Canadian landsat studies for monitoring hydrologic conditions and coastal environments: A summary

This report summarizes a major paper reviewing Canadian work using Landsat imagery for studying changes in lakes and in coastal environments. The nature of environmental change is discussed. For lakes and coastal environments, it is suggested that change is either seasonal, long term, short term or constant; examples of each are given. There is also an important distinction between natural and man-induced change. Outlined in the paper are studies of the filling of the LG2 Reservoir, water level and vegetation changes in the Peace-Athabasca Delta, possible vegetation changes due to the construction of Roberts Bank Port near Vancouver and measurement of surface suspended sediment concentration in the Bay of Fundy using chromaticity analysis.     

Assessing ecohydrological factors variations and their relationships at different spatio-temporal scales in semiarid area,northwestern China

As a typical semiarid farming-pastoral ecotone sensitive to the environmennt, the Plain of West Liaohe Basin (WLBP) is currently experiencing drastic environmental changes. To identify how environmental change affect vegetation in the WLBP, we analysed spatiotemporal variation characteristics of Ecological environment factors based on monthly and annual air temperature (T), precipitation (P) and Normalized Difference Vegetation Index (NDVI) from 1982 to 2015. And the correlations between them were investigated by correlation analysis (Simple correlation, partial correlation and complex correlation) at temporal and spatial scale. The results showed that: (1) the vegetation growth of the WLBP showed ameliorated trend, with a change rate of 0.004/yr.; (2) P was more sensitive to NDVI than T; (3) and the influence of hydrothermal changes on vegetation growth was more significant than that of the change of single climate factors at time scales; (4) the effects of anthropogenic factors on vegetation change were 75.07% (1982–1993) and 98.08% (1994–2015), respectively. At the temp-special scales, P&T and land use type change (LUCC) were the main climatic and anthropogenic factors that affect vegetation changes, respectively.     

Quantitative contribution of climate change and anthropological activities to vegetation carbon storage in the Dongting Lake basin in the last two decades

The Dongting Lake Basin is an important hydrological regulation and flood storage area in the Yangtze River Basin, which plays an important role in maintaining regional ecological security. The watershed vegetation and its carbon sequestration capacity have changed dramatically due to climate change and human activities in the last two decades. In this paper, the monthly and annual vegetation net primary productivity (NPP) of the Dongting Lake basin during 2000 to 2020 was firstly estimated using the improved Carnegie-Ames-Stanford Approach (CASA) model. Then the multi-year NPP change trend and its significance were analyzed based on Theil-Sen median and Mann-Kendall method. Subsequently, the Hurst index was used to simulate the vegetation NPP persistence in the study area. Finally, the driving mechanisms of vegetation NPP changes in the study area were explored using partial correlation coefficients and residual analysis. The results demonstrated that: 1) The annual average NPP in the basin showed a fluctuating and increasing trend from 273.54 to 718.30 g C/m²·yr¹ during 2000 to 2020, and except for autumn, all seasons (spring, summer, winter) and annual NPP series showed an upward trend. The spatial distribution of vegetation NPP is characterized by an asymmetrical horseshoe shape in general, with high values in the west, south and east parts, and low values in the Lake area; 2) During the study years, about 84.38 % of the basin area showed a significant and extremely significant increase of NPP; 3) The future trend of vegetation NPP in the basin shows that the area of decrease (22.79 %) is more than the area of increase (11.35 %). The Chang-Zhu-Tan urban agglomeration will generally show a continuous and extremely significant reduction trend, while parts of Dongting Lake will show a continuous and extremely significant increase trend; 4) The correlation between solar radiation and NPP is stronger than the other two meteorological factors (precipitation and temperature). Temperature has a significant inhibitory effect on NPP, solar radiation has a significant promoting effect on NPP, and the effect of precipitation on NPP was relatively complicated. The relative importance of meteorological factors on vegetation NPP was ranked as follows: solar radiation > precipitation > temperature. The impacts of both climate change and human activities on NPP changes showed great spatial variability, and the positive contributions (89.81 % for climate change and 82.87 % for human activities) were both greater than the negative contributions.     

A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring

Remote sensing applications have greatly enhanced ability to monitor and manage in the areas of forestry. Accurate measurements of regional and global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Study of vegetation phenology is required for understanding of variability in ecosystem. In this paper, monitoring of vegetation dynamics using time series of satellite data is presented. Vegetation variability (vegetation rate) in different topoclimatic areas is investigated. Original software using IDL interactive language for processing of satellite long-term data series was developed. To investigate growth dynamics vegetation rate inferred from remote sensing was used. All estimations based on annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Vegetation rate for Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) was calculated using MODIS data. The time series covers spring seasons of each of 9 years, from 2000 to 2008. Comparison of EVI and NDVI derived growth rates has shown that NDVI derived rates reveal spatial structure better. Using long-term data of vegetation rates variance was estimated that helps to reveal areas with anomalous growth rate. Such estimation shows sensitivity degree of different areas to different topoclimatic conditions. Woods of heights depend on spatial topoclimatic variability unlike woods of lowlands. Principal components analysis shows vegetation with different rate conditions. Also it reveals vegetation of same type in areas with different conditions. It was demonstrated that using of methods for estimating the dynamic state of vegetation based on remote sensing data enables successful monitoring of vegetation phenology.     

Space platform albedo measurements as indicators of change in arid lands

The change in albedo of arid lands is an indicator of changes in their condition and quality, including density of vegetative cover, erosion, deposition, surficial soil moisture, and man-made change. In general, darkening of an arid land surface indicates an increase in land quality while brightening indicates a decrease in quality, primarily owing to changes in vegetation.Landsat multiband images taken on different dates can be converted to black-and-white albedo images. Subtraction of one image from another, pixel by pixel, results in an albedo change map that can be density sliced to show areas that have brightened or darkened by selected percentages. These maps are then checked in the field to determine the reasons for the changes and to evaluate the changes in land condition and quality.The albedo change mapping technique has been successfully used in the arid lands of western Utah and northern Arizona and has recently been used for detection of coal strip mining activities in northern Alabama.     

Assessment of plant vitality detection through fluorescence and reflectance imagery

Recent studies of the vegetation fluorescence show that it can be successfully used as an intrinsic indicator of plant photosynthetic activity. With respect to the vegetation spectral reflectance, the chlorophyll (Chl) fluorescence is more specific as an observable of basic biophysical processes in the plant cells. Laser induced fluorescence is widely used in near range remote sensing, but it is not suitable for the global monitoring of vegetation. Decades of active fluorometry studies have collected useful information of leaf reaction to natural and anthropogenic stress. Still the passive fluorescence, the one that could be registered from satellite orbit has still to prove its advantage over widely used reflectance signature. The weakness of the signal and the lack of experience with passive fluorescence measurements require extensive technical, theoretical and experimental studies. New imaging fluorometres are to be designed for measuring steady state fluorescence in controlled and natural conditions.

In order to compare reflectance and steady state fluorescence sensitivity to stress impact, a set of experiments have been conducted under controlled illumination conditions in a bio-chamber, designed by the author’s team. The equipment allows plant vitality to be monitored both by passive fluorescence and spectral reflectance imaging. Different types of stress factors (heat and drought stress, acid impact) were investigated to demonstrate equipments ability in monitoring changes of fluorescence signal. Selected fluorescence images of foliage illustrate an early detection of plant dysfunction and the temporal and spatial spreading of the stress impact. Analysis shows that fluorescence imaging of green plants can be developed as a highly effective early warning remote sensing method, which could have application for an ecosystems’ monitoring along with high-spectral reflectance imagery.     

Some aspects of land transformation in the western mediterranean desert of egypt

The western Mediterranean desert of Egypt has a long history of land-use. With recent development activities, land transformation is progressing at a high rate. Monitoring of changes to allow for predictions of long-term effects of these activities is viewed at three levels: (a) quantities of ecosystem components; (b) detailed distribution of patterns of land-use, vegetation and physiography; and (c) general distribution of the salient features of land. This study provides estimates at the first (a) and second (b) levels of changes in this region due to the main land-use types: grazing rain-fed farming, and irrigated farming.Grazing had little effects on soil characters, but it resulted in lower soil stability and abundance of plants and above-soil invertebrates. Irrigation resulted in water-logging and salinization, formation of calcic horizons, decrease in soil organic matter and soluble nitrogen, and in increase of above-and below-soil biota.A comparison of the distribution of vegetation and land-use in one of the sectors in 1964 and 1981, using maps based on aerial photographs and ground-truth data, indicated remarkable changes in areas of rain-fed farming, and in vegetation composition due to over-grazing.     

Results of analysis of human impact on environment using the time series of vegetation satellite images around large industrial centers

The paper shows the efficiency of an application of the vegetation index image time series to determine long-term vegetation dynamics. The influence of large industrial centers of Siberia on the near-by vegetation is demonstrated. The analysis of the data shows that the influence of industrial waste is stronger in the Siberian North. These regions are characterized by critical conditions for vegetation existence. In the south of the Krasnoyarsk region, human impact is also important, but the possibility of vegetation self-rehabilitation is higher. The present-day economic situation in Russia is unique, with a temporary abrupt fall of industrial production and its following increase. Thus, we managed to analyze the degree of human impact on the environment within a relatively short-time interval.     

A simplified data assimilation method for reconstructing time-series MODIS NDVI data

The Normalized Difference Vegetation Index (NDVI) is an important vegetation index, widely applied in research on global environmental and climatic change. However, noise induced by cloud contamination and atmospheric variability impedes the analysis and application of NDVI data. In this work, a simplified data assimilation method is proposed to reconstruct high-quality time-series MODIS NDVI data. We extracted 16-Day L3 Global 1 km SIN Grid NDVI data sets for western China from MODIS vegetation index (VI) products (MOD13A2) for the period 2003–2006. NDVI data in the first three years (2003–2005) were used to generate the background field of NDVI based on a simple three-point smoothing technique, which captures annual features of vegetation change. NDVI data for 2006 were used to test our method. For every time step, the quality assurance (QA) flags of the MODIS VI products were adopted to empirically determine the weight between the background field and NDVI observations. Ultimately, more reliable NDVI data can be produced. The results indicate that the newly developed method is robust and effective in reconstructing high-quality MODIS NDVI time-series.     

A study of backscattered spectra dynamics of agricultural crops during growth period on the territory of the Krasnoyarskii Krai (Russia)

The work presents the results of the study aimed at determining the seasonal dynamics of the spectral brightness and reflectance of agricultural crops (wheat, barley and oats) in the Krasnoyarskii Krai (Russia). The analysis of spectral curves obtained through field ground measurements and from satellite data showed that fine spectral differences can be used to study the spatial distribution of various types of vegetation and their ecological state. Based on the created electronic spectral brightness data base, the possibilities are shown of using spectrophotometric information for determining morphophysiological changes occurring in the plants and their species composition. The determined contrasts can be effectively used to obtain necessary information while processing space images, which suffer from natural interferences (varying optical thickness of the atmosphere, cloudiness, alterations in the scanner’s angle of view, varying solar height, and highly inhomogeneous underlying surface).     

Experiment for mapping land cover and it’s change in southeastern Sri Lanka utilizing 250 m resolution MODIS imageries

Utilizing freely available MODIS NDVI and Natural color imageries of 250 m spatial resolution produced by NASA, an experiment was made to map land-cover and its change with an emphasis on vegetation cover in southeastern Sri Lanka, which plays a vital role for control of green house gas. For the change detection purpose, 1987 land cover map made by present authors from Landsat MSS image and extensive ground truth survey data was used as the base map. The result of the experiment shows that MODIS data are useful to make a land cover map of 250 m spatial resolution for tropical areas with high cloud coverage like Sri Lanka. It was found that the forest cover decrease amounted as large as 21% in 19 years time span in southeastern Sri Lanka, the prominent forest region of the country. On the other hand homestead/vegetation and mixed vegetation/scrub dominant categories increased by 13.7% and 7.1%, respectively. These changes are considered due to a large clearance of forest areas for agriculture and building houses to accommodate increasing inhabitants.     

Vegetation cover mapping from NOAA/AVHRR

The visible and near infrared channels, Ch₁ and CH₂ respectively, on the Advanced Very High Resolution Radiometer (AVHRR) provide daily information for monitoring changes in vegetation and crops. Data from these channels are used to create a normalized vegetation index (NVI) that is sensitive to changes in green leaf biomass and is represented mathematically by:

$\text{NVI =}\text{CH}{}_2\text{? CH}{}_1\text{CH}{}_2\text{+ CH}{}_1$

Operational products generated at NOAA include full-scale 1-km resolution images of the NVI covering areas viewed in a single swath of the polar-orbiting NOAA satellite. Global scale NVI images are also produced by compositing over a seven-day period, saving the maximum NVI created daily for each local array (resolution of 15 km at the equator to 30 km at the poles). Such seven-day mapping reduces the effect of cloud contamination. The global vegetation indices are used by foreign and U.S. government agencies for operational and experimental purposes such as assessment of crop conditions, monitoring potential desert locust breeding grounds, forest fire danger models, and monitoring range lands for forage availability. Examples include changes in the NVI in the Lake Chad vicinity, 1981–1982 and 1984; western United States NVI; and seasonal variations of the NVI in the Sahel using the global operational data base, 1982–1983.     

Study of changes in the lineament structure,caused by earthquakes in South America by applying the lineament analysis to the Aster (Terra) satellite data

The region between Southern Peru and Northern Chile is one of the most seismically and volcanically active regions in South America. This is caused by a constant subduction of the South American Plate, converging with the Nazca Plate in the extreme North of Chile. We used the 15 and 30 m resolution satellite images, provided by the ASTER (VNIR and SWIR) instrument onboard the Terra satellite to study changes in the geological faults close to earthquake epicenters in southern Peru. Visible and infrared spectral bands were analysed using “The Lineament Extraction and Stripes Statistic Analysis” (LESSA) software package to examine changes in the lineament features and stripe density fields caused by seismic activity. We used the satellite images 128 and 48 days before and 73 days after a 5.2 Richter scale magnitude earthquake. The fact that the seasonal variations in the South of Peru and North of Chile are very small, and the vegetation is very limited, allowed us to establish substantial changes in the lineament and the stripe density field features. We develop a methodology that allows to evaluate the seismic risk in this region for the future.     

Geological exploration and landuse using Landsat data,Sierra Leone,West Africa

Band 7 Landsat Imagery was successfully used to map broad outcrop belts in Sierra Leone because of the lithological control of topography and vegetation. Digital analysis in specific areas suggest the usefulness of certain techniques in mapping excavated areas and to indicate areas of future mineral exploration.     

Relationships between soil properties of the abandoned fields and spectral data derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER)

The structural transformation of Polish agriculture after 1989 has been leading to significant changes in land use. As a result a large part of formerly ploughed fields lies abandoned and they occur across considerable variability in soil typological units. Accurate information about soil conditions within the abandoned fields facilitates proper management in the new socio-economic situation. Such information can be collected using satellite images since the structure and condition of the vegetation growing on the abandoned fields reflects soil properties. The objective of this study is to evaluate the relationships between physical and chemical attributes of soil within the abandoned fields and spectral reflectance patterns recorded by ASTER sensors onboard Terra Satellite. Soil samples were collected at five abandoned fields which have not been ploughed since 2000 and analyzed in the laboratory to determine their physical and chemical properties. Nine ASTER nearly cloud-free pictures were used for this study in order to derive the remote-sensing attributes of the abandoned fields. In order to evaluate the relationships between soil fertility and remotely sensed data, partial least-squares (PLS) and a multiple linear regression (MLR) analysis between these two datasets were carried out. In the regression analysis, only soil TEB (total exchangeable bases) stock in the whole profile displayed the highest correlation with remotely sensed data acquired in April and May and the best predictors were NDVI and LSWI vegetation indices.     

Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.     

Assessment of the sensitivity of vegetation to El-Niño/Southern Oscillation events over China

This research explores the sensitivity of vegetation in China to El-Niño/Southern Oscillation (ENSO) events from 1982 to 2006. The ENSO events are defined by the Multivariate ENSO Index (MEI), and variation in vegetation cover is captured by the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI). Pearson’s χ2 test was used to identify the areas where the variation in vegetation was sensitive to El Niño and La Niña events. The difference in the sensitivity of various ecosystems was investigated using the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product in 2000. Composite NDVI graphs during El Niño, La Niña and non-ENSO years were also produced to investigate the ENSO relationship with the six vegetation ecosystems during El Niño, La Niña and normal phases. The results show that most of the ENSO-sensitive land in China is only affected by one of the two phases of ENSO events, and the area of El Niño-sensitive vegetation is much larger than that of La Niña-sensitive vegetation. North China and the Hengduan Mountains are the two cores of the El Niño-sensitive areas, while the La Niña-sensitive areas are mainly distributed in the central, northwest and northeast regions of China. The sensitivity of vegetation varies across ecosystems: grassland and shrubland had the largest share of El Niño-sensitive areas, and sparse vegetation and savanna were the most sensitive to La Niña events. Overall, the impacts of El Niño events on vegetation in China had regular seasonal variation, while the impacts of La Niña events had regular zonal distribution.     

差分吸收光谱法污染物连续监测系统

紫外—可见差分吸收光谱法 (DOAS)是一种新型在线式烟气排放污染物自动监测的可行方法 ,它在不改变被测试样成分的前提下 ,可以同时对多种气体进行连续测量。对获得的吸收光谱数据由计算机处理 ,可实时记录烟气中各种污染物的含量 ,并对未知成分的气体进行判断。介绍了基于这种测量方法的测试系统的构成、工作原理和测试结果     

Canadian Landsat studies for monitoring agricultural intensification and urbanization: A summary

This report summarizes a major paper reviewing the progression of work using Landsat for land use and agricultural monitoring in Canada since 1973. From the launch of Landsat to the present, the focus has moved from using simple visual techniques for interpretation of photographic products to the use of conceptually simple methods which now employ the power of special-purpose image analysis hardware and the standard geometrically corrected products available in Canada. Outlined in the major paper are studies on urban growth, large area land use mapping, crop studies (related to both crop area estimates and erosion potential), assessment of changes in vegetation vigour and clearing of land in areas which were devoted to both dry land farming and forestry. This report emphasizes developments in land use studies.     

基于光电编码器的电机变周期速度观测器设计

针对光电编码器在伺服系统应用中速度估计易受系统振动干扰和存在量化误差的问题,设计了一种基于变采样周期观测器的速度估计算法.通过观测器的积分运算抑制振动干扰;通过采样周期和光电编码器脉冲的同步,使量化误差最小;为了减小观测器离散域极点变化对算法性能的影响,保证变周期观测器在较大速度范围保持较高精度,给出了一种观测器增益系数的计算方法.实验表明该算法可以在保证动态性能的同时,有效抑制振动和量化误差引起的估计误差,提高速度估计精度.