基于Landsat-8数据和劈窗算法的地表温度反演及城市热岛效应研究

陆地表面温度(Land Surface Temperature,LST)是地表能量平衡组分中的一个重要参数。随着卫星遥感技术的快速发展,遥感反演成为获取区域LST的一个重要手段。目前已有学者提出多种基于遥感数据反演LST的算法,其中劈窗算法被证明是一种精度较高的算法。基于Landsat-8卫星30 m空间分辨率的陆地成像仪(OLI)数据和100 m分辨率的热红外传感器(TIRS)数据,采用劈窗算法计算了无锡地区的LST,并采用地面实测水温数据和同步的MODIS温度产品对Landsat-8的计算结果进行了验证和对比分析。结果表明:基于Landsat-8数据和劈窗算法获取的LST精度较高,误差1K。在计算的LST结果基础上,进一步提取了热场变异指数来分析城市热岛空间分布特征,给出了城市热岛效应的定量化描述,并就不同地表覆盖类型对热岛效应的影响进行了分析。     

National aeronautics and space administration

The United States National Aeronautics and Space Administration is an important real and potential source of global environmental data. This paper describes some of its capabilities as they relate to the their R&D and their data centers.     

A Comparison of Spatial and Spectral Image Resolution for Mapping Invasive Plants in Coastal California

We explored the potential of detecting three target invasive species: iceplant (Carpobrotus edulis), jubata grass (Cortaderia jubata), and blue gum (Eucalyptus globulus) at Vandenberg Air Force Base, California. We compared the accuracy of mapping six communities (intact coastal scrub, iceplant invaded coastal scrub, iceplant invaded chaparral, jubata grass invaded chaparral, blue gum invaded chaparral, and intact chaparral) using four images with different combinations of spatial and spectral resolution: hyperspectral AVIRIS imagery (174 wavebands, 4 m spatial resolution), spatially degraded AVIRIS (174 bands, 30 m), spectrally degraded AVIRIS (6 bands, 4 m), and both spatially and spectrally degraded AVIRIS (6 bands, 30 m, i.e., simulated Landsat ETM data). Overall success rates for classifying the six classes was 75% (kappa 0.7) using full resolution AVIRIS, 58% (kappa 0.5) for the spatially degraded AVIRIS, 42% (kappa 0.3) for the spectrally degraded AVIRIS, and 37% (kappa 0.3) for the spatially and spectrally degraded AVIRIS. A true Landsat ETM image was also classified to illustrate that the results from the simulated ETM data were representative, which provided an accuracy of 50% (kappa 0.4). Mapping accuracies using different resolution images are evaluated in the context of community heterogeneity (species richness, diversity, and percent species cover). Findings illustrate that higher mapping accuracies are achieved with images possessing high spectral resolution, thus capturing information across the visible and reflected infrared solar spectrum. Understanding the tradeoffs in spectral and spatial resolution can assist land managers in deciding the most appropriate imagery with respect to target invasives and community characteristics.     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

Detecting deforestation with a spectral change detection approach using multitemporal Landsat data: a case study of Kinabalu Park, Sabah, Malaysia

Tropical deforestation is occurring at an alarming rate, threatening the ecological integrity of protected areas. This makes it vital to regularly assess protected areas to confirm the efficacy of measures that protect that area from clearing. Satellite remote sensing offers a systematic and objective means for detecting and monitoring deforestation. This paper examines a spectral change approach to detect deforestation using pattern decomposition (PD) coefficients from multitemporal Landsat data. Our results show that the PD coefficients for soil and vegetation can be used to detect deforestation using change vector analysis (CVA). CVA analysis demonstrates that deforestation in the Kinabalu area, Sabah, Malaysia has significantly slowed from 1.2% in period 1 (1973 and 1991) to 0.1% in period 2 (1991 and 1996). A comparison of deforestation both inside and outside Kinabalu Park has highlighted the effectiveness of the park in protecting the tropical forest against clearing. However, the park is still facing pressure from the area immediately surrounding the park (the 1km buffer zone) where the deforestation rate has remained unchanged.     

NEAR REAL-TIME MAPPING OF THE 1975 MISSISSIPPI RIVER FLOOD IN LOUISIANA USING LANDSAT IMAGERY1

ABSTRACT: The project described in this report was undertaken by the Louisiana State Planning Office to establish the extent of backwater flooding in Louisiana in April 1975. Band 7 Landsat imagery, enlarged to a scale of 1:250,000 was used to visually identify flooded areas. Inundated areas were delineated on overlays keyed to 1:250,000 U.S. Geological Survey topographic quadrangles. Tabular data identifying acres flooded, according to land use type, were derived by merging the flood map overlays with computerized 1972 land use data. Approximately 1.12 million acres of the state were inundated by flood waters. The total acreage and land use types affected by flooding were determined within 72 hours from the time the flood areas were imaged. Flooded maps were prepared for 26 parishes. Field observations were made by Louisiana Cooperative Extension Service county agents in order to determine the accuracy of parish flood maps and flood acreage figures by land use type. Results indicated that this was a fast, accurate, and relatively inexpensive method of compiling flood data for disaster planning and postflood analysis.     

Landsat ETM+ Images in the Estimation of Seasonal Lake Water Quality in Boreal River Basins

We investigated the use of Landsat ETM+ images in the monitoring of turbidity, colored dissolved organic matter (CDOM), and Secchi disk transparency (Z(SD)) in lakes of two river basins located in southern Finland. The ETM+ images were acquired in May, June, and September 2002 and were corrected for atmospheric disturbance using the simplified method of atmospheric correction (SMAC) model. The in situ measurements consisted of water sampling in the largest lake of the region, routine monitoring results for the whole study area, and Z(SD) observations made by volunteers. The ranges of the water quality variables in the dataset were as follows: turbidity, 0.6-25 FNU; absorption coefficient of CDOM at 400 nm, 1.0-12.2 m(-1); Z(SD), 0.5-5.5 m; and chlorophyll a concentration, 2.4-80 mug L(-1). The estimation accuracies of the image-specific empirical algorithms expressed as relative errors were 23.0% for turbidity, 17.4% for CDOM, and 21.1% for Z(SD). If concurrent in situ measurements had not been used for algorithm training, the average error would have been about 37%. The atmospheric correction improved the estimation accuracy only slightly compared with the use of top-of-atmospheric reflectances. The accuracy of the water quality estimates without concurrent in situ measurements could have been improved if in-image atmospheric parameters had been available. The underwater reflectance simulations of the ETM+ channel wavelengths using water quality typical for Finnish lakes (data from 1113 lakes) indicated that region-specific algorithms may be needed in other parts of the country, particularly in the case of Z(SD). Despite the limitations in the spectral and radiometric resolutions, ETM+ imagery can be an effective aid, particularly in the monitoring and management of small lakes (<1 km(2)), which are often not included in routine monitoring programs.     

Changes in Forest Area Along Stream Networks in an Agricultural Catchment of the Great Barrier Reef Lagoon

Scenes from the series of multispectral sensors on the Landsat satellites were used to map recent changes (between 1972 and 2004) in forest cover within and adjacent to stream networks of an intensively farmed region of the southern Great Barrier Reef catchment (Australia). Unsupervised ISODATA classifications of Tasseled-Cap transformed data (at 57 m ground resolution) mapped forest and cleared areas within 150 m of Pisoneer catchment waterways with 72.2% overall accuracy (K(hat) = 0.469), when adjusted for the size of each class. Although the user's accuracy was higher for the forest class (82.1 +/- 8.4% at alpha = 0.05), large errors of commission (34.2 +/- 8.3%) substantially affected map accuracy for the cleared class. The main reasons for misclassification include: (1) failure to discriminate narrowly vegetated riparian strips; (2) misregistration of scenes; and (3) spectral similarity of ground cover. Error matrix probabilities were used to adjust the mapped area of classes, resulting in a decline of forest cover by 12.3% and increase of clearing by 18.5% (22.4 km(2) change; 95% confidence interval: 14.3-29.6 km(2)) between 1972 and 2004. Despite the mapping errors, Landsat data were able to identify broad patterns of land cover change that were verified from aerial photography. Most of the forest losses occurred in open forest to woodland habitat dominated by Eucalyptus, Corymbia, and Lophostemon species, which were largely replaced by sugarcane cropping. Melaleuca communities were similarly affected, though they have a much smaller distribution in the catchment.     

遥感数据时间分辨率对土地覆盖变化监测的影响

由于土地覆盖通常存在年际变化和季节变化,区分人为活动引起的变化与这种自然变化需要两期数据时间一致。论文利用黑龙江省1975、1990、2000、和2005代表年Landsat数据,分析了数据时间差在16 d MODIS-NDVI时间序列的误差。研究发现,Landsat数据4个代表年的年际差分别为1975±4 a,1990±4.5 a,2000±1.5 a,2005±1.5 a,季节差为47 d。Landsat季节差对MODIS-NDVI的影响是:当季节差为16~48 d时,东北地区耕地与草地以生长高峰期为参照的MODIS-NDVI变化最高可达0.4以上,林地MODIS-NDVI变化0.1~0.2;当时间差<16 d时,如果仍以生长高峰期为绝对参照,东北大部分地区误差<0.1,只有少数耕地误差0.1~0.2。如果以两个时间为相对参照,则<16 d的误差也可能导致较大的MODIS-NDVI误差,其大小有明显的季节性。在生长高峰期7月12日至8月28日,8 d±8 d的时间差导致的NDVI差大于0.1的像元仅2.93%,是变化检测最佳时期;但在除此之外的6月10日至9月29日间,8 d±8 d时间差导致NDVI差大于0.1的像元比例超过11.42%,选择Landsat必须避开这一敏感期。结论:利用高时间分辨率MODIS-NDVI可在3个方面提高Landsat变化检测效果:①辅助选择最佳时间;②当无法选择最佳时间时,评估时间差可能引起的误差和方向;③直接使用生物物理参数作为变化检测的指标之一。     

基于Landsat ETM+等影像的无锡市十年陆地生态环境遥感评价

遥感和GIS技术的发展为研究区域生态环境变化提供了有效手段,以无锡市2004-2013年的ETM＋等遥感影像和GDEM高程数据为数据源,运用遥感和GIS方法提取生态因子信息并进行陆地生态状况遥感评价。结果表明,无锡市近十年陆地生态环境整体趋好。