Maria Budzynska

Monitoring Wetlands Ecosystems Using ALOS PALSAR (L-Band, HV) Supplemented by Optical Data: A Case Study of Biebrza Wetlands in Northeast Poland

The aim of the study was to elaborate the remote sensing methods for monitoring wetlands ecosystems. The investigation was carried out during the years 2002–2010 in the Biebrza Wetlands. The meteorological conditions at the test site varied from extremely dry to very wet. The authors propose applying satellite remote sensing data acquired in the optical and microwave spectrums to classify wetlands vegetation habitats for the assessment of vegetation changes and estimation of wetlands’ biophysical properties to improve monitoring of these unique, very often physically impenetrable, areas. The backscattering coefficients (σ°) calculated from ALOS PALSAR FBD (Advanced Land Observing Satellite, Phased Array type L-band Synthetic Aperture Radar, Fine Beam Dual Mode) images registered at cross polarization HV on 12 May 2008 were used to classify the main wetland communities using ground truth observations and the visual interpretation method. As a result, the σ° values were distributed among the six wetlands’ vegetation classes: scrubs, sedges-scrubs, sedges, reeds, sedges-reeds, rushes, and the areas of each community and changes were assessed. Also, the change in the biophysical variable as Leaf Area Index (LAI) is described using the information from PALSAR data. Strong linear relationships have been found between LAI and σ° derived for particular wetland classes, which then were applied to elaborate the maps of LAI distribution. The other variables used to characterize the changing environmental conditions are: surface temperature (Ts) calculated from NOAA AVHRR (National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer) and Normalized Difference Vegetation Index (NDVI) from ENVISAT MERIS (ENVIronmental SATellite MEdium Resolution Imaging Spectrometer). Differences of almost double Ts between “dry” and “wet” years were noticed that reflect observed weather conditions. The highest values of NDVI occurred in years with a sufficient amount of precipitation with the lowest in “dry” years. NDVI values variances within the same wetlands class resulted mainly from the differences in soil moisture. The results of this study show that the satellite data from microwave and optical spectrum gave the repetitive spatial information about vegetation growth conditions and could be used for monitoring wetland ecosystems.

Study in Biebrza Wetlands using optical and microwave satellite data

This study was conducted during 2003-2009 in Biebrza Wetlands, a NATURA 2000 and Ramsar Convention test site situated in Northeast Poland. It is one of the largest in Europe natural rich biotope with the large amount of unique spices of flora and important zone for nesting and wintering for fauna. Protection of wetlands that are very sensitive ecosystems are of great importance in nature conservation for carbon and water cycles. Changes of soil water content affect plant cover and lead to elimination or preference of certain species. Controlling soil moisture is essential for protection of peat-forming plant communities and slow down drying processes against mineralization and carbon exhaust. Data from optical and microwave satellite images and soil-vegetation ground measurements were analyzed to develop methods for monitoring and mapping soil-vegetation parameters over wetlands. This study was conducted in the framework of national grant N N526021733 and ESA projects AOID.122 and AOALO.3742.

Importance of grasslands monitoring applying optical and radar satellite data in perspective of changing climate

Grasslands deliver wide range of ecosystem services such as carbon sequestration, water quality, flood and erosion control as well as biomass. But since they are impacted by climate change, there is a need for their constant monitoring. Due to climate changes the following grasslands growth conditions are modified: soil moisture, biomass and as a consequence carbon balance. Required multi-temporal and spatial observations are possible with satellite data. The objective of this paper is to present the long term observations of temperature and vegetation conditions (NDVI) of grasslands on the basis of MODIS satellite data as well as already performed and further scheduled frequent analysis of carbon balance, soil moisture and biomass performed with the application of Sentinel1 A; B and Sentinel2 A&B.

Application of Sentinel-1 VH and VV and Sentinel-2 for soil moisture studies

The results of application of microwave and optical satellite data for soil moisture (SM) assessment are presented. The research has been carried out from 2015 to 2016 at Biebrza Wetlands test site located in North-East Poland, designated by Ramsar Convention as Wetlands of International Importance. A regression models based on Sentinel-1 backscattering coefficients (σ°) have been developed to generate the soil moisture (SM) maps over Biebrza Wetlands. The optical data from Sentinel-2 have been used for the classification of wetlands vegetation habitats to improve SM predictions. The wetland vegetation differed, there were reeds, sedge-moss, sedges, grass-herbs, and grass. The majority of the changes occurred in moist habitats, while anthropogenic appeared more stable during study period. The observed changes were referred to moving/grazing changes and weather effects causing droughts/floods. SM differed from 30% during the drought season in 2015 to 95% in the wet season in 2016. It has been examined the impact of biomass and SM on microwave signal under changing soil moisture and vegetation growth conditions. Vegetation biomass has been characterized by measured in-situ LAI and by vegetation indices calculated from Sentinel-2, Terra MODIS data. The impact of SM and LAI on σ° calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when SM is low. The analysis have been done to estimate the threshold of the SM values which dominate the backscatter. This study demonstrates the capability of Sentinel-1/2 data to estimate SM, offering an important advantage for wetlands monitoring.

The study of multifrequency microwave satellite images for vegetation biomass and humidity of the area under Ramsar convention

Wetland ecosystems keep large amounts of organic carbon and have large influence on global climate change. Net ecosystem exchange (NEE) have been modeled by means of microwave satellite images. Assessment of biomass and soil moisture has been essential for the study to elaborate the methodology for evaluating carbon sink at the ecosystem under Ramsar Convention. Backscattering coefficient (σ̊) calculated from microwave images acquired by ENVISAT, ALOS and Sentinel-1 radar sensors was analyzed along with ground truth measurements of biomass, LAI, soil moisture (SM) and NEE carried out for vegetation classes distinguished from MERIS image. The models for NEE were developed using IS4 VV which represented vegetation biomass and IS4 HH representing SM. Application of the independent set of microwave data which were possible to gather gives a valuable opportunity to verify the accuracy in assessment of biomass and humidity based on various available sensors.

Study and implementation of microwave and optical data for assessment of carbon balances for wetlands under changes of biomass and humidity conditions

The results of measurements of CO2 exchange in various wetland communities were elaborated for the area of Biebrza National Park in north-eastern Poland. The research has been done within ongoing ESA-PECS and National Research Project (No N N526 160040) realized in the Institute of Geodesy and Cartography, Remote Sensing Department in Warsaw. CO2 flux measurements were performed with a static chamber method from April till September from 2010 - 2012. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined and the best combination of microwave variables ENVISAT ASAR (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. Carbon input to an ecosystem occurs through the process of photosynthesis. The rate of photosynthesis (CO2 uptake) is referred to as gross primary production (GPP). CO2 is in turn released to the atmosphere through respiration. The difference between GPP and Reco is referred to as net ecosystem exchange (NEE). By estimating the direction of NEE, it is possible to determine whether a surface is a likely source or a sink of carbon. The NEE has been related to biomass and soil moisture which was also related to the ratio of NDVI and Ts from NOAA/AVHRR.

Microwave satellite data applied for agriculture area — Case study — Poland

The radar data have been used for establishing the proper crop information system in Poland. The objective of the study is to find an efficient method of crop classification based on satellite microwave data and to find the relationship of different soil — vegetation parameters on backscatter. There is a large demand of microwave images as due to often cloud effect these satellite data are available during a certain growth season. Wielkopolska region located in western Poland was selected for the research works. This region, characterized by intensive agricultural practices and diversified agricultural pattern, was equipped with ground truth information, which enabled to make properly the whole classification process.

Detection of water deficit using optical data — case study Poland

The SPOT VEGETATION and NOAA AVHRR images have been used as the source of information on crop growing conditions and yield forecast for cereals and winter wheat in Poland. Three indices — Vegetation Condition Index (VCI), Accumulated Vegetation Condition Index (AVCI) based on NDVI and Temperature Condition Index (TCI) based on surface temperature have been computed for agriculture area in Poland. These indices were correlated with cereal yield and critical periods of crop development were found as significant for this relationship. The information about indices from particle decades was included into the cereals and winter wheat yield modelling. The database of the indices and obtained statistical models were used for developing the Predictive Indices (PTVCI, PTAVCI, VCIAVG) applied for the forecast of yield for each decade of the year. The method may be used operationally due to its simplicity and easy obtainable data.

Application of Microwave Data for Agriculture Area

The study was carried out for agricultural area in Poland for the years 2003-2007. The aim of the project was to examine the impact of soil-vegetation parameters on backscatter calculated from ENVISAT.ASAR under various polarizations and incidence angles. The extensive field measurements have been carried out simultaneously to satellite overpasses. Additionally to microwave acquisitions the optical data from TERRA.ASTER satellite have been used to distinguish different crop types. There has been applied two approaches: (1) for each of the class the equations for calculation of LAI and soil moisture from microwave data have been derived using statistical analyses, and the maps of LAI and soil moisture have been presented; (2) the semi empirical water-cloud model has been applied to describe the contribution of soil moisture and winter wheat descriptor as LAI on backscattering coefficient. The results show that presented methods can be implemented into monitoring of crop growth.