
Modernization of pastoral systems based on the use of Urochloa species in the Colombian Eastern Llanos needs the use of remote sensing techniques from satellite platforms to estimate the amount of offered forage. In the Carimagua Research Centre of the Colombian Corporation for Agricultural Research (Agrosavia), an Urochloa humidicola cv. Llanero pasture was evaluated using Landsat 8 and Sentinel 2A images. The NDVI, SAVI, EVI and GNDVI vegetation indexes determined by using the blue, green, red and near infrared bands; and the results analyzed with the R free software, to relate those indexes with forage availability field measures taken during the dry season. Forage availability ranged between 290 and 656 kg DM ha-1 and the vegetation indexes for the Landsat 8 and Sentinel 2A sensors were: NDVI = 0.67 (±0.037) and 0.69 (±0.061); SAVI = 0.48 (±0.048) and 0.41 (±0.046); EVI = 0.70 (±0.052) and 0.41 (±0.047); and GNDVI = 0.60 (±0.028) and 0.70 (±0.034), respectively. The relationships between vegetation indexes and forage availability were linear. The Coefficient of Determination (R2= 0.56‒0.72) and the Mean Square Error (MSR =63.95‒80.16) of the prediction equations were used. In conclusion, under the conditions of the study, the EVI for Landsat 8 and NDVI for Sentinel 2A were considered adequate for estimating forage availability of Urochloa humidicola cv. Llanero.
Modernisation of pastoral systems based on the use of Urochloa species in the Colombian Eastern Llanos need the use of remote sensing techniques from satellite platforms to estimate amount of offered forage. In the Carimagua Research Centre of the Colombian Corporation for Agricultural Research (Agrosavia), an Urochloa humidicola cv. Llanero pasture was evaluated using Landsat 8 and Sentinel 2A images. The NDVI, SAVI, EVI et GNDVI vegetation indexes determined by using the blue, green, red and near infrared bands ; and the results analyzed with the R free software, to relate those indexes with forage availability field measures taken during the dry season. Forage availability ranged between 290 and 656 kg DM ha-1 and the vegetation indexes for the Landsat 8 and Sentinel 2A sensors were : NDVI = 0,67 (±0,037) and 0,69 (±0,061) ; SAVI = 0,48 (±0,048) and 0,41 (±0,046) ; EVI = 0,70 (±0,052) and 0,41 (±0,047) ; et GNDVI = 0,60 (±0,028) and 0,70 (±0,034), respectivement. The relationships between vegetation indexes and forage availability were linear. The Coefficient of Determination (R2= 0,56-0,72) and the Mean Square Error (MSR =63,95-80,16) of the prediction equations were used. En conclusion, under the conditions of the study, the EVI for Landsat 8 and NDVI for Sentinel 2A were considered adequate for estimating forage availability of Urochloa humidicola cv. Llanero.
Modernization of pastoral systems based on the use of Urochloa species in the Colombian Eastern Llanos need the use of remote sensing techniques from satellite platforms to estimate amount of offered forage. In the Carimagua Research Centre of the Colombian Corporation for Agricultural Research (Agrosavia), an Urochloa humidicola cv. Llanero pasture was evaluated using Landsat 8 and Sentinel 2A images. The NDVI, SAVI, EVI y GNDVI vegetation indexes determined by using the blue, green, red and near infrared bands; and the results analyzed with the R free software, to relate those indexes with forage availability field measures taken during the dry season. Forage availability ranged between 290 and 656 kg DM ha-1 and the vegetation indexes for the Landsat 8 and Sentinel 2A sensors were: NDVI = 0.67 (±0.037) and 0.69 (±0.061); SAVI = 0.48 (±0.048) and 0.41 (±0.046); EVI = 0.70 (±0.052) and 0.41 (±0.047); y GNDVI = 0.60 (±0.028) and 0.70 (±0.034), respectively. The relationships between vegetation indexes and forage availability were linear. The Coefficient of Determination (R2= 0.56‒0.72) and the Mean Square Error (MSR =63.95‒80.16) of the prediction equations were used. In conclusion, under the conditions of the study, the EVI for Landsat 8 and NDVI for Sentinel 2A were considered adequate for estimating forage availability of Urochloa humidicola cv. Llanero.
يحتاج تحديث النظم الرعوية القائمة على استخدام أنواع أوروكلوا في يانوس الشرقية الكولومبية إلى استخدام تقنيات الاستشعار عن بعد من منصات الأقمار الصناعية لتقدير كمية الأعلاف المعروضة. في مركز أبحاث Carimagua التابع للمؤسسة الكولومبية للبحوث الزراعية (Agrosavia)، السيرة الذاتية Urochloa humidicola cv. تم تقييم مرعى Llanero باستخدام صور Landsat 8 و Sentinel 2A. يتم تحديد مؤشرات الغطاء النباتي NDVI و SAVI و EVI و GNDVI باستخدام النطاقات الزرقاء والخضراء والحمراء وبالقرب من الأشعة تحت الحمراء ؛ والنتائج التي تم تحليلها باستخدام برنامج R free، لربط تلك المؤشرات بالتدابير الميدانية لتوافر الأعلاف المتخذة خلال موسم الجفاف. تراوح توافر العلف بين 290 و 656 كجم DM ha -1 وكانت مؤشرات الغطاء النباتي لمستشعرات Landsat 8 و Sentinel 2A هي: NDVI = 0.67 (±0.037) و 0.69 (±0.061 )؛ SAVI = 0.48 (±0.048) و 0.41 (±0.046 )؛ EVI = 0.70 (±0.052) و 0.41 (±0.047 )؛ و GNDVI = 0.60 (±0.028) و 0.70 (±0.034)، على التوالي. كانت العلاقات بين مؤشرات الغطاء النباتي وتوافر الأعلاف خطية. تم استخدام معامل التحديد (R2 = 0.56 − 0.72) وخطأ متوسط المربع (MSR =63.95 − 80.16) لمعادلات التنبؤ. في الختام، في ظل ظروف الدراسة، تم اعتبار مؤشر الضعف الاقتصادي لـ Landsat 8 و NDVI لـ Sentinel 2A مناسبًا لتقدير توافر العلف لـ Urochloa humidicola cv. Llanero.
Forage, Geography, Life Sciences, Forestry, Normalized Difference Vegetation Index, Agronomy, Food and Agriculture in Latin America, Agricultural and Biological Sciences, Leaf area index, FOS: Mathematics, Pathology, Pasture, Medicine, Agroecology and Sustainable Agriculture, General Agricultural and Biological Sciences, Biology, Agroecology, Vegetation (pathology), Animal science, Mathematics, Food Science
Forage, Geography, Life Sciences, Forestry, Normalized Difference Vegetation Index, Agronomy, Food and Agriculture in Latin America, Agricultural and Biological Sciences, Leaf area index, FOS: Mathematics, Pathology, Pasture, Medicine, Agroecology and Sustainable Agriculture, General Agricultural and Biological Sciences, Biology, Agroecology, Vegetation (pathology), Animal science, Mathematics, Food Science
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