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.

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.

Analysis of forest cover change at Khadimnagar National Park, Sylhet,Bangladesh, using Landsat TM and GIS data

We mapped the forest cover of Khadimnagar National Park （KNP） of Sylhet Forest Division and estimated forest change over a period of 22 years （1988-2010） using Landsat TM images and other GIS data. Supervised classification and Normalized Difference Vegetation Index （NDVI） image classification approaches were applied to the images to produce three cover classes, viz. dense forest, medium dense forest, and bare land. The change map was produced by differencing classified imageries of 1988 and 2010 as before image and after image, respectively, in ERDAS IMAGINE. Error matrix and kappa statistics were used to assess the accuracy of the produced maps. Overall map accuracies resulting from supervised classification of 1988 and 2010 imageries were 84.6% （Kappa 0.75） and 87.5% （Kappa 0.80）, respec- tively. Forest cover statistics resulting from supervised classification showed that dense forest and bare land declined from 526 ha （67%） to 417 ha （59%） and 105 ha （13%） to 8 ha （1%）, respectively, whereas medium dense forest increased from 155 ha （20%） to 317 ha （40%）. Forest cover change statistics derived from NDVI classification showed that dense forest declined from 525 ha （67%） to 421 ha （54%） while medium dense forest increased from 253 ha （32%） to 356 ha （45%）. Both supervised and NDVI classification approaches showed similar trends of forest change, i.e. decrease of dense forest and increase of medium dense forest, which indicates dense forest has been converted to medium dense forest. Area of bare land was unchanged. Illicit felling, encroachment, and settlement near forests caused the dense forest decline while short and long rotation plantations raised in various years caused the increase in area of medium dense forest. Protective measures should be undertaken to check further degradation of forest at KNP.

On Urban Heat Island of Beijng Based on Landsat TM Data

Land surface temperature (LST) of Beijing area was retrieved from Landsat TM thermal band data utilizing a radiative transfer equation and the urban heat island (HUI) effects of Beijing and its relationship with land cover and normalized difference vegetation index (NDVI) were discussed. The result of LST showed that the urban LST was evidently higher than the suburban one. The average urban LST was found to 4.5 ℃ and 9 ℃ higher than the suburban and outer suburban temperature, respectively, which demonstrated the prominent UHI effects in Beijing. Prominent negative correlation between LST and NDVI was found in the urban area, which suggested the low percent vegetation cover in the urban area was the main cause of the urban heat island.

基于SPOT4和Landsat5 TM的不同影像融合方法质量对比研究

【目的】探究不同影像融合方法对SPOT4全色影像和Landsat5 TM多光谱影像融合效果的影响。【方法】采用13种不同的影像融合算法开展融合试验,并通过定性和定量分析的方式,对融合结果进行综合评价分析。【结果】结果表明,融合影像的信息熵相比原影像有所增强,RGB三通道的熵值分布更为均匀,主要集中在50~200之间。此外,不同地物类型对融合方法的效果产生了显著影响。对于水体和植被,Brovey、HSV、IHS和EF方法展现出了良好的光谱保真性和细节增强能力,因此更适用于目视解译。NND法在这些区域出现了轻微的光谱失真现象,导致其分类精度偏低。【结论】针对不同传感器的影像选择适当的融合方法,对于提高遥感影像的解译精度和应用价值具有重要意义。

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.

Improved Geological Interpretation Using Landsat TM Data in Lancang-Jinghong Area, Yunnan Province, China

Landsat TM digital spectral data of Lancang Jinghong area (Yunnan P ro vince) has been used for the purpose of geological interpretation. To meet this object, different image processing techniques including selected band color comp osites, principal component analysis and IHS decorrelation stretching are used t o improve the discrimination of different lithological and structural features i n the area.It was found that IHS decorrelation stretching images obtained from t he transformation of false color composite 741 (in red, green and blue) prov ided the best results based on the original data.By combining the characteristic s of images produced by different approaches and other canonically transformed i mages with available geological data and surface observations, the geological in terpretation could be done with satisfactory degree of accuracy.

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.

基于Landsat TM数据估算雷竹林地上生物量

结合Landsat TM遥感数据和雷竹林样地调查数据,采用偏最小二乘回归法(PLS)建立雷竹林地上生物量估算模型,利用该模型估算临安市雷竹林地上部分生物量。结果表明:雷竹单株地上部分生物量与胸径及雷竹林地上部分生物量与株数之间都呈极显著相关(P<0.01);通过PLS-Bootstrap法筛选自变量能够提高模型精度;模型预测的雷竹林地上生物量均方根误差为3.45t·hm-2,满足大范围估算的精度要求;临安市雷竹林地上生物量为13～25t·hm-2,均值为19.52t·hm-2。

Landsat TM遥感影像中厚云和阴影去除

提出了一种新的利用多时相LandsatTM影像数据进行的厚云及其阴影去除的方法。该方法通过分析厚云及其阴影的光谱特征,设计了厚云和云阴影识别模型。该算法的实现是采用图像配准技术、非监督分类、像元替换等运算,计算出厚云和云阴影区域的TM影像替换数据,进而得到消除或者减少云影响的TM遥感影像。试验结果表明本文提出的厚云及其阴影去除方法效果很好,能消除或者弱化云对TM影像数据的影响。

基于Landsat-TM数据的农牧交错带景观结构研究——以内蒙古自治区兴和县为例

根据1989年和 2000年的两期 Landsat-TM数据,应用景观类型斑块等级结构和景观空间格局指数等景观生态学指标,对地处典型农牧交错带地区的兴和县景观结构进行研究.结果表明,该地区农田和草地是平原和丘陵区的主体景观类型;不同景观类型斑块大小等级结构变化各异,耕地和草地斑块明显增大,乔木林地和水体斑块趋于减小;景观破碎化明显增强.

基于Landsat TM/ETM数据的锡林河流域土地覆盖变化

根据1987年、1991年、1997年和2000年4期Landsat TM/ETM影像的土地利用/土地覆盖分类结果,运用地理信息系统空间分析方法,分析了内蒙古锡林河流域1987～2000年间各土地利用类型及草甸草原、典型草原、荒漠草原的数量变化和空间变化特征.分析结果显示,锡林河流域土地利用/土地覆盖变化的主要特征为草甸草原、典型草原面积的大幅减少和荒漠草原、农田和沙漠化土地面积的大幅增加及城镇的扩张.其中面积增加最大的是荒漠草原,增加了2328 km2;相当于1987年荒漠草原面积的56%.农出和城镇面积逐年增大,分别从1987年的114.3 km2和25.2 km2增加到2000年的332.1 km2和43.6 km2.面积减少最多的是羊草+丛生禾草、羊草+杂类草等优良高产温带典型草原类型,共减少2040km2.草甸草原面积亦呈逐年减少的趋势,从1987年的1103 km2减少到2000年375 km2,面积减少了65.9%.农出、沙化地及城镇等非草原土地利用类型面积增加了62.5%.

利用Landsat TM遥感数据监测冬小麦开花期主要长势参数

为精准农业技术体系中的小麦农艺处方管理决策提供详尽的全局性信息,该文以2007-2009年试验实测数据为基础,以Landsat TM影像为遥感数据源,分析了试验样点开花期冬小麦主要长势参数与品质和产量间以及与卫星遥感变量间的相关性,分别建立及评价了TM影像遥感变量监测冬小麦开花期SPAD值、生物量、叶面积指数和叶片氮含量的模型。结果表明:冬小麦开花期,选用作物氮反射指数、近红外波段反射率和归一化植被指数这些遥感变量分别反演冬小麦SPAD值、生物量、叶面积指数和叶片氮含量是可行的;SPAD值、生物量、叶面积指数和叶片氮含量遥感监测模型的精度较高,均方根误差分别为3.12、216.5kg/hm2、0.269和0.162,以此为基础,制作出具有实际农学意义的冬小麦开花期不同等级SPAD值、生物量、叶面积指数和叶片氮含量遥感监测专题图,实现了主要长势参数空间分布量化表达。基于卫星影像的农田面状信息获取技术克服了点状信息的不足,为农业生产管理决策及时提供信息支持,使该研究技术更利于大面积应用和推广。

基于单通道算法的HJ-1B与Landsat 5 TM地表温度反演一致性研究

针对传感器参数与Landsat 5 TM较为相近的环境减灾卫星HJ-1B的热红外数据是否能达到与TM6反演地表温度同样的效果的问题,作者获取了2009年4月15日覆盖北京地区相同范围的HJ-1B影像和Landsat 5 TM影像,采用Ji m啨nez-Mu oz和Sobrino的普适性单通道算法,通过遥感数据获取反演参数,对研究区的地表温度进行反演,并对两类数据反演结果的一致性进行了分析和评价。通过对反演结果的统计分析和分级填图表明,基于普适性单通道算法的HJ-1B与TM的热红外波段反演的地表温度在数值上和空间分布趋势上一致性较高。因此,具有较高时间分辨率和较大幅宽等优势的HJ-1B IRS数据在地表温度反演方面具有更大的潜力和应用范围。

使用LANDSAT-5TM数据反演金塔地表温度

使用Landsat-5 TM的热红外波段资料,用Weng等、Qin等及Jimenez Mu^noz等三种不同的方法对金塔地区地表温度进行反演,并将反演得到的结果与实测值进行比较。结果表明,三种方法均能较好地反演出金塔绿洲地表温度的分布状况,其中,Weng等及Qin等的反演方法反演的结果较好,绝对误差均<1.9°C;而Jimenez Mu^noz等的方法反演的结果较差。

基于Landsat TM影像的冬小麦拔节期主要长势参数遥感监测

【目的】强化冬小麦长势遥感监测机制,为田间生产管理提供信息支撑。【方法】以2007—2009年试验实测数据为基础,以Landsat TM影像为数据源,分析试验样点拔节期冬小麦主要长势参数与品质、产量以及卫星遥感变量间的相关性,分别建立及评价了TM影像遥感变量监测冬小麦拔节期叶面积指数(LAI)、生物量、SPAD值和叶片氮含量(LNC)的模型。【结果】冬小麦拔节期,选用中红外波段的反射率(B5)、归一化植被指数(NDVI)、DSW5和绿波段的反射率(B2)等遥感变量分别反演冬小麦的SPAD值、生物量、LAI和LNC是可行的;SPAD值、生物量、LAI和LNC遥感监测模型的精度较高,以此为基础,制作出了具有实际农学意义的冬小麦拔节期不同等级SPAD值、生物量、LAI和LNC遥感监测专题图,实现了主要长势参数空间分布量化表达。【结论】研究结果可为广大农学家、农业部门决策者和田间管理人员提供及时的农情信息。

基于Landsat TM图像的北京城市地表温度遥感反演研究

利用北京地区LandsatTM热红外波段数据,采用单通道算法反演得到北京地区地面温度分布图。从反演结果可以看出,北京城区地面温度比郊区地表温度高,郊区地表温度较低,密云水库、官厅水库等水体的温度最低,总体上北京城市热岛效应显著。地表比辐射率是通过Van经验公式反演得到,通过对比分析,表明该方法对自然地表的比辐射率反演效果较好。

基于Landsat TM数据的北京城市热岛研究

利用Landsat TM热红外波段数据,根据辐射传输方程反演得到北京地区地表温度,讨论了北京城市热岛现象及其与土地覆盖类型和植被指数的关系。结果显示,北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近郊区和远郊区地表温度分别高出4.5℃和9℃,城市热岛效应明显。城区不同地表覆盖类型的地表温度也有显著差异,城市地表温度与NDVI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。