南京市夏季热岛特征及其与土地利用覆盖关系研究   总被引：4，自引：0，他引：4  

裴欢  房世峰 《干旱气象》2008,26(1):23-27

利用南京市7月的Landsat TM热红外波段数据,根据单窗算法反演得到南京市地表温度,讨论了南京市热岛特征,并分析了产生这种现象的原因。通过遥感和地理信息系统相结合,运用Landsat TM数据,提取出南京市下垫面类型,分析了不同地表覆盖类型的热辐射特征并定量地分析了土地利用及植被对地表温度的影响。结果显示,南京市夏季主要存在3个热岛中心,分别是建成区、大厂区和八卦洲。南京城区地表温度明显比郊区地表温度高,通过地表温度对比分析发现,城区平均地表温度比城市边缘和远郊区地表温度分别高出3.5℃和5.7℃,城市热岛效应明显。不同地表覆盖类型的地表温度也有显著差异,从高到低依次为：城镇建设用地、耕地、草地、林地、水体。城镇建设用地与水体的表面温度最大相差14℃。城市地表温度与植被覆盖度具有明显的负相关关系,城市地表植被覆盖度低是城市热岛出现的主要原因,今后应当更加注重城市绿地建设,提高植被覆盖率。  相似文献   

Environmental Monitoring of Bombetoka Bay and the Betsiboka Estuary,Madagascar,Using Multi-temporal Satellite Data     

Tsilavo Raharimahefa  Timothy M Kusky 《中国地质大学学报(英文版)》2010,(2)

The causes and consequences of soil erosion in Madagascar have been the focus of recent environmental debates.The Betsiboka,Madagascar's largest river stretching 600 km from the high central plateau to the northwest coast on the Mozambique Channel,is a major conduit for transporting lateritic soils and sediments derived from the highlands of Central Madagascar to the sea.These entrained lateritic sediments color the river a blood-red hue,as if the life of the island is being drained away.In this study,Lands...  相似文献   

用陆地卫星TM6数据演算地表温度的单窗算法   总被引：263，自引：3，他引：263  

覃志豪 《地理学报》2001,56(4):456-466

陆地卫星 TM数据 (TM6)热波段表示地表热辐射和地表温度变化。长期以来 ,从 TM6数据中演算地表温度通常是通过所谓大气校正法。这一方法需要估计大气热辐射和大气对地表热辐射传导的影响 ,计算过程很复杂 ,误差也较大 ,在实际中应用不多。根据地表热辐射传导方程 ,推导出一个简单易行并且精度较高的演算方法 ,把大气和地表的影响直接包括在演算公式中。该算法需要用地表辐射率、大气透射率和大气平均温度 3个参数进行地表温度的演算。验证表明 ,该方法的地表温度演算较高。当参数估计没有误差时 ,该方法的地表温度演算精度达到 <0 .4℃ ,在参数估计有适度误差时 ,演算精度仍达 <1 .1℃。因该方法适用于仅有一个热波段的遥感数据 ,故称为单窗算法。  相似文献   

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud   总被引：1，自引：0，他引：1  

Murali Krishna Gumma  Pardhasaradhi G. Teluguntla  Adam Oliphant  Jun Xiong  Chandra Giri 《地理信息系统科学与遥感》2020,57(3):302-322

ABSTRACT

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (≥250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop a high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, 10 time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the three time-periods over 12 months (monsoon: Days of the Year (DOY) 151–300; winter: DOY 301–365 plus 1–60; and summer: DOY 61–150), taking the every 8-day data from Landsat-8 and 7 for the years 2013–2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the five agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N = 2179) in five AEZs. The classification was performed on GEE for each of the five AEZs using well-established knowledge-base and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N = 1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full-resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/.  相似文献   

Monitoring interannual dynamics of desertification in Minqin County,China, using dense Landsat time series     

Xiaolin Zhu  Kwok Huen Leung  Wing Sze Li  Lek Kin Cheung 《International Journal of Digital Earth》2020,13(8):886-898

ABSTRACT

Minqin County in northwestern China is highly affected by desertification. Campaigns have been initiated in recent decades to combat desertification in Minqin. To assess the effectiveness of these campaigns, this study used a dense Landsat time series from 1987 to 2017 to investigate the interannual dynamics of vegetation coverage and greenness over the past 31 years. First, this study applied an advanced technology to reconstruct a high-quality Landsat annual time series. Specifically, one image in the vegetation-peak season was selected as the base image in each year, and then problematic pixels were interpolated by the neighborhood similar pixel interpolator using ancillary images in the same year. Second, the land cover map and the enhanced vegetation index (EVI) were derived from all reconstructed images. Third, the change of vegetation coverage and EVI values over the 31 years were analyzed. The results show that the total vegetation coverage and greenness increased during the 31 years. Linking this change trend to other factors suggests that vegetation in Minqin County is highly affected by agriculture and groundwater supply rather than by climate. To mitigate desertification in a sustainable way, agriculture should be well managed to avoid overconsumption of natural resources such as underground water.  相似文献   

地形效应校正的遥感地热异常提取     

周桃勇  王正海  秦昊洋  曾雅琦 《遥感学报》2020,24(3):265-276

在山地复杂地形条件下,利用热红外遥感获得的地表温度分布显著受到地形的影响,真实的地热异常信息往往难以识别,热红外遥感应用于山区地热勘探受到极大限制。以广东龙川地热勘查区为研究区,初步探讨了山地环境中如何抑制地形效应,以有效提取地热异常。首先,基于Landsat ETM+遥感数据反演地表温度,分析坡向和坡度两个地形因子与地表温度的关系;然后,在此基础上,将研究区的地表温度按坡向分成3个子区(阳坡、过渡坡和阴坡),根据阳坡地表温度与坡向的线性拟合关系将其校正到水平坡度上;最后,结合地质构造分布和地表覆被情况,在3个子区识别了4处地热异常,并与已知地热点进行比较验证。结果表明:坡向分区和阳坡坡度校正能够有效抑制地形效应,提高遥感地热异常识别精度,为山区地热资源的预测评价提供新思路。  相似文献   

应用随机辐射传输模型反演云南松林分郁闭度   总被引：1，自引：0，他引：1  

李骁尧  黄华国 《遥感学报》2020,24(6):752-765

随机辐射传输模型可用于模拟水平分布不均一森林的辐射传输过程。本文以云南松林分为研究对象，提出一种应用随机辐射传输模型的郁闭度反演方法。该方法以随机辐射传输模型中参数与林分郁闭度的定量关系为基础，提出了针对云南松的冠型等效模型，构建了郁闭度和卫星反射率（GF-1和Landsat 8卫星影像）的查找表，并实施了反演。基于野外实测的30个样地进行了郁闭度数据验证，并和基于NDVI回归模型的反演方法进行对比。结果表明，反演结果能够较准确反映云南松林分郁闭状况（R²=0.8345，RMSE=0.0688），通过冠型修正能够降低反演误差，冠型等效模型是合理的。反演方法机理清晰且适用范围广，研究成果可为大面积森林郁闭度反演提供模型和方法支持。  相似文献   

苏州运河水质的TM分析   总被引：1，自引：0，他引：1  

李旭文  季耿善  杨静 《遥感学报》1993,(1)

本文利用苏州地区陆地卫星TM数据和同期的地面水质监测资料建立了TM图像遥感水质模型,并将该模型应用于TM可见光彩色合成图像的分割处理,得到苏州地区水质空间分布图像。结合苏州运河水网的水文及水污染特征对遥感水质空间分布图像作了分析。结果表明TM数据真实地反映了苏州地区水质的空间分布规律,并得到当地环境监测部门的验证。  相似文献   

Assessment of the feasibility of utilizing Landsat for detection and monitoring of landfills in a statewide GIS     

E. Johnson  M. Klein  K. Mickus 《Environmental Geology》1993,22(2):129-140

Use of satellite data could be beneficial and cost effective in detecting and monitoring landfills in a state-wide geographic information system (GIS). To assure the feasibility of this approach, multitemporal Landsat data were used to detect several selected active and inactive landfills in central and southwest Missouri. The landfills were visually delineated from aerial photography of approximately the same two dates. A classification procedure based on homogeneity of the digital numbers was performed on each landfill scene for each time period using four spectral bands: two visible, one near-infrared, and one mid-infrared. The mid-infrared band proved more useful in delineating landfills, especially when spectral change was compared to the near-infrared band. The active landfills were spectrally different from surrounding land cover as were the two landfills which closed after the collection of the first Landsat scene. These landfills showed considerable areal change between the two selected time periods as verified by the aerial photographs. The inactive landfills were more difficult to discern from surrounding land cover types because they were grass covered and spectrally similar to pasture. Consequently, areal change could not be assigned to these older landfills because the reclamation process was practically complete.  相似文献   

用Landsat TM订正NOAA／AVHRR监测洪涝精度方法研究     

纪瑞鹏  张淑杰  班显秀  陈鹏狮 《气象科技》2004,32(1):60-62

为了提高NOAA卫星监测洪涝灾害精度，分别对NOAA和TM卫星资料监测洪涝灾害的光学原理进行阐述，并以黑山县和台安县为例，利用Landsat TM资料空间分辨率高的特点，对NOAA／AVHRR资料监测洪涝精度进行订正分析，平均相对误差为4．4％。研究结果表明，利用TM对NOAA监测洪涝精度进行订正是提高NOAA卫星监测洪涝精度可行的有效方法。  相似文献