Author : 
Milind Bunyan, Shibu Jose, Robert Fletcher

Year : 2019
Title : Edge Effects in Small Forest Fragments: Why More Is Better?

Journal :  American Journal of Plant Sciences


 They investigated the response of microenvironment and edaphic variables to distance from a tropical montane forest (locally known as shola)-grassland edge using one-edge and multiple-edge models. 

 The edpahic variables did not show any differences between the grassland and shola soils. The conventional one-edge models sufficiently explained variation trends in micro environment along the edge to interior gradient in large fragments. 

 As with other studies on small fragments though, they observed no edge effects with the use of a conventional one-edge model. However, the inclusion of multiple edges in small fragments significantly improved model fit. Thus, small fragments dominated by edge habitat may in fact resemble larger fragments with the inclusion of multiple edges.


Author : 
Ian A. Smith, Lucy R. Hutyra, Andrew B. Reinmann1, Jonathan R. Thompson, David W. Allen

Year : 2019
Title : Evidence for edge enhancements of soil respiration in temperate forests

Journal :  Geophysical Research Letters


 Forest fragmentation impacts carbon uptake and storage, however, the magnitude and direction of fragmentation impacts on soil respiration remain poorly characterized. They quantify soil respiration rates along edge-to-interior transects in two temperate broad-leaf forests in the eastern US that vary in climate, species composition, and soil type. They observe average soil respiration rates 15-26% higher at the forest edge compared to the interior, corresponding to large gradients in soil temperature. These results suggest that estimates of soil respiration in the temperate forest region may be underestimating biological emissions of carbon dioxide.


Author : 
Moura-Bueno, J. M.
Dalmolin, R. S. D.
ten Caten, A.
Dotto, A. C.
Dematte, J. A. M.

Year : 2019
Title : Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions

Journal :  Geoderma


The aim of this research was to i) characterize and identify differences among spectra obtained for subtropical soils samples, ii) evaluate different pre-processing techniques and multivariate methods to propose SOC prediction models from the spectral data and iii) evaluate the performance of SOC prediction models calibrated from the stratification of a local library.

 Spectral reflectance measurements were performed in the laboratory with a spectroradiometer in the range of 350–2500 nm. Six pre-processing techniques were applied to the spectra (including derivatives, normalization and non-linear transformations) and four multivariate calibration methods, namely, partial least squares regression (PLSR), multiple linear regre…


Author : 
Tümsavaş Zeynal, Tekin Yücel, Ulusoy Yahya, Mouazen Abdul M

Year : 2019
Title : Prediction and mapping of soil clay and sand contents using visible and near-infrared spectroscopy

Journal :  Biosystems engineering


The aim of this research was to examine the potential of visible and near infrared (Vis
-NIR) spectroscopy for the prediction and mapping of sand and clay fractions of soils.

 This study demonstrated that soil sand and clay can be successfully measured and mapped using Vis-NIR spectroscopy under both laboratory and on-line scanning conditions.

 A partial least squares (PLS) regression with leave-one-out cross-validation analysis was carried out using the calibration set, and the resulting model prediction ability was tested using the prediction set. 

 Models developed were used to predict sand and clay content using laboratory spectra and spectra collected on-line from the field. Results showed an “excellent” laboratory prediction performance for both sand (regressi…


Author : 
Soltani, I. Fouad, Y. Michot, D. Breger, P. Dubois, R. Cudennec, C.

Year : 2019
Title : A near infrared index to assess effects of soil texture and organic carbon content on soil water content

Journal :  European Journal of Soil Science


 Characterization of soil hydrodynamic properties is important for assessing the soil water regime. Over the last decades, diffuse reflectance spectroscopy (DRS) techniques have been used increasingly. Methods based on DRS offer several advantages compared with conventional ones because they are rapid, cost-effective and non-destructive. Therefore, the spread within the soil science community of soil spectroscopy in the visible (vis), near (NIR) and mid-infrared (MIR) spectral ranges enabled various physical, chemical and biological soil properties to be assessed.

 Spectra were converted into continuum removal and we focused on the absorption band near 1920 nm, which is linked to combination vibrations of water. They defined a new index b…


Author : 
Chongfeng Gonga, Shixiao Yua, Heather Joesting, Jiquan Chen

Year : 2013
Title : Determining socioeconomic drivers of urban forest fragmentation with historical remote sensing images
Journal :  Landscape and Urban Planning


To quantify the land-use change during this rapid urbanization process and explore the underline drivers, nine sets of Landsat images from 1973 through 2005 were used to calculate the landscape metrics of forest patches. 

 They found that the forest in Shen-zhen had been restored to 85.85% of pre-urbanization coverage by 2005, but was characterized with smaller, isolated patches across the landscape. 

 The changes in patch density, distribution, and shape during the 30-year study period were nonlinear and defined by episodic periods. The stepwise multiple regression models with socioeconomic drivers provided further explanation for fragmentation rates in patch density, distribution, and shape, with modeled R-squared of 0.837, 0.759, and 0.985 and P-values…


Author : 
Meihua Yang, Dongyun Xu, Songchao Chen, Hongyi Li  and Zhou Shi

Year : 2019
Title : Evaluation of Machine Learning Approaches to Predict Soil Organic Matter and pH Using vis-NIR Spectra

Journal :  Sensors


 Visible-near infrared (vis-NIR) spectroscopy with multivariate calibration can be used to effectively estimate soil properties. In this study, 523 soil samples were collected from paddy fields in the Yangtze Plain, China.

 Four machine learning approaches—partial least squares regression (PLSR), least squares-support vector machines (LS-SVM), extreme learning machines (ELM) and the Cubist regression model (Cubist)—were used to compare the prediction accuracy based on vis-NIR full bands and bands reduced using the genetic algorithm (GA).

The coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to inter-quartile distance (RPIQ) were used to assess the prediction accuracy. 

The ELM with GA reduced bands was the best model for SOM (SOM: R…