Hybrid CNN model for classification of rumex obtusifolius in Grassland by Al-Badri, Ahmed Husham, Ismail, Nor Azman, Al-Dulaimi, Khamael, Rehman, Amjad, Abunadi, Ibrahim, Bahaj, Saeed Ali

“…L.) is one of the vital broad-leaved weeds in grassland that needs removal. It affects dairy products and reduces their quality. …”
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GIS-based probability assessment of fire risk in grassland and forested lanscapes of Golestan province, Iran by Adab, Hamed, Kanniah, Kasturi D., Solaiman, Karim

Assessment of land use and land cover changes in association with hydrometeorological parameters in the Upper Indus Basin by Bilal, Hazrat, Siwar, Chamhuri, Mokhtar, Mazlin, Kanniah, Kasturi Devi, Govindan, Rajesh, Al-Ansari, Tareq

“…The mainland cover types in terms of area coverage are barren land 53%, grassland 31% and permanent snow and ice 15%. Vegetation like forestland, grassland, cropland and savanna increased significantly during the period of observation. …”

Estimation of hydrodynamic roughness over land in tropical environment using lidar data:a case study in Ayer Keroh, Melaka by Mohamad Aseham, Siti Idayu, Abd. Rahman, Muhammad Zulkarnain, Rasib, Abd. Wahid, Ariffin, Azman

“…The study area is divided into four landcover classes i.e. building, forest, grassland and paved road. The airborne LiDAR data was obtained using the Optech ALTM 3100 in 2009 with a posting density of about 0.69 point per meter squared. …”

Mapping grass above-ground biomass of grazing-lands using satellite remote sensing by Isa Muhammad Zumo, Isa Muhammad Zumo, Hashim, Mazlan, Hassan, NoorDyana

“…Several studies have been conducted globally to quantify grassland biomass utilizing satellite data, but rarely in African Savannah, particularly in Jibiro grazing land, Nigeria. …”

Groundwater quality and hydrogeological characteristics of Malacca state in Malaysia by Shirazi, Sharif Moniruzzaman, Adham, Md. Ibrahim, Zardari, Noorul Hassan, Ismail, Zubaidah, Imran, Hosen M. D., Mangrio, Munir Ahmed

Modelling grass land carrying capacity from satellite remote sensing by Zumo, I. M., Hashim, M., Hassan, N. D.

“…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. …”
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Potential of palsar data in retrieving spatial variability of soil moisture in tropical catchment by Mohd. Khan, Nor Liyana, Ibrahim, Ab. Latif, Askari, Muhamad

“…The higher coefficient is found in rubber area and followed by oil palm, grassland and shrub area with R = 0.89, 0.79, 0.38 and 0.13 respectively. …”
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Assessing the Forest cover changes of Yankari game reserve using remote sensing and GIS techniques by Hossain, Md. Sharafat, Ariff, Shahidah Mohammed

“…The percentage changes from forest cover to grassland was 22.93% from 1990-2001, 24.48% from 2001-2011 and 35.52% from 1990-2011.Also forest changes to open space was 18.29%, from 1990-2001, 7.78% from 2001-2011 and 13.64% from 1990-2011.While forest change to agriculture was 0.50% from 1990-2001, 2.15% from 2001-2011 and 2.98% from 1990-2011. …”
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Landfill site selection by integrating analytical hierarchy process and geographic information system by Mohamad, Izni Izzati, Mohd. Yunus, Mohd. Zulkifli, Ahmad, Fatimah Shafinaz

“…In GIS method, there are six parameters selected which are main road, plantation, residential area, swamp, grassland and river coverage . The findings identified two potential sites for landfill area because it s atisfied all given requirements. …”
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Impact of urbanization on the sediment yield in tropical watershed using temporal land-use changes and a GIS-based model by Bello, A. A. D., Hashim, N. B., Haniffah, R. M.

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Landfill site suitability using geographic information system and analytical hierarchy process by Mohamad, Izni Izzati

“…In GIS method, there are six parameters selected which are main road, plantation, residential area, swamp, grassland and river coverages. The findings identified two potential sites for landfill area because it satisfied all given requirements. …”
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Landcover classification: does airborne lidar alone capable of producing good quality of landcover map? by Abdul Rahman, Muhammad Zulkarnain, Ismail, Zamri, Rasib, Abd. Wahid, Wan Kadir, Wan Hazli, Ariffin, Azman

“…Generally, both classification methods agree that the LiDAR-derived features require the multispectral images to improve the classification results, especially for grassland, tilled land, and paved road. The landcover classification using only the LiDAR-derived data tends to produce lower overall classification accuracy than the classification based on just the multispectral images.…”

Modelling vegetationloss and greenhouse gas emissions in Kaduna, Nigeria by Bununu, Yakubu Aliyu, Muhamad Ludin, Ahmad Nazri, Hosni, Nafisa

“…Tropical forests and other vegetated landscapes like grasslands and wooded savannahs play a major role in the global carbon sequestration process and their conservation and protection offers immense potential for reducing greenhouse gas emissions and global warming. …”