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1.
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
2.
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
3.
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
4.
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
5.
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. 相似文献
6.
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
7.
The effects of urban development on the natural ecosystem and its link to the increased flooding in Houston, Texas were evaluated. Houston is suitable for this type of analysis due to its 1.95 million population, large geographic area and fast growth rate. Using neural network techniques, four Landsat Thematic Mapper images were grouped into five land use classes for the period 1984 to 2003: vegetation, bare ground, water, concrete and asphalt. Results show that asphalt and concrete increased 21% in the time period 1984–1994, 39% in 1994–2000 and 114%, from 2000 to 2003, while vegetation suffered an overall decrease. When change detection data are compared with runoff ratio data, a relationship between increased runoff and urban development is apparent, which indicates increased chances of flooding. Initial results of this work are made available to the public in GIS format via internet using Arc Internet Map Server (ArcIMS) at . 相似文献
8.
Floods in Malaysia have been increasing in frequency and magnitude as reflected in the Kelantan Flood event in 2014 that resulted in a huge loss of lives and properties. Whereas remote sensing (RS) and geographical information system (GIS) tools have been extensively applied in flood disaster management, there are few reports and studies on the impact of floods on the land use/land cover environment in a post-disaster assessment. In this study, an integrated modelling approach was developed that used Landsat 8 OLI TIRS (Operational Land Imager (OLI) and Thermal Infrared Sensor) data, flood indexing and classification processes to estimate the impact of flood on the environment. The Normalized Difference Flood Index-3 (NDFI 3) is an improvement on NDFI 2 that takes into account the effects of cloud shadow in the images when extracting flood index areas. The flood model developed showed good agreement when compared with flooded areas shown in SAR (synthetic-aperture radar) image. The results of the flood extent as a proxy for damage estimation showed that the total flooded area was 502.34 km 2 for the Kelantan Flood event in 2014, with plantation and built-up area accounting for 43 and 34.6% respectively. The least affected land uses/land covers were deforested area and forest, which accounted for 12.2 and 10.2% respectively. The RS and GIS technique developed in this post-disaster damage assessment is effective, relatively inexpensive and simple to implement by local authorities in support of post-flood disaster planning and decision-making. 相似文献
9.
The relationship between climate change and vegetation dynamics in the southwestern karst region of China has been identified
by recent studies. Based on previous researches and AVHRR (Advanced Very High Resolution Radiometer) GIMMS (Global Inventory
Monitoring and Modeling Studies) NDVI (Normalized Difference Vegetation Index) (1982–2003) and AVHRR GloPEM (Global Production
Efficiency Model) NPP (Net Primary Production) (1981–2000) datasets, vegetation dynamics impacted by climate change in the
southwestern karst region of China were assessed. The results show that: (1) since the early 1980s, both vegetation cover
density and net primary production have insignificant ascending tendencies. However, the inter-annual variation rates of vegetation
indexes have apparent spatial differentiations; (2) the correlation coefficients between the inter-annual variations of vegetation
indexes and the inter-annual variations of climate factors vary geographically; (3) as indicated by NDVI and NPP, various
vegetation types have different responses to climate change, and the annual mean temperature variation has more significant
impact on vegetation dynamics than the annual precipitation variation in the study area; (4) distribution laws of correlation
coefficients between the inter-annual variations of vegetation indexes and the inter-annual variations of climate factors
in different climate conditions are apparent. All these findings will enrich our knowledge of the natural forces which impact
the stability of the karst ecosystems and provide scientific basis for the management of the karst ecosystems. 相似文献
10.
In the twenty-first century, land use changes, massive expansion of urbanization, population growth, economic crisis, environmental issues are the main challenges of developing countries. Climate change and its effects on human health are the major concerns for the different age groups of the population. The study delved into the causes associated with climate change and climate change-related myriad health impacts on the study population. This study has used a concurrent mixed-method research design. The quantitative and qualitative data were collected from the study area. Perception and knowledge about climate change and its consequences on health was based on a quantitative approach of Bi-variate analysis and Chi-Square test and Fisher’s exact test; this study also used qualitative data analysis. Study results show that most respondents pointed out that temperature increases throughout the year and 90% of the respondents reported that rainfall pattern has also changed. Similarly, 65% of respondents agreed in their statements in favour of increased natural calamities in this region. The study findings show that more than 40% of population faces dengue fever and 10% of people also suffer from malaria. More than 60% of the urban population suffered from asthma. Similarly, more than 70% of the population also got affected by cold and cough due to weather variability. Focus Group Discussion (FGD) and In-depth interviews of the participants also affirmed the fact that climate variability induced diseases and health problems in Kolkata Metropolitan areas. Urban residents perceived that excessive urbanization contributes to the changes in regional climate and human health. The study will encourage the policy-makers and local government to mitigate adverse health effects driven by climate change in the Kolkata Metropolitan Region. 相似文献
11.
Frequent human activity and rapid urbanization have led to an assortment of environmental issues. Monitoring land-cover change is critical to efficient environmental management and urban planning. The current study had two objectives. The first was to compare pixel-based random forest (RF) and decision tree (DT) classifier methods and a support vector machine (SVM) algorithm both in pixel-based and object-based approaches for classification of land-cover in a heterogeneous landscape for 2010. The second was to examine spatio-temporal land-cover change over the last two decades (1990–2010) using Landsat data. This study found that the object-based SVM classifier is the most accurate with an overall classification accuracy of 93.54% and a kappa value of 0.88. A post-classification change detection algorithm was used to determine the trend of change between land-cover classes. The most significant change from 1990 to 2010 was caused by the expansion of built-up areas. In addition to the net changes, the rate of annual change for each phenomenon was calculated to obtain a better understanding of the process of change. Between 1990 and 2010, an average of 4.53% of lands turned to the built-up annually and there was an annual decrease of about 0.81% in natural land. If the current trend of change continues, regardless of the actions of sustainable development, drastic declines in natural areas will ensue. The results of this study can be a valuable baseline for land-cover managers in the region to better understand the current situation and adopt appropriate strategies for management of land-cover. 相似文献
12.
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
13.
陆地生态系统碳储量与全球气候变化密切相关,研究海岸带地区土地利用变化对生态系统服务碳储量的影响,对于区域生态系统保护及社会经济可持续发展具有重要意义.以辽宁省海岸带地区为例,分析了1995—2018年海岸带地区的土地利用变化特征,运用InVEST模型碳储量模块估算了1995—2018年区域生态系统的碳储量,结果表明:(... 相似文献
14.
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
15.
Normalized Difference Vegetation Index (NDVI) data were used to investigate vegetation changes after Hurricane Katrina (2005)
for the Weeks Bay Reserve and surrounding area of coastal AL. Landsat 5 satellite images were acquired before landfall (March
24, 2005), after landfall (September 16, 2005), and 8 months after landfall (April 28, 2006). The March 2005 to September
2005 image comparison showed that average NDVI values decreased by 49% after landfall. Continuing into the next year, average
NDVI values were −44% lower in April 2006 than they were in March 2005. Among habitat types, the estuarine emergent wetland
experienced the largest average NDVI value decrease (−64%). The estuarine emergent wetland NDVI values continued to decrease
by −27% from September 2005 to April 2006, whereas other habitats increased in NDVI. This continued suppression of NDVI values
was attributed to increased salinity from the storm surge and to regional drought conditions that occurred after landfall.
These results provide insight into the sensitivity of coastal vegetation from the interactions of both tropical cyclones and
long-term environmental conditions. 相似文献
16.
This study aims to assess the potential of several ancillary input data for the improvement of unsupervised land cover change detection in arid environments. The study area is located in Central Iraq where desertification has been observed. We develop a new scheme based on known robust indices. We employ Landsat (multispectral scanner, thematic mapper, and enhanced thematic mapper) satellite data acquired in 1976, 1990, and 2002. We use the Normalized Deferential Vegetation Index, Normalized Differential Water Index (NDWI), Salinity Index (SI), and Eolian Mapping Index. Two new equations were applied for the SI and the NDWI indices. Validation was performed using ground truth data collected in 16 days. We show that such an approach allows a robust and low-cost alternative for preliminary and large-scale assessments. This study shows that desertification has increased in the study area since 1990. 相似文献
17.
More recently, driven by rapid and unguided urbanisation and climate change, Ghanaian cities are increasingly becoming hotspots for severe flood-related events. This paper reviews urbanisation dynamics in Ghanaian cities, and maps flood hazard zones and access to flood relief services in Kumasi, drawing insight from multi-criteria analysis and spatial network analysis using ArcGIS 10.2. Findings indicate that flood hazard zones in Kumasi have been created by natural (e.g., climate change) and anthropogenic (e.g., urbanisation) factors, and the interaction thereof. While one would have expected the natural factors to guide, direct and steer the patterns of urban development from flood hazard zones, the GIS analysis shows that anthropogenic factors, particularly urbanisation, are increasingly concentrating population and physical structures in areas liable to flooding in the urban environment. This situation is compounded by rapid land cover/use changes and widespread haphazard development across the city. Regrettably, findings show that urban residents living in flood hazard zones in Kumasi are also geographically disadvantaged in terms of access to emergency services compared to those living in well-planned neighbourhoods. 相似文献
18.
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
19.
文中主要应用遥感方法计算了黄河三角洲地表蒸发量及其地表特征参数。地表特征参数及其合理组合揭示出黄河三角洲下垫面的基本特征:农田植被指数和天然植被的植被指数有不同的变化规律,下垫面覆盖度低,裸地较多,地表较湿润,蒸发量较大。蒸发量时空分布主要受下垫面条件控制,滨海裸地和受人类活动影响较大的农田等地蒸发量较大,年际平均蒸发量在570~860 mm之间。 相似文献
20.
在湿地景观类型分类基础上,利用RS及GIS技术提取了1986、1995和2010年胶州湾滨海湿地的Landsat卫星假彩色合成影像的空间属性数据,利用斑块动态度、斑块密度指数、景观多样性指数、斑块破碎化指数研究了胶州湾滨海湿地的景观格局变化及累积环境效应。结果表明,1986～2010年胶州湾滨海湿地总面积减少,河流与河口湿地面积稍有增大,潮间带滩涂和潮上带湿地面积和斑块数减小;养殖池面积增大、斑块数增多,盐田面积减小、斑块数基本未变,增加了湿地公园这种新的人工湿地景观类型。期间,湿地的景观斑块密度指数、多样性指数和景观斑块破碎化指数增大了。上述湿地面积和景观格局变化是由围垦、城市化、港口和道路建设、河流径流量和输沙量减少、海岸侵蚀、海水入侵、全球变暖、海面上升等因素引起的,并导致湿地生物多样化水平下降、有害植物入侵、环境净化功能降低、污染和赤潮灾害加重、植被退化演替、渔业资源衰退和湿地生态系统服务价值降低等累积环境效应。为减轻这些不利的累积环境效应,应采取建设湿地自然保护区、控制养殖池和盐田规模、发展工业循环经济和生态农业等措施保护胶州湾滨海湿地。 相似文献
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