Distinguishing Growth Stages of Wheat Crop by Remote Sensing Techniques and Time Series Analysis

Remote sensing has attracted the attentions by providing a broad and comprehensive view of the world. The use of remote sensing in various fields such as agriculture is constantly expanding. Spectral bands in visible and infrared ranges can be used to discriminate between phenomena and ground cover by computing various spectral indices. Investigating plant physiology is essential to know the physiological and ecological aspects of plant functions. In this study, images of Sentinel-2 satellite were used to compute spectral indices and correlate them with phenological stages of wheat crop in two agricultural centers in Fars province, Iran. Zadoks scale is one of the most reputed methods to state growth stages of wheat crop. The Zadoks scale uses two-digit codes to demonstrate different phenological processes. In this study, nine growing stages were carefully identified using ground truth method. After calculating two spectral indices of normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) on satellite images of various dates during the growing season, NDVI and SAVI time series were generated. Each time series image consisted of nine bands, each band being an image obtained from a wheat growing stage. Study the trend between NDVI and SAVI indices and the Zadoks scale showed that the phenological stages of wheat can be identified using remote sensing technology

Intercomparison of Surface Albedo Retrievals from MISR, MODIS, CGLS Using Tower and Upscaled Tower Measurements

Surface albedo is of crucial interest in land–climate interaction studies, since it is a key parameter that affects the Earth’s radiation budget. The temporal and spatial variation of surface albedo can be retrieved from conventional satellite observations after a series of processes, including atmospheric correction to surface spectral bi-directional reflectance factor (BRF), bi-directional reflectance distribution function (BRDF) modelling using these BRFs, and, where required, narrow-to-broadband albedo conversions. This processing chain introduces errors that can be accumulated and then affect the accuracy of the retrieved albedo products. In this study, the albedo products derived from the multi-angle imaging spectroradiometer (MISR), moderate resolution imaging spectroradiometer (MODIS) and the Copernicus Global Land Service (CGLS), based on the VEGETATION and now the PROBA-V sensors, are compared with albedometer and upscaled in situ measurements from 19 tower sites from the FLUXNET network, surface radiation budget network (SURFRAD) and Baseline Surface Radiation Network (BSRN) networks. The MISR sensor onboard the Terra satellite has 9 cameras at different view angles, which allows a near-simultaneous retrieval of surface albedo. Using a 16-day retrieval algorithm, the MODIS generates the daily albedo products (MCD43A) at a 500-m resolution. The CGLS albedo products are derived from the VEGETATION and PROBA-V, and updated every 10 days using a weighted 30-day window. We describe a newly developed method to derive the two types of albedo, which are directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), directly from three tower-measured variables of shortwave radiation: downwelling, upwelling and diffuse shortwave radiation. In the validation process, the MISR, MODIS and CGLS-derived albedos (DHR and BHR) are first compared with tower measured albedos, using pixel-to-point analysis, between 2012 to 2016. The tower measured point albedos are then upscaled to coarse-resolution albedos, based on atmospherically corrected BRFs from high-resolution Earth observation (HR-EO) data, alongside MODIS BRDF climatology from a larger area. Then a pixel-to-pixel comparison is performed between DHR and BHR retrieved from coarse-resolution satellite observations and DHR and BHR upscaled from accurate tower measurements. The experimental results are presented on exploring the parameter space associated with land cover type, heterogeneous vs. homogeneous and instantaneous vs. time composite retrievals of surface albedo

Towards a better understanding of land surface exchange processes over agricultural crop stands

Weather and climate models are useful tools for projecting the influence of global climate change on the regional scale. These models are critically dependent on an accurate representation of soil-plant-atmosphere interactions, which are simulated by Land Surface Models (LSMs). The present PhD thesis was designed to improve the representation of land surface exchange processes of croplands in the Noah-MP land surface model. This thesis aims: a) to elucidate the nature of the energy imbalance over a winter wheat stand and to identify the appropriate post-closure method for the study region Kraichgau, southwest Germany; b) to improve the representation of the green vegetation fraction (GVF) dynamics of croplands in the Noah-MP for a more accurate computation of surface energy and water fluxes; and c) to determine the effect of aggregating different crop types with various shares into a single generic cropland class on the simulation of water and energy exchange between land surface and atmosphere.Wetter- und Klimamodelle sind nützliche Werkzeuge, um den Einfluss des globalen Klimawandels auf die regionale Ebene zu projizieren. Diese Modelle sind entscheidend von einer genauen Darstellung der Wechselwirkungen zwischen Boden, Pflanzen und Atmosphäre abhängig, welche durch Land Surface Models (LSMs) simuliert werden. Die Dissertation wurde erstellt, um die Darstellung von Landoberflächenaustauschprozessen von Ackerland im Noah-MP-Landoberflächenmodell zu verbessern. In Doktorarbeit geht es um: a) die Art des Energieungleichgewichts über einem Winterweizenbestand aufzuklären und die geeignete Post- Closure-Methode für die Region Kraichgau (Südwestdeutschland) zu identifizieren; b) die Darstellung der Dynamik der Grünen Vegetationsfraktion (GVF) von Anbauflächen im Noah-MP für eine genauere Berechnung der Oberflächenenergie und der Wasserflüsse zu verbessern; und c) um die Auswirkungen der Aggregation verschiedener Kulturarten mit unterschiedlichen Anteilen zu einer einzigen generischen Ackerflächenklasse auf die Simulation des Wasser- und Energieaustauschs zwischen Landoberfläche und Atmosphäre zu bestimmen

Development of a satellite-based dynamic regional vegetation model for the Drâa catchment

Analysing and modelling land cover dynamic of the vegetation under a changing hydrological cycle inside the semi-arid area resulting from the global climate change are a difficult task. It is important to be able to understand and predict the characteristics and availability of vegetation as result of the global climate. This study was carried out inside the upper and middle Drâa catchment in south Morocco, focusing on the natural vegetation outside rural and agricultural areas. Development of a dynamic regional land cover model is traditionally driven by site specific plant growing parameters or by spatial information from remote sensing (e.g. NDVI). By scaling both approaches to a regional level plant activity can be analysed with the MODIS sensor and interpreted by local measurements. By using signal processing techniques, a double regression approach was developed and tested under the conditions of temporal trends and performance parameters. Completed by a regional adopted vegetation model, important productivity parameters could be extracted. This semi-automatic approach is realized in the conceptual model MOVEG Drâa, bringing together remote sensing, meteorological and other data and techniques. An extensive phenological database was built up by integrating Terra MODIS NDVI time series (2000 until 2008), a vegetation monitoring network and 10 years of meteorological measurements. In order to validate the method a comprehensive field measurement along a North-South transect was established. The results show that a robust point conclusion on vegetation trends and parameters on a statistical significant level is possible. Based on these findings a spatial explicit output was realized by a spatial extrapolation technique considering the annual and intra-annual vegetation trends. Based on the IPCC Scenarios (A1B and B1) a forecast of vegetation activity and productivity was implemented until 2050. MOVEG DRAA is an improvement to the hitherto state of unknown atmospheric-vegetation-relationship for the semi-arid area of southern Morocco. The study reveals that the semi automatic modular model approach is capable of handling the highly variable vegetation signal and projecting further scenarios of environmental changes. The model output will help to refine all models using land cover information (e.g. pastoral modelling), hydrological modelling (e.g. SWAT) and meteorological parameterisations (e.g. FOOD3DK). The output of the MOVEG DRAA model can also built a valuable information source for all kind of land users

Improving estimation of gross primary productivity of terrestrial ecosystems

The MOderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity to monitor and quantify seasonal changes of vegetation and phenology. MODIS has the potential to improve the estimation, which is based on the algorithms for the NOAA Advanced Very High Resolution Radiometer (AVHRR), of biophysical/biochemical variables of vegetation. My doctoral study improves estimation of gross primary productivity (GPP) through two aspects: first, my study improved the detection of vegetation phenology by distinguishing MODIS contaminated observations and contamination-free observations, and secondly, I inverted the fraction of absorbed photosynthetically active radiation (PAR) by chlorophyll using radiative transfer models and daily MODIS data. My dissertation has five aspects: (1) to develop a procedure to distinguish atmospherically contaminated observations, snow contaminated observations and contamination-free observations; (2) to monitor vegetation phenology using reflectance of the seven MODIS spectral bands for land and relative vegetation indices; (3) to clarify the concepts of fractions of PAR absorbed by canopy, leaf and chlorophyll; (4) to explore the potential of estimating the fractions of PAR absorbed at different scales; and (5) to check if vegetation seasonal MODIS spectral variations during plant growing season are only due to vegetation\u27s anisotropic nature. A procedure to extract contamination-free daily MODIS observations is proposed and developed. It has been employed for the Harvard Forest site, the Howland Forest site, the Walker Branch Watershed Forest site, the km67 Forest site in tropic, a soybean site in Nebraska, the Xilingol grassland site in China, the Bartlett Experimental Forest site, and two broadleaf deciduous forest sites in Missouri. The extracted MODIS signals (reflectance and vegetation indices) provide rich information for interpretation. The richness of information from the results goes beyond the widely used normalized difference vegetation index (NDVI) and leaf area index (LAI). The more precise phenology information can be used for seasonal GPP estimation. The concepts of fractions of PAR absorbed by canopy, leaf and chlorophyll are described. I extracted fraction of PAR absorbed by chlorophyll for the Harvard Forest site, the Bartlett Experimental Forest site and the two deciduous broadleaf forest sites in Missouri using a coupled canopy-leaf radiative transfer model and daily MODIS data. Metropolis algorithm is used to invert the variables in the radiative transfer model. It provides posterior distributions for individual variables. Some of the inverted variables have been partly evaluated though validation for all variables is extremely expensive. Using the values of inverted variables of the two forest sites in Missouri, I calculated reflectance for the seven MODIS spectral ranges with real MODIS viewing geometries through whole growing season. I found that there should be other factors, except vegetation\u27s anisotropic nature, due to seasonal MODIS spectral variations of the forests during the plant growing season. My study suggests that in addition to measurements of canopy-level variables (e.g., LAI), field measurements of leaf-level variables (e.g., chlorophyll, other pigments, leaf dry matter, and leaf water content) will be useful for both remote sensing and ecological research

New Advances and Contributions to Forestry Research

New Advances and Contributions to Forestry Research consists of 14 chapters divided into three sections and is authored by 48 researchers from 16 countries and all five continents. Section Whither the Use of Forest Resources, authored by 16 researchers, describes negative and positive practices in forestry. Forest is a complex habitat for man, animals, insects and micro-organisms and their activities may impact positively or negatively on the forest. This complex relationship is explained in the section Forest and Organisms Interactions, consisting of contributions made by six researchers. Development of tree plantations has been man’s response to forest degradation and deforestation caused by human, animals and natural disasters. Plantations of beech, spruce, Eucalyptus and other species are described in the last section, Amelioration of Dwindling Forest Resources Through Plantation Development, a section consisting of five papers authored by 20 researchers. New Advances and Contributions to Forestry Research will appeal to forest scientists, researchers and allied professionals. It will be of interest to those who care about forest and who subscribe to the adage that the last tree dies with the last man on our planet. I recommend it to you; enjoy reading it, save the forest and save life

Goddard Visiting Scientist Program for the Space and Earth Sciences Directorate

A visiting scientist program was conducted in the space and earth sciences at GSFC. Research was performed in the following areas: astronomical observations; broadband x-ray spectral variability; ground-based spectroscopic and photometric studies; Seyfert galaxies; active galactic nuclei (AGN); massive stellar black holes; the differential microwave radiometer (DMR) onboard the cosmic background explorer (COBE); atmospheric models; and airborne and ground based radar observations. The specific research efforts are detailed by tasks