YIELD ESTIMATION OF SUNFLOWER PLANT WITH CNN AND ANN USING SENTINEL-2

Due to food security and agricultural land management, it is crucial for decision makers and farmers to predict crop yields. In remote sensing based agricultural studies, spectral resolutions of satellite images, as well as temporal and spatial resolution, are important. In this study, we investigated whether there is a relationship between the Normalized Different Vegetation Index (NDVI) and Normalized Different Vegetation Index Red-edge (NDVIred) indices derived from the Sentinel-2 satellite. In addition, the efficiency of linear regression, Convolutional Neural Network (CNN), and Artificial Neural Network (ANN) techniques are examined with the use of indices in yield estimation. In this context, yield data of 48 sunflower parcels were obtained in 2018. The obtained results showed that both NDVI and NDVIred can be used to estimate the yield of sunflowers. The best results were obtained from the combination of the NDVI and the CNN technique with the RMSE equal to 20,874 Kg/da on 30 June 2018. Concerning the results, although there is not much superiority between the two indices, the best results were generally obtained from CNN as the method.

Sustainable Agricultural Land Management in Garut Regency, West Java Province, Indonesia

The high land conversion rate to other sectors has led the government to issue Law No. 41 in 2009 concerning Protection of Sustainable Agricultural Land (SAL). The study aims to identify the distribution of sustainable agricultural land uses and determine agricultural land-use changes from 2016 to 2019 and determine farmers' understanding of sustainable agricultural land control in the strategic area of Garut Regency. We overlaid the land use maps of Garut Regency in 2016 and 2019 and conducted a survey using an online questionnaire with a Google form. The research location is in five districts in Garut Regency. The results showed no land conversion in the area of existing sustainable agricultural land in Garut Regency. The total rice field area is 6,081 hectares, with about 24% is sustainable agricultural land. From 2016 to 2019, the rice field area decreased by 12 hectares. The farmers' awareness of SAL tends to be more likely aware of the sustainable agricultural land area, as many as 39% of farmers aware of sustainable agricultural land. The incentives given to farmers who control sustainable agricultural land are tax deduction, agricultural infrastructure supply, agricultural production facilities subsidies, and land certification facilities. The majority of the respondents are aware of these incentives. In conclusion, no sustainable agricultural land is converted, even though changes occur in non-sustainable agricultural land. The impact of this study is for recommendations to the government in sustainable agricultural land management.

Impacts of forest cover on surface runoff quality in small catchments

Forest cover influences not only the amount of surface runoff, but also its quality. The concentrations of chemicals in surface runoff differ between forest catchments and non-forest catchments (agricultural areas). The authors investigated the chemical compositions of surface runoff in two small neighboring catchments (forest, non-forest), by analyzing and summarizing data over a period of 26 years from 1986 to 2012. During this period, the stock and absorption area of forest stands increased, air quality improved, the agricultural landscape was partly regenerated, and global climate change became apparent. The authors observed differences in surface runoff between forest- and non-forest catchments. However, these differences were not mainly caused by the influence of the forest cover, but by changes in agricultural land management. Since 2006, agricultural land has been managed without the use of artificial fertilizers, which reduced the contents of pollutants in surface runoff from the non-forest catchment. The existence of the forest as such excludes or noticeably eliminates the use of fertilizers and chemical substances that affect water quality.

Geospatial technology with the integration of MCDA to identify potential irrigation site for agricultural land management in Wanka watershed, Northwestern Ethiopia

Irrigation improves the productivity of agriculture in any country. Irrigation is viewed as a fundamental approach to ensure food security, improve crop productivity, income of smallholder farmers, ensure food security, alleviate poverty and improve the economy of the farming community by generating additional income. As a result, the goal of this study was to identify prospective irrigated lands for agricultural land management in the Wanka watershed in northwestern Ethiopia using geospatial technology and multi-criteria decision-making analysis. Identifying sites for surface irrigation for agricultural land management is not a simple task, which needs consideration of many criteria such as slope, soil texture, soil depth, soil drainage, land use/land cover and distance from the water supply were used to determine the best possible location. Each factor was categorized into highly suitable, moderately suitable, marginally suitable and currently not suitable. The final result showed that the watershed had a high opportunity for surface irrigation. About 498 km2 of the watershed's total area is potentially suitable for surface irrigation, whereas the remaining 443 km2 is not. In the research area, there is sufficient land area accessible for surface irrigation development if those locations with highly suitable to marginally suitable areas are properly utilized.

Agricultural Land Management Based On Local Arisival Of The Kaili Da’a Tribe In Dombu Village

This study aims to describe the local wisdom of the Kaili da’a Tribe in managing agricultural land in Dombu Village, Marawola District, Sigi Regency, Central Sulawesi. This research is descriptive qualitative, the research subjects in this study are the people of the Kaili da’a Tribe in Dombu village with the key informant of the Kaili da’a tribal chief, the types and sources of data are primary data and secondary data with data collection methods through observation and interviews. Qualitative descriptive data analysis technique. The results of this study indicate that the cultivation of agricultural land is carried out traditionally in accordance with the local wisdom of the Kaili da’a Tribe, while the management of agricultural land of the Kaili da’a Tribe includes: 1) Preparation includes customary council meetings and traditional ceremonies, 2) Land Opening, 3) Plowing of Land, 4) Land Harvesting, 5) Basic Fertilization.

Research on the Scale of Agricultural Land Moderate Management and Countermeasures Based on Farm Household Analysis

The scale of agricultural land management was scientifically measured to provide a theoretical reference for improving the efficiency of agricultural land utilization, optimizing the industrial structure, and effectively solving the “three rural problems”. Based on 368 microfarmers’ agricultural land management questionnaire responses, the Cobb–Douglas production function was used to measure the average household size in different zones of Shawan City, Xinjiang, and then to calculate the total scale of moderate management in the region, and to divide the supplementary and reduced zones of arable land. The proposed countermeasures and suggestions for achieving the scale of moderate management from the perspectives of both people and land are presented. The results show the following: (1) the average suitable operating scales of households in the hilly area, the agricultural area in the oasis plain, and the oasis–desert interlace area were 5.15, 9.28, and 7.74 ha, respectively. (2) The moderate total scales of operation in the low hilly area, the middle oasis plain agricultural area, and the lower oasis–desert ecotone were 60,380, 112,510, and 115,500 ha, respectively. (3) Two areas, the low mountainous and hilly areas and the oasis plain farming areas, are supplementary areas of arable land, which should be supplemented by improving the management capacity of farmers, cultivating two new agricultural business entities, increasing land transfers, developing modern agriculture, and reducing the degree of fragmentation of arable land. The oasis–desert staggered area is the area where the scale of arable land is reduced. We should vigorously implement the work of retreating land and reducing water, and guide farmers to engage in secondary and tertiary industries so as to reduce the scale of arable land.

Agricultural Land Transition in the “Groundnut Basin” of Senegal: 2009 to 2018

The study aims to reveal the transition features of agricultural land use in the Groundnut Basin of Senegal from 2009 to 2018, especially the impact of urbanization on agricultural land and the viewpoint of farmland spatiotemporal evolution. Integrated data of time series MCD12Q1 land-use images of 2009, 2012, 2015, and 2018 were used to provide a land transition in agricultural and urban areas through the synergistic methodology. Socio-economic data was also used to serve as a basis for the argument. The results highlight that: (1) Agricultural land increased by 14.53%, with a dynamic index of 1.45 from 2009–2018. (2) Over the same period, urbanization increased by 2.80%, with a dynamic index of 0.28. (3) In different regions, the transition of agricultural land in Kaffrine is most intense (expansion rate: 22.80%). The same situation of urbanization happened in Thiès Region with a value of 7.94%. Except for Thiès, agricultural land in other regions has not yet been subject to major pressure due to urbanization. Overall, the farming system in Groundnut Basin is an extensive model, the recommendations from the point of view of land-use planning and land law are necessary to ensure efficient agricultural land management in the area.

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