Monitoring global vegetation dynamics with ERS-1 wind scatterometer data

ERS-1 wind scatterometer (WSC) data is analysed over a wide range of terrain types for the period May 1992-April 1994. Comparison is made with Global Vegetation Index (GVI) data for the monitoring of vegetation dynamics. Results show that WSC data display a well-pronounced seasonality over most vegetated surfaces. The highest sensibility to vegetation dynamics is found over semi-arid regions and boreal zones. In these two cases, there is a marked seasonality in environmental parameters which is well depicted by σ⁰ temporal profiles. However, the sensibility of the ERS-1 response is much less pronounced over densely vegetated surfaces. In yspite of its low spatial resolution, the usefulness of a C-band scatterometer for monitoring vegetation dynamics is shown.     

Quality assessment of SRTM C- and X-band interferometric data: Implications for the retrieval of vegetation canopy height

The Shuttle Radar Topography Mission distinguished itself as the first near-global spaceborne mission to demonstrate direct sensitivity to vertical vegetation structure. Whether this sensitivity is viewed as exploitable signal or unwanted bias, a great deal of interest exists in retrieving vegetation canopy height information from the SRTM data. This study presents a comprehensive application-specific assessment of SRTM data quality, focusing on the characterization and mitigation of two primary sources of relative vertical error: uncompensated Shuttle mast motion and random phase noise. The assessment spans four test sites located in the upper Midwestern United States and examines the dependence of data quality on both frequency, i.e., C-band vs. X-band, and the number of acquired datatakes. The results indicate that the quality of SRTM data may be higher than previously thought. Novel mitigation strategies include a knowledge-based approach to sample averaging, which has the potential to reduce phase noise error by 43 to 80%. The strategies presented here are being implemented as part of an ongoing effort to produce regional- to continental-scale estimates of vegetation canopy height within the conterminous U.S.     

Investigation of C- and X-band backscattering signatures of Baltic Sea ice

Backscattering signatures of various Baltic Sea ice types and open water leads were measured with the helicopter-borne C- and X-band Helsinki University of Technology scatterometer (HUTSCAT) during six ice research campaigns in 1992–1997. The measurements were conducted at incidence angles of 23° and 45°. The HUTSCAT data were assigned by video imagery into various surface type categories. The ground data provided further classification of the HUTSCAT data into different snow wetness categories (dry, moist and wet snow). Various basic statistical parameters of backscattering signature data were used to study discrimination of open water leads and various ice types. The effect of various physical parameters (e.g. polarization, frequency, snow condition) on the surface type discrimination was investigated. The results from the data analysis can be used to help the development of sea ice classification algorithms for space-borne SAR data (e.g. Radarsat and Envisat). According to the results from the maximum likelihood classification it is not possible to reliably distinguish various surface types in the SAR images only by their backscatter intensity. In general, the best ice type discrimination accuracy is achieved with C-band VH-polarization σ° at an incidence angle of 45°.     

Monitoring corn and soybean crop development with hand-held radiometer spectral data

Red and photographic infrared data were collected with a hand-held radiometer under a variety of conditions at 4- to 12-day intervals throughout the growing season and were used to monitor corn and soybean growth and development. The normalized difference transformation was used to effectively compensate for the variation in irradiational conditions. With these data, plotted against time, green-leaf biomass dynamics were compared between the crops. By this approach, based entirely upon spectral inputs, the crop canopies were nondestructively monitored. Five spectral stages were defined and were related to crop development for corn and soybeans.     

Inferring Greenland melt and refreeze severity from SeaWinds scatterometer data

Two SeaWinds radar scatterometers operated in tandem for 9 months in 2003, enabling resolution of the diurnal cycle in Greenland. This dataset provides unprecedented temporal resolution for Ku-band scattering observations of snow and ice melt conditions. As a step towards improved radar-based melt intensity estimation, a simple Markov melt–thaw model is developed to estimate melt and refreeze indices. The melt indices model is evaluated with the aid of a simple geophysical–electromagnetic model and validated by comparing tandem SeaWinds observations against automated weather station data. The new approach is used to analyse the melt conditions over the Greenland ice-sheet in 2003. The strengths and limitations of the approach are considered.     

An algorithm for the retrieval of sea surface wind fields using X-band TerraSAR-X data

TerraSAR-X (TS-X) is a new, fully polarized X-band synthetic aperture radar (SAR) satellite, which is a successor of the Spaceborne Imaging Radar X-band Synthetic Aperture Radar (SIR-X-SAR) and the SRTM. TS-X has provided high-quality image products over land and oceans for scientific and commercial users since its launch in June 2007. In this article, a new geophysical model function (GMF) is presented to retrieve sea surface wind speeds at a height of 10 m (U ₁₀) based on TS-X data obtained with VV polarization in the ScanSAR, StripMap and Spotlight modes. The X-band GMF was validated by comparing the retrieved wind speeds from the TS-X data with in situ observations, the high-resolution limited area model (HIRLAM) and QuikSCAT scatterometer measurements. The bias and root mean square (RMS) values were 0.03 and 2.33 m s^?1, respectively, when compared with the co-located wind measurements derived from QuikSCAT. To apply the newly developed GMF to the TS-X data obtained in HH polarization, we analysed the C-band SAR polarization models and extended them to the X-band SAR data. The sea surface wind speeds were retrieved using the X-band GMF from pairs of TS-X images obtained in dual-polarization mode (i.e. VV and HH). The retrieved results were also validated by comparing with QuikSCAT measurements and the results of the German Weather Service (DWD) atmospheric model. The obtained RMS was 2.50 m s^?1 when compared with the co-located wind measurements derived from the QuikSCAT, and the absolute error was 2.24 m s^?1 when compared with DWD results.     

Monitoring fire-affected areas using Thematic Mapper data

In this paper three methods for updating inventories of burned areas have been presented and examined. They include Multitemporal Principal Component Analysis (MPCA), Change Vector Analysis (CVA) and Multitemporal NDVI Classification (MNC). First, 11 Landsat-5 Thematic Mapper (TM) images of a forest area were radiometrically corrected to derive a multitemporal series of intercomparable images for each spring from 1984 to 1994. Then, in order to check the feasibility of the three approaches, they were used for mapping fire burns that occurred during 1992. The various procedures yielded different maps of burned areas; the MNC method seemed to be more reliable than the others, because it merges spectral data corresponding not only to 1992 (pre-fire) and 1993 (post-fire) but also to 1994 (the second year after the fires), which is key in the vegetation regeneration. Finally, this methodology was automated to yield an inventory of burned areas for each year during the period of study.     

Monitoring East African vegetation using AVHRR data

NOAA Advanced Very High Resolution Radiometer satellite data are applied to regional vegetation monitoring in East Africa. Normalized Difference Vegetation Index (NDVI) data for a one-year period from May 1983 are used to examine the phenology of a range of vegetation types. The integrated NDVI data for the same period are compared with an ecoclimatic zone map of the region and show marked similarities. Particular emphasis is placed on quantifying the phenology of the Acacia Commiphora bushlands. Considerable variation was found in the phenology of the bushlands as determined by the satellite NDVI, and is explained through the high spatial variability in the distribution of rainfall and the resulting green-up of the vegetation. The relationship between rainfall and NDVI is further examined for selected meteorological stations existing within the bushland. A preliminary estimate is made of the length of growing season using an NDVI thresholding technique     

动态工作流中利用触发器监控信息与数据流

在一个组织中对信息和数据流进行监控和验证是一个复杂、艰难的过程,它不仅包括要完成复杂的查询,还有代码的重写、重编译及每次增加或改变信息后系统的重新运行.主动数据库系统通过探测数据库信息的变化及对变化做出回应来支持该应用,这包括支持指定的触发器系统来完成对某些数据的控制任务和监控信息的改变,而当前触发器系统的问题就在于在一个动态的和不断演化的环境中它对探测和监控信息和数据流的支持有限,为突破该限制提出了一种机制,该机制中触发器可以在动态的工作流环境中对信息和数据流进行监控.     

Interpretation of C- and X-band radar images over an agricultural area,the Flevoland test site in the Agriscatt-87 campaign

C-band SAR and X-band SLAR radar backscattering data collected over an agricultural area in The Netherlands, during the Agriscatt 1987 campaign, were compared and analysed in relation to type and structural properties of soil cover. The C- and X-band data were found to be similar in major trends. The variation in field-average radar backscattering values, however, was smaller in the C-band than in the X-band. Some fields showed a strong look direction dependence while others showed a strong polarization dependence of the backscattering. From field observation and from a theoretical analysis, incorporating the different structures and spatial orientations of the canopies elements, it was shown that non-uniform azimuthal distribution was the main cause for this phenomenon. It was concluded that these different types of backscattering behaviour can be two aspects of a single physical mechanism.

Signature interpretation problems may arise when these effects—non-uniform azimuthal distributions being caused by prevailing winds, lodging, harvesting or heliotropic behaviour-are not properly accounted for. This may be particularly important when monitoring systems like the ERS-I SAR are used, operating in two different look directions, i.e., in the ascending and descending nodes. For instance, in the data set investigated, the effect of look direction and state of polarization on the separation between classes of land cover type and condition was found to be large.     

Monitoring fall foliage coloration dynamics using time-series satellite data

Fall foliage coloration is a phenomenon that occurs in many deciduous trees and shrubs worldwide. Measuring the phenology of fall foliage development is of great interest for climate change, the carbon cycle, ecology, and the tourist industry; but little effort has been devoted to monitoring the regional fall foliage status using remotely-sensed data. This study developed an innovative approach to monitoring fall foliage status by means of temporally-normalized brownness derived from MODIS (Moderate Resolution Imaging Spectroradiometer) data. Specifically, the time series of the MODIS Normalized Difference Vegetation Index (NDVI) was smoothed and functionalized using a sigmoidal model to depict the continuous dynamics of vegetation growth. The modeled temporal NDVI trajectory during the senescent phase was further combined with the mixture modeling to deduce the temporally-normalized brownness index which was independent of the surface background, vegetation abundance, and species composition. This brownness index was quantitatively linked with the fraction of colored and fallen leaves in order to model the fall foliage coloration status. This algorithm was tested by monitoring the fall foliage coloration phase using MODIS data in northeastern North America from 2001 to 2004. The MODIS-derived timing of foliage coloration phases was compared with in-situ measurements, which showed an overall absolute mean difference of less than 5 days for all foliage coloration phases and about 3 days for near peak coloration and peak coloration. This suggested that the fall foliage coloration phase retrieved from the temporally-normalized brownness index was qualitatively realistic and repeatable.     

Classification of new-ice in the Greenland Sea using Satellite SSM/I radiometer and SeaWinds scatterometer data and comparison with ice model

In the ice covered waters of the Greenland Sea the polarisation ratio of QuikSCAT SeaWinds Ku-band (13.4 GHz) scatterometer measurements and the polarisation ratio of DMSP-SSM/I 19 GHz radiometer measurements are used in combination to classify new-ice and mature ice. In particular, the formation of the new-(frazil/pancake)-ice ‘Odden’ (8° W, 75° N) March 11th-18th, 2001, is used in the study. The results of the ice cover classification in the Greenland Sea are compared to model parameters from a sea ice model. The classification of each ice pixel is performed using its backscatter and radiative properties as reflected in the polarisation ratio. Our results based on these comparisons show that the transformation into older mature (sheet) ice occurs within 5-10 days. During one day the new-ice cover increased by 33 000 km². The new-ice appears in March 2001 as a peninsula (maximum extent 56 000 km²) appended to the belt of older ice drifting along the East Coast of Greenland. These results are consistent with the ice model and with Radarsat images. Furthermore, using the ice model it is demonstrated that the new-ice/mature ice threshold in the classification corresponds to the physical transition of the ice cover from pancake ice to a consolidated young-ice sheet. The classification of each pixel into ice or water is done using two scatterometer parameters, namely the polarisation ratio and the daily standard deviation of the backscatter.     

Assessing snowmelt dynamics with NASA scatterometer (NSCAT) data and a hydrologic process model

The presence of snow strongly impacts the exchange of moisture and energy between the land surface and atmosphere. In the interior of the northern hemisphere continents, snowmelt on frozen soils can cause or exacerbate major floods. Microwave remote sensing from satellite platforms has the potential to monitor the freeze-thaw status of soil and overlying snow packs over large areas. We evaluate the backscatter response of the NSCAT scatterometer to changing snow surface conditions, especially freeze and thaw status, using a macroscale hydrology model and the NSCAT backscatter data for the upper Mississippi River basin of the north central U.S. and the Boreal Ecosystem Atmosphere Study (BOREAS) region in central Canada. We compared the snowmelt conditions simulated by the Variable Infiltration Capacity (VIC) macroscale hydrology model driven with surface meteorological observations with NSCAT measurements for 1996-1997 snow season. A mid-winter thaw event (in February) and late season melt (April-May) are evaluated for both regions. Comparison of backscatter images with daily and hourly-modeled snow surface wetness and temperature showed that the model agreed with the backscatter for snow surface wetness on some days but not on others. Factors such as NSCAT overpass times, vegetation on the ground and their freeze-thaw state, and liquid moisture content appear to contribute to these discrepancies.     

Monitoring subway construction using Sentinel-1 data: a case study in Bucharest,Romania

ABSTRACT

In Bucharest, new subway tunnels are under construction since 2011. The whole project of extending Bucharest underground infrastructure is due to be finished by 2030. The M-5 artery has been under construction since 2011 and ongoing. In December 2015, dewatering procedures in one of the metro stations caused serious damage to the surface infrastructure above, which subsided and partially collapsed in some locations. This paper relies on multi-temporal interferometry techniques to characterize displacement patterns of the ground surface above M-5 beltway between 2014 and 2018, and presents the capacity of Sentinel-1 satellite imagery to detect potential hazards in urban environments. Two stacks of Synthetic Aperture Radar (SAR) images acquired between October 2014 and October 2018 by the Sentinel-1 A and B satellites on ascending and descending orbits have been processed using the Delft Persistent Scatterer Interferometry algorithm (DePSI). The results indicate atypical acceleration in velocities starting in November 2015, prior to the described events, and manifesting until April 2016, when the ground was completely stabilized. The displacement trends and velocity values in the area of the Eroilor underground station were successfully validated using the ground-based Global Navigation Satellite Systems (GNSS) technique.     

Monitoring leaf area of sugar beet using ERS-1 SAR data

This paper presents the results of field testing a radar model which relates leaf area index to radar backscatter for ERS-1 C-band VV polarization SAR data. Ground truth measurements of leaf area index and soil moisture content were made in selected sugar beet fields, with simultaneous acquisition of ERS-1 SAR image data. Radar backscatter coefficients were derived from the calibrated ERS-1 SAR data. The Leeuwen and Clevers expression of the water cloud model was fitted to determine the in situ relationship between radar back-scatter and leaf area index. The model can be inverted analytically to calculate leaf area index from radar backscatter. The results show considerable potential for the operational application of ERS-1 SAR data in crop monitoring.     

Monitoring global land surface using Nimbus-7 37 GHz data Theory and examples

Abstract

Radiative transfer models for 37 GHz brightness temperatures are developed under simplifying assumptions and the implications of the models are illustrated and discussed using the Nimbus-7 scanning multichannel microwave radiometer (SMMR) observations of the Earth's surface from January 1979 to December 1985. The difference of vertically and horizontally polarized brightness temperatures (ΔT) decreases with increasing vegetation density (that is, as the canopy water content per unit ground area increases) and this effect of vegetation density on ΔT is illustrated by the time series of ΔT over areas with varied vegetation density and phenology. Furthermore, the ΔT decreases as the surface roughness increases, and thus mountainous areas within sparsely vegetated areas (like the Sahara) have the appearance of more densely vegetated areas. Also, the ΔT values increase when the soil gets wet or flooded, and this effect is illustrated by correlating the temporal variations of ΔT with the river height for an area within the Amazon Basin. As examples of a more quantitative analysis of the ΔT data, empirical relations are developed between the integrated-average of the 84 months of ΔT data and the annual rainfall, primary productivity and actual evaporation. An analytical relation between primary productivity and ΔT is also established from physically based models under simplifying assumptions. Colour-coded maps of primary productivity and actual evaporation based upon the SMMR data are displayed and discussed in relation to other observations. It is concluded that to realize the full potential of the ΔTdata it would be necessary to calibrate and validate this data against ground observations and develop more realistic radiative transfer models in order to gain a better physical understanding.     

Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data

While existing remote sensing-based drought indices have characterized drought conditions in arid regions successfully, their use in humid regions is limited. We propose a new remote sensing-based drought index, the Scaled Drought Condition Index (SDCI), for agricultural drought monitoring in both arid and humid regions using multi-sensor data. This index combines the land surface temperature (LST) data and the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, and precipitation data from Tropical Rainfall Measuring Mission (TRMM) satellite. Each variable was scaled from 0 to 1 to discriminate the effect of drought from normal conditions, and then combined with the selected weights. When tested against in-situ Palmer Drought Severity Index (PDSI), Palmer's Z-Index (Z-Index), 3-month Standardized Precipitation Index (SPI), and 6-month SPI data during a ten-year (2000-2009) period, SDCI performed better than existing indices such as NDVI and Vegetation Health Index (VHI) in the arid region of Arizona and New Mexico as well as in the humid region of North Carolina and South Carolina. The year-to-year changes and spatial distributions of SDCI over both arid and humid regions generally agreed to the changes documented by the United States Drought Monitor (USDM) maps.     

Monitoring geomorphologic changes using Landsat TM and ETM+ data in the Hendijan River delta,southwest Iran

Beach and delta areas are dynamic physical features with changes occurring at many spatial and temporal scales due to both general and catastrophic events. Geomorphic changes such as temporal and periodic changes in riverbeds and coasts are common events in all deltaic areas. The Hendijan river basin is located in the southwest of Iran, close to the city of the Hendijan and many villages and rural settlements. Changes in various geomorphic features, such as riverbed and shoreline migration, Sebkhas, alluvial terraces, meanders and old, dry rivers over 48 years of time, were detected and identified using Landsat TM and ETM satellite data and topographic maps. Simple bands subtraction, principal component analysis (PCA) and fuzzy logic were used to identify regions that have undergone land cover change. Results of this study show that the Hendijan River channel has migrated several times over the last 48 years. Several meanders and ox‐bow lakes remain as a result of migration. The shoreline has migrated over 4 km into the Persian Gulf. The resulting maps can be used in an integrated coastal zone information system as it has been proposed for the Heddijan delta.     

Monitoring land-use change-associated land development using multitemporal Landsat data and geoinformatics in Kom Ombo area,South Egypt

Due to the progressive increase in population, sustainable development of desert land in Egypt has become a strategic priority in order to meet the increasing demands of a growing population for food and housing. Such obligations require efficient compilation of accurate land-cover information in addition to detailed analysis of archival land-use changes over an extended time span. In this study, we applied a methodology for mapping land cover and monitoring change in patterns related to agricultural development and urban expansion in the desert of the Kom Ombo area. We utilized the available records of multitemporal Landsat Thematic Mapper and Enhanced Thematic Mapper Plus images to produce three land-use/land-cover maps for 1988, 1999 and 2008.

Post-classification change detection analysis shows that agricultural development increased by 39.2% through the study period with an average annual rate of land development of 8.7 km² year^?1. We report a total increase in urbanization over the selected time span of approximately 28.0 km² with most of this urban growth concentrated to the east of the Nile and occurring through encroachment on the former old cultivated lands. The archival record of the length of irrigation canals showed that their estimated length was 341.5, 461.8 and 580.1 km in the years 1988, 1999 and 2008, respectively, with a 70% increase in canal length from 1988 to 2008. Our results not only accurately quantified the land-cover changes but also delineated their spatial patterns, showing the efficiency of Landsat data in evaluating landscape dynamics over a particular time span. Such information is critical in making effective policies for efficient and sustainable natural resource management.