Land Use Change in Hongta District in Yuxi City, China Based on Archived Landsat Data of the Past 30 Years

Urban expansion, which has affected ecosystem functioning and services at local to global scale, is projected to have aggravating impacts on landscape in the future. A detailed study on spatiotemporal patterns of Hongta District in Yuxi City over a relatively long timeframe was conducted using multi-temporal Landsat TM, ETM+ and OLI data of 1987-2017 associated with Geographic Information System techniques and landscape analysis approaches. Results showed that sealed surfaces (urban area) have expanded from 1.4% to 11.8%, with an annually increasing rate of 7.63%. Trees, farm areas and barren lands all underwent a slight reduction during this time period, whereby 23.8% of farms and 9.8% of bare lands transferred into sealed surfaces. Focusing on the urban expansion pattern, it presents a uninuclear polarizing polygon mode illustrating the urbanization sprawl over time to all directions. The greatest expansions are seen in NNE and SSE direction, mainly because of the topographic constraints. A trade-off between urbanization and sustainable development is under investigation by reclaiming barren soil at the mountain range to transfer farming areas from low altitude plains to make way for urban growth.

Utilization of Landsat Data for Quantifying and Predicting Land Cover Change in the Bumbuna Watershed in Sierra Leone

Rural communities in third world countries are concerned over land use changes resulting from resource exploitation. This is the case for the Bumbuna watershed in Sierra Leone following impoundment of the Bumbuna reservoir in 2009. Farmers have increased activities along the riparian zones in protest against inundation of their farmlands. The dam operators warn this practice would threaten sustainable power supply;the farmers contend the reservoir is increasing and taking over their farms. However, it is difficult to resolve this issue without a means of quantifying the change and developing early warning systems for land cover in the watershed. This research presents a case for the use of remotely sensed Landsat data for quantification of land cover change and the development of predictive models to inform preparedness for imminent problems that may arise from land use practices. In situ water loggers, in combination with manual readings, recorded water levels in 30-minute intervals since 2009. These datasets combined with spectral values of Landsat 7 and Landsat 8 for the development of regression algorithms for predictive purposes. Digital photographs and satellite imagery illustrated the changes in land cover over time (a 33% water rise and 44% NDVI change from 2009 to 2015). These visual and spectral pictures confirm the usefulness of remotely sensed data for early warning systems in the watershed. Results of the regression analysis show Band 1 (Blue) and Band 4 (NIR) as statistically significant predictors for water level in the reservoir. The tests accounted for 84% (R2) of the data with p-values less than α at the 0.05 confidence level. However, future trials of the model will consider reducing the 4.6 error margin to minimize deviations from the observed data.

A phenology-based vegetation index for improving ratoon rice mapping using harmonized Landsat and Sentinel-2 data

Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.

基于Landsat数据的重庆市热环境时空格局变化研究

针对当前热环境加剧对城市生态环境和人类健康带来的严重威胁,采用辐射传输方程法和Landsat数据对2001年和2019年重庆市主城九区地表温度(Land Surface Temperature,LST)进行反演,对研究区城市热环境时空变化进行研究。基于此选取景观指数和驱动因子对热力景观格局变化和热环境驱动机制进行研究。结果表明:①2001—2019年,重庆市主城九区城市热环境明显增强,高温区域明显增多且整体向北扩张,到2019年LST总体呈现“内高外低”的分布格局。②中温区最大斑块指数增长了近12倍,代替次低温区成为研究区优势斑块类型。斑块数量和密度均下降了约62%,说明重庆市主城区的热力景观总体上呈聚集化,连通性较强。③NDVI和DEM与LST呈负相关,NDBI与LST呈正相关,影响程度为NDBI>NDVI>DEM。

基于Landsat数据的地表温度反演差异及参数分析

只有基于准确的地表温度反演算法计算出的产品数据,才能正确推广使用。研究基于Landsat-8、Landsat-9和气象站数据,对比了5种常用地表温度反演算法的结果,并对不同算法的反演结果和参数灵敏度进行了测试。结果表明:基于地表比辐射率参数计算的辐射传输方程和单通道算法反演结果与地面实测数据吻合较好。基于大气水汽参数计算的单窗算法和劈窗算法的反演结果均高于实测温度。基于平均温度参数计算的单窗算法反演精度误差较大。此外,比较了两种遥感数据在不同地物上反演温度的一致性。研究结果可为地表温度反演和产品选择提供参考。

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遥感数据的森林火灾过火面积估算——以贵州毕节市赫章县“3·18”火灾为例

以贵州省毕节市赫章县2021年3月18日较大森林火灾为例,利用火灾前后Landsat 8遥感数据及ENVI遥感数据处理分析软件,通过图像预处理、计算归一化植被指数和燃烧面积指数等方法,提取森林火灾过火区域,计算过火面积。结果表明,利用Landsat 8数据能够较好地提取森林火灾过火区域,过火面积估算准确率达96.2%。

Wetland vegetation biomass estimation and mapping from Landsat ETM data: a case study of Poyang Lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18–28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.

Spatio-temporal changes of underground coal fires during 2008-2016 in Khanh Hoa coal field(North-east of Viet Nam) using Landsat time-series data

Underground coal fires are one of the most common and serious geohazards in most coal producing countries in the world. Monitoring their spatio-temporal changes plays an important role in controlling and preventing the effects of coal fires, and their environmental impact. In this study, the spatio-temporal changes of underground coal fires in Khanh Hoa coal field(North-East of Viet Nam) were analyzed using Landsat time-series data during the 2008-2016 period. Based on land surface temperatures retrieved from Landsat thermal data, underground coal fires related to thermal anomalies were identified using the MEDIAN+1.5×IQR(IQR: Interquartile range) threshold technique. The locations of underground coal fires were validated using a coal fire map produced by the field survey data and cross-validated using the daytime ASTER thermal infrared imagery. Based on the fires extracted from seven Landsat thermal imageries, the spatiotemporal changes of underground coal fire areas were analyzed. The results showed that the thermalanomalous zones have been correlated with known coal fires. Cross-validation of coal fires using ASTER TIR data showed a high consistency of 79.3%. The largest coal fire area of 184.6 hectares was detected in 2010, followed by 2014(181.1 hectares) and 2016(178.5 hectares). The smaller coal fire areas were extracted with areas of 133.6 and 152.5 hectares in 2011 and 2009 respectively. Underground coal fires were mainly detected in the northern and southern part, and tend to spread to north-west of the coal field.

基于Landsat影像准东矿区土壤湿度分布特征研究

为研究准东矿区土壤湿度时空分布特征及变化趋势,选取2001—2021年11期的Landsat遥感影像,计算归一化植被指数和地表温度,并以NDVI-LST特征空间为基础构造TVDI模型,反演准东矿区土壤湿度并进行分级,得到准东矿区各级土壤湿度面积,并采用灰色预测GM(1,1)模型对土壤湿度分布进行了预测。结果表明:2001—2021年,准东矿区总体土壤湿度较低,以四级和五级土壤湿度为主,两者面积总和占矿区总面积的85%以上;北部和东部区域土壤湿度较高,中部和西南部区域土壤湿度较低;矿区内一级、二级、三级土壤湿度面积年际变化不大,在0~2000 km^(2)波动;四级、五级土壤湿度面积变化表现出互为相反趋势。灰色预测GM(1,1)结果表明:2023—2039年,在0~1000 km^(2)内,一级土壤湿度面积略有增大,二级土壤湿度面积逐渐减小并趋于0,三级土壤湿度面积逐年下降,四级土壤湿度面积呈现逐年上升趋势,五级土壤湿度面积稳定在3000 km^(2)左右,表明该矿区土壤湿度整体呈减小趋势。

基于Landsat影像数据的香格里拉市优势树种蓄积量估测模型构建

以香格里拉市优势树种高山栎、高山松、云冷杉及云南松为研究对象,构建基于遥感的森林蓄积量估测模型。采用2006年和2016年的Landsat TM/OLI影像及二类调查数据,随机从每期数据中各选取100个小班,提取其影响因子,利用相关性强的因子构建RF模型和MLR模型。结果表明,2006年各树种蓄积量RF模型的拟合R2在0.779~0.862范围,预测精度P值为80.17%~92.16%;2016年RF模型的拟合R2为0.761~0.865,预测精度P值为81.61%~95.53%。建立MLR模型后,2006年树种蓄积量估测模型的拟合R2为0.214~0.336,预测精度P值为34.12%~47.16%;2016年模型的拟合R2为0.238~0.391,预测精度P值为34.82%~52.57%。估测结果与二类调查数据的误差为:高山栎、高山松、云冷杉、云南松分别增加了8.54×105m3、3.65×106m3、4.12×106m3、3.96×104m3,误差分别为0.36%、0.78%、0.44%、0.62%。对比二种模型估测结果表明,随机森林模型能更精确地估测优势树种蓄积量。

High Resolution Land Cover Datasets Integration and Application Based on Landsat and GlobCover Data from 1975 to 2010 in Siberia

Land cover is recognized as one of the fundamental terrestrial datasets required in land system change and other ecosystem related researches across the globe. The regional differentiation and spatial-temporal variation of land cover has significant impact on regional natural environment and socio-economic sustainable development. Under this context, we reconstructed the history land cover data in Siberia to provide a comparable datasets to the land cover datasets in China and abroad. In this paper, the European Space Agency(ESA) Global Land Cover Map(GlobCover), Landsat Thematic Mapper(TM), Enhanced Thematic Mapper(ETM), Multispectral Scanner(MSS) images, Google Earth images and other additional data were used to produce the land cover datasets in 1975 and 2010 in Siberia. Data evaluation show that the total user′s accuracy of land cover data in 2010 was 86.96%, which was higher than ESA GlobCover data in Siberia. The analysis on the land cover changes found that there were no big land cover changes in Siberia from 1975 to 2010 with only a few conversions between different natural forest types. The mainly changes are the conversion from deciduous needleleaf forest to deciduous broadleaf forest, deciduous needleleaf forest to mixed forest, savannas to deciduous needleleaf forest etc., indicating that the dominant driving factor of land cover changes in Siberia was natural element rather than human activities at some extent, which was very different from China. However, our purpose was not just to produce the land cover datasets at two time period or explore the driving factors of land cover changes in Siberia, we also paid attention on the significance and application of the datasets in various fields such as global climate change, geopolitics, cross-border cooperation and so on.

Analysis of Urban Change in Shenzhen City Based on Landsat Archived Data

With the ongoing development of economy and urbanization in China, the change of land use types has attracted more and more attention. In this study we focused on the urban development of Shenzhen City, Guangdong Province, analyzing Landsat 5 TM and Landsat 8 OLI data. We used an SVM based classification, a land transfer matrix approach, a directional growth analysis method and we calculated the inversion of land surface temperature to derive information of land cover changes that occurred in the time period between 1987 and 2017. The results are combined with Shenzhen’s economy, transportation policy and other aspects to find the driving forces of the urban development. The results show that during the observed 30 years, the area of construction land has increased significantly. Most of it is converted from other lands, and some of them are reclaimed. Most rapidly developing are areas west and northwest of the Bao’an, Nanshan and Longhua. The vegetated areas decreased slightly. Caused by the continuous increase of the construction land, the so-called heat island effect emerges slightly but continuously.

Assessment and Evaluation of Band Ratios, Brovey and HSV Techniques for Lithologic Discrimination and Mapping Using Landsat ETM⁺and SPOT-5 Data

This study aims to assess and to evaluate band ratios, brovey and HSV (Hue-Saturation-Value) techniques for discrimination and mapping the basement rock units exposed at Wadi Bulghah area, Saudi Arabia using multispectral Landsat ETM+ and SPOT-5 panchromatic data.?FieldSpec instrument is utilized to collect the spectral data of diorite, marble, gossan and volcanics, the main rock units exposed at the study area. Spectral profile of diorite exhibits very distinguished absorption features around 2.20 μm and 2.35 μm wavelength regions. These absorption features lead to lowering the band ratio values within the band-7 wavelength region. Diorite intrusions appear to have grey and dark grey image signatures on 7/3 and 7/2 band ratio images respectively. On the false color composite ratio image (7/3:R;7/2:G and 5/2:B), diorite, marble, gossan and volcanics have very dark brown, dark blue, white and yellowish brown image signatures respectively. Image fusion between previously mentioned FCC ratio image and high spatial resolution (5 meters) SPOT-5 panchromatic image is carried out by using brovey and HSV transformation methods. Visual and statistical assessment methods prove that HSV fused image yields best image interpretability results rather than brovey image. It improves the spatial resolution of the original FCC ratios image with acceptable spectral preservation.

Alteration Information Extraction by Applying Synthesis Processing Techniques to Landsat ETM+Data: Case Study of Zhaoyuan Gold Mines, Shandong Province, China

Satellite remote sensing data are usually used to analyze the spatial distribution pattern of geological structures and generally serve as a significant means for the identification of alteration zones. Based on the Landsat Enhanced Thematic Mapper （ETM＋） data, which have better spectral resolution （8 bands） and spatial resolution （15 m in PAN band）, the synthesis processing techniques were presented to fulfill alteration information extraction： data preparation, vegetation indices and band ratios, and expert classifier-based classification. These techniques have been implemented in the MapGIS-RSP software （version 1.0）, developed by the Wuhan Zondy Cyber Technology Co., Ltd, China. In the study area application of extracting alteration information in the Zhaoyuan （招远） gold mines, Shandong （山东） Province, China, several hydorthermally altered zones （included two new sites） were found after satellite imagery interpretation coupled with field surveys. It is concluded that these synthesis processing techniques are useful approaches and are applicable to a wide range of gold-mineralized alteration information extraction.

利用Landsat数据研究城市热岛效应的时空分布规律

利用收集到的2006—2020年西宁市的相关气象和遥感数据,研究西宁市地表温度、地表亮温的时空变化特征,城市热岛强度的空间分布特征呈现从城市中心向四周递减,主要是因为城区大规模人工不透水用地白天吸收大量的太阳辐射,太阳辐射直接转化为热量,因此地面温度较高,加强了热岛强度。此外,烟粉尘排放量也是城市热岛效应的重要影响因子,主要来源于道路扬尘、建筑施工扬尘、汽车尾气等,加之西宁市长年干燥,这些烟粉尘不易被带走,由于温室效应而加剧了城市热岛效应。

基于Landsat 8 OLI卫星遥感数据的黄前水库水源地保护区水土流失监测

近年来,为了提升饮用水水源地的综合监管水平,遥感监测技术得到了广泛应用。本文中基于landsat8 OLI卫星遥感数据,采用ENVI、Arc GIS等遥感图像处理技术,研究了黄前水库水源地保护区的植被覆盖度及水土流失分布特征。结果表明:黄前水库饮用水水源地保护区的林草覆盖度较高,占保护区总面积的57.32%;而水土流失较为严重,土壤侵蚀面积占55.30%,其中,以轻度、中度为主。该成果为黄前水库饮用水水源地保护区的水土流失监测和生态环境综合治理提供了技术支撑。

Landsat新型热红外地表温度产品与MODIS地表温度产品的交互对比

美国地质调查局(USGS)2020年12月正式发布了基于Landsat热红外光谱数据生产的2级地表温度产品(Landsat Collection 2 Level-2 surface temperature,LC2L2ST),但目前还鲜有该地表温度产品的相关研究报道。由于美国地质调查局已宣布自2022年开始将不提供除该产品之外的其他地表温度数据,因此有必要对该产品进行适时的评估。在同类遥感卫星产品中,MODIS地表温度产品的质量最被广大用户认可,应用也最为广泛,因此首次将Landsat新型热红外地表温度产品与MODIS地表温度产品进行交互对比,以评估新产品与MODIS地表温度产品的一致性。分别选取了我国的不同地区(福州、太湖、银川、敦煌)作为试验区,以20对同日过空的LC2L2ST与MODIS地表温度影像为数据源进行交互对比。影像涵盖植被、水体、建筑、荒漠等地物以及不同的季节。在试验区影像上选取一系列均质样区(ROI),通过各样区的地表温度均值散点进行拟合回归分析,研究二者地表温度间的差异及定量关系,并提出彼此转换的模型。结果表明,Landsat地表温度新产品与MODIS地表温度产品具有很高的相关性,4个试验区的决定系数(R^(2))皆大于0.98,集成4个试验区的总R^(2)也接近0.98;但LC2L2ST比MODIS的地表温度平均高0.90℃(RMSE=2.29℃)。分析发现,二者地表温度数据间的差异与其在空间分辨率、观测角度、地物类型和季节的不同有关。从不同地物和季节来看,LC2L2ST在晚秋和冬季略低于MODIS的地表温度,而在夏季极端高温的城镇、荒漠地区则明显高于MODIS的地表温度,且偏差可近7℃。总的看来,Landsat新型地表温度产品与MODIS同类产品的相关性显著,但在夏季的城市和沙漠地区的差异较大,因此,LC2L2ST新产品在夏季高温季节的适用性仍有待进一步基于地面实测温度的验证。鉴于两种地表温度数据产品仍存在着一定差距,因此二者如要协同使用,需要进行转换。本研究基于4个试验区的560个ROI样区构建了二者地表温度间的转换方程,并通过验证发现,经转换后的两数据差异性得到大幅缩小。因此,必要的数据转换有利于二者数据的协同使用,可为长时间序列的地表温度变化监测提供连续的遥感数据。

PALSAR-FBS L-HH Mode and Landsat-TM Data Fusion for Geological Mapping

Characterized by lithological diversity and rich mineral resources, Benshangul-Gumuz National Regional State located in Asosa Zones, Western Ethiopia has been investigated for geological mapping and morpho-structural lineaments extraction using PALSAR (Phased Array type L-band Synthetic Aperture Radar ) Fine Beam Single (FBS) L-HH polarization and Landsat-5 TM (Thematic Mapper ) datasets. These data were preprocessed to retrieve ground surface reflectance and backscatter coefficients. To overcome the geometry acquisition between the two sensors, they were geometrically and topographically rectified using ASTER-V2 DEM. Intensity-Hue-Saturation, directional filters and automatic lineaments extraction were applied on the datasets for lithological units’ discrimination and structural delimitation for potential mineral exploration. The obtained results showed good relationship among the topographic morphology, rock-substrate, structural variations properties, and drainage network. The spectral variations were easily associated with lithological units. Likewise, the morpho-structural information highlighted in the PALSAR image was visible without altering the radiometric integrity of the details in TM bands through the fusion process. Moreover, predominant lineaments directions trending NE-SW, NS, and NW-SE were identified. Results of this study highlighted the importance of the PALSAR FBS L-HH mode and TM data fusion to enhance geological features and lithological units for mineral exploration particularly in tropical zones.