An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India

Artificial neural network application in comparison with modeling allometric equations for predicting above-ground biomass in the Hyrcanian mixed-beech forests of Iran

(2016) Ali Asghar Vahedi   BIOMASS & BIOENERGY

A Study on General Allometric Relationships Developed for Biomass Estimation in Regional Scale Taking the Example of Tectona grandis Grown in Bundelkhand Region of India

(2016) D. Deb et al.   CURRENT SCIENCE

Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass

(2016) Timothy G. Gregoire et al.   REMOTE SENSING OF ENVIRONMENT

Matching the phenology of Net Ecosystem Exchange and vegetation indices estimated with MODIS and FLUXNET in-situ observations

(2016) M. Balzarolo et al.   REMOTE SENSING OF ENVIRONMENT

Comparing aboveground structure and aboveground carbon storage of an age series of moso bamboo forests subjected to different management strategies

(2015) Tian-Ming Yen   Journal of Forest Research

Satellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest

(2014) Romà Ogaya et al.   ANNALS OF FOREST SCIENCE

An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model

(2014) Sebahattin Tiryaki et al.   CONSTRUCTION AND BUILDING MATERIALS

Thresholds of Logging Intensity to Maintain Tropical Forest Biodiversity

(2014) Zuzana Burivalova et al.   CURRENT BIOLOGY

Model selection for ecologists: the worldviews of AIC and BIC

(2014) Ken Aho et al.   ECOLOGY

Improved allometric models to estimate the aboveground biomass of tropical trees

(2014) Jérôme Chave et al.   GLOBAL CHANGE BIOLOGY

Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery

(2014) Katharine Kelsey et al.   Remote Sensing

Evaluation of hydrogeochemical processes and groundwater quality in the Jhansi district of Bundelkhand region, India

(2013) Abhay Kumar Singh et al.   Environmental Earth Sciences

Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data

(2013) Laxmi Kant Sharma et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

An alternative approach for delineating eco-sensitive zones around a wildlife sanctuary applying geospatial techniques

(2013) Shovik Deb et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Using MODIS time series data to estimate aboveground biomass and its spatio-temporal variation in Inner Mongolia’s grassland between 2001 and 2011

(2013) Tian Gao et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

The prediction of the critical factor of safety of homogeneous finite slopes using neural networks and multiple regressions

(2012) Yusuf Erzin et al.   COMPUTERS & GEOSCIENCES

Monitoring spatiotemporal variations of diel radon concentrations in peatland and forest ecosystems based on neural network and regression models

(2012) Fatih Evrendilek et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Derivation of Relationships between Spectral Vegetation Indices from Multiple Sensors Based on Vegetation Isolines

(2012) Hiroki Yoshioka et al.   Remote Sensing

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

(2011) Fanghua Hao et al.   ENVIRONMENTAL MODELING & ASSESSMENT

Modeling Aboveground Biomass in Tropical Forests Using Multi-Frequency SAR Data—A Comparison of Methods

(2011) Sandra Englhart et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Assessment of community-based initiatives in sustainable management of Indian dry deciduous forests

(2011) Debajit Datta et al.   INTERNATIONAL JOURNAL OF SUSTAINABLE DEVELOPMENT AND WORLD ECOLOGY

How to fit nonlinear plant growth models and calculate growth rates: an update for ecologists

(2011) C. E. Timothy Paine et al.   Methods in Ecology and Evolution

Application of artificial neural networks in global climate change and ecological research: An overview

(2010) ZeLin Liu et al.   CHINESE SCIENCE BULLETIN

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

(2010) Scott L. Powell et al.   REMOTE SENSING OF ENVIRONMENT

Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests

(2009) T.M. Basuki et al.   FOREST ECOLOGY AND MANAGEMENT

An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps

(2008) H.A. Nefeslioglu et al.   ENGINEERING GEOLOGY