Author:
Zumo Isa Muhammad,Hashim Mazlan,Hassan Noor Dyana
Abstract
Abstract
Developments in Remote Sensing (RS) satellite technology have made it possible to apply RS products for agricultural purposes, including modelling grassland carrying capacity (CC) of grazing land. However, determining the grazing land CC using pixel based approach is relatively new. This study modelled CC using pixel based approach and later compare it with the convetional method. Sentinel 2A MSI, in-situ Grass Above-ground Biomass (GAB) of 30 sample points and livestock data were used for the modelling CC of Daware grazing land northeast Nigeria. The result indicate that the available grass in the grazing land can only support 2,377,419 goats/sheep for 6 months or 4909 cattle for 1 month. This indicates that the grazing land was over grazed. The result of this study shows areas of grass available for rotational grazing throughout the season, thereby contributing to accurate modelling of grazing lands in Savannah and similar eco system.
Reference20 articles.
1. Livestock feed resources in southern Ethiopia: The case of meskan district;Ebro,2017
2. Drought consequences for cow-calf production in Wyoming: 2011—2014;Scasta;Rangelands,2015
3. Mapping Seasonal Variations of Grazing Land Above-ground Biomass with Sentinel 2A Satellite Data;Zumo;IOP Conference Series: Earth and Environmental Science,2020
4. Human Appropriation of Net Primary Productivity and Rural Livelihoods: Findings from Six Villages in Zimbabwe;Pritchard;Ecological Economics,2018
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献