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Rubber (Hevea brasiliensis) tree cultivation is being continuously expanded northward by replacing evergreen forests and swidden-related regenerated vegetation across the uplands of mainland Southeast Asia (MSEA), e.g., Laos, a landlocked mountainous country. The non-native tree establishment in the northern tropical edge, or the non-traditional suitable planting area, provides stable supplies of natural latex, yet also leads to severe ecological degradation and environmental effects in water conservation, soil quality, rainforest fragmentation and biodiversity. Rubber plantations in the northern part of MSEA are normally characterized by periodic deciduous during the dry season, along with a lengthy defoliation-foliation duration, because of seasonal variations in temperature and precipitation. It thus lays a phenological and physiological base for dynamics monitoring with common multispectral (e.g., near-infrared and short-wave infrared bands) satellites, particularly Landsat. However, whether Sentinel-2 red-edge based algorithms are suitable for discriminating rubber plantations is not yet exclusively reported. Here, we developed a red-edge spectral indices (RESI) method through the normalization of three red-edge bands and applied it to identify and map rubber plantations in Luang Namtha Province of northern Laos, where a rubber boom begun in the mid-2000s. The RESI algorithm highlights the sensitivity of red-edge bands to the changes in moisture content and canopy density of rubber plantations. The area of mature rubber plantations was estimated to be 771.2 km2 in this province bordering southwest China in 2018, which was nearly twice as much as that of 2011, with the overall accuracy and kappa coefficient up to 92.50% and 0.91, respectively. Our phenology-based RESI approach not only indicates that Sentinel-2 imagery holds significant potential for monitoring rubber plantations, but also improves the remotely-sensed methods of rubber boom mapping via introducing the red-edge channel. 相似文献
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《International Journal of Digital Earth》2013,6(3):307-323
ABSTRACTForests of the Sierra Nevada (SN) mountain range are valuable natural heritages for the region and the country, and tree height is an important forest structure parameter for understanding the SN forest ecosystem. There is still a need in the accurate estimation of wall-to-wall SN tree height distribution at fine spatial resolution. In this study, we presented a method to map wall-to-wall forest tree height (defined as Lorey’s height) across the SN at 70-m resolution by fusing multi-source datasets, including over 1600 in situ tree height measurements and over 1600?km2 airborne light detection and ranging (LiDAR) data. Accurate tree height estimates within these airborne LiDAR boundaries were first computed based on in situ measurements, and then these airborne LiDAR-derived tree heights were used as reference data to estimate tree heights at Geoscience Laser Altimeter System (GLAS) footprints. Finally, the random forest algorithm was used to model the SN tree height from these GLAS tree heights, optical imagery, topographic data, and climate data. The results show that our fine-resolution SN tree height product has a good correspondence with field measurements. The coefficient of determination between them is 0.60, and the root-mean-squared error is 5.45?m. 相似文献
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高精度曲面建模应用中边界误差解决方案 总被引：2，自引：1，他引：1
提出一种SAR数据检测桥面高度的反演方法。用几何射线描述桥梁散射机制, 依据去取向理论和分类参数分析, 得到SAR成像中桥梁结构目标单次、二次、三次散射的成像规律。通过SAR图像分类参数的聚类与细化、滤波和Hough变换直线检测算法, 检测出单次、二次和三次散射回波所成位置线图像, 进一步构成桥面高度的反演算法。用机载Pi-SAR数据反演了日本鸣门大桥的桥面高度和桥面宽度, 并与实测数据对比。按照该方法, 进一步采用星载ALOS-PALSAR数据检测中国东海大桥的桥面高度。反演方法是可行的。 相似文献
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Advanced analysis of differences between C and X bands using SRTM data for mountainous topography 总被引：1，自引：0，他引：1
Umut Güneş Sefercik Mehmet Alkan 《Journal of the Indian Society of Remote Sensing》2009,37(3):335-349
By Interferometric Synthectic Aperture Radar (InSAR), during the Shuttle Radar Topography Mission (SRTM) height models have
been generated, covering the earth surface from 56° south to 60.25° north. With the exception of small gaps in steep parts,
dry sand deserts and water surfaces, the free available US C-band data cover the earth surface from 56° south to 60.25° north
completely while the X-band data, distributed by the DLR (German Aerospace Center), cover it only partially. The C-band and
X-band radar cannot penetrate the vegetation because of the short wavelength. Therefore, the height models are not Digital
Elevation Models (DEM) representing bare Earth surface without any details, they are Digital Surface Models (DSM) representing
the visible surface including vegetation and buildings. In the area of Zonguldak, Turkey, C-band and X-band DSMs are available
and have been analysed in cooperation between Zonguldak Karaelmas University (ZKU) and Leibniz University of Hannover. The
digitized contour lines from the 1:25,000 scale topographic maps and also a more precise height model derived directly from
large scale photogrammetric mapping are used as reference height models.
The terrain inclination influences the accuracy strongly, but also the directions of the inclination in relation to the radar
view direction, the aspects, are important. Independent from the aspects, the analysed results do have root mean square differences
against the reference data fitting very well to the Koppe formula SZ=a+b*tan α. The analyses are made separately for open
and forest areas, with clear accuracy differences between both. Also, the analysis of X-band separately for three sub-areas
is done and the positive effect of double observation to the accuracy has been clearly determined. The C-band data are only
available with a spacing of 3 arcsec, corresponding to 92m × 70m, while the X-band data do have a spacing of 1 arcsec. This
is important for the interpolation in the mountainous test area. The accuracy of the height points is approximately the same
for the C- and the X-band data. But the C-band data which have three times larger spacing than Xband data, do not include
the same morphological information. While C-band data contain very generalised contour lines X-band data have quite more details
depending on 1 arcsec point spacing. The differential DEMs have been generated, separately, for displaying the differences
between SRTM height models and reference DEMs of the test field. 相似文献
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林木空间格局对大光斑激光雷达波形的影响模拟 总被引：5，自引：1，他引：5
激光雷达是近年来国际上发展十分迅速的主动遥感技术，在森林参数的定量测量和反演上取得了成功应用。激光雷达具有与被动光学遥感不同的成像机理，对植被空间结构和地形的探测能力很强。大光斑激光雷达系统一般指光斑直径在8—70m、连续记录激光回波波形的激光雷达系统。由于大光斑连续回波的激光雷达的光斑尺寸通常大于林木冠幅，波形中往往包含了森林冠层和许多森林元素的信息而不仅仅是单株树的信息。对于搭载在ICESAT卫星上的GLAS而言，光斑直径为70m，因此光斑对应着一片森林，包括很多棵树，在GLAS的激光光斑内树木的空间分布会有一定变化。同时激光雷达发射的脉冲信号在激光光斑内的分布也不均匀，而是从中心到边缘呈递减的分布。因此树木空间分布模式的变化对波形会产生一定的影响。通过对几种典型的树木空间格局进行模拟（包括规则分布、均匀（随机）分布和集群分布），假定激光光斑内能量呈高斯分布，模拟了各种树木分布模式林分的激光雷达信号。从模拟结果可见，森林的空间分布模式对大光斑激光雷达波形有明显的影响，对于波形面积（AWAV）和波形半能量高度（HOME），规则分布〉随机分布〉团状分布。其中对于HOME而言，规则分布和随机分布十分接近，而对于AWAV而言，聚集中心的变动不太敏感。 相似文献
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Yanqiu Xing Alfred de Gier Junjie Zhang Lihai Wang 《International Journal of Applied Earth Observation and Geoinformation》2010
Light Detection And Ranging (LiDAR) has a unique capability for estimating forest canopy height, which has a direct relationship with, and can provide better understanding of the aboveground forest carbon storage. The full waveform data of the large-footprint LiDAR Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat), combined with field measurements of forest canopy height, were employed to achieve improved estimates of forest canopy height over sloping terrain in the Changbai mountains region, China. With analyzing ground-truth experiments, the study proposed an improved model over Lefsky's model to predict maximum canopy height using the logarithmic transformation of waveform extent and elevation change as independent variables. While Lefsky's model explained 8–89% of maximum canopy height variation in the study area, the improved model explained 56–92% of variation within the 0–30° terrain slope category. The results reveal that the improved model can reduce the mixed effects caused by both sloping terrain and rough land surface, and make a significant improvement for accurately estimating maximum canopy height over sloping terrain. 相似文献
8.
针对X波段导航雷达对海杂波的成像,研究了利用多谱勒频移和布拉格散射来探测海表面流的方法。提出了一种结合几何滤波模型的X波段雷达海流反演预处理算法,此算法不需要已知的最大海流流速进行带通滤波处理,结合线性波理论色散方程以及最小二乘算法,可以得到精确的海表面流速。与传统的X波段导航雷达测流方法相比,该算法简单高效,占用资源少,并且不仅适用于岸基X波段导航雷达,还适用于船载X波段导航雷达。与附近站点高频地波雷达表面流数据进行对比实验,二者结果的一致性表明了本文方法是可行的。 相似文献
9.
I. N. Tziavos 《Journal of Geodesy》1996,70(6):357-373
The Stokes formula is efficiently evaluated by the one-and two- dimensional (1D, 2D) fast Fourier transform (FFT) technique in the plane and on the sphere in order to obtain precise geoid determinatiover a large area such as Europe. Using a high-pass filtered spherical harmonic reference model (OSU91A truncated to different degrees), gridded gravity anomalies and geoid heights were produced and the anomalies were used as input in the FFT software. Various tests were performed with respect to the different kernel functions used, to the spherical computations in bands, as well as to windowing, edge effects and extent of the area. It is thus demonstrated that, in geoid computations over large regions, the 1D spherical FFT and the 2D multiband spherical FFT in combination with discrete spectra for the kernel functions and 100% zero-padding give better results than those obtained by the other transform techniques. Additionally, numerical tests were carried out at the same test area using the planar fast Hartley transform (FHT) instead of the FFT and the results obtained by the two attractive alternatives were compared regarding the requirements in both computer time and computer memory needed in geoid height computations.A slightly modified version of the paper has been presented at the XX EGS General Assembly, Hamburg, 3–7 April, 1995 相似文献
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应用面向对象的决策树模型提取橡胶林信息 总被引：4，自引：0，他引：4
橡胶林的无序和不合理种植引发了一系列的生态问题,快速监测橡胶林空间分布及动态变化,对橡胶的合理种植、区域生态环境保护以及有关部门的规划决策有重要的指导意义。以MODIS归一化植被指数NDVI时间序列数据和多时相的Landsat TM数据为基础分析橡胶林的季相和光谱特征,确定橡胶识别的关键时期和特征参数,构建面向对象的决策树分类模型,开展橡胶信息提取研究。结果表明,多时相的遥感数据可反映橡胶的季相特征,以TM数据为基础计算得到的陆表水分指数LSWI和归一化植被指数NDVI可作为橡胶识别的光谱特征参数,橡胶休眠期是利用遥感方法进行橡胶提取的最佳时期。相比于单时相数据,利用包含橡胶关键物候期的多时相遥感数据能得到更高的橡胶林提取精度。 相似文献
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Forest monitoring tools are needed to promote effective and data driven forest management and forest policies. Remote sensing techniques can increase the speed and the cost-efficiency of the forest monitoring as well as large scale mapping of forest attribute (wall-to-wall approach). Digital Aerial Photogrammetry (DAP) is a common cost-effective alternative to airborne laser scanning (ALS) which can be based on aerial photos routinely acquired for general base maps. DAP based on such pre-existing dataset can be a cost effective source of large scale 3D data. In the context of forest characterization, when a quality Digital Terrain Model (DTM) is available, DAP can produce photogrammetric Canopy Height Model (pCHM) which describes the tree canopy height. While this potential seems pretty obvious, few studies have investigated the quality of regional pCHM based on aerial stereo images acquired by standard official aerial surveys. Our study proposes to evaluate the quality of pCHM individual tree height estimates based on raw images acquired following such protocol using a reference filed-measured tree height database. To further ensure the replicability of the approach, the pCHM tree height estimates benchmarking only relied on public forest inventory (FI) information and the photogrammetric protocol was based on low-cost and widely used photogrammetric software. Moreover, our study investigates the relationship between the pCHM tree height estimates based on the neighboring forest parameter provided by the FI program.Our results highlight the good agreement of tree height estimates provided by pCHM using DAP with both field measured and ALS tree height data. In terms of tree height modeling, our pCHM approach reached similar results than the same modeling strategy applied to ALS tree height estimates. Our study also identified some of the drivers of the pCHM tree height estimate error and found forest parameters like tree size (diameter at breast height) and tree type (evergreenness/deciduousness) as well as the terrain topography (slope) to be of higher importance than image survey parameters like the variation of the overlap or the sunlight condition in our dataset. In combination with the pCHM tree height estimate, the terrain slope, the Diameter at Breast Height (DBH) and the evergreenness factor were used to fit a multivariate model predicting the field measured tree height. This model presented better performance than the model linking the pCHM estimates to the field tree height estimates in terms of r² (0.90 VS 0.87) and root mean square error (RMSE, 1.78 VS 2.01 m). Such aspects are poorly addressed in literature and further research should focus on how pCHM approaches could integrate them to improve forest characterization using DAP and pCHM. Our promising results can be used to encourage the use of regional aerial orthophoto surveys archive to produce large scale quality tree height data at very low additional costs, notably in the context of updating national forest inventory programs. 相似文献
14.
以浙江省海宁市4种代表行道树(广玉兰、无患子、悬铃木、香樟树)为研究对象,结合无人机(UAV)影像和三维激光扫描数据,利用ContextCapture、LiDAR360软件完成点云拼接、滤波、降噪和编辑,通过迭代最近点算法实现点云精细匹配,完成多平台点云数据融合,进而得到数字表面模型与数字高程模型,并制作冠层高度模型;采用分水岭分割算法对不同行道树树种的冠层高度模型进行单木分割,并综合局部最大值法实现单木树高、冠幅的参数提取。结果表明,本文方法进行行道树单木分割的精度高,树高、冠幅参数提取值的效果好,满足行道树几何参数调查要求。 相似文献
15.
Forest plantations are an important source of terrestrial carbon sequestration. The forest of Robinia pseudoacacia in the Yellow River Delta (YRD) is the largest artificial ecological protection forest in China. However, more than half of the forest has appeared different degrees of dieback and even death since the 1990s. Timely and accurate estimation of the forest aboveground biomass (AGB) is a basis for studying the carbon cycle of forests. Light Detecting and Ranging (LiDAR) has been proved to be one of the most powerful methods for forest biomass estimation. However, because of an irregular and overlapping shape of the broadleaved forest canopy in a growing season, it is difficult to segment individual trees and estimate the tree biomass from airborne LiDAR data. In this study, a new method was proposed to solve this problem of individual tree detection in the Robinia pseudoacacia forest based on a combination of the Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) with the Backpack-LiDAR. The proposed method mainly consists of following steps: (i) at a plot level, trees in the UAV-LiDAR data were detected by seed points obtained by an individual tree segmentation (ITS) method from the Backpack-LiDAR data; (ii) height and diameter at breast height (DBH) of an individual tree would be extracted from UAV and Backpack LiDAR data, respectively; (iii) the individual tree AGB would be calculated through an allometric equation and the forest AGB at the plot level was accumulated; and (iv) the plot-level forest AGB was taken as a dependent variable, and various metrics extracted from UAV-LiDAR point cloud data as independent variables to estimate forest AGB distribution in the study area by using both multiple linear regression (MLR) and random forest (RF) models. The results demonstrate that: (1) the seed points extracted from Backpack-LiDAR could significantly improve the overall accuracy of individual tree detection (F = 0.99), and thus increase the forest AGB estimation accuracy; (2) compared with MLR model, the RF model led to a higher estimation accuracy (p < 0.05); and (3) LiDAR intensity information selected by both MLR and RF models and laser penetration rate (LP) played an important role in estimating healthy forest AGB. 相似文献
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K. S. Rao S. M. Phalke Jyoti Sarup H. K Al-Jassar 《Journal of the Indian Society of Remote Sensing》2006,34(4):369-375
The first data set of X-band Digital Elevation Model (DEM), derived from Shuttle Radar Topography Mission (SRTM), of Gujarat
Earthquake affected area was processed to assess the geo-coding and height accuracy. A detailed survey of the study area was
carried out using Differential-GPS systems to get accurate control points. Though, it is the first data set processed without
Attitude and Orbit Determination Avionics, the geo-coding and height accuracy is good. It is observed that there is an average
shift of-1.5 pixels in Latitude and 2.5 pixels in Longitude with 1.5 pixels Standard Deviation (STD). A comparison of SRTM
and Differential-GPS heights indicates that there is a bias of 7.4 m with STD of 3.4 m. This is in agreement with the height
errors reported by the Deutschen Zentrums fur Luft- und Raumfahrt (DLR) in Height Error Map (HEM) data set. 相似文献
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Monoculture rubber plantations have been replacing tropical rain forests substantially in Southern China and Southeast Asia over the past several decades, which have affected human wellbeing and ecosystem services. However, to the best of our knowledge on the extent of rubber plantation expansion and their stand ages is limited. We tracked the spatiotemporal dynamics of deciduous rubber plantations in Xishuangbanna, the second largest natural rubber production region in China, from 2000 to 2010 using time-series data from the Phased Array type L-band Synthetic Aperture Radar (PALSAR), Landsat, and Moderate Resolution Imaging Spectroradiometer (MODIS). We found that rubber plantations have been expanding across a gradient from the low-elevation plains to the high elevation mountains. The areas of deciduous rubber plantations with stand ages ≤5, 6–10, and ≥11-year old were ~1.2 × 105 ha, ~0.8 × 105 ha, and ~2.9 × 105 ha, respectively. Older rubber plantations were mainly located in low-elevation and species-rich regions (500–900 m) and younger rubber trees were distributed in areas of relative high-elevation with fragile ecosystems. Economic and market factors have driven the expansion of rubber plantations, which is not only a threat to biodiversity and environmental sustainability, but also a trigger for climatic disasters. This study illustrates that the integration of microwave, optical, and thermal data is an effective method for mapping deciduous rubber plantations in tropical mountainous regions and determining their stand ages. Our results demonstrate the spatiotemporal pattern of rubber expansions over the first decade of this century. 相似文献
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Quantitative estimates of forest vertical and spatial distribution using remote sensing technology play an important role in better understanding forest ecosystem function, forest carbon storage and the global carbon cycle. Although most remote sensing systems can provide horizontal distribution of canopies, information concerning the vertical distribution of canopies cannot be detected. Fortunately, laser radars have become available, such as GLAS (Geoscience laser altimeter system). Because laser radar can penetrate foliage, it is superior to other remote sensing technologies for detecting vertical forest structure and has higher accuracy. GLAS waveform data were used in this study to retrieve average tree height and biomass in a GLAS footprint area in Heilongjiang Province. However, GLAS data are not spatially continuous. To fill the gaps, MISR (multi- angle imaging spectrometer) spectral radiance was chosen to predict the regional continuous tree height by developing a multivariate linear regression model. We compared tree height estimated by the regression model and GLAS data. The results confirmed that estimates of tree height and biomass based on GLAS data are considerably more accurate than estimates based on traditional methods. The accuracy is approximately 90%. MISR can be used to estimate tree height in continuous areas with a robust regression model. The R2, precision and root mean square error of the regression model were 0.8, 83% and 1 m, respectively. This study provides an important reference for mapping forest vertical parameters. 相似文献
19.
Forest structural diversity metrics describing diversity in tree size and crown shape within forest stands can be used as indicators of biodiversity. These diversity metrics can be generated using airborne laser scanning (LiDAR) data to provide a rapid and cost effective alternative to ground-based inspection. Measures of tree height derived from LiDAR can be significantly affected by the canopy conditions at the time of data collection, in particular whether the canopy is under leaf-on or leaf-off conditions, but there have been no studies of the effects on structural diversity metrics. The aim of this research is to assess whether leaf-on/leaf-off changes in canopy conditions during LiDAR data collection affect the accuracy of calculated forest structural diversity metrics. We undertook a quantitative analysis of LiDAR ground detection and return height, and return height diversity from two airborne laser scanning surveys collected under leaf-on and leaf-off conditions to assess initial dataset differences. LiDAR data were then regressed against field-derived tree size diversity measurements using diversity metrics from each LiDAR dataset in isolation and, where appropriate, a mixture of the two. Models utilising leaf-off LiDAR diversity variables described DBH diversity, crown length diversity and crown width diversity more successfully than leaf-on (leaf-on models resulted in R² values of 0.66, 0.38 and 0.16, respectively, and leaf-off models 0.67, 0.37 and 0.23, respectively). When LiDAR datasets were combined into one model to describe tree height diversity and DBH diversity the models described 75% and 69% of the variance (R² of 0.75 for tree height diversity and 0.69 for DBH diversity). The results suggest that tree height diversity models derived from airborne LiDAR, collected (and where appropriate combined) under any seasonal conditions, can be used to differentiate between simple single and diverse multiple storey forest structure with confidence. 相似文献
20.
This study scrutinises the use of terrestrial laser scanning (TLS) to measure diameter at breast height (DBH) and tree height at individual tree species level. LiDAR point cloud scans are collected from uniformly defined control points. The result of processed TLS data demonstrates the precise measurements of tree height and DBH by comparing it with field data (DBH, tree height, tree species and location). The average tree height and DBH obtained through TLS measurements were 9.44?m and 43.30?cm, respectively. A linear equation between TLS derived parameters and field measured values were established, which gave the coefficient of determination (r2) of 0.79 and 0.96 for tree height and DBH, respectively. Further, these parameters were used to calculate above ground biomass (AGB) for individual tree species by considering a non-destructive approach. The total AGB and carbon stock from 80 different trees are computed to be 49.601 and 22.320?tonnes, respectively. 相似文献