Erika Michéli

Use of combined digital elevation model and satellite radiometric data for regional soil mapping

Abstract Previous reports demonstrated that data from air- and spaceborne sensors are appropriate for delineation of soil patterns. Also, many attempts have been made to use digital elevation model (DEM) for deriving soil information. However, little is known about the potential use of low spatial resolution satellite and digital elevation data in small-scale soil mapping. A case study was conducted to assess the use of integrated terrain and Advanced Very High Resolution Radiometer (AVHRR) databases for small-scale soil pattern delineation. The main objective was to test the effect of the addition of terrain descriptor data to the AVHRR data set on the classification results. Two database were used for the study. The first one was purely AVHRR data and contained the five basic AVHRR channels and the normalized difference vegetation index (NDVI) of five different dates, while in the second database the AVHRR data was complemented with a DEM, a curvature, a slope, an aspect and the potential drainage density layers. The performance of these two databases when employed to derive soil information was compared. These databases were then further processed using the Discriminant Analysis Feature Extraction (DAFE) function (which is based on a canonical analysis procedure), and were then classified using the Fisher linear discriminant, and the ECHO spectral–spatial classifiers. Based on the results, it was concluded that the two reflective bands, the middle infrared, the two thermal bands and the NDVI provided a relatively wide range of detectable soil information. The use of single images or small dimensional AVHRR data sets (less then 10 layers) does not result in acceptable performances, while the use of multispectral and multitemporal databases improved the classification performance very significantly. However, the purely AVHRR-based model could not always delineate soil variations related to terrain differences, and resulted in an overall classification performance of 49.1%. Digital elevation and terrain descriptor data were essential in the model for achieving acceptable results. In the second part of the study an integrated AVHRR-terrain database was used, where five terrain layers were added to the 30 AVHRR channels. Two different spatial resolutions were compared, 500 m and 1 km, respectively. The use of elevation, slope, aspect and curvature as differentiating criteria often lead to a satisfactory result in terrain characterization, particularly in large-scale mapping. However, with those variables extracted from DEM of physiographically complex areas, e.g., — where plain areas and mountainous/hilly regions occur together in the same study — often lose their ability to delineate soil variations of the level lands. Beyond these terrain descriptors we implemented a new function, called potential drainage density (PDD) to improve the performance of the model on the plain areas. The classification accuracy of the integrated AVHRR-terrain database was improved significantly over the case when only AVHRR data was in the model. The classification performances of the three different resolution images were 87.3% for the 500-m resolution image and 70.1% for the 1-km resolution image.

Soil Atlas of Africa

of water, nutrients and as a medium for growing. Soil stores, filters, buffers and transforms substances that are introduced into the environment. This capability is crucial in producing and protecting water supplies and for regulating greenhouse gases. Soil is a provider of raw materials. Soil is also an incredible habitat and gene pool. Soil is a fundamental component of our landscape and cultural heritage. The properties of soil vary tremendously from region to region. Soils under tropical rainforests are vulnerable to erosion and nutrient depletion if the vegetation cover is removed. Oasis regions in deserts and the Sahel show how seemingly infertile soils can be cultivated in the presence of water. The wetlands of Congo and other major African systems are stores of soil organic carbon and important wildlife habitats. The black, clay-rich soils of the Nile Valley in Sudan are rich in nutrients but difficult to cultivate when very wet or very dry. Soils with high salt levels are not suitable for the cultivation of crops but may support a unique plant community. AFRICA SOIL ATLAS OF

A regional scale soil mapping approach using integrated AVHRR and DEM data

Abstract There is an increasing need for reasonably accurate small-scale soil databases. The compilation of a continental or global-scale soil database requires a lot of spatially and thematically accurate soil data. The aim of this study was to test a method for small-scale soil mapping in Italy using Advanced Very High Resolution Radiometer (AVHRR) and digital elevation data. This method was employed in an earlier study in Hungary for a much smaller area and a significantly different soil-forming environment. An integrated, 45-layer AVHRR-terrain database was used for the study, including a digital elevation model (DEM), slope, curvature, aspect, potential drainage density, and the five bands of AVHRR data for eight different dates. The data were processed using the Discriminant Analysis Feature Extraction (DAFE) function, which is based on a canonical analysis procedure. Two types of images (basic and transformed) were classified using the maximum likelihood classifier. Two training sets were chosen that have identical geographic coverage, but differ in the level of soil classification. One set was based on the soil units (SU) of the FAO-revised legend, while the other set represented major soil groupings (MSG). The best 10, 15, 20, 25, 30, 35, 40 and 45 layers were selected using the Bhattachryya feature selection method and were then classified. The results of the different sets were compared. The performance of the purely AVHRR and purely terrain-data-based images, respectively, were also interpreted. The results indicate that the terrain descriptors alone are not sufficient for soil classification. However, the feature selection algorithms always selected the DEM and its derivatives among the first ones, highlighting their importance for soil-landscape characterization. When using AVHRR data alone, test class performances of 49.8 percent (MSG) and 48.6 percent (SU) were achieved. Integration of terrain data into the AVHRR database produced relatively small improvements (4.6 and 2.8 percent). The best test class performances were achieved when all available channels were used for the classification, namely 51.4 for the FAOs SUs and 54.4 for the MSGs on the basic image, and 51.7 and 54.4 respectively on the DAFE-transformed images. The most informative AVHRR bands were found to be from the spring period (April-May), while the most abundant bands were the visible-red (band 1) and bands 3 and 4.

Organic Carbon as a Major Differentiation Criterion in Soil Classification Systems

Soil is the largest terrestrial pool of organic carbon (OC), however the spatial distribution of the estimated 1.5–2.3 Tt organic carbon content of the soil cover has great variation horizontally and vertically. As organic carbon is one of the most important soil constituents, governing important functions and properties of soils, it is one of the major differentiation criteria in internationally used soil classification systems, such as Soil Taxonomy (ST) and the World reference base for soil resources (WRB), and most national systems. Several soil units at the highest level of the systems, such as surface and subsurface horizons, modifiers and qualifiers are defined on the basis of presence and amount of OC and/or depth and thickness of OC rich soil layers. As a result of the evaluation of current definitions of ST and the WRB, and analyses of international soil data sets (US NASIS and the ISRIC WISE) it was concluded that there are sufficient number of categories for expression of the amount, kind and vertical distribution of OC, however several of the definitions are very complicated, and not always consistent throughout the systems. This makes interpretation and also computation of categories difficult. With globally available data and mathematical tools, there is an opportunity to improve definitions and adjust arbitrarily set limits. An improved set of organic carbon related diagnostics could serve the needs of a future global classification system, mapping and monitoring OC, and also modeling of related estimations and processes.

Digital Soil Morphometrics Brings Revolution to Soil Classification

Soil classification systems are grouping soils with similar properties. The distinguishing properties are the ones that we are able to observe or measure. As the state of knowledge and the need of users are changing, the definitions should be tested and changes should be accommodated. The recent boom of observation technologies, data storage, and data processing achievements provided new opportunities to predict similarities and differences in soils. The tools of digital soil morphometrics are resulting in new parameters and properties and in deriving continuous depth functions. This chapter reviews the criteria of soil parameters and their novel methods for field observation and definition (horizon depth, texture, color, structure, organic matter, mottling, and carbonates). The internationally endorsed soil classification systems could potentially be supported with these new approaches. The review is based on the WRB and is supplemented with an example of predicting soil diagnostic horizons using digital soil morphometrics. The application of faster, efficient, and more objective measurements can bring revolution to the classification of soils.

The Next Generation of Soil Survey Digital Products

Advances in computer technology (within the past two decades) and access to geographically accurate digital environmental data (i.e., elevation and its derivatives, geology, land use, climate, parent material, and remotely sensed spectral data) have created enormous advancements in our ability to produce soil information at fine spatial resolutions (10–90 m). The data contained in each of these grid cells are data rich in nature and include probability and uncertainty information that allow the modeling of the soil continuum. The same advances in computer technology and digital information are now being applied to data capture for pedon descriptions. Coined “digital morphometrics,” this set of methodologies provide the potential to collect pedon soil property information that defines the continuum of the soil column, no longer restricting pedon information to aggregated “blocks” of data. Potentials and application of this new data model for pedon descriptions will be examined, studied, and presented in this paper.

Javaslat talajosztályozási rendszerünk megújítására: alapelvek, módszerek, alapegységek

A jelenlegi, 1960 evekben kidolgozott genetikus alapokon nyugvo magyar talaj-osztalyozasi rendszerunk modernizalasara az elmult evtizedek hazai tapasztalatai, dokumentalt adathalmazai, valamint a nemzetkozi standardok es elvarasok alapjan teszunk javaslatot. Munkank kiindulasi alapja az elődeink altal definialt 29 talaj-kepző folyamat, 39 talajtipus, es az azokhoz kapcsolodo tartalmi leiras es vizsgalati adatokbol nyert informacio. Modszereink az egyszerű elemzesek es statisztikai szamitasok mellet a pedometria modszerere, a taxonomiai tavolsagszamitasra es klaszteranalizisre tamaszkodtak. Eredmenyeink alapjan a jelenlegi hazai talajtipusok egy resze jol elkulonithető, masok pontosabb definiciora szorulnak, vagy egyes esetekben osszevonasra kerul-hetnek. A nemzetkozi gyakorlatban meglevő es hazankban is jellegzetes tipusokat pedig, bevezetesre javaslunk. A szigorubb es mind a melysegi, morfologiai es osszetetelbeli tulajdonsagok te-kinteteben szamszerűbb meghatarozasokon alapulo javasolt struktura kozpont...

Soil organic matter map of Hungary derived from digital elevation model and satellite data

One of the major stresses on the soil functions is the decline of soil organic matter (SOM) content. Soil Information and Monitoring Systems were setup to survey the recent situation and estimate the rate and trend of potential changes in different soil properties and components including SOM. These Monitoring systems are profile or point based networks with regular sampling periods, which can provide limited, often insignificant percentage of the country surface. The collected data need to be extrapolated to create continuous coverage of the land area of interest.

Comparison of biological and chemical properties of arable and pasture Solonetz soils

Soil samples were collected from salt-affected soils (Solonetz) under different land uses, namely arable (SnA) and pasture (SnP), to investigate the effects of land use on microbiological [basal soil respiration (BSR), microbial biomass carbon (MBC), dehydrogenase activity (DHA) and phosphatase activity] and chemical properties [organic carbon (OC), humic ratio (E4/E6), pH, electrical conductivity (EC), ammonium nitrogen (NH 4- N), nitrate nitrogen (NO 3- N), available forms of phosphorus (P 2 O 5 ), potassium (K 2 O), calcium (Ca 2+ ), magnesium (Mg 2+ ), sodium (Na + )] and on the moisture content. The results showed that the two sites, SnA and SnP, were statistically different from each other for all the microbiological and chemical parameters investigated except Na+ and moisture content. Higher values of MBC (575.67 μg g -1 ), BSR (9.71 μg CO 2 g -1 soil h -1 ), DHA (332.76 μg formazan g -1 day -1 ) and phosphatase activity (0.161 μmol PNP g -1 hr -1 ) were observed for the SnP soil. Great heterogeneity was found in SnP in terms of microbiological properties, whereas the SnA plots showed more homogeneous microbiological activity due to ploughing. 75.34% of variance was explained by principal component one (PC1), which significantly separated SnA and SnP, especially on the basis of soil MBC and P 2 O 5 . Moreover, it was concluded that the pasture land (SnP) was microbiologically more active than arable land (SnA) among the Hungarian salt-affected soils investigated.

Javaslat a hazai láptalajok osztályozásának megújítására

A szerves talajok osszetetele, kepződesi korulmenyei, es foldrajzi, ill. domborzati elterjedese jelentősen elter az asvanyi talajoketol. A tomegukben megőrzott hatalmas mennyisegű szerves szen es kornyezetuk biologiai sokfelesege (biodiverzitasa) kapcsan a klimavaltozas altal leginkabb erintett talajok, ezert megkulonboztetett figyelem iranyul e talajokra. Kiterjedesukre, lebomlottsagi fokukra, szerves szenkeszletukre igen elterő irodalmi es terkepi adatok allnak rendelkezesre. Ugyanakkor eppen a klimavaltozas vonatkozasaban oriasi a globalis es helyi megbizhato adatigeny az emlitett kerdesekben. Hazai laptalajaink osztalyozasi, felvetelezesi es mintaveteli modszereinek megujitasara teszunk javaslatot a nemzetkozi standardok figyelembe vetelevel. A megujitott Laptalaj meghatarozasban a legfontosabb kovetelmenyek a 20% szerves szentartalomra, a 40 cm vastagsagra es az alacsony terfogattomegre vonatkoznak. Az altipus es valtozati tulajdonsagok a lebomlottsag fokat, a melysegi, kemhatas viszonyokat, ill. sok...