Multi-source Satellite Data Research Articles

Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area.

Remote sensing of alpine lake water environment changes on the Tibetan Plateau and surroundings: A review

Alpine lakes on the Tibetan Plateau (TP) are key indicators of climate change and climate variability. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring lake changes on the TP and surroundings and understanding climate change impacts, particularly in remote and inaccessible areas where there are lack of in situ observations. This paper firstly introduces characteristics of Tibetan lakes, and outlines available satellite observation platforms and different remote sensing water-body extraction algorithms. Then, this paper reviews advances in applying remote sensing methods for various lake environment monitoring, including lake surface extent and water level, glacial lake and potential outburst floods, lake ice phenology, geological or geomorphologic evidences of lake basins, with a focus on the trends and magnitudes of lake area and water-level change and their spatially and temporally heterogeneous patterns. Finally we discuss current uncertainties or accuracy of detecting lake area and water-level changes from multi-source satellite data and on-going challenges in mapping characteristics of glacial lakes using remote sensing. Based on previous studies on the relationship between lake variation and climate change, it is inferred that the climate-driven mechanisms of lake variations on the TP still remain unclear and require further research.

New dimensions of urban landscapes: The spatio-temporal evolution from a polynuclei area to a mega-region based on remote sensing data

Currently our world is facing a migration process of a huge dimension – from rural to urban areas. In 1975 37.7% of the global population were urban dwellers, 1990 already 43%, today little over 50%, and in 2050 the expected number is 67.2%. This great process shapes new spatial urban landscapes, in dimension and pattern. In this study we aim at analyzing the spatial evolution of a once polynuclei urban area to a mega-region in a 35 years time frame. Using multi-temporal and multi-source satellite data we classify urban footprints of a mega-region – the Hong Kong–Shenzhen–Guangzhou mega-region in Southern China – for the years 1975, 1990, 2000 and 2011. Based on this geospatial data set we aim at turning the qualitative and fuzzy definitions of mega-regions into a physical concept. Furthermore, we suggest a set of spatial features potentially characteristic for the evolution of mega-regions. In particular we apply and develop a multiude of spatial metrics at three spatial levels, namely the entire mega-region, the hinterlands between different cities and the cities themselves. The result is a novel spatial approach to capture, measure and analyze new shapes of urban landscapes.

Modelling the diurnal variations of urban heat islands with multi-source satellite data

Examination of the diurnal variations in surface urban heat islands (UHIs) has been hindered by incompatible spatial and temporal resolutions of satellite data. In this study, a diurnal temperature cycle genetic algorithm (DTC-GA) approach was used to generate the hourly 1 km land-surface temperature (LST) by integrating multi-source satellite data. Diurnal variations of the UHI in ‘ideal’ weather conditions in the city of Beijing were examined. Results show that the DTC-GA approach was applicable for generating the hourly 1 km LSTs. In the summer diurnal cycle, the city experienced a weak UHI effect in the early morning and a significant UHI effect from morning to night. In the diurnal cycles of the other seasons, the city showed transitions between a significant UHI effect and weak UHI or urban heat sink effects. In all diurnal cycles, daytime UHIs varied significantly but night-time UHIs were stable. Heating/cooling rates, surface energy balance, and local land use and land cover contributed to the diurnal variations in UHI. Partial analysis shows that diurnal temperature range had the most significant influence on UHI, while strong negative correlations were found between UHI signature and urban and rural differences in the normalized difference vegetation index, albedo, and normalized difference water index. Different contributions of surface characteristics suggest that various strategies should be used to mitigate the UHI effect in different seasons.

Establishing an operational waterhole monitoring system using satellite data and hydrologic modelling: Application in the pastoral regions of East Africa

Timely information on the availability of water and forage is important for the sustainable development of pastoral regions. The lack of such information increases the dependence of pastoral communities on perennial sources, which often leads to competition and conflicts. The provision of timely information is a challenging task, especially due to the scarcity or non-existence of conventional station-based hydrometeorological networks in the remote pastoral regions. A multi-source water balance modelling approach driven by satellite data was used to operationally monitor daily water level fluctuations across the pastoral regions of northern Kenya and southern Ethiopia. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used for mapping and estimating the surface area of the waterholes. Satellite-based rainfall, modelled run-off and evapotranspiration data were used to model daily water level fluctuations. Mapping of waterholes was achieved with 97% accuracy. Validation of modelled water levels with field-installed gauge data demonstrated the ability of the model to capture the seasonal patterns and variations. Validation results indicate that the model explained 60% of the observed variability in water levels, with an average root-mean-squared error of 22%. Up-to-date information on rainfall, evaporation, scaled water depth and condition of the waterholes is made available daily in near-real time via the Internet (http://watermon.tamu.edu). Such information can be used by non-governmental organizations, governmental organizations and other stakeholders for early warning and decision making. This study demonstrated an integrated approach for establishing an operational waterhole monitoring system using multi-source satellite data and hydrologic modelling.

Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

Abstract. Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80% of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in situ datasets. In this study, we used 12 yr (1998–2009) of existing multi-source satellite and model-assimilated global weather data. We used a calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of the Gibe III dam using three different approaches – a historical approach, a rainfall based approach, and a statistical approach to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the Gibe III dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8–10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 1–2 m (95% confidence) compared to the lake level modeled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modeling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas along the Lake Turkana shoreline that are vulnerable to fluctuations in lake levels due to the Gibe III dam were also identified. This study demonstrates the effectiveness of using existing multi-source satellite data in a basic modeling framework to assess the potential hydrological impact of an upstream dam on a terminal downstream lake. The results obtained from this study could also be used to evaluate alternative dam-filling scenarios and assess the potential impact of the dam on Lake Turkana under different operational strategies.

Satellites Capture the Drought Severity Around China's Largest Freshwater Lake

A severe drought occurred in the region of Poyang Lake, the largest freshwater lake in China in early 2011, causing various environmental problems and posing a significant threat to local animals and humans. The event has caught extensive attention from many environmental groups as well as from national and international news media. Yet there has been no quantitative report on the severity of the drought except some qualitative description of water levels and local dry/wet conditions. Here we demonstrate how satellites can provide a quantitative measure of the severity of the large-scale drought, and how the current drought event may compare with historical conditions. The inclusion of the multi-source satellite data over a 12-year period also led to the conclusion that the drought was primarily caused by the significantly low precipitation. While there was a widespread rumor in China that the impoundment of the Three Gorges Dam (TGD) could lead to the severe drought, available data did not support such a hypothesis. Through this example, we hope to provide a perspective on the unique value of multi-source satellite data in quantifying environmental conditions in a changing climate.

Changing landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: Land use/land cover, vegetation cover changes estimated using multi-source satellite data

The eco-environment in the Three Gorges Reservoir Area (TGRA) in China has received much attention due to the construction of the Three Gorges Hydropower Station. Land use/land cover changes (LUCC) are a major cause of ecological environmental changes. In this paper, the spatial landscape dynamics from 1978 to 2005 in this area are monitored and recent changes are analyzed, using the Landsat TM (MSS) images of 1978, 1988, 1995, 2000 and 2005. Vegetation cover fractions for a vegetation cover analysis are retrieved from MODIS/Terra imagery from 2000 to 2006, being the period before and after the rising water level of the reservoir. Several analytical indices have been used to analyze spatial and temporal changes. Results indicate that cropland, woodland, and grassland areas reduced continuously over the past 30 years, while river and built-up area increased by 2.79% and 4.45% from 2000 to 2005, respectively. The built-up area increased at the cost of decreased cropland, woodland and grassland. The vegetation cover fraction increased slightly. We conclude that significant changes in land use/land cover have occurred in the Three Gorges Reservoir Area. The main cause is a continuous economic and urban/rural development, followed by environmental management policies after construction of the Three Gorges Dam.

Satellite Image Analysis for Disaster and Crisis-Management Support

This paper describes how multisource satellite data and efficient image analysis may successfully be used to conduct rapid-mapping tasks in the domain of disaster and crisis-management support. The German Aerospace (DLR) has set up a dedicated crosscutting service, which is the so-called Center for satellite-based Crisis Information (ZKI), to facilitate the use of its Earth-observation capacities in the service of national and international response to major disaster situations, humanitarian relief efforts, and civil security issues. This paper describes successful rapid satellite mapping campaigns supporting disaster relief and demonstrates how this technology can be used for civilian crisis-management purposes. During the last years, various international coordination bodies were established, improving the disaster-response-related cooperation within the Earth-observation community worldwide. DLR/ZKI operates in this context, closely networking with public authorities (civil security), nongovernmental organizations (humanitarian relief organizations), satellite operators, and other space agencies. This paper reflects on several of these international activities, such as the International Charter Space and Major Disasters, describes mapping procedures, and reports on rapid-mapping experiences gained during various disaster-response applications. The example cases presented cover rapid impact assessment after the Indian Ocean Tsunami, forest fires mapping for Portugal, earthquake-damage assessment for Pakistan, and landslide extent mapping for the Philippines

The Use of Multisource Satellite and Geospatial Data to Study the Ecological Effects of Urbanization:A Case of the Urban Agglomerations in Bohai Rim

The Use of Multisource Satellite and Geospatial Data to Study the Ecological Effects of Urbanization:A Case of the Urban Agglomerations in Bohai Rim

The use of multisource satellite and geospatial data to study the effect of urbanization on primary productivity in the United States

Data from two different satellites, a digital land cover map, and digital census data were analyzed and combined in a geographic information system to study the effect of urbanization on photosynthetic productivity in the United States. Results show that urbanization can have a measurable but variable impact on the primary productivity of the land surface. Annual productivity can be reduced by as much as 20 days in some areas, but in resource limited regions, photosynthetic production can be enhanced by human activity. Overall, urban development reduces the productivity of the land surface, and those areas with the highest productivity are directly in the path of urban sprawl.

Multisource ERS-1 and optical data for vegetal cover assessment and monitoring in a semi-arid region of Algeria

This paper highlights advantages of using Synthetic Aperture Radar (SAR) data combined with multispectral data to improve vegetal cover assessment and monitoring in a semi-arid region of southern Algeria. We present a number of preprocessing and processing techniques using multidate optical data analysis alone and SAR ERS-1 and Landsat Thematic Mapper (TM) data integration due to aspects of radar image enhancement techniques and the study of roughness of different types of vegetation in steppic regions. Image data integration has become a valuable approach to integrate multisource satellite data. It has been found that image data from different spectral domains (visible, near-infrared, microwave) provides datasets with complementarity information content and can be used to improve the spatial resolution of satellite images. In this communication, we present a part of the cooperation research project which deals with fusing ERS-1 SAR geocoded images with Landsat TM data, investigating different combinations of integration and classification techniques. The methodology consists of several steps: (1) Speckle noise reduction by comparative performance of different filtering algorithms. Several filtering algorithms were implemented and tested with different window sizes, iterations and parameters. (2) Geometric superposition and geocoding of optical images regarding SAR ERS-1 image and resampling at unique resolution of 25 m. (3) Application of different numerical combinations of integration techniques and unsupervized classifications such as the Forgy method, the MacQueen method and other methods. The results were compared with vegetal cover mapping from aerial photographs of the region of Foum Redad in the south of the Saharian Atlas. The combinations proposed above allow us to distinguish different themes in the arid and semi-arid regions in the south of the Saharian Atlas using a colour composite image and show a good correlation between different types of land cover and land use and radar backscattering level in the SAR data which corresponds essentially to the roughness of the soil surface.

Image processing applications for geologic mapping

The use of satellite data, particularly Landsat images, for geologic mapping provides the geologist with a powerful tool. The digital format of these data permits applications of image processing to extract or enhance information useful for mapping purposes. Examples are presented of lithologic classification using texture measures, automatic lineament detection and structural analysis, and use of registered multisource satellite data. In each case, the additional mapping information provided relative to the particular treatment is evaluated. The goal is to provide the geologist with a range of processing techniques adapted to specific mapping problems.