![]() ![]() Mendes, T., Henriques, S., Catalao, J., Redweik, P., & Vieira, G. ![]() Mapping and monitoring geological hazards using optical, LiDAR, and synthetic aperture RADAR image data. In 2015 IEEE international geoscience and remote sensing symposium (IGARSS) (pp. UAV: Low-cost remote sensing for high-resolution investigation of landslides. In Engineering Geology for Society and Territory- Volume 5 (pp. The use of UAV to monitor and manage the territory: perspectives from the SMAT project. IEEE Transactions on Robotics, 30(1), 177–187.įarfaglia, S., Lollino, G., Iaquinta, M., Sale, I., Catella, P., Martino, M., & Chiesa, S. Applied Geomatics, 6(1), 27–36.Įndres, F., Hess, J., Sturm, J., Cremers, D., & Burgard, W. GNSS network products for post-processing positioning: limitations and peculiarities. Determination of landslide and driftwood potentials by fixed-wing UAV-borne RGB and NIR images: a case study of Shenmu Area in Taiwan. Geological map of the Monviso massif (Western Alps). This report provided a drone survey analysis of compost percentage and vegetation indices of agricultural land.īalestro, G., Fioraso, G., & Lombardo, B. It can calculate real-time leaf stress analysis. It had used to estimate the leaf conductance rate with the variation of atmospherically changing. It measured degree and demonstrated GPS view using irrigation techniques to control water stress. Correlation of plant growth p ≤0.01, r = 0.77 and − 0.77 with conductance. NDVI, green normalized difference vegetation index (GNDVI), soil brightness index (SBI), green vegetation index (GVI), degree of yellow vegetation index (YVI), nitrogen sufficiency index (NSI), perpendicular vegetation index (PVI), transformed vegetation index (TVI), soil adjusted vegetation index (SAVI) and vegetation condition index (VCI) vegetation indices are used to the correlation of plant growth control with managing leaf strength and import python packages display the Vegetation various Real-time value in QGIS. The implemented view focused only on growth controlling of plant in-depth irrigation between 30 and 90 cm in 60% deviation. Irrigation techniques followed the treatment of the plant within continuous data per second. Standard irrigation level is 60% to produce the plant growing. Multispectral and hyperspectral views had used for analyzing the tested data. Real-time monitoring coupled in NIR imaging geometrically and radiometrically adjusted to measure temperature. NDVI sensors are loaded to produce high-density images. NIR and NDVI images had water content values and precision values which is mixed in managing water resources. This paper describes the analysis of drone remote sensing using the normalized difference vegetation index (NDVI)/Near-infrared band (NIR) sensor in a multispectral view of agricultural land. We have two methods, first one neural network algorithm of quantum geographic information system (QGIS) and another one global positioning system (GPS) with drone. Now, we need an organic spraying system at a low cost. Remote sensing is a big technology for reducing this requirement. Farmers have more requirements for the completion of cultivations. ![]()
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