FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

ABSTRACT

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.     

THE STUDY AND MAPPING OF HUMAN IMPACTS ON NATURE IN DIFFERENT REGIONS OF THE USSR USING SPACE IMAGERY

The authors present the results of experiments in the use of remote sensing imagery for construction of maps depicting human modification of nature. Four diverse areas within the USSR were selected as mapping sites, providing a broad range of environmental and land-use characteristics for investigation. Human impacts were most effectively mapped for two desert sites. The authors recommend combining satellite imagery with terrestrial spectrometric observations or color-infrared photography in investigations of environmental change in steppeland and forested territory. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1984, No. 6, pp. 11-18.     

Parallelizing maximum likelihood classification on computer cluster and graphics processing unit for supervised image classification

ABSTRACT

Supervised image classification has been widely utilized in a variety of remote sensing applications. When large volume of satellite imagery data and aerial photos are increasingly available, high-performance image processing solutions are required to handle large scale of data. This paper introduces how maximum likelihood classification approach is parallelized for implementation on a computer cluster and a graphics processing unit to achieve high performance when processing big imagery data. The solution is scalable and satisfies the need of change detection, object identification, and exploratory analysis on large-scale high-resolution imagery data in remote sensing applications.     

USE OF SPACE IMAGERY IN THE STUDY OF MASS EXCHANGE IN GLACIER SYSTEMS

The author surveys the use of remote sensing imagery in the study of mass exchange in glaciers, i.e., glacier dynamics resulting from phase changes in the water which they contain. A program of research now underway at the Institute of Geography (USSR Academy of Sciences) in conjunction with the “Priroda” Remote Sensing Center (Moscow) focuses on improving methods of data collection and mapping of glacier dynamics from space imagery, and particularly on identifying natural glacioclimatic zones believed to represent specific mass exchange conditions or regimes. The boundary of glacier nourishment separating areas of accumulation and ablation represents a key glacioclimatic indicator of mass exchange on satellite imagery and aerial photography. Translated from: Geodeziya i kartografiya, 1986, No. 5, pp. 26–31.     

MONITORING ENVIRONMENTAL IMPACTS OF LENINGRAD ON THE SURROUNDING AREA

The author, a remote sensing specialist in Leningrad University's Department of Atmospheric Physics, describes the use of space imagery in a program for monitoring the city's impacts on the surrounding environment. The paper examines applications of LANDSAT and “Meteor” satellite imagery and “Soyuz-22” space photography in the study of industrial smoke plumes, jet contrails, atmospheric haze, albedo, the urban heat island, urban sprawl (including nighttime imagery), fallout of suspended particulates, and wastewater discharges into the Gulf of Finland. Translated from: Grigor'yev, A. A. Antropogennyye vozdeystviya na prirodnuyu sredy po nablyudeniyam iz kosmosa [Human Impacts on the Environment From Observations From Space]. Leningrad: Nauka, 1985, pp. 129-141 [Chapter 7].     

中国南方森林冠顶高度Lidar反演—以江西省为例

激光雷达(Lidar)与光学遥感的有效结合对中国南方区域森林冠顶高度反演意义重大,而国产卫星将为中国森林生态研究提供新的数据源。本文联合利用大脚印激光雷达GLA和国产MERSI数据,在实现GLAS波形数据处理和不同地形条件下森林冠顶高度反演算法基础上,建立了区域尺度不同森林类型林分冠顶高度GLAS+MERSI联合反演关系模型,进行了江西地区森林冠顶高度反演。总体上,GLAS激光雷达森林冠顶高度估算精度较高;且在与MERSI 250 m数据的联合反演模型中,针叶林模型精度较好(R²=0.7325);阔叶林次之(R²=0.6095);混交林较差(R²=0.4068)。分析发现,考虑了光学遥感生物物理参数的GLAS+MERSI联合关系模型在区域森林冠顶高度估算中有较高精度,且在空间分布上与土地覆盖数据分布特征非常一致。     

基于无人机LiDAR和高空间分辨率卫星遥感数据的区域森林郁闭度估测模型

森林郁闭度是森林资源调查中的一个重要因子,对森林质量评价具有重要作用。随着人工智能技术和遥感技术的不断发展,研究如何利用深度学习有效协同不同空间覆盖能力的遥感数据实现区域森林郁闭度的估测具有重要意义。由此提出了一种协同应用高密度无人机激光雷达和高空间分辨率卫星遥感数据,对区域森林郁闭度进行定量估测的深度学习模型（UnetR）。对用于图像分类的Unet模型的损失函数进行改进,并在卷积层后加入批量归一化层,使其具有对连续变量进行定量估测的能力。与全卷积神经网络、随机森林和支持向量机回归模型进行对比实验。结果表明,UnetR模型的均方根误差较低,估测精度较高,为实现区域森林郁闭度遥感监测提供了一种人力成本低、自动化程度高的估测方法。     

AUTOMATED MAPPING FROM SCANNER IMAGE INTERPRETATION

A methodology for the interpretation and mapping of lineaments and related geological features from medium-resolution, Meteor satellite scanner imagery is described. Special emphasis is placed on improving traditional methods of transferring information interpreted from remote sensing materials onto a cartographic base through compensation for the special character of geometric distortion on scanner imagery and selection of appropriate map projections for the cartographic base. This boils down to the development of computer models for correlating control points on a scanner image and map base, and algorithms for the plotting both of that base and the thematic image elements that are the focus of interest. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1986, No. 3, pp. 35–40.     

高分辨率光学卫星遥感影像高精度无地面控制精确处理的理论与方法

卫星影像全球无地面控制高精度几何定位是卫星摄影测量技术发展追求的主要目标,也是实现困难地区和境外地区测图的关键支撑技术。本文围绕我国国产遥感卫星的技术发展,详细论述了高分辨率光学卫星遥感影像高精度无地面控制几何定位的理论与方法,在天星地一体化全链路误差建模分析的基础上,提出了在轨几何定标理论与方法、稳态重成像几何处理模型与方法及大规模无地面控制区域网平差理论与方法。将本文方法应用于资源三号卫星影像的数据处理,试验结果满足1∶50 000测图精度,证明了理论和方法的正确性。     

SATELLITE MEASUREMENTS OF LAND PARAMETERS AS PART OF AN INTERNATIONAL PROGRAM OF CLIMATE RESEARCH

The role of remote sensing in one aspect of the World Climate Research Program is summarized. More specifically, unresolved theoretical and methodological problems are outlined for the use of remote sensing imagery (in conjunction with the International Land Surface Climatology Project) to derive quantitative parameters of land (and ice) surface characteristics. These parameters are raw data for models of the overall circulation of the atmosphere, which can be used to generate maps of albedo, surface roughness, hydrology, etc. A list of preliminary standards for satellite monitoring of land surface characteristics is included. Translated from: Izvestiya Vsesoyuznogo Geograficheskogo Obshchestva, 1988, No. 2, pp. 161-165.     

CBERS-02B星数据质量评价及其铀成矿要素解译应用研究

利用遥感影像处理技术和数理统计方法,评价了中巴地球资源一号卫星02B星（CBERS—02B,以下简称02B星）遥感数据的空间特性和辐射特征,并与ETM＋多光谱数据主要特征参数进行了对比分析。在此基础上,以江西桃山花岗岩型铀矿田为试验区,结合航空放射性数据,开展了基于02B星遥感数据的控矿断裂带、热液蚀变带及主要成矿岩体等铀成矿要素的光谱特征识别与提取,并对该数据的地学应用潜力进行了评价。     

Assessment of Fragmentation and Disturbance Patterns in Eastern Ghats: A Case Study in R.V. Nagar Range,Visakhapatnam District,Andhra Pradesh,India

At present the biodiversity in Eastern Ghats is threatened by loss of habitats, exploitation and unscientific management of natural resources, forest fire, biological invasion and other anthropogenic pressures. In this context, we have assessed the forest cover changes, fragmentation and disturbance in the R.V. Nagar Range of Eastern Ghats region, Andhra Pradesh using satellite remote sensing and GIS techniques. Satellite data of IRS-1A LISS II of 1988 and IRS-P6 LISS III of 2006 were assessed for forest cover changes in 1 sq.km grid and generated as Sensitivity Index map. Further the road and settlement buffer of 1000 m was generated to represent Threat Index map. From 1988 to 2006, the forest cover had a total cover loss of 35.2 sq.km and increase in scrub cover by 7.2%. Over all change analysis from 1988 to 2006 with reference to forest cover indicates, negative changes (loss of forest area) accounted for 48.1 sq.km area and positive changes (gain of forest) for an area of 12.1 sq.km of area. The results of the change detection using multi-date satellite imagery suggest degradation in forest cover over two decades, which necessitates the conservation measures in this range with high priority.     

An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery

Mapping forest structure variables provides important information for the estimation of forest biomass, carbon stocks, pasture suitability or for wildfire risk prevention and control. The optimization of the prediction models of these variables requires an adequate stratification of the forest landscape in order to create specific models for each structural type or strata. This paper aims to propose and validate the use of an object-oriented classification methodology based on low-density LiDAR data (0.5 m^?2) available at national level, WorldView-2 and Sentinel-2 multispectral imagery to categorize Mediterranean forests in generic structural types. After preprocessing the data sets, the area was segmented using a multiresolution algorithm, features describing 3D vertical structure were extracted from LiDAR data and spectral and texture features from satellite images. Objects were classified after feature selection in the following structural classes: grasslands, shrubs, forest (without shrubs), mixed forest (trees and shrubs) and dense young forest. Four classification algorithms (C4.5 decision trees, random forest, k-nearest neighbour and support vector machine) were evaluated using cross-validation techniques. The results show that the integration of low-density LiDAR and multispectral imagery provide a set of complementary features that improve the results (90.75% overall accuracy), and the object-oriented classification techniques are efficient for stratification of Mediterranean forest areas in structural- and fuel-related categories. Further work will be focused on the creation and validation of a different prediction model adapted to the various strata.     

Examining the Phenological Cycle of Barley (Hordeum vulgare) Using Satellite and in situ Spectroradiometer Measurements for the Detection of Buried Archaeological Remains

The detection of buried archaeological remains using satellite remote sensing is still an open question in archaeological research. This research investigates how the phenological stages of crops can be used support the detection of buried archaeological remains. Ground remote sensing data using the GER-1500 spectroradiometer were obtained from two sites. One site was the Neolithic settlements in central Greece and the other was in Alampra village in Cyprus. For the latter, an archaeological environment was simulated and ground spectroradiometric measurements were systematically acquired over the different phases of the phenological cycle of barley crops. The acquired in situ reflectance measurements have been converted to "in-band" reflectance values of the Landsat TM/ETM+ using the satellite relative spectral responses filters (RSR). Based on the proposed methodology, 97 Landsat MSS, TM, and ETM+ satellite images were acquired (covering a period from 1983 to 2011), for the Thessalian (Greek) site. It has been found that phenological-cycle observations can provide valuable information for identifying buried archaeological remains. Such observations may be used in cases where the spatial resolution of satellite imagery is not high and therefore cannot help support the detection of archaeological remains using standard interpretation techniques.     

辐射产品的卫星影像内部畸变几何标定

针对卫星发射以后,由于外部太空环境的变化和相机光学系统的径向畸变导致卫星成像影像的外部误差和内部畸变,须对光学遥感相机长期周期性地进行几何标定消除卫星影像系统误差和相机指向角误差提高卫星影像几何定位精度的问题,该文从简单易行的角度出发,基于相机的CCD固定偏差原理构建一种新型的模型或内标定算法消除影像的内部畸变,以经过畸变改正的卫星影像辐射产品为参考控制,采用亚像素匹配法构建内部畸变模型修正卫星遥感影像的内部畸变,并分别以不同侧摆角和影像行数的SJ9A和ZY3为实验和参考控制数据构建和验证新型标定模型的有效性和实用性。     

高分二号异轨立体数据的森林高度提取

森林植被碳储量的空间分布格局及其动态变化是陆地生态系统碳收支核算的基础。作为森林地上生物量的重要指示因子,森林高度的精确估算是提高森林植被碳储量估算精度的关键。现有研究已证明,由专业星载摄影测量系统获取的立体观测数据可用于森林高度提取,但光学遥感数据最大的问题是受云雨等天气因素的影响严重。区域森林地上生物量产品的生产需要充分挖掘潜在数据源。国产高分二号卫星(GF-2)虽然不是为获取立体观测数据而设计的专业星载摄影测量系统,但其获取的图像空间分辨率可达0.8 m,且具备±35°的的侧摆能力,在重复观测区域可构成异轨立体观测。本文以分别获取于2015年6月20日和2016年7月19的GF-2数据作为立体像对,其标称轨道侧摆角分别为0.00118°和20.4984°,以激光雷达数据获取的林下地形(DEM)和森林高度(CHM)为参考,对利用GF-2立体观测数据进行森林高度提取进行了研究。通过对立体处理得到的摄影测量点云的栅格化得到DSM,以激光雷达数据提供的DEM作为林下地形,得到了GF-2的CHM。结果表明GF-2提取的CHM与激光雷达CHM空间分布格局较为一致,两者之间存在明显的相关性,像素对像素的线性相关性(R2)达到0.51,均方根误差(RMSE)为3.6 m。研究结果表明,在林下地形已知的情况下,GF-2立体观测数据可用于森林高度估算。     

Spatial variation in elephant impact on the Zambezi teak forest in the Chobe national park,Botswana

Abstract

Tectonic mapping and geologic evolution of a region were historically conducted on the basis of field observations. After the advent of remote sensing technology, tectonic mapping became much easier and structural mapping through imagery has gained credibility and suitability in regional mapping, tectonic evolution and modeling. In this regard, an attempt has been made to make use of the satellite technology to bring out the structural trends and the fracture/lineament pattern in Biligirirangan region of Northern Tamil Nadu through satellite remote sensing. The folded architecture in Biligirirangan region has evolved from structural trends. The subsurface structures of the region were derived through resistivity contours and resistivity images created by GIS software.

The surficial information derived from the satellite imagery and subsurface structures derived from the resistivity contours and images were integrated with field observations. This integration has given a clear tectonic picture of the Biligirirangan region and the tectonic structures were then analysed for tectonic forces, evolution and modeling.

The study determined that the Structural trends were mostly in a N‐S direction and the folds were of isoclinal type with alternating synclinal and anticlinal folds of an easterly dipping nature. These folds in conjunction with the lineaments have brought out the palaeostress pattern of the Biligirirangan region. The study further suggests that the regional compressive force trending in ENE‐WSW direction was responsible for the present configuration of folds. In addition, the study also focuses the efficacy of the satellite imagery in tectonic analysis and the resistivity contours and images for the subsurface structural analysis.     

热带森林植被的动态变化遥感监测

本文讨论了以热带森林植被为主体的再生资源的面积动态变化监测。研究中包括两个部分。首先,我们利用多时相遥感图像对大面积的西双版纳州进行地类判读,系统地分析了森林植被的动态变化。其次,利用Landsat MSS和TM数据对自然保护区的动态变化进行了包含无监督分类和归一化差值植被指数分析的数字图像处理,变化分类也相当符合实际。总的实验结果表明,这种监测方法是很有效的,可在再生资源监测中特别是在森林植被监测中加以推广应用。     

INTERPRETATION OF ECOLOGICAL-SOIL CHARACTERISTICS OF WOODED STEPPE ZONE IN THE CENTRAL RUSSIAN UPLAND

The authors describe how remote sensing imagery can be employed in the identification of different types of chernozem soils in a predominantly agricultural zone (forest steppe), where natural vegetation (normally one of the best vegetation indicators) has been largely displaced by farm fields. A multi-stage methodology is outlined whereby small-scale imagery is used to delineate large regions of similar bioclimatic-geologic characteristics, from which areas of similar soil formation conditions are distinguished. Multispectral and multitemporal space imagery then is employed to detect less salient ecological-soil differences that can affect phototone and image texture. Translated by Edward Torrey, Alexandria, VA 22308 from: G. V. Dobrovol'skiy and V. L. Andronikov, eds., Aerokosmicheskiye metody v pochvovedenii i ikh ispol'zovaniye v sel'skom khozyaystve: sbornik nauchnykh trudov [Remote Sensing Methods in Soil Science and Their Utilization in Agriculture: A Collection of Scientific Works]. Moscow: Nauka, 1990, pp 103–109.     

Modeling Remote Sensing Satellite Collection Opportunity Likelihood for Hurricane Disaster Response

State and local agencies involved in emergency response to natural disasters such as hurricanes have explicitly indicated they need imagery covering the disaster area within three days of the event; and more desirably within 24 hours of the event. Airborne image collections have often been used but suffer from several problems, most noticeably the collection time (days or week) required for larger areas. The use of remote sensing satellites carrying high spatial resolution sensors has often been touted as the logical response for rapidly collecting post-disaster event imagery for emergency response. Unfortunately, satellites are maintained on fixed orbits. The repeat interval for remote sensing satellites carrying high spatial resolution sensors, even with pointable sensors, is on the order of several days, depending on the latitude for the disaster event. Fortunately, more than one satellite carries high spatial resolution imagery. This combination of requirements and restrictions may result in either a relatively high (or low) likelihood of collecting imagery within the three-day window of opportunity. This research investigated the likelihood of collecting imagery over a hurricane disaster area based on the orbital cycles of three high spatial resolution imaging satellites. Using the spatial-temporal distribution of historic hurricane landfall locations as a proxy for the probability distribution of future hurricanes by latitude, the "visibility" of each landfall location to future satellite imaging opportunities was determined. The results indicate that the likelihood of collecting imagery within one day of the event varied between 17 and 39 percent by relying on one satellite image provider. However, if either of three satellite imagery sources (i.e., Ikonos-2, Quickbird-2, and Orbview-3) could be used, then the likelihood increased to 61 percent. By relying on three satellite imagery providers there is a likelihood of between 94 and 100 percent of collecting imagery within two or three days, respectively, after the event.