جستجوی مقالات مرتبط با کلیدواژه « dynamic statistical model » در نشریات گروه « جنگلداری »

Drought in Zagros, which is one of the most important ecosystems in Iran, is a big challenge. Remote sensing has a unique application in diagnosis, monitoring and management of natural resources. The purpose of this study is to investigate and analyze the drought situation in the middle and southern Zagros basin based on atmospheric general circulation models and neural network in relation to remote sensing indices NDVI, VCI, TCI, VHI, DDI, EVI, NDWI and SAVI. At first the Modis satellite time series images were used in a 20-year period. First the mentioned indicators were produced from MOD021KM products of Terra sensor from 2000 to 2019. Then amount of precipitation were estimated by using of statistical-dynamic model MP5 under RCP 2.6, RCP 4.5 and RCP 8.5 scenarios and neural network and Remote sensing indicators during the period from 2020 to 2039, And then the state of droughts was investigated in 2 periods of 20 years based on the SPI method (2000-2019) and based on RCP scenarios and remote sensing methods and neural networks for the next 20 years (2021-2039). The results showed that both in the period of 2000-2019 and 2020-2039, the high areas of the studied area have and will have severe and very severe wet year. Also, the spatial analysis of droughts and remote sensing indices of the second period has depicted an irregular pattern in all indices, and only in NDVI and SAVI indices, the spatial analysis of droughts has been able to present a relatively regular pattern