Update and spatial extension of strategic forest inventories using time series remote sensing and modeling     

《International Journal of Applied Earth Observation and Geoinformation》2020

Up-to-date forest inventory information relating the characteristics of managed and natural forests is fundamental to sustainable forest management and required to inform conservation of biodiversity and assess climate change impacts and mitigation opportunities. Strategic forest inventories are difficult to compile over large areas and are often quickly outdated or spatially incomplete as a function of their long production cycle. As a consequence, automated approaches supported by remotely sensed data are increasingly sought to provide exhaustive spatial coverage for a set of core attributes in a timely fashion. The objective of this study was to demonstrate the integration of current remotely-sensed data products and pre-existing jurisdictional inventory data to map four forest attributes of interest (stand age, dominant species, site index, and stem density) for a 55 Mha study region in British Columbia, Canada. First, via image segmentation, spectrally homogenous objects were derived from Landsat surface-reflectance pixel composites. Second, a suite of Landsat-based predictors (e.g., spectral indices, disturbance history, and forest structure) and ancillary variables (e.g., geographic, topographic, and climatic) were derived for these units and used to develop predictive models of target attributes. For the often difficult classification of dominant species, two modelling approaches were compared: (a) a global Random Forests model calibrated with training samples collected over the entire study area, and (b) an ensemble of local models, each calibrated with spatially constrained local samples. Accuracy assessment based upon independent validation samples revealed that the ensemble of local models was more accurate and efficient for species classification, achieving an overall accuracy of 72% for the species which dominate 80% of the forested areas in the province. Results indicated that site index had the highest agreement between predicted and reference (R² = 0.74, %RMSE = 23.1%), followed by stand age (R² = 0.62, %RMSE = 35.6%), and stem density (R² = 0.33, %RMSE = 65.2%). Inventory attributes mapped at the image-derived unit level captured much finer details than traditional polygon-based inventory, yet can be readily reassembled into these larger units for strategic forest planning purposes. Based upon this work, we conclude that in a multi-source forest monitoring program, spatially localized and detailed characterizations enabled by time series of Landsat observations in conjunction with ancillary data can be used to support strategic inventory activities over large areas.  相似文献   

The 2019 Brumadinho tailings dam collapse: Possible cause and impacts of the worst human and environmental disaster in Brazil     

《International Journal of Applied Earth Observation and Geoinformation》2020

On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed catastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13 × 10⁶ m²), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream.  相似文献   

分布式光纤声波传感器及其在天然地震学研究中的应用     

张丽娜  任亚玲  林融冰  宋政宏  曾祥方 《地球物理学进展》2020,(1):65-71

分布式光纤声波传感器(Distributed Acoustic Sensing,DAS)是近年来兴起的超密集地震观测系统,具有一系列观测密度高、观测成本低、耐受恶劣环境等优势,在油气行业得到了广泛应用,也引起了天然地震学界的关注.本文简要回顾了DAS系统的测量原理、发展历程、技术方案、介绍了测量原理及其响应特性,然后围绕多个观测实验,介绍浅部结构成像、深部结构探测和地震监测三个方向的典型应用实例,最后讨论了DAS系统在天然地震学研究中应用面临的挑战和发展趋势.  相似文献   

基于长时间序列遥感数据的阿伯德尔国家公园 生态环境质量评价     

王法溧  何晓宇  方泽兴  魏显虎  叶虎平  施令飞 《地球信息科学学报》2019,21(9):1479-1479

阿伯德尔国家公园位于号称肯尼亚“水塔”的阿伯德尔山脉上,是肯尼亚重要的旅游景区和珍稀动植物保护区,开展该地生态环境质量评价对肯尼亚水资源保护与可持续发展具有重要的意义。本研究基于1987-2018年的Landsat系列遥感数据,通过计算综合遥感生态指数RSEI,结合趋势线分析法对阿伯德尔国家公园近32年间生态环境质量变化进行客观定量分析。研究结果显示：① 1987-2018年研究区RSEI均值从0.62下降到0.51,生态环境质量退化的区域面积为551.52 km ²,占总面积的71.85%,表明在气候变化和人类活动影响下,1987-2018年研究区的环境状况呈恶化趋势;②环境质量显著恶化的区域主要分布于亚高山植被区和东部低海拔森林覆盖区,亚高山地区植被生态系统结构单一,稳定性差,对气候变化和人类活动更为敏感;而东部区域存在过度开发,非法砍伐森林等现象,且旅游开发强度大,环境恶化与人类活动密切相关。  相似文献   

Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns     

《International Journal of Applied Earth Observation and Geoinformation》2020

To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R² = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R² = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km² due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R² = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R² = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km²–100 km²). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R² = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R² = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.  相似文献   

Estimating fractional cover of crop,crop residue,and soil in cropland using broadband remote sensing data and machine learning     

《International Journal of Applied Earth Observation and Geoinformation》2020

The fractional vegetation cover (FVC), crop residue cover (CRC), and bare soil (BS) are three important parameters in vegetation–soil ecosystems, and their correct and timely estimation can improve crop monitoring and environmental monitoring. The triangular space method uses one CRC index and one vegetation index to create a triangular space in which the three vertices represent pure vegetation, crop residue, and bare soil. Subsequently, the CRC, FVC, and BS of mixed remote sensing pixels can be distinguished by their spatial locations in the triangular space. However, soil moisture and crop-residue moisture (SM-CRM) significantly reduce the performance of broadband remote sensing CRC indices and can thus decrease the accuracy of the remote estimation and mapping of CRC, FVC, and BS. This study evaluated the use of broadband remote sensing, the triangular space method, and the random forest (RF) technique to estimate and map the FVC, CRC, and BS of cropland in which SM-CRM changes dramatically. A spectral dataset was obtained using: (1) from a field-based experiment with a field spectrometer; and (2) from a laboratory-based simulation that included four distinct soil types, three types of crop residue (winter-wheat, maize, and rice), one crop (winter wheat), and varying SM-CRM. We trained an RF model [designated the broadband crop-residue index from random forest (CRRF)] that can magnify spectral features of crop residue and soil by using the broadband remote sensing angle indices as input, and uses a moisture-resistant hyperspectral index as the target. The effects of moisture on crop residue and soil were minimized by using the broadband CRRF. Then, the CRRF-NDVI triangular space method was used to estimate and map CRC, FVC, and BS. Our method was validated by using both laboratory- and field-based experiments and Sentinel-2 broadband remote-sensing images. Our results indicate that the CRRF-NDVI triangular space method can reduce the effect of moisture on the broadband remote-sensing of CRC, and may also help to obtain laboratory and field CRC, FVC, and BS. Thus, the proposed method has great potential for application to croplands in which the SM-CRM content changes dramatically.  相似文献   

Discussion on establishing monitoring networks for temperature fields of shallow thermal energy in Shandong,China          下载免费PDF全文

ZHOU Bo  WEI Shan-ming  WANG Tao  NIE Yu-peng  WANG Chuan-qi 《地下水科学与工程》2019,7(1):86-93

In the recent decade, the construction projects related to shallow geothermal energy engineering have undergone rapid development in Shandong Province. The predominant type of these developments and applications was heat exchange through buried tubes and the main targets were residential and office buildings. However, an overwhelming majority of the completed geothermal heat pump projects lacked monitoring devices so that they were unable to comprehensively reflect the background values for the geothermal fields within the province and few researches were conducted on their influence on the geological environment. In this paper, locations for monitoring shallow geothermal energy and their validity of the monitoring point deployment were studied in view of the development and application status as well as geological background conditions of various projects located in multiple cities providing data support for analyzing the fluctuation trend and influence of large-scale shallow geothermal energy applications on the shallow geothermal and the feasibility and parameter designs of newly built systems in Shandong Province in the future.  相似文献   

Main progress and prospect for China's hydrogeological survey          下载免费PDF全文

WU Ai-min  HAO Ai-bing  GUO Hai-peng  LIU Jing-tao  ZHANG Er-yong  WANG Huang  WANG Xin-feng  WEN Xue-ru  ZHANG Cui-guang 《地下水科学与工程》2020,8(3):195-209

This paper reviewed the main achievements of hydrogeological survey in China, summarized the significant progress of hydrogeological survey over the past decade, and forecasted the key responsibilities for hydrogeological survey in the p14th Five-year Planq. The significant progress includes: China established the 1: 50 000 standard hydrogeological survey system with Chinese characteristics and produced the new generation of high-quality hydrogeological maps; the national groundwater monitoring project was completed and accepted, which marks China taking the leading position in groundwater monitoring internationally; fruitful results were achieved in the national groundwater quality survey, and groundwater quality background values were basically identified and checked; hydrogeological and environmental geological survey was continuously promoted in karst areas and the ecological restoration of rocky desertification achieved remarkable results; China strengthened layer exploration techniques for groundwater, integrating the key and practical techniques of layer exploration and monitoring; the exploration of groundwater in the poverty-stricken regions and old revolutionary base areas were effectively promoted to strongly guarantee the poverty alleviation and drinking water safety; the mystery of desert groundwater was uncovered, making up for the shortage of 1: 250 000 hydrogeological survey in the Badain Jaran Desert; and more efforts were made to conduct survey on the water resources in the basin, and to finish the unified measurement of national-scale groundwater level.  相似文献   

Estimation of groundwater storage from seismic data using deep learning     

Timo Lähivaara  Alireza Malehmir  Antti Pasanen  Leo Kärkkäinen  Janne M.J. Huttunen  Jan S. Hesthaven 《Geophysical Prospecting》2019,67(8):2115-2126

Convolutional neural networks can provide a potential framework to characterize groundwater storage from seismic data. Estimation of key components, such as the amount of groundwater stored in an aquifer and delineate water table level, from active-source seismic data are performed in this study. The data to train, validate and test the neural networks are obtained by solving wave propagation in a coupled poroviscoelastic–elastic media. A discontinuous Galerkin method is applied to model wave propagation, whereas a deep convolutional neural network is used for the parameter estimation problem. In the numerical experiment, the primary unknowns estimated are the amount of stored groundwater and water table level, while the remaining parameters, assumed to be of less of interest, are marginalized in the convolutional neural network-based solution. Results, obtained through synthetic data, illustrate the potential of deep learning methods to extract additional aquifer information from seismic data, which otherwise would be impossible based on a set of reflection seismic sections or velocity tomograms.  相似文献   

Intra-survey reservoir fluctuations – implications for quantitative 4D seismic analysis     

Veronica Omofoma  Colin MacBeth  Hamed Amini 《Geophysical Prospecting》2019,67(2):282-297

During the time taken for seismic data to be acquired, reservoir pressure may fluctuate as a consequence of field production and operational procedures and fluid fronts may move significantly. These variations prevent accurate quantitative measurement of the reservoir change using 4D seismic data. Modelling studies on the Norne field simulation model using acquisition data from ocean-bottom seismometer and towed streamer systems indicate that the pre-stack intra-survey reservoir fluctuations are important and cannot be neglected. Similarly, the time-lapse seismic image in the post-stack domain does not represent a difference between two states of the reservoir at a unique base and monitor time, but is a mixed version of reality that depends on the sequence and timing of seismic shooting. The outcome is a lack of accuracy in the measurement of reservoir changes using the resulting processed and stacked 4D seismic data. Even for perfect spatial repeatability between surveys, a spatially variant noise floor is still anticipated to remain. For our particular North Sea acquisition data, we find that towed streamer data are more affected than the ocean-bottom seismometer data. We think that this may be typical for towed streamers due to their restricted aperture compared to ocean-bottom seismometer acquisitions, even for a favourable time sequence of shooting and spatial repeatability. Importantly, the pressure signals on the near and far offset stacks commonly used in quantitative 4D seismic inversion are found to be inconsistent due to the acquisition timestamp. Saturation changes at the boundaries of fluid fronts appear to show a similar inconsistency across sub-stacks. We recommend that 4D data are shot in a consistent manner to optimize aerial time coverage, and that additionally, the timestamp of the acquisition should be used to optimize pre-stack quantitative reservoir analysis.  相似文献