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Geospatial Techniques for Paddy Crop Acreage and Yield Estimation

机译:稻田种植​​面积和产量估计的地理空间技术

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摘要

Paddy crop acreage and yield estimation using geospatial technology were carried out in North Eastern Dry Zone (Zone-2) covering Shorapur taluk, Yadgir district, Karnataka state, India, during rabi late sown or summer 2016-17 season. The study area is located between 16° 20? to 17° 45? north latitude and 76° 04? to 77° 42? east longitude, at an elevation of 428 meters above mean sea level. The RESOURCESAT-1 LISS III satellite image of 31~(st) January 2017, 24~(th) February 2017, 20~(th) March 2017 and LANDSAT-8 of 15~(th )April 2017 were used for paddy crop acreage estimation at taluk level. Paddy signatures were identified using ground truth GPS data and then, these temporal imageries were subjected to NDVI classification and estimated the paddy biomass and further validated with the ground-truthing in corresponding to Green Seeker NDVI value. The estimated paddy crop acreage through imagery NDVI were 2145.75 ha, 17602.21 ha, 19838 ha and 23004.01 ha area during Jan-2017, Feb-2017, March-2017 and April-2017 respectively. When these results were compared with acreage estimates as reported by the State Department of Agriculture, shown a relative deviation of 11.41, 35.78, 23.01 3.89 per cent for Jan-2017, Feb-2017, March-2017 and April-2017 respectively. Therefore, LandSat-8 NDVI paddy acreage has showed significantly on par with the ground truth data at the crop harvest stage. Relative deviation of 10.75 for yield comparison among imagery NDVI biomass yield with the DOA yield estimation infer that NDVI biomass yield estimation would give better result at 90 days after sowing. Positive correlation of NDVI values with estimated acreage and yield, indicates that application of remote sensing techniques for forecasting paddy biomass yield is more accurate, economical and could be beneficial to the policy makers for quick decisions.
机译:水稻作物面积和利用地理空间技术的产量估计在东北干燥区(Zone-2)覆盖Shorapur Taluk,Yadgir区,印度卡纳塔克邦,在rabi晚播种或2016-17赛季夏季。研究区位于16°20之间?到17°45?北纬和76°04?到77°42?东经,高度高于228米的海平面。 2017年1月31〜(ST)的资源-1 Liss III卫星图像2017年1月,24〜(Th)2017年2月,2017年3月20日和15〜(Th)2017年4月15〜(Th)用于稻田种植面积Taluk水平估计。使用地面真理GPS数据识别稻田签名,然后对这些时间成像进行NDVI分类并估计稻田生物量并进一步验证与绿色寻求者NDVI值相对应的地面追踪。估计的稻田种植面积通过图像NDVI分别于2017年1月至2017年3月至2017年3月至2017年3月至2017年3月,19838公顷,19838公顷,19838公顷,19838公顷,19838张HA和23004.01公顷地区。当这些结果与国家农业部报告的面积估计进行比较时,分别显示11.41,35.78,33.01 3.89%的相对偏差分别于2017年1月至2017年3月至2017年3月至2017年至2017年。因此,Landsat-8 NDVI稻谷面积与作物收获阶段的地面真实数据表示显着显着。 10.75的相对偏差在图像NDVI生物量产量与DOA产量估计的比较,推断NDVI生物质产量估计将在播种后90天内提高结果。 NDVI值具有估计的面积和产量的正相关性表明,用于预测水稻生物质产量的遥感技术的应用更为准确,经济,可能对决策者进行快速决策有益。

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