Effects of soil surface roughness on soil processes and remote sensing data interpretation and its measuring techniques - a review

Surface roughness is a very important physical feature of soil, affecting various soil processes and accuracy of remote sensing data interpretation. Thus, there is a need to describe it quantitatively. The main aim of the paper was to show needs and benefits of collecting quantitative information about soil surface roughness which is the most relevant parameter used as an index to predict water and wind erosion. Surface roughness can reduce soil erosion and soil losses even by up to 31%. Thereby, it increases the development of fauna and flora and improves the structure of soil and its biological quality. In the first section of the paper there are presented definitions of soil roughness proposed by different authors. The next section explains how various factors influence soil surface roughness. Then, the categorization of soil surface roughness discussed in literature is presented. The next part of the paper includes information about a role of soil roughness in agricultural, soil science and a hydrology research. Moreover, soil surface roughness plays an important role in a remote sensing of soils. The knowledge of quantitative soil surface roughness allows more accurate interpretation of the soil properties from remote sensing data, because this soil feature can decrease soil spectra even over 70% and makes their analysis difficult. In addition, deepening knowledge about soil roughness will allow more precise conclusions about the amount of reflected shortwave solar radiation indirectly shaping the Earth’s climate. In the final section, the techniques for measuring and indices for describing soil roughness are shown. However, the authors prefer a photogrammetry technique for collecting these data, because it is quick and easy to use, ensuring high resolution and accuracy of data (about 1 mm) and the image processing is currently simplifid as software to process is absolutely affordable

Land-related global habitability science issues

The scientific investigation of the viewpoint of the biosphere that living organisms and their physical and chemical environment are bound, inseparable parts of one set of closely coupled global processes of the global biogeochemical system, life and life support cycles, is discussed as one of the major scientific challenges of the next decade by building from understanding land processes to interdisciplinary, holistic studies of biospheric dynamics including human impacts

Spatial variability of actual evaporation in a prairie landscape

Land surface evaporation has considerable spatial variability that is not reflected in meteorological station data alone. Knowing the spatial variability of evaporation is important for describing drought, managing agricultural land, and is valuable for improving the parameterization of hydrological models and land surface schemes over large areas. General difficulties arise for obtaining reliable, spatially distributed evaporation estimates as a result of uncertainty in estimation techniques, scale issues and complexities regarding land surface and atmospheric interactions, and the spatial and temporal variability of key factors governing the evaporation process. Estimating evaporation is further complicated when soil moisture becomes a critical limitation, particularly during drought. An examination of the spatial variability of evaporation and its association with governing factors was conducted in Prairie landscapes using three modelling techniques. First, eddy covariance measurements and reference meteorological data were obtained at two Prairie locations to assess the accuracy of physically-based models for calculating point estimates of actual evaporation under non-limited soil moisture conditions and during drought. Second, estimates of actual evaporation were distributed at the field scale in order to examine the impacts of driving factors and their spatial associations on upscaled evaporation estimates. This required the assimilation of high resolution visible and thermal images which were used to derive estimates of surface albedo and surface emitted longwave radiation. These were combined along with surface reference observations to develop an index of the mid-day radiation in order to distribute a known value of mean daily net radiation over the field. Third, archived historical climate data were used as input for a continuous hydrological simulation to examine spatial and temporal variations in evaporation across the Prairie region of Western Canada during a drought and non-drought period. Results of this research showed that the spatial variability of evaporation could be derived at the field scale by integrating remote sensing and surface reference climate data with a physically-based evaporation model. Surface temperature and soil moisture, and net radiation were found to be highly variable spatially at field scales whilst meteorological conditions tended to be less variable spatially but showed strong temporal variability. At the field scale it was found that the variability in albedo and surface temperature were both important for characterizing differences in surface state conditions. Their combined influence was reflected in the resulting pattern of net radiation that governed the distribution of actual evaporation estimates obtained with the Granger and Gray evaporation model. It was found that an areal estimate of evaporation obtained from the means of driving factors was similar to the areal average obtained from the distributed estimates. This was attributed to the offsetting interactions among the driving factors which effectively reduced the variability of the model estimates. In general, the physically-based models examined were found to provide reasonable estimates of actual evaporation when driven by observations at point-scales over multi-day and seasonal periods. This included periods when soil moisture was not a strong limitation and also under drought conditions. Variations in the spatial pattern of actual evaporation provided a useful indicator of drought across the Prairie region of Western Canada. The results contribute to a better understanding of the effects of spatial associations of key factors on evaporation estimates in a Prairie landscape. The methodology developed for distributing net radiation from assimilated visible and thermal images could potentially be used in regional scale modelling applications for improving evaporation estimates using point scale estimation techniques. The modelling algorithms applied to derive point estimates of evaporation from surface reference data may be useful for operational purposes that require estimates of actual evaporation and for characterizing drought

Advanced Sensors and Applications Study (ASAS)

The present EOD requirements for sensors in the space shuttle era are reported with emphasis on those applications which were deemed important enough to warrant separate sections. The application areas developed are: (1) agriculture; (2) atmospheric corrections; (3) cartography; (4) coastal studies; (5) forestry; (6) geology; (7) hydrology; (8) land use; (9) oceanography; and (10) soil moisture. For each application area. The following aspects were covered: (1) specific goals and techniques, (2) individual sensor requirements including types, bands, resolution, etc.; (3) definition of mission requirements, type orbits, coverages, etc.; and (4) discussion of anticipated problem areas and solutions. The remote sensors required for these application areas include; (1) camera systems; (2) multispectral scanners; (3) microwave scatterometers; (4) synthetic aperture radars; (5) microwave radiometers; and (6) vidicons. The emphasis in the remote sensor area was on the evaluation of present technology implications about future systems

Regionalization of surface flux densities and moisture indicators in composite terrain : a remote sensing approach under clear skies in Mediterranean climates

The growing concern about environment has increased the number of land surface processes studies. Computer simulation models of land surface processes have been developed for a range of scales and with different levels of physical complexity. Because the interactions between soil, vegetation and atmosphere vary both spatially and temporally, regional evaporation in heterogeneous natural landscapes is difficult to predict by means of computer simulation models. Remote sensing measurements of land surface radiative properties offer however a means to indirectly measure land surface state conditions at a range of scales. A straightforward estimation of evaporation from radiative properties of the land surface is hampered by the fact that only a very few parameters of the classical flux-profile relationships can be estimated directly from remote sensing measurements. Moreover, the accuracy of surface temperature measurements necessary to solve flux-profile relationships is still poor. Inclusion of ground measurements is a possible solution, but the absence of such data on large scales and for heterogeneous land surfaces where these parameters are not measured, forms an immediate obstacle for the implementation of remote sensing algorithms.A Surface Energy Balance Algorithm for Land (SEBAL) has been developed in a way that the need for collateral measurements is partly eliminated, a very accurate surface temperature map is no longer required (although it should be as good as possible) and a land use classification to relate surface temperature to evaporation is not needed. Each pixel is characterized by a surface hemisherical reflectance, surface temperature and a vegetation index. The methodology composes of multiple flux-profile relationships for small sub-areas. Although the concept has a physical basis, the parameters are estimated by empirical relationships, for instance a relationship between near-surface vertical air temperature difference and surface temperature forms an essential component in the estimation of the sensible heat flux density.The absolute surface energy balance terms are estimated on an instantaneous time basis. Temporal integration of instantaneous surface flux densities is feasible using the evaporative fraction (latent heat flux density/net available energy): The evaporative fraction remains fairly constant during daytime hours for both homogeneous and heterogeneous areas. A physical explanation for this is given. A bulk surface resistance of a heterogeneous landscape has been related analytically to canopy and bare soil evaporation resistances. Measurements in central Spain have shown that the evaporative fraction and bulk surface resistance are suitable indicators to describe areal patterns of near-surface soil water content. Although the bulk surface resistance has a distinct diurnal variation, it is much less affected by changes in net available energy and therefore preferred to describe the energy partitioning for longer time series (weeks, months).SEBAL has been validated with data available from regional evaporation projects in Egypt and Spain. The error of high resolution evaporative fraction estimations decreases from 20% to 10% at a scale of 1 km to 5 km respectively, The error of low resolution evaporative fraction images at a scale of 100 km is approximately 1 to 5 %. Hence, the error averages out if a larger set of pixels is considered. It is concluded that the uncertainty of evaporation in regional water balances and model studies can be substantially reduced by estimating evaporation with remote sensing measurements using the proposed SEBAL technique

Annual variation of bare arable soil areas on a global scale

Wydział Nauk Geograficznych i GeologicznychArable land around the world has a 12% share of the global land area. This thesis was created as a part of a project aimed at estimation of shortwave radiation reflected from those surfaces according to various scenarios based on the farming methods. This thesis was created as a part of a project aimed at estimation of shortwave radiation reflected from those surfaces according to various scenarios based on the farming methods. Its key element was the estimation of the bare soil area, defined for its spectral properties, as the area of arable land not covered by vegetation on more than 15% on its surface. In conventional agriculture, during the period immediately following the planting of crops, the soil stays bare until the newly planted crops reach defined above share of surface cover. This work focuses on estimating the periods of bare soil that occur after the planting of 13 major crops at the global scale; those selected crops are wheat, maize, barley, sorghum, soybeans, millet, cotton, rapeseed, groundnuts, potato, cassava, rye, and sugar beet. The supplementary objective of the study was to determine which soil groupings, and in what proportions, were bare during those periods. Arable land, divided into extensive agricultural regions located on six continents, was analyzed. The estimation of bare soil acreage was performed based on publicly available spatial datasets including the distribution of arable land in the world, crop calendars containing planting dates and the geographic distribution of crops. The arable land in the world was first divided into agricultural regions inspired by the division proposed by United States Department of Agriculture. For each region, average daily temperatures were used to predict plant growth stages. For each crop within a region, the planting date was used as the beginning of the bare soil period, which ended when it reached a stage where at least 15% of the surface was covered by vegetation. The aggregated periods concerning every crop within any given region resulted in an annual variation of bare soil area. The acreages of soil grouping used in agriculture for any region were then extracted based on the location of arable land and the region’s boundaries.The global annual variation of bare soil area shows that the maximum level occurs around the 140th day of the year (DOY) (middle of May), influenced primarily by the planting of crops occurring in the northern hemisphere. Up to 1.5 million km2of soil surface stays bare at that time. Centered on that maximum is a period of bare soil lasting for almost four months, between the 92nd DOY and the 200th DOY (early April and end of July), when two lesser maxima were observed, of around 900,000 and 700,000 km2, respectively. The equivalent of that period, resulting from planting in the southern hemisphere, starts around the 330th DOY (middle of November) and lasts for about a month, reaching almost 400,000 km2. The other distinguishable episode of bare soil in the southern hemisphere was noted between the 15th and the 25th DOY (second half of January) when its area reached 100,000 km2. Asia is the super region with by far the largest area of arable land and consequently, it sports the highest acreage of bare soil. During the aforementioned maximum in the northern hemisphere occurring around the 140th DOY, the Asian super region contributes around 700,000 km2 of bare soil, which is almost half of the bare soil area for the whole northern hemisphere at that time, with Lithosols, Cambisols, and Gleysols being the major soil groupings that stay bare. In Europe, two distinct periods of bare soil were found; during the first, starting around the 40th DOY (middle of February) and lasting until the 150th DOY (end of May), the steady increase of the bare soil area lasts until the 140th DOY (middle of May) when it reaches almost 500,000 km2, after which a rapid decline was observed. The second, manifesting two and a half months later, lasts between around the 230th and the 290th DOY (middle of August to middle of October), and exceeds 100,000 km2. Chernozems, Cambisols, and Luvisols are dominant soil groupings on arable land in Europe. Similar trends, related to the European bare soil areas, were found in the North American super region, where a period of maximum bare soil area occurs in late spring, and a second period, characterized by a much smaller area, follows the main one three months later. The maxima coincide with the aforementioned ones in Asia and Europe, reaching 300,000 km2 of bare soil around the 140th DOY. Similar to Europe, the second period sports a much smaller bare soil area, short of 30,000 km2. The dominant soil groupings in agricultural use in North America are Kastanozems, Luvisols, and Chernozems. Africa is a super region whose area is divided between both northern and southern hemispheres, which shows in the annual variation of its bare soil area. Three distinct periods were found there, the major one around the middle of a year lasted for about two and a half months, between the 167th and the 230th DOY (middle of June to middle of August) with the bare soil area being up to almost 400,000 km2. The other peak occurs about a month and a half earlier, between the 95th and the 115th DOY (roughly the month of April) and is characterized by a bare soil area exceeding 120,000 km2. The last notable episode of bare soil in Africa manifests itself between the 317th DOY and the 10th day of the following year (middle of November to the middle of January), with the area of soil uncovered by vegetation reaching almost 100,000 km2. Luvisols together with Arenosols, followed by Vertisols, are the most extensively farmed soil groupings in Africa. The majority of arable land in the southern hemisphere is found in the South American super region, which is reflected in the annual variation of bare soil area, which is similar to that of the whole southern hemisphere. The maximum lasts for around two weeks, between the 330th and the 345th DOY (end of November to the middle of December), when almost 500,000 km2 of arable soil is bare. A secondary peak was observed between the 15th and the 30th DOY (second half of January), sporting around 100,000 km2 of bare soil area. Ferrasols is the most commonly farmed soil grouping in the region, followed by Phaozems and Luvisols. In Oceania, the maximum area of bare soil slightly exceeds 25,000 km2 for about two weeks in the first half of June, followed by a rapid decline. A secondary period is characterized by a longer duration but the smaller area, lasting between the 313th and the 14th DOY (middle of November to middle of January) with about 5,000 km2 of arable land which is not covered by vegetation at that time. Luvisols are the dominant soil grouping under cultivation in Oceania, followed by Planosols, Solonetz, and Vertisols. The obtained variations of bare soil areas together with the corresponding share of soil groupings for all regions were used in other work in order to estimate the amount of shortwave radiation reflected from those surfaces according to various scenarios based on the farming methods.Grunty orne stanowią około 12% powierzchni lądów na całym świecie. Niniejsza praca powstała w ramach projektu dążącego do oszacowania ilości promieniowania krótkofalowego odbijanego od tych powierzchni. Kluczowym jej elementem było oszacowanie areału odkrytej gleby, definiowanej ze względu na jej właściwości spektralne, jako powierzchni gruntów ornych niepokrytych roślinnością w stopniu większym niż 15%. W przypadku rolnictwa konwencjonalnego, w okresie bezpośrednio po sianiu lub sadzeniu roślin gleba pozostaje odkryta, dopóki nowo zasiane lub zasadzone rośliny nie osiągną fazy wzrostu powodującej pokrycie powierzchni w wyżej zdefiniowanym stopniu. Praca ta koncentruje się na oszacowaniu okresów kiedy gleba pozostaje odkryta, które występują po sianiu lub sadzeniu 13 głównych upraw w skali globalnej; te wybrane uprawy to pszenica, kukurydza, jęczmień, sorgo, soja, proso, bawełna, rzepak, orzeszki ziemne, ziemniaki, maniok, żyto i burak cukrowy. Celem badania było ustalenie, które główne grupy glebowe (major soil groupings wg definicji FAO–UNESCO) oraz w jakich areałach pozostają odkryte. Przeanalizowane zostały grunty orne podzielone na regiony rolnicze położone na sześciu kontynentach. Oszacowanie areału odkrytej gleby przeprowadzono przy użyciu publicznie dostępnych zbiorów danych przestrzennych, w tym rozmieszczenia gruntów ornych na świecie, geograficznego rozmieszczenia upraw oraz kalendarzy upraw zawierających daty sadzenia. Używane zbiory danych zostały w pierwszej kolejności podzielone na regiony rolnicze zainspirowane podziałem zaproponowanym przez Departament Rolnictwa Stanów Zjednoczonych. Dla każdego z tych regionów zastosowano średnie dzienne temperatury w celu oszacowania etapów wzrostu roślin. Dla każdej uprawy w regionie data sadzenia została wykorzystana jako początek okresu występowania odkrytej gleby, który kończy się, gdy osiągnie etap, w którym gleba zostaje pokryte roślinnością. Zagregowane okresy dotyczące każdej uprawy w danym regionie posłużyły do ustalenia rocznej zmienności powierzchni odkrytej gleby. Areały głównych grup glebowych wykorzystywanych w rolnictwie dla każdego z regionów zostały następnie obliczone na podstawie lokalizacji gruntów ornych i granic regionu. Analizując wszystkie grunty orne na świecie, maksymalny poziom odkrycia występuje około 140 dnia roku (day of year - DOY);(połowa maja), i jest spowodowany przede wszystkim przez sianie oraz sadzenie roślin uprawnych na półkuli północnej. W tym czasie do 1,5 mln km2 powierzchni gruntów ornych nie jest pokryta przez rośliny. Wyżej opisane maksimum występuje podczas okres odsłoniętej gleby trwającego przez prawie cztery miesiące, między 92 DOY a 200 DOY (początek kwietnia a koniec lipca), kiedy zaobserwowano dwa pomniejsze maksima, odpowiednio około 900 000 i 700 000 km2. Odpowiednik tego okresu, wynikający z siania oraz sadzenia na półkuli południowej, zaczyna się około 330 DOY (połowa listopada) i trwa około miesiąca, osiągając prawie 400 000 km2. Inny wyraźnie widoczny okres odkrytej gleby na półkuli południowej odnotowano między 15 a 25 DOY (druga połowa stycznia), kiedy jego powierzchnia osiągnęła 100 000 km2. Azja to kontynent o zdecydowanie największym areale odkrytej gleby wynikający ze zdecydowanie największej powierzchni gruntów ornych. Podczas wspomnianego maksimum na półkuli północnej, występującego około 140 DOY, azjatycki region odpowiada za około 700 000 km2 odkrytej gleby, a więc prawie połowę powierzchni odkrytej gleby dla całej półkuli północnej w tym czasie, z Lithosols, Cambisols i Gleysols jako głównymi grupami gleb, które pozostają odkryte. W Europie znaleziono dwa odrębne okresy odkrytej gleby; podczas pierwszego, rozpoczynającego się około 40 DOY (połowa lutego) i trwającego do 150 DOY (koniec maja), stały wzrost powierzchni odkrytej gleby trwa do 140 DOY (połowa maja), kiedy osiąga ona prawie 500 000 km2, po czym następuje gwałtowny spadek tego areału. Drugi, zaczynający się dwa i pół miesiąca później, trwa od około 230 do 290 DOY (od połowy sierpnia do połowy października) i przekracza 100 000 km2. Chernozems, Cambisols i Luvisols są dominującymi grupami glebowymi na gruntach ornych w Europie. Podobne tendencje jak w przypadku odsłoniętych gleb na kontynencie europejski zanotowano w Ameryce Północnej, w przypadku której okres największej powierzchni odkrytej gleby występuje późną wiosną, a drugi okres, obejmującym znacznie mniejszy areał, następuje trzy miesiące później. Maksymalne wartości występują w podobnym okresie jak w wyżej wymienionych Azji i Europie, osiągając 300 000 km2 odkrytej gleby około 140 DOY. Podobnie jak w Europie, drugi okres charakteryzuje się znacznie mniejszą powierzchnię odkrytej gleby, poniżej 30 000 km2. Dominującymi grupami glebowymi uprawianymi w Ameryki Północnej są Kastanozems, Luvisols i Chernozems. Afryka jest kontynentem zajmującym półkulą północną, jak i południową, co jest odzwierciedlone w rocznym przebiegu areału odkrytej gleby. Wyróżniono tam trzy osobne okresy, największy z nich występuje w połowie roku i trwa około dwóch i pół miesiąca, między 167 a 230 DOY (od połowy czerwca do połowy sierpnia), podczas którego powierzchnia odkrytej gleby osiąga prawie 400 000 km2. Drugi szczyt występuje około półtora miesiąca wcześniej, między 95 a 115 DOY (w kwietniu) i charakteryzuje się areałem odkrytej gleby przekraczającym 120 000 km2. Ostatni znaczący okresy odkrytej gleby w Afryce ustalono między 317 DOY a 10 dniem następnego roku (od połowy listopada do połowy stycznia), przy czym odkryty areał gleby sięga prawie 100 000 km2. Luvisols wraz z Arenosols oraz Vertisols, są najbardziej ekstensywnie uprawianymi grupami glebowymi w Afryce. Roczna zmienność powierzchni odsłoniętej gleby na kontynencie Ameryki Południowej ma podobny przebieg jak w przypadku całej półkuli południowej. Maksimum areału odsłoniętej gleby trwa przez około dwa tygodnie, między 330 a 345 DOY (koniec listopada do połowy grudnia), kiedy prawie 500 000 km2 gruntów ornych pozostaje odkrytych. Drugi szczyt zaobserwowano między 15 a 30 DOY (druga połowa stycznia), w którego trakcie około 100 000 km2 gruntów ornych jest odsłoniętych. Ferrasols są najczęściej uprawianą grupą glebową na kontynencie, a następnie Phaozems i Luvisols. W Oceanii maksymalny areał odkrytej gleby nieznacznie przekracza 25 000 km2 przez okres około dwóch tygodni w pierwszej połowie czerwca, po czym następuje jego gwałtowny spadek. Drugi okres charakteryzuje się dłuższym czasem trwania, ale mniejszym areałem, utrzymującym się od 313 do 14 DOY (od połowy listopada do połowy stycznia) z około 5000 km2 gruntów ornych, które nie są w tym czasie pokryte roślinnością. Luvisols są dominującą grupą glebową pod uprawą w Oceanii, a następnie Planosols, Solonetz i Vertisols.project 2014/13/B/ST10/02111, financed by the Polish National Science Cente

Earth resources: A continuing bibliography with indexes (issue 59)

This bibliography lists 518 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors

Agricultural Meteorology and Climatology

Agricultural Meteorology and Climatology is an introductory textbook for meteorology and climatology courses at faculties of agriculture and for agrometeorology and agroclimatology courses at faculties whose curricula include these subjects. Additionally, this book may be a useful source of information for practicing agronomists and all those interested in different aspects of weather and climate impacts on agriculture. In times when scientific knowledge and practical experience increase exponentially, it is not a simple matter to prepare a textbook. Therefore we decided not to constrain Agricultural Meteorology and Climatology by its binding pages. Only a part of it is a conventional textbook. The other part includes numerical examples (easy-to-edit worksheets) and recommended additional reading available on-line in digital form. To keep the reader's attention, the book is divided into three sections: Basics, Applications and Agrometeorological Measurements with Numerical Examples