Knowledge of spatial and temporal variations in crop growth is important for crop management and stable crop production for the food security of a country. A combination of crop growth models and remote sensing data is a useful method for monitoring crop growth status and estimating crop yield. The objective of this study was to use spectral-based biomass values generated from spectral indices ...

The use of hydroacoustics is currently being studied and developed as a promising non-intrusive methodology to monitor manage fish stocks in aquaculture farms. main objective this study was develop an acoustic method for the estimation density biomass inland farms test accuracy precision estimates with real data provided by company. conducted sea bass (Dicentrarchus labrax) production ponds loc...

Aim of the study: The aim of this study was to develop a model for above-ground biomass estimation for Pinus radiata D. Don in Asturias. Area of study: Asturias (NE of Spain). Material and methods: Different models were f itted for the different above-ground components and weighted regression was used to correct heteroscedasticity. Finally, all the models were refitted simultaneously by use of ...

The spatial distribution of plant diversity and biomass informs management decisions to maintain biodiversity and carbon stocks in tropical forests. Optical remotely sensed data is often used for supporting such activities; however, it is difficult to estimate these variables in areas of high biomass. New technologies, such as airborne LiDAR, have been used to overcome such limitations. LiDAR h...

In tree biomass estimations, it is important to consider the property of additivity, i.e., the total tree biomass should equal the sum of the components. This work presents functions that allow estimation of the stem and crown dry weight components of Pyrenean oak (Quercus pyrenaica Willd.) trees. A procedure that considers additivity of tree biomass components is presented, and applied to a pa...

Abstract. Biomass is an important indicator in the ecological and management process that can now be estimated at higher temporal spatial resolutions because of unmanned aircraft systems (UAS). LiDAR sensor technology has advanced enabling more compact sizes integrated with UAS platforms. Its signals are capable penetrating through vegetation canopies capture information along plant structure. ...

Root biomass is one of the most relevant root parameters for studies of plant response to environmental change, soil carbon modeling or estimations of soil carbon sequestration. A major source of error in root biomass quantification of agricultural crops in the field is the presence of extraneous organic matter in soil: dead roots from previous crops, weed roots, incorporated above ground plant...

Three-year forest above-ground biomass change is to be measured using L-band synthetic aperture radar (SAR) backscatter. Measurements are also made using P-band backscatter for comparison. The radar data were collected in the airborne BioSAR 2007 and BioSAR 2010 campaigns over the hemiboreal Remningstorp test site in southern Sweden. Regression models for biomass will be developed using referen...

Accurate monitoring of grassland biomass at high spatial and temporal resolutions is important for the effective utilization of grasslands in ecological and agricultural applications. However, current remote sensing data cannot simultaneously provide accurate monitoring of vegetation changes with fine temporal and spatial resolutions. We used a data-fusion approach, namely the spatial and tempo...