Satellite-based monitoring and statistics for raft and cage aquaculture in China’s offshore waters

Based on Landsat 8 remote sensing images, a combination of an unsupervised classification algorithm and artificial review was used to extract areas for Chinese offshore raft and cage aquaculture in 2018. The results of the extraction showed that China’s 2018 coastal zone raft aquaculture area comprised 194,110 ha, of which the province having the largest raft aquaculture area was Jiangsu (28.77 %), followed by Fujian (20.42 %) and Shandong (13.11 %). The cage aquaculture area covered 57,847,799 square meters, of which the provinces with the largest cage aquaculture area were Fujian (64.81 %), Guangdong (17.45 %), and Liaoning (5.63 %). In addition, by combining high-resolution remote sensing image visual interpretation and field investigation, the classification of 1200 sample points in four regions was determined, and the accuracy of the aquaculture area extraction was found to be 87.35 %. The extraction results can be used not only to evaluate China’s aquaculture production but also offer significant reference value for scientific planning related to sea use, ecological environmental protection, and marine disaster prevention and mitigation.     

TM数据的Kauth-Thomas变换在盐渍土分析中的作用——以阳高盆地为例

本文就经过Kauth-Thomas变换的TM数据用于雁北阳高盆地盐渍化程度分析进行了探讨。通过模拟TM数据和TM影像数据进行变换分析,并与标准假彩色合成和K-L变换比较,取得了较好的结果。     

An ensemble pansharpening approach for finer-scale mapping of sugarcane with Landsat 8 imagery

We tested the effects of three fast pansharpening methods – Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Additive Wavelet Transform (AWT) – on sugarcane classification in a Landsat 8 image (bands 1–7), and proposed two ensemble pansharpening approaches (band stacking and band averaging) which combine the pixel-level information of multiple pansharpened images for classification. To test the proposed ensemble pansharpening approaches, we classified “sugarcane” and “other” land cover in the unsharpened Landsat multispectral image, the individual pansharpened images, and the band-stacked and band-averaged ensemble images using Support Vector Machines (SVM), and assessed the classification accuracy of each image. Of the individual pansharpened images, the AWT image achieved higher classification accuracy than the unsharpened image, while the IHS and BT images did not. The band-stacked ensemble images achieved higher classification accuracies than the unsharpened and individual pansharpened images, with the IHS-BT-AWT band-stacked image producing the most accurate classification result, followed by the IHS-BT band-stacked image. The ensemble images containing averaged pixel values from multiple pansharpened images achieved lower classification accuracies than the band-stacked ensemble images, but most still had higher accuracies than the unsharpened and individual pansharpened results. Our results indicate that ensemble pansharpening approaches have the potential to increase classification accuracy, at least for relatively simple classification tasks. Based on the results of the study, we recommend further investigation of ensemble pansharpening for image analysis (e.g. classification and regression tasks) in agricultural and non-agricultural environments.     

Characterization of aboveground biomass in an unmanaged boreal forest using Landsat temporal segmentation metrics

Canada is dominated by forested ecosystems which are subject to various inventory and management practices, with more northern boreal forests subject to neither. Our objectives were to measure the capacity of temporal trajectory metrics for estimating selected forest attributes in a northern Canadian boreal forest context using Landsat imagery and investigate the importance of different types of temporal trajectory metrics. Results indicated that Wetness was the best Tasseled Cap (TC) component for aboveground biomass estimation (R² = 50%, RMSE% = 56%), and the combination of simple and complex metrics from all TC components produced the highest R² (62%) and lowest RMSE% (49%). Using a similar combination of variables, other forest attributes were estimated equally reliably with lower RMSE% values. The most important temporal trajectory metrics were simple and described TC component values at each point of change in the temporal trajectory, however the most important variables overall were environmental variables.     

基于OSTU算法利用新型水体指数进行Landsat数据自适应阈值水体自动提取研究

利用Landsat数据,结合NDWI与MNDWI提取水体信息的特点提出了一种新的水体指数NMWI,并结合OSTU算法自适应地确定最佳分割阈值,完成了对海洋、河流、湖泊和水库4种主要的典型水体信息的自动提取,均取得了较好的效果。     

Spatiotemporal reflectance blending in a wetland environment

To understand the mechanism of wetland cover change with both moderate spatial resolution and high temporal frequency, this research evaluates the applicability of a spatiotemporal reflectance blending model in the Poyang Lake area, China, using 9 time-series Landsat-5 Thematic Mapper images and 18 time-series Terra Moderate Resolution Imaging Spectroradiometer images acquired between July 2004 and November 2005. The customized blending model was developed based on the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). Reflectance of the moderate-resolution image pixels on the target dates can be predicted more accurately by the proposed customized model than the original ESTARFM. Water level on the input image acquisition dates strongly affected the accuracy of the blended reflectance. It was found that either of the image sets used as prior or posterior inputs are required when the difference of water level between the prior or posterior date and target date at Poyang Hydrological Station is <2.68 m to achieve blending accuracy with a mean average absolute difference of 4% between the observed and blended reflectance in all spectral bands.     

应用TM影像进行大比例尺土地利用类型划分探讨——以花江喀斯特峡谷区示范区为例

通过花江示范区土地利用类型的划分,说明利用TM遥感数据进行喀斯特峡谷区1∶ 10000大比例尺土地利用类型划分中存在的问题,包括混合像元、阴影、同物异谱、同谱异物,以及独特的石旮旯土。根据国家环保局2000年分类标准,结合花江喀斯特峡谷的实际情况,本文采用了RS、GI S和传统勾绘技术相结合的方法进行土地利用类型划分,分类结果表明此方法是可行的,其精度可达89. 65% 。      

1990—2018年中巴经济走廊冰湖时空变化特征

中巴经济走廊是贯通南北丝路的关键枢纽。在全球变暖的背景下, 区域内冰川变化情况复杂, 部分冰川出现前进或跃动现象, 冰湖溃决的风险在不断上升, 进而威胁中巴经济走廊的建设与民生安全。基于1990—2018年Landsat TM/ETM+/OLI遥感影像, 利用目视解译方法提取了中巴经济走廊3期冰湖编目数据, 并分析了28年来该区域内冰湖的总体变化趋势、 空间异质性以及成因。结果表明： 中巴经济走廊目前共发育有2 380个冰湖, 总面积为（131.76±19.08） km², 集中分布于喀喇昆仑山脉和喜马拉雅山脉; 1990—2018年期间, 冰湖总体面积扩张速度为0.48%·a^-1, 但各个山脉不同规模冰湖面积变化差异较大。中巴经济走廊在气温和降水的共同作用下, 区内冰湖面积呈扩张趋势, 同时气温和降水变化率的空间差异使得冰湖面积变化存在空间差异; 冰川的快速退缩增加了区内冰湖溃决的风险。     

采用SilviScan-3TM研究木材性质的方法及其在气候变化研究中的应用

系统介绍了利用SilviScan-3TM测量细胞结构、木材密度、微纤丝角和划分年轮界线的方法,并以祁连山青海云杉为例,分析青海云杉6个木材性质参数(年轮细胞直径、年轮细胞壁厚、年轮宽度、年轮密度、年轮微纤丝角、年轮弹性模量)与气候因子的关系,以期为利用多个树轮参数研究气候提供参考。结果表明:6个木材性质参数与月平均气温和月降水量都有显著相关的月份,但显著相关的时间段不同,并且微纤丝角和细胞结构参数中包含的气候信息强于常用的年轮宽度和年轮密度。SilviScan-3TM测量木材性质参数的优越性体现在:测量精度高、速度快,能在同一个试样上测量多个参数并能精确定年。     

利用Landsat TM6数据反演大亚湾海水表层温度

基于Landsat TM6数据,采用覃志豪单窗算法(MW)、Jiménez-Mu(n)oz单通道算法(SC)和Weng算法计算了大亚湾海域的海表温度(Sea Surface Temperature,SST),分析比较了3种算法反演的海温空间分布特征,并选取12个样本点与实测数据进行了比较.结果表明:3种算法反演的海温分布特征基本一致,在3幅海温图像上可以清晰地观察到大亚湾核电站的热废水扩散特征;反演温度与实测温度的差值平均值分别为-2.21℃、0.19℃和-4.68℃,以SC算法误差最小.