years (1991–2021) using Landsat data (TM, ETM + , and OLI/TIRS) and machine learning algorithms (MLA). The finding reveals that the mean LST over the entire study domain grows significantly between 1991 and, 2021due to urbanization (β coefficient 0.400, 0.195, 0.07, and 0.06 in 1991, 2001, 2011, and 2021 respectively) and loss of green space (β coefficient − 0.295, − 0.025, − 0.125 and − 0.065 in 1991, 2001, 2011 and 2021 respectively). The highest class recorded for agricultural land (49.60 km², accounting for 33.94% of the total land area) was in 1991 followed by vegetation (41.27 km², 28.19% of the total land area), and built-up land (27.59 km², 18.84% of the total land area). The sharp decline of vegetation cover will continue until 2021 due to increasing built-up areas (r = − 0.531, − 0.329, − 0.538, and − 0.063 in the 1991, 2001, 2011 and 2021 respectively). Built-up land (62.60 km², accounting for 42.76% of the total land area, an increase of 35.01 km² from 1991) as the highest class followed by water bodies (21.57%, 32.60 km² of the land area), and agricultural land (31.57 km², 21.57% of the land area) in 2021. Remote sensing techniques proved to be an important tool to urban planners and policymakers to take adequate steps to promote sustainable development and minimize urbanization influence on LST. Urban green space (UGS) can help improve the overall liveability and environmental sustainability of Bhubaneswar city.

     

Review on Validation of Remotely Sensed Land Surface Temperature

Land Surface Temperature (LST) is an important input parameter for many land surface models. Retrieving LST from remote sensing is the main approach for modelling the radiance balance and energy budget at both regional and global scales. Validation of remotely sensed LST is helpful to evaluate its accuracy and stability. Furthermore, it is meaningful for the retrieval and application of remotely sensed LST. Here, first, theories and methods of LST retrieval were reviewed. Second, four validation methods, including the Temperature-based (T-based), Radiance-based (R-based), cross comparison and Time-series analysis, were reviewed and compared. An in-depth examination was conducted for the T-based method from the aspects including the approaches for acquiring the ground truth value, the target LST products, the uncertainty sources. Finally, some important issues in LST validation were discussed.     

Linkage of urban expansion and land surface temperature using geospatial techniques for Jaipur City,India

The aim of this study is to understand the land use change and urban expansion of Jaipur City of Rajasthan (India). Landsat 5 TM and Landsat 8 OLI satellite data of 4 years, i.e., 1993, 2000, 2010, and 2015 are used for land use and land surface temperature (LST) analysis. ERDAS Imagine and ArcGIS software are used to conduct the analysis. Urban settlement increased from 13.5 to 57.3% in the study period. Open land is mainly changed to urban areas. Urban settlement is also expanded to peri-urban area of Jaipur City. Jaipur City expanded along three directions i.e., north, west, and south and less development is found in the east direction. Based on radial analysis, it is observed there is not much development within the periphery of 2 km (close to city center) but maximum growth is observed within the distance from 4 to 6 km radius of city center. Expansion intensity was observed highest in the period 2015–2010 from 6 km onwards and reached to a maximum value close to 17 km²/year. In LST analysis, there is less change in extreme temperature, but more areal increase in average temperature range (30–35 °C). Urbanization is the main driving process of land cover changes and consequently changes in LST.     

MODIS地表温度产品在青藏高原连续多年冻土区的适用性分析

利用自动气象站观测的长波辐射计算得到的地表温度对MODIS地表温度(LST)产品在青藏高原中部连续多年冻土区的精度进行验证, 并利用具有较高空间分辨率的Landsat 5 TM和Landsat 7 ETM+反演的地表温度与MODIS LST产品进行了对比分析. 结果表明: 白天MODIS LST产品的平均绝对误差(MAE)和均方根误差(RMSE)分别约为3.42~4.41 ℃和4.41~5.29 ℃, 夜晚MODIS产品MAE和RMSE分别为2.15~2.90 ℃和3.05~3.78 ℃, 精度高于白天; MODIS LST与TM、ETM+反演的地表温度一致性较好, 相关系数分别达到0.85和0.95. 说明MODIS LST产品在连续多年冻土区的适用性较高, 是研究多年冻土地表热状况的一个非常好的数据源. 而且, 不同空间尺度的遥感数据之间一致性较好, 可考虑将多源遥感数据应用于多年冻土热状况监测研究.     

近十年淮南矿区地表热环境时空演变分析

地表温度是描述陆表过程和反映地表特征的重要参数.研究矿区地表温度的时空演变特征,对于理解煤矿开采活动对矿区生态环境的影响具有重要意义.淮南矿区是我国东部典型的高潜水位煤矿区,为了探究该区域地表温度的时空异质性与开采扰动的关系,利用2008—2018年5期Landsat影像进行地表温度的反演和下垫面信息提取,结合热力景观...