Методы направленные на повышение эффективности времени и затрат как необходимые средства в калибрации данных при дистанционном зондировании

The conventional sampling methods are no longer capable of satisfying the rapidly growing demand toward data and information. There has been a need for a measuring technology that provides broad opportunities of evaluating local or global processes or balances according to various aspects. Hyperspectral imaging spectroscopy, one of the most advanced technologies in optical remote sensing, but to clarify the relation between the feature-specific spectral respond of a surface or material and the studied factor large number of samples are necessary. The objective is to present the technological capabilities of remote sensing of our Institute and to show an alternative method for moisture content mapping which is adequate to collect the necessary amount of data to calibrate and validate airborne hyperspectral images for quantitative measurement of soil moisture content.Tradiciniai mėginių ėmimo metodai jau nebegali patenkinti sparčiai augančio duomenų ir informacijos poreikio. Būtina tapo matavimo technologija, kuri suteikia plačias galimybes įvertinti vietos ir globalių procesų sprendimus pagal įvairius aspektus. Vizualizavimo spektroskopija, viena iš pažangiausių optinių nuotolinių stebėjimų technologijų, tačiau norint nustatyti ryšį tarp paviršiaus arba medžiagos specifinių spektrinių savybių ir analizuojamų veiksnių, reikia paimti daug mėginių. Darbo tikslas yra pateikti Institute sukurtus nuotolinių stebėjimų technologinius įrenginius bei parodyti alternatyvų dirvos drėgnio žemėlapių sudarymo metodą, kuris yra taikomas norint surinkti reikiamą kiekį duomenų, naudojamų kalibruoti ir patvirtinti vizualizavimo spektroskopijos gautus vaizdus, pagal kuriuos atliekamas dirvožemio drėgnio kiekybiniam įvertinimui.Традиционные способы отбора образцов почвы больше уже неспособны удовлетворить стремительно нарастающую потребность в области информационных данных. Необходима стала измерительная технология, которая обеспечивает применяемый широком кругом метод анализа как локальных и глобальных процессов, так и изучения уравновешенных природных систем. Среди оптической дистанционной измерительной техники одной из самых развитых разработок является гиперспектральный дистанционного зондирования, однако для установления зависимости между специфическими спектральными разнообразиями свойств поверхности ландшафта и исследуемым фактором требуется многочисленное количество образцов. В статье представлены разработанные Институтом приборы дистанционных исследований, кроме того альтернативный способ для измерения влаги почвы, который делает осуществимым количественную калибрацию гиперспектральных снимков и валидацию множества результатов

Advances in Remote Sensing applications in site-specific plant production

The objective of this paper is to present an overview of applied remote sensing technologies in agriculture and biosystems engineering in the last decade. Satellite based remote sensing applications were - and still are - applied whereas airborne applications and UAV technology were also in the focus of our late research interest. Various sensors were applied for different purposes: multispectral images from satellite platforms as well as a hyperspectral imaging system operated on an airplane was investigated in the early phase of our monitoring work. Recently multispectral imaging in RGB and NIR channels have been applied on various UAV's. The aim of the research in the early stages were to determine the role of multispectral and hyperspectral based vegetationindices for prodicting yield and grain quality of spring barley in Hungary. Spring barley is commonly used as a raw material for beer production. In order to fulfil the quality expectations of the beer industry, grain protein content prediction and measurement plays an important role in spring barley production and marketability. Multispectral vegetation indices were based on Landsat satellite images, meanwhile hyperspectral indices were based on AISA DUAL Airborne Hyperspectral Imaging Systems. In order to be able to compare data with the calculated indices, yield data was collected during harvest (AgroCom Terminal and Yield Mapping System). Quality data (protein content) was collected by two methods: (a) by band in a systematic grid and analyzed in a laboratory; (b) during harvest by Zeltex On-Combine Grain Analyzer. All collected data was converted to 25 by 25 m and 1 by 1 m pixel size maps by means of interpolation techniques (ArcGIS). Results showed that prediction of grain quality compared to Quantity was achievable with higher confidence in both cases. Correlation between multispectral vegetation indices and yield was in the best case r=-0.5854/n=206/, meanwhile between hyperspectral vegetation indices and yield correlation showed much lower correlation. At the same time correlation between multispectral vegetation indices and grain protein content was r=-0,8118/n=206/, while between hyperspectral vegetation indices and protein content /hand collected samples/ the best result was r=-0.5033. An Airborne measurement campaing war carried out in 2009, where for precision crop production, images were collected prior to harvest in July, and site specific data collection was carried out in order to collect field data about winter wheat yield as well asprotein content. Data collected during harvest by means of on-line sensors was interpolated into the same resolution map as the hyperspectral image. Later a second hyperspectral image was taken with the aim of investigation of the applicability of the technology for soil management. At the same time soil samples were collected from an approximately 16 hectare field. Soil moisture measurement was carried out by means of gravimetric and TDR methods. Furthermore, apparent soil electrical conductivity (ECa) was measured by Veris Techniologies on-line ECa mapping instrument. Geostatistical analysis was carried out in order to compare the different data layers. In the last five years interest in UAV's as carriers has grown enormously worldwide, while sensor technology is developing rapidly. Images during a winter wheat vegetation period and maize vegetation period were taken by mean of RGB and multiSPEC 4C multispectral imaging system (Airinov Inc.). UAV based images were compared with various data collected during the vegetation periods. In the last part of the paper results of UAV based image analysis are reported

Continuous field soil moisture content mapping by means of apparent electrical conductivity (ECa) measurement

Abstract A soil moisture content map is important for providing information about the distribution of moisture in a given area. Moisture content directly influences agricultural yield thus it is crucial to have accurate and reliable information about moisture distribution and content in the field. Since soil is a porous medium modified generalized Archie’s equation provides the basic formula to calculate moisture content data based on measured ECa. In this study we aimed to find a more accurate and cost effective method for measuring moisture content than manual field sampling. Locations of 25 sampling points were chosen from our research field as a reference. We assumed that soil moisture content could be calculated by measuring apparent electrical conductivity (ECa) using the Veris-3100 on-the-go soil mapping tool. Statistical analysis was carried out on the 10.791 ECa raw data in order to filter the outliers. The applied statistical method was ±1.5 interquartile (IRQ) distance approach. The visualization of soil moisture distribution within the experimental field was carried out by means of ArcGIS/ArcMAP using the inverse distance weighting interpolation method. In the investigated 25 sampling points, coefficient of determination between calculated volumetric moisture content data and measured ECa was R2 = 0.87. According to our results, volumetric moisture content can be mapped by applying ECa measurements in these particular soil types.</jats:p