Satellite remote sensing of sea-ice and its operational monitoring method along the coast of China

Sea-ice is an important operational item for real timely monitoring and forecasting marine environment of China. This paper introduces an operational method of satellite remote sensing to monitor sea- ice using quantitative data of NOAA, and its contents include computer processing of AVHRR sounding data of NOAA and its program design, imagery processing of sea-ice imagery from satellite and their thematic analysis. The sea-ice satellite colour imageries processed via this software system are able to interpret sea-ice pattern, characterizing it by thickness, maximum position of ice boundary, floe concentration and dynamic process of ice changing. At the same time, analyses of the ice condition of the Bohai Sea for the two-year period (1986-1988) as monitored by satellite have been summarized.

Overview of Grassland Degradation Research Based on Remote Sensing Monitoring

In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal characteristics and driving factors of grassland degradation and in order to deeply understand the research status of grassland degradation monitoring methods and evaluation index system, this paper mainly investigates the research progress of grassland degradation remote sensing monitoring methods and evaluation indicators. Furthermore, this paper summarizes the more commonly used remote sensing monitoring methods and evaluation methods, analyzes the problems existing in the evaluation indicators of grassland degradation, and points out the research direction of the evaluation indicators in the future. Finally, a comprehensive remote sensing monitoring and evaluation system are established in this paper. Research findings: because of the variety of grassland degradation types and the emergence of remote sensing monitoring and evaluation methods, establishing a comprehensive remote sensing monitoring and evaluation system to classify and summarize the research methods of different grassland degradation can lay a foundation for the development of grassland degradation evaluation and monitoring in the future and provide research ideas. It is the trend of grassland degradation remote sensing research in the future.

Applications of Satellite Remote Sensing Technology in China's Environmental Monitoring

The environmental conditions in China are still very serious. In the years to come, the mission for environmental treatment and protection, supervision,

Development of a large-scale remote sensing ecological index in arid areas and its application in the Aral Sea Basin

The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.

Progress and development on multi-parameters remote sensing application in earthquake monitoring in China

In this paper, the progress and development on remote sensing technology applied in earthquake monitoring research are summarized, such as differential interference synthetic aperture radar （D-InSAR）, infrared remote sensing, and seismo-ionospheric detecting. Many new monitoring data in this domain have been used, and new data processing methods have been developed to obtain high-precision images about crustal deformation, outgoing longwave radiation （OLR）, surface latent heat flux （SLHF）, and ionospheric parameters. The development in monitoring technology and data processing technique largely enriches earthquake research information and provides new tools for earthquake stereoscope monitoring system, especially on the space part. Finally, new developing trend in this area was introduced, and some key problems in future work were pointed out.

REMOTE SENSING FOR ENVIRONMENTAL MONITORING IN GUANGZHOU

The comprehensive investigation of aerial remote sensing in Guangzhou was a systematic project to meet the needs of urban construction, planning and management, and environmental protection by the remote sensing technique. The project was consisted of five parts, i.e., urban geology, natural resources, urban developing state, urban environment and a series of remote sensing mapping. This paper shows the ways to monitor the environment of Guanzhou by the aerial remote sensing technique.

A STUDY OF SOIL CONSERVATION MONITORING INFORMATION SYSTEM BASED ON REMOTELY SENSED DATA FOR A CATCHMENT ON THE LOESS PLATEAU

The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.

Grassland degradation in Northern Tibet based on remote sensing data

This study selected vegetation cover as the main evaluation index, calculated the grassland degradation index （GDI） and established the remote sensing monitoring and evaluation system for grassland degradation in Northern Tibet, according to the National Standard （GB19377-2003）, based on the remote sensing data such as NDVI data derived from NOAA/AVHRR with a spatial resolution of 8 km of 1981-2000, from SPOT/VGT with a spatial resolution of 1 km of 2001 and from MODIS with a spatial resolution of 0.25 km of 2002-2004 respectively in this area, in combination with the actual condition of grassland degradation. The grassland degradation processes and their responses to climate change during 1981-2004 were discussed and analyzed in this paper. The result indicated that grassland degradation in Northern Tibet is very serious, and the mean value of GDI in recent 20 years is 2.54 which belongs to the serious degradation grade. From 1981 to 2004, the GDI fluctuated distinctly with great interannual variations in the proportion of degradation degree and GDI but the general tendency turned to severe-grade during this period with the grassland degradation grade changed from light degraded to serious degraded in Northern Tibet. The extremely serious degraded and serious degraded grassland occupied 1.7% and 8.0% of the study area, the moderate and light degraded grassland accounted for 13.2% and 27.9% respectively, and un-degraded grassland occupied 49.2% of the total grassland area in 2004. The grassland degradation was serious, especially in the conjunctive area of Naqu, Biru and Jiali counties, the headstream of the Yangtze River lying in the Galadandong snow mountain and glaciers, the area along the Qinghai-Tibet highway and railway, and areas around the Tanggula and Nianqingtanggula snow mountains and glaciers. So the snow mountains and glaciers as well as their adjacent areas in Northern Tibet were sensitive to climate change and the areas along the vital communication line with frequent human activities experienced relatively serious grassland degradation.

Monitoring of winter wheat distribution and phenological phases based on MODIS time-series： A case study in the Yellow River Delta, China

Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.

Satellite dataset analysis of recent vegetation variation in Tibet region

This research investigates the recent distribution variation trends of vegetation in the Tibet region using Normalized Difference Vegetation Index （NDVI） data from 2000 to 2007. It also discusses the causes of vegetation degradation in typical regions （such as Nagqu） based on climatic conditions, human activity, and other influencing factors. Results show that the areas with the best vegetation cover are in Nyingchi and the southern part of Shannan, followed by Chamdo, the Lhasa area, and the eastern part of Nagqu. Vegetation in various regions exhibits significant seasonal differences. The vegetation status has improved in some parts of the Tibet region in the past few years, while the areas with the most serious degradation are in the middle and southem parts of the Nagqu region. On average, distinct vegetation degradation occurred between 2003 and 2006 in the whole Tibet region but vegetation has been increasing since 2006. The vegetation cover in summer basically determines the annual vegetation status. An increase in precipitation and decrease in wind speed generally corresponds to an increase in vegetation cover. The reverse is also true： a decrease in precipitation and increase in wind speed correspond to the decrease in vegetation cover. NDVI is thus positively related to temperature and precipitation but has a negative relation with wind speed. Increasing temperature and decreasing precipitation have led to the present vegetation degradation in Nagqu, and vegetation in all of these regions has been affected by growth of human population, intensified urbanization, livestock overgrazing leading to the proliferation of noxious plants, extraction of underground minerals and alluvial gold, extensive harvesting of traditional Chinese medicinal plants [e.g., Cordyceps sinensis, Caladium spp., and saffron crocus （Crocus sativus）], and serious rodent and other pest damage.

Response of glacier area variation to climate change in the Kaidu-Kongque river basin,Southern Tianshan Mountains during the last 20 years

Glaciers are crucial water resources for arid inland rivers in Northwest China.In recent decades,glaciers are largely experiencing shrinkage under the climate-warming scenario,thereby exerting tremendous influences on regional water resources.The primary role of understudying watershed scale glacier changes under changing climatic conditions is to ensure sustainable utilization of regional water resources,to prevent and mitigate glacier-related disasters.This study maps the current(2020)distribution of glacier boundaries across the Kaidu-Kongque river basin,south slope of Tianshan Mountains,and monitors the spatial evolution of glaciers over five time periods from 2000-2020 through thresholded band ratios approach,using 25 Landsat images at 30 m resolution.In addition,this study attempts to understand the role of climate characteristics for variable response of glacier area.The results show that the total area of glaciers was 398.21 km^(2)in 2020.The glaciers retreated by about 1.17 km^(2)/a(0.26%/a)from 2000 to 2020.The glaciers were reducing at a significantly rapid rate between 2000 and 2005,a slow rate from 2005 to 2015,and an accelerated rate during 2015-2020.The meteorological data shows slight increasing trends of mean annual temperature(0.02℃/a)and annual precipitation(2.07 mm/a).The correlation analysis demonstrates that the role of temperature presents more significant correlation with glacier recession than precipitation.There is a temporal hysteresis in the response of glacier change to climate change.Increasing trend of temperature in summer proves to be the driving force behind the Kaidu-Kongque basin glacier recession during the recent 20 years.

Review of the Impact of Grassland Degradation on Ecosystem Service Value

In recent years, grassland degradation has become one of China’s most critical environmental problems due to the interaction of natural environmental factors and human causes. Based on the systematic analysis of the spatial characteristics of grassland degradation and the current research status of environmental drivers, this paper summarizes and summarizes the research methods on the impact of grassland degradation on natural ecological service function and social and economic value to understand further the natural ecological service function of grassland degradation and its impact on social and economic benefits. The results show that since the function of grassland ecosystem service is much larger than the biomass value it provides, we should focus on the effective management of grassland from the design concept of ecological service function to achieve the sustainable development of grassland. We should do an excellent job in the comprehensive application of various ecosystems and service value evaluation methods in the future.

Continuous land cover change monitoring in the remote sensing big data era

Since the late 20th century,global change issues have attracted lots of attention.As a key component of global changes,land cover and land use information has been increasingly important for improved understanding of global environmental changes and feedbacks between social and environmental systems(Verburg et al.,2015).A set of national and global scale land cover/use products with higher spatial and temporal resolutions have been developed to fill this gap.In China,existing efforts include China’s

Siberian silkmoth outbreaks surpassed geoclimatic barrier in Siberian Mountains

Siberian silkmoth(SSM,Dendrolimus sibiricus Tschetv.)is the most important defoliator of Siberian pine(Pinus sibirica Du Tour)and fir(Abies sibirica Ledeb.)stands.Warming-induced SSM outbreaks are one of the major driving factors of successions within the taiga zone.It is suggested that climate change impacted the SSM range and life cycle.We analyzed the migration of alpine and northerly SSM outbreak boundaries in Siberia and the impact of the climate variables and topography on the outbreak dynamics.We used time-series scenes(multispectral data,and vegetation indexes EVI and NDII)in combination with field studies,climate variables,and GIS techniques.We found that SSM outbreaks in the area of alpine boundary shifted about 370 m uphill since the mid of 1950.The outbreak onset was promoted by increased dryness and active temperatures and decreased root zone moisture content in the spring-early summer period.The terrain topography strongly affected SSM outbreak onset and dynamics.Initially,the outbreak was located at the middle elevations on the gentle concave southeastern slopes,which are the favorable insect habitats between outbreaks.Then the outbreak expanded uphill and downhill,to steeper slopes,and both concave and convex terrains.Alongside with elevation range expansion,SSM surpassed its northern historical outbreak boundary:the potential outbreaks’boundary moved about 300 km northward.Climate warming contributes to SSM migration into former outbreak free conifer stands located in highlands and at northern latitudes.

Sandy desertification trend in western Northeast China Plain in the past 10 years

The west sandy land of the Northeast China Plain is located in the eastern huge sandy belt of mid-latitude in Eurasia and the eastern fringe of desertified land with best bio-climatic conditions in China. With rapid economic development, the deterioration of eco-environment has occurred and the desertification becomes very obvious. The first part of this paper studies the regional differences of landscape patterns and explores the regional differences of desertification. The second part aims to reveal the dynamics of desertification in the 1990s by using NOAA/AVHRR data and thematic data in GIS database. This work lays a scientific basis for the rehabilitation and development of the sandy lands.

Multi-temporal monitoring of wheat growth by using images from satellite and unmanned aerial vehicle

Recently near-ground remote sensing using unmanned aerial vehicles(UAV)witnessed wide applications in obtaining field information.In this research,four Rapideye satellite images and eight RGB images acquired from UAV were used from early June to the end of July,2015 covering two experimental winter wheat fields,in order to monitor wheat canopy growth status and analyze the correlation among satellite images based normalized difference vegetation index(NDVI)with UAV’s RGB images based visible-band difference vegetation index(VDVI)and ground variables of the sampled grain protein contents.Firstly,through image interpretation of UAV’s multi-temporal RGB images with fine spatial resolution,the wheat canopy color changes could be intuitively and clearly monitored.Subsequently,by monitoring the changes of satellite images based NDVI as well as VDVI values and UAV’s RGB images based VDVI values,the conclusions were made that these three vegetation indices demonstrated the same and synchronized trend of increasing at the early stage of wheat growth season,reaching up to peak values at the same timing,and starting to decrease since then.The results of the correlation analysis between NDVI of satellite images and sampled grain protein contents show that NDVI has good predicative capability for mapping grain protein content before ripening growth stage around June7,2015,while the reliability of using satellite image based NDVI to predict grain protein contents becomes worse as ripening stage approaches.The regression analysis between UAV’s RGB image based VDVI and satellite image based VDVI as well as NDVI showed good coefficients of determination.It is concluded that it is feasible and practical to temporally complement satellite remote sensing by using UAV’s RGB images based vegetation indices to monitor wheat growth status and to map within-field spatial variations of grain protein contents for small scale farmlands.

Remote monitoring cost minimization for an unreliable sensor network with guaranteed network throughput

In this paper we consider a link-unreliable remote monitoring scenario where the monitoring center is geographically located far away from the region of the deployed sensor network,and sensing data by the sensors in the network will be transferred to the remote monitoring center through a third party telecommunication service.A cost associated with this service will be incurred,which will be determined by the number of gateways employed and the cumulative volume of data successfully received within a specified monitoring period.For this scenario,we first formulate a novel constrained optimization problem with an objective to minimize the service cost while a pre-defined network throughput is guaranteed.We refer to this problem as the throughput guaranteed service cost minimization problem and prove that it is NP-complete.We then propose a heuristic for it.The key ingredients of the heuristic include identifying gateways and finding an energy-efficient forest of routing trees rooted at the gateways.We also perform theoretical analysis on the solution obtained.Finally,we conduct experiments by simulations to evaluate the performance of the proposed algorithm.Experimental results demonstrate the proposed algorithm outperforms other algorithms in terms of both the service cost and the network lifetime.