The use of remote sensing in soil and terrain mapping – a review (pdf download available) sustainable urban drainage systems legislation

ABSTRACT: Soil organic carbon (SOC) plays an important role in climate change regulation notably through release of CO2 following land use change such a deforestation, but data on stock change levels are lacking. Sustainable urban drainage systems case study This study aims to empirically assess SOC stocks change between 1991 and 2011 at the landscape scale using easy-to-access spatially-explicit environmental factors. Private drainage systems The study area was located in southeast Madagascar, in a region that exhibits very high rate of deforestation and which is characterized by both humid and dry climates.


Land drainage systems We estimated SOC stock on 0.1 ha plots for 95 different locations in a 43,000 ha reference area covering both dry and humid conditions and representing different land cover including natural forest, cropland, pasture and fallows. Advanced drainage systems atlanta We used the Random Forest algorithm to find out the environmental factors explaining the spatial distribution of SOC. Advanced drainage systems buxton nd We then predicted SOC stocks for two soil layers at 30 cm and 100 cm over a wider area of 395,000 ha. Natural drainage systems By changing the soil and vegetation indices derived from remote sensing images we were able to produce SOC maps for 1991 and 2011. Advanced drainage systems pipeline Those estimates and their related uncertainties where combined in a post-processing step to map estimates of significant SOC variations and we finally compared the SOC change map with published deforestation maps. Advanced drainage systems vicksburg ms Results show that the geologic variables, precipitation, temperature, and soil-vegetation status were strong predictors of SOC distribution at regional scale. Advanced drainage systems ceo We estimated an average net loss of 10.7% and 5.2% for the 30 cm and the 100 cm layers respectively for deforested areas in the humid area. Advanced drainage systems orlando fl Our results also suggest that these losses occur within the first five years following deforestation. Install drainage systems No significant variations were observed for the dry region. Advanced drainage systems reviews This study provides new solutions and knowledge for a better integration of soil threats and opportunities in land management policies.

ABSTRACT: Relationships between parent material and soil are not well understood and generally only reported in qualitative form. Advanced drainage systems inc ohio We present a classification of parent material for pedologic purposes, which includes twelve lithology classes based on mineralogical and chemical composition. Advanced drainage systems jackson ms The relationships of these lithology classes with six key soil properties (soil organic carbon, pH, cation exchange capacity, sum of bases, total P and clay %) were examined in a case study over New South Wales, Australia. Advanced drainage systems eagle grove iowa We used multiple linear regression, Random Forest and Cubist tree models based on a soil dataset of over 3200 points. Sustainable urban drainage systems suds Semi-quantitative estimates are derived of change in these soil properties with a change in lithology class, and an associated silica index, for example, a 22% relative decrease in soil organic carbon with each 10% rise in silica, broadly equivalent to a change from shale to granite, assuming other factors remain constant.

Parent material covariates are essential for the effective modelling and mapping of soil properties. Sustainable drainage systems a guide for developers Widely available lithology data have the potential for greater use in digital soil modelling and mapping (DSMM) programs. Pipeline drainage systems We compared the performance of the classified lithology data with other continuous, geophysical parent material covariates such as gamma radiometrics in digital soil models and maps over NSW. What is sustainable urban drainage systems The lithology covariate was demonstrated to exert the greatest influence on all six soil properties, coming well ahead of all geophysical parent material and other environmental covariates. Advanced drainage systems careers Validation statistics demonstrated strong improvement in both model and map quality when the lithology covariate was included. Advanced drainage systems ipo For example, Lin’s concordance for the Cubist sum of bases model rose from 0.46 with no parent material covariates to 0.58 with the continuous geophysical covariates to a high of 0.77 when lithology was also used. Surface and subsurface drainage systems The improvement was typically slightly less marked in the final digital maps than for the calibration models, probably due to the lower reliability of the lithology grid derived from broad scale polygonal geological and soil data. Advanced drainage systems emitter A process is suggested for the application of lithology data into DSMM programs. Advanced drainage systems stock symbol Despite the potential drawbacks of using polygonal data, properly organised categorical lithology data can be a strong covariate to complement other continuous geophysical data sources in DSMM programs, particularly where reliable and fine scale geological and soil data are available.

ABSTRACT: Relationships between parent material and soil are not well understood and generally only reported in qualitative form. Advanced drainage systems phone number We present a classification of parent material for pedologic purposes, which includes twelve lithology classes based on mineralogical and chemical composition. Sustainable urban drainage systems design manual The relationships of these lithology classes with six key soil properties (soil organic carbon, pH, cation exchange capacity, sum of bases, total P and clay %) were examined in a case study over New South Wales, Australia. Advanced drainage systems sebring fl We used multiple linear regression, Random Forest and Cubist tree models based on a soil dataset of over 3200 points. Advanced drainage systems 4 in Semi-quantitative estimates are derived of change in these soil properties with a change in lithology class, and an associated silica index, for example, a 22% relative decrease in soil organic carbon with each 10% rise in silica, broadly equivalent to a change from shale to granite, assuming other factors remain constant.

Parent material covariates are essential for the effective modelling and mapping of soil properties. Advanced drainage systems stock Widely available lithology data have the potential for greater use in digital soil modelling and mapping (DSMM) programs. Advanced drainage systems brazil in We compared the performance of the classified lithology data with other continuous, geophysical parent material covariates such as gamma radiometrics in digital soil models and maps over NSW. Advanced drainage systems The lithology covariate was demonstrated to exert the greatest influence on all six soil properties, coming well ahead of all geophysical parent material and other environmental covariates. Advanced drainage systems ohio Validation statistics demonstrated strong improvement in both model and map quality when the lithology covariate was included. Advanced drainage systems heidelberg ontario For example, Lin’s concordance for the Cubist sum of bases model rose from 0.46 with no parent material covariates to 0.58 with the continuous geophysical covariates to a high of 0.77 when lithology was also used. Sustainable urban drainage systems The improvement was typically slightly less marked in the final digital maps than for the calibration models, probably due to the lower reliability of the lithology grid derived from broad scale polygonal geological and soil data. Advanced drainage systems mendota il A process is suggested for the application of lithology data into DSMM programs. Sustainable drainage systems definition Despite the potential drawbacks of using polygonal data, properly organised categorical lithology data can be a strong covariate to complement other continuous geophysical data sources in DSMM programs, particularly where reliable and fine scale geological and soil data are available.