Integration of remotely sensed indices for land cover changes caused by the 2009 Victorian bushfires using Landsat TM imagery

In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.

An automatic detection of green tide using multi-windows with their adaptive threshold from Landsat TM/ETM plus image

Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of green tide is presented from Landsat TM/ETM plus image which needs not the atmospheric correction. In order to achieve an automatic detection of green tide, a linear relationship（y =0.723 x＋0.504） between detection threshold y and subtraction x（x=λnir–λred） is found from the comparing Landsat TM/ETM plus image with the field surveys.Using this relationship, green tide patches can be detected automatically from Landsat TM/ETM plus image.Considering there is brightness difference between different regions in an image, the image will be divided into a plurality of windows（sub-images） with a same size firstly, and then each window will be detected using an adaptive detection threshold determined according to the discovered linear relationship. It is found that big errors will appear in some windows, such as those covered by clouds seriously. To solve this problem, the moving step k of windows is proposed to be less than the window width n. Using this mechanism, most pixels will be detected[n/k]×[n/k] times except the boundary pixels, then every pixel will be assigned the final class（green tide or sea water） according to majority rule voting strategy. It can be seen from the experiments, the proposed detection method using multi-windows and their adaptive thresholds can detect green tide from Landsat TM/ETM plus image automatically. Meanwhile, it avoids the reliance on the accurate atmospheric correction.

Spatial Pattern of Land Cover Change Using Remotely Sensed Imagery and GIS: A Case Study of Omo-Shasha-Oluwa Forest Reserve, SW Nigeria (1986-2002)

Spatial patterns of land cover changes in the Omo-Shasha-Oluwa Forest Reserves were conducted on Landsat TM and ETM+ imageries of 1986 and 2002 using remote sensing and GIS techniques. Extent of tree plantation (Gmelina arborea) grew from about 145 sq. km in 1986 to about 322 sq. km in 2002 (122% increase). The natural forest declined from about 2569 sq. km in 1986 to about 2253 sq. km by 2002, while the non-forest areas increased by some 5% from 341 km2?in 1986 to about 490 km2?by 2002. Land cover pattern and its changes in the study area are linked to both natural and anthropogenic processes such as illegal logging, demand for soft wood for industries and expansion of settlements. The conversion of natural forest into monoculture plantations should be discouraged because they do not give room for biodiversity. Specific forestry and environmental laws and regulations that significantly address landscape changes in reserved and protected areas should be enforced to reduce activities that negatively affect the forest reserves. There is also the need to develop a wider and more integrated GIS system of the forest and other land resources in the country to assist different kinds of planning and management activities.

Improving wavelet reconstruction algorithm to achieve comprehensive application of thermal infrared remote sensing data from TM and MODIS

According to the data characteristics of Landsat thematic mapper （TM） and MODIS, a new fu sion algorithm about thermal infrared data has been proposed in the article based on improving wave let reconstruction. Under the domain of neighborhood wavelet reconstruction, data of TM and MO DIS are divided into three layers using wavelet decomposition. The texture information of TM data is retained by fusing highfrequency information. The neighborhood correction coefficient method （NC CM） is set up based on the search neighborhood of a certain size to fuse lowfrequency information. Thermal infrared value of MODIS data is reduced to the space value of TM data by applying NCCM. The data with high spectrum, high spatial and high temporal resolution, are obtained through the al gorithm in the paper. Verification results show that the texture information of TM data and high spec tral information of MODIS data could be preserved well by the fusion algorithm. This article could provide technical support for high precision and fast extraction of the surface environment parame ters.

Monitoring coal fires in Datong coalfield using multi-source remote sensing data

Numerous coal fires burn underneath the Datong coalfield because of indiscriminate mining.Landsat TM/ETM,unmanned aerial vehicle（UAV）,and infrared thermal imager were employed to monitor underground coal fires in the Majiliang mining area.The thermal field distributions of this area in 2000,2002,2006,2007,and 2009 were obtained using Landsat TM/ETM.The changes in the distribution were then analyzed to approximate the locations of the coal fires.Through UAV imagery employed at a very high resolution（0.2 m）,the texture information,linear features,and brightness of the ground fissures in the coal fire area were determined.All these data were combined to build a knowledge model of determining fissures and were used to support underground coal fire detection.An infrared thermal imager was used to map the thermal field distribution of areas where coal fire is serious.Results were analyzed to identify the hot spot trend and the depth of the burning point.

Remote sensing analysis of mangrove distribution and dynamics in Zhanjiang from 1991 to 2011

Mangrove forests provide valuable societal and ecological services and goods. However, they have been experiencing high annual rates of loss in many parts of the world. In order to evaluate a long-term wetland conservation strategy that compromises urban development with comprehensive wetland ecosystem management, remote sensing techniques were used to analyze the changing mangrove distribution in the Zhanjiang Mangrove Forest National Nature Reserve. Between 1991 and 2000, the mangrove area within the study region declined from 2 264.9 to 2 085.9 ha consistent with an annual decrease of 0.79%. However, there was an overall 34.3% increase in mangrove coverage from 2 085.9 to 2 801.8 ha between 2000 and 2011. Major causes of forest loss include local human pressures in the form of deforestation, conversion to agriculture, and natural forces such as erosion. The recent gain in mangrove forest cover is attributed to eff ective conservation management in the nature reserve area, including intensive mangrove plantation eff orts and increased local awareness of wetland conservation.

Study the Urban Expansion of Taif City Using Remote Sensing and GIS Techniques for Decision Support System

The goal of this study is to spatially portray Taif’s urban expansion and determine for last 30 years, from 1990 to 2020. It is only including the residential neighborhoods approved by the Taif Municipality, which is responsible and organized for urban planning in the city. The geographical location of the city of Taif is a vital crossroad between eastern and western parts of the Kingdom of Saudi Arabia, which made it a tourist destination, as well as commercial and agricultural preference for many years, as it was considered the summer capital of the KSA. Moreover, it serves as the entrance to Makkah city from the eastern side. The proposed study has necessitated because the lack of recent scientific studies that dealt with the spatial analysis of urban expansion and its trends in the city of Taif and follow the stages of expansion during periods of time by relying on remote sensing and geographic information systems (GIS) techniques. The many development projects in the city of Taif, such as Taif International Airport, the new Taif project, and other projects, which will cause an increase in demand for residential, commercial, industrial and service units have also prompted the proposed study. This was investigated using a multitemporal Landsat data for the years of 1990, 2002 and 2020, as well as census data from 1990 to 2020, along with Remote Sensing (RS) and Geographic Information System (GIS) techniques. The results revealed that over the last 30 years, urban land cover has increased by 20,448 (ha) whereas other land covers, such as green area, have decreased significantly by 14,554 (ha). The results also indicate that the increase in urban areas amounted to 114.8% during the period from 1990 to 2020. The locations of new developments such as Taif airport, Taif university, Ministry of Housing projects, etc. were located to the North and Northeast. This is due to the area’s topography, which played a major role in determining the direction of urban expansion. According to the study, multiple urban centers, rising low-density dispersed communities, and leapfrogging growth were all hallmarks of urban expansion in Taif. The study demonstrated that Taif is at risk of ecosystem loss as a result of continued urban expansion. To ensure environmental sustainability, the current effort asks for actions that will restrict urban sprawl and prepare the city for future growth.

基于决策树的Landsat TM/ETM+图像中太湖蓝藻水华信息提取

以9期Landsat TM/ETM＋影像为数据源,基于K-T变换和归一化植被指数（NDW）,建立了湖泊蓝藻水华信息提取的决策树模型.基于大气顶面反射率图像,选用2005年10月17日太湖图像进行了对比验证,表明决策树模型比单波段阈值法、多波段阈值法（RVI、DVI、NDW）能够更有效地提取蓝藻水华信息,区分陆生植被、水生植物和水华,省去了水体掩膜的过程.使用太湖2002年10月25日和2011年7月22日图像、巢湖2005年8月12日的图像,验证决策树模型方法和工作流程的有效性.使用多期TM图像确定了阈值的取值范围,其中,亮度、绿度、NDVI的下限值依次为0.191、-0.007、-0.054,湿度下限范围为0.07～0.15;亮度阈值上限范围为0.3～0.7、绿度为0.2～0.5、湿度为0.1～0.3,这些结果可作为湖泊蓝藻水华遥感监测的参考.

基于Landsat 7 ETM+影像的大庆地区林带遥感调查

利用遥感和GIS技术 ,采用美国最新的Landsat7ETM +影像的 15m全色波段和 30m多光谱波段影像 ,对大庆地区的防护林地进行遥感调查。通过图像处理与分析得到了最佳的用于解译的影像 ,在野外调查的基础上 ,建立了林地的解译标志 ,量算了防护林带的宽度 ,查清了防护林的类型及实际面积 。

基于多时相Landsat TM/ETM的阿尼玛卿山冰川变化监测

采用遥感及地理信息系统技术,利用多时相Landsat TM/ETM影像和数字高程模型(SRTMDEM),结合中国冰川目录,获得阿尼玛卿山地区不同年份的冰川范围,进行冰川变化监测。综合分析该冰川的变化情况,计算冰川进退变化速率,并对其中4个变化较大的冰川进行详细的分析统计。结果表明:从1991年至2009年,阿尼玛卿山地区既有退缩冰川也有前进冰川,其中冰川退缩面积为15.30km2,前进面积为4.46km2。总体面积持续退缩,其中退缩最大的冰川长度缩短了900m,其它冰川也存在不同程度的变化。

基于Landsat7 ETM+图像提取蛤蟆沟林场浅覆盖区蚀变遥感异常

受植被、地形、阴影、第四系等干扰因素影响,覆盖区的遥感蚀变异常提取是一项具有探索性的研究课题。以内蒙古自治区阿尔山市蛤蟆沟林场为研究区,根据蚀变岩光谱特征,利用Landsat7 ETM+多光谱图像,在剔除多种干扰因素的基础上,运用主成分分析法提取了浅覆盖区蚀变遥感异常,分析了蚀变分布特征与影响因素,指出下一步应加强植被抑制和消除地形阴影效应研究。

基于Landsat TM/ETM+/OLI遥感大数据分析南京市1984—2015年大气能见度变化趋势

对南京市1984-2015年Landsat4／5／7／8卫星TM／ETM＋／OLI传感器获取的遥感数据，利用ENVI遥感软件的FLAASH大气校正模块，进行了区域大气能见度（VIS）遥感反演。结果表明，时间跨度达30余年的Landsat卫星遥感数据影像序列反演的VIS呈明显的下降趋势，20世纪80年代数值较高，“差”能见度（〈10kin）的观测率不到6％，21世纪以来VIS下降明显，“差”能见度的观测率为20％-25％。与2010-2015年南京市PM10、PM2.5监测数据进行了对比，在城市空气清洁及污染较轻时，星地监测结果有较好的一致性，但中到重污染天气时FLAASH算法反演VIS偏高，侧重于代表离主城区距离远的偏远乡野山林地区的能见度状况。

松花坝水源区Landsat 7 ETM+遥感影像融合对比研究

采用IHS变换、Brovey变换、PCA变换、Gram-Schmidt变换、CN变换和小波变换等遥感影像融合方法,对松花坝水源区2002年Landsat 7 ETM+多光谱数据与全色波段进行融合,并结合影像的光谱统计参数选取相应评价指标,对这些方法进行评价。结果表明,6种融合方法均能不同程度地提高影像质量,源于同一传感器的不同分辨率影像融合能够有效避免异源传感器影像融合所常见的实相及校正误差,PCA变换效果最佳。

基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法

利用遥感技术快速准确地提取耕地信息是耕地保护的关键环节。以山东省商河县为例,提出了一种基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法。首先采用毯子覆盖法计算多季相遥感影像每个像元的上分形信号和下分形信号,对比分析耕地和其他土地利用类型的分形特征,选取上分形信号的第3尺度作为特征尺度,提取商河县耕地空间分布特征;其次采用同时期的土地利用矢量数据、Esri land cover数据和统计数据进行耕地信息提取精度评价;最后分别设置多季相分形提取与单季相分形提取、现有土地利用数据产品的对比实验,并基于点位匹配度和面积匹配度进行评价。结果表明:多季相数据更能反映农作物生长的复杂性,有助于提高耕地信息的提取精度;不同土地利用类型在不同分形尺度的信号值各不相同,分形特征可以在不同尺度上清晰地刻画出不同土地利用类型的分异性;基于矢量数据和Esri land cover数据评价的多季相分形特征耕地提取点位匹配度为87.13%和89.83%,面积匹配度为99.73%和97.91%,均比单季相分形提取结果精度高;综合考虑点位匹配度、面积匹配度和空间分布特征,研发方法能有效区分耕地和其他土地利用类型,提取结果更优,且与统计数据有更高的一致性。该方法可准确提取耕地信息,为耕地的动态监测和损害评估提供技术支撑。

基于Landsat 8和机器学习的塔城地区草地地上生物量估测模型

以新疆塔城地区为研究区,利用植被指数、气象数据、地形数据作为自变量,结合研究区样地实测生物量数据,分析并比较K近邻回归(KNN)、多元线性回归(MLR)、梯度提升决策树(GBDT)和随机森林回归(RF)和极端梯度提升(XGBoost)5种机器学习模型,进而分析并比较采用投票回归器(Voting regressor)和堆叠(Stacking)方法构建的2种集成学习模型的估测精度。结果表明,基于Stacking集成学习模型性能最优,R^(2)达0.764,RMSE和MAE分别为23.29 g/m^(2)和16.8 g/m^(2),进而利用最优模型进行草地地上生物量(Above ground biomass,AGB)反演制图。

A Feasible Atmospheric Correction Method to TM Image

In this paper, an atmospheric correction method to TM image is presented, which can simulate the atmospheric correction parameters, such as optical depth, sky radiance and path radiance at the time the satellite passes,by using interpolation among local meteorological records, parameterization models and dark pixels. The TM image of the Nanjing area in China was corrected by this method. For analyzing the accuracy of this method, the calculated reflectance, apparent reflectance and ground measured reflectance were compared. NDVI before and after atmospheric cor- rection were also compared. The results show that the method is applicable and efficient in the visible to near infrared band of TM image. In order to improve the accuracy of the method, the infrared spectrum measured data for the two other bands of TM image are required in future field investigations. The method is suitable to many other satellite optical remote sensing images with the same or similar spectral characteristics of TM images.

基于Landsat 8 OLI和资源3号立体像对数据的桉树森林蓄积量估测

【目的】探索Landsat8 OLI数据和立体数据在估算桉树森林蓄积量(forest stock volume,FSV)中的潜力,并且准确地估计桉树的FSV。【方法】以3幅Landsat8 OLI图像和资源3号立体数据为遥感数据源,并且结合少量地面调查数据实现了桉树FSV的遥感估计。研究中提取了三类遥感特征用于估计桉树FSV:第一类是包括植被指数和单波段反射率在内的光谱特征;第二类是基于Landsat 8 OLI图像的单波段提取的8种纹理特征;第三类是基于资源3号立体像对数据和开源的数字高程模型(digital elevation model,DEM)提取的冠层高度模型(canopy height model,CHM)。利用Boruta算法对三类遥感特征进行提取,之后建立了随机森林(random forest,RF)、K-最近邻(K-nearest neighbor,KNN)和支持向量机(support vector machine,SVM)3种机器学习模型以及传统的多源线性回归模型(multiple linear regression,MLR),并以决定系数(R2)、均方根误差(root mean square error,RMSE)和相对均方根误差(relative root mean square error,rRMSE)作为评价指标对模型结果进行评估。【结果】基于ZY-3立体像对数据和开源的DEM数据提取的CHM与桉树的FSV具有很强的相关性,Pearson相关系数达到了0.71。仅仅利用基于Landsat 8 OLI图像提取的光谱和纹理特征难以准确2地估计桉树的FSV,估测模型的R为0.29~0.38,rRMSE为35.65%~43.30%,存在严重的数据饱和问题。2当变量集中加入CHM后,模型的估测精度明显提高,R达到了0.64~0.66,rRMSE为25.74%~26.41%。【结论】使用Landsat 8 OLI数据估算桉树FSV时存在严重的数据饱和问题,并且使用空间分辨率为30 m的纹理特征难以有效地改善森林蓄积量的估计精度。利用资源3号立体像对数据和开源的DEM数据可以提取较为准确的CHM,并且所提取的CHM可以解决改善光学数据的饱和问题,从而提高桉树FSV的估计精度。

Study of Forest Cover Change Dynamics between 2000 and 2015 in the Ikongo District of Madagascar Using Multi-Temporal Landsat Satellite Images

Satellite images are considered reliable data that preserve land cover information. In the field of remote sensing, these images allow relevant analyses of changes in space over time through the use of computer tools. In this study, we have applied the “discriminant” change detection algorithm. In this, we have verified its effectiveness in multi-temporal studies. Also, we have determined the change in forest dynamics in the Ikongo district of Madagascar between 2000 and 2015. During the treatments, we have used the Landsat TM satellite images for the years 2000, 2005 and 2010 as well as ETM+ for 2015. Thus, analyses carried out have allowed us to note that between 2000-2005, 1.4% of natural forest disappeared. And, between 2005-2010, forests degradation was 1.8%. Also, between 2010-2015, about 0.5% of the natural forest conserved in 2010 disappeared. Furthermore, we have found that the discriminant algorithm is considerably efficient in terms of monitoring the dynamics of forest cover change.

基于Landsat 8数据的广东石马河流域水质参数反演研究

针对河流水域水质进行高效快速监测的需要,本文以2021年2月广东石马河流域水体为研究对象,利用Landsat 8的OLI遥感影像对试验区域的环城河化学需氧量进行遥感反演研究。本文首先对实测水质数据和相应卫星影像数据波段值进行相关性分析,然后选取相关性最高的遥感波段值对水质进行回归分析,最后建立了适用于石马河流域的三次多项式反演模型。经反演预测结果与现场实测水质数据对比,试验结果表明所建立的水质反演模型能对石马河流域水质化学需氧量浓度进行高效快速监测。

基于Landsat 8影像提取豫中地区冬小麦和夏玉米分布信息的最佳时相选择

遥感技术对大尺度农业实时监测提供了一个理想的手段,遥感影像植被分类的最佳时相对作物种植面积遥感监测非常重要。本文选取2020年至2021年的6景Landsat 8影像,覆盖了夏玉米从乳熟到收获、冬小麦从越冬到成熟的生育期,以此分析不同时相的冬小麦-夏玉米与其他地类在光谱特征和NDVI上的差异,通过决策树的方法提取豫中地区冬小麦-夏玉米的空间分布情况。结果表明,冬小麦-夏玉米在不同生长发育时期,提取到的面积比有所不同,对于夏玉米而言,乳熟时期的提取效果要优于之后的时期,其在2020年8月26日的总体精度最高,为83.60%,Kappa系数为0.72,分类质量很好;对于冬小麦而言,最佳识别时期则处于冬小麦的越冬期,其在2021年1月1日的总体精度最高,为92.36%,Kappa系数为0.81,信息提取效果很好。除了作物自身生长过程的覆盖度变化,分类精度随成像时间而改变。多时相信息提取也发现,受到天气等环境条件限制,夏玉米和冬小麦的种植区域不完全重叠,山区冬季不适合冬小麦种植从而没有与夏玉米出现重叠分布。本研究有助于我们从宏观上对作物分布及生长状况作出及时有效的判断,对农业监测,特别是对轮作农田的信息管理和作物物候、种植面积等研究具有广阔的应用前景。