Page 288 - NGTU_paper_withoutVideo

کیتاموئژ نیون یاهدربراک و اه یروآ نف یلم سنارفنک

2
Assistant Professor of Remote Sensing at University of Tabriz , Tabriz, Iran , h_emami@tabriz.ac.ir
3 Bachelor of Surveying, Tabriz, Iran, Ha_re_2015@yahoo.com
Abstract: Soil moisture is one of the most important parameters in the soil system and is defined as
the amount of water in the space between the soil particles. In general, soil moisture can be a
combination of soil surface moisture, representing water content up to a depth of 10 cm above the
soil, and soil moisture depth of up to 200 cm from the soil surface, indicating the amount of water
available to plants. Okay, defined. Soil moisture is a highly variable temporal and spatial parameter,
especially at the soil surface. The most important factors affecting spatial variability of soil surface
moisture include topography, soil properties and characteristics, type and density of vegetation, mean
moisture, precipitation depth, solar radiation, emissivity and surface temperature, and other
meteorological and climatic factors. Soil moisture is directly measured by land-based methods and
indirectly by remote sensing. Since terrestrial measurements are usually costly and time consuming
over large areas, methods such as remote sensing can be used to estimate soil moisture at very large
spatial scales. The purpose of this study was to estimate soil moisture content using remote sensing
indices. Due to regular data in the USA region, the calibration of the soil moisture estimation model
was performed through USDA data. And given the high similarity of the Marand area with the USA,
the statistical modeling for the Marand area was studied. For this purpose, all indices were extracted
using LANDSAT 8 satellite imagery and validated with the soil moisture values obtained from the
American Soil Classification System. In this study, the study area was described and then, using
optimal indices, a soil moisture estimation model was obtained. The results showed that there was a
good correlation between soil surface moisture and LST, ABDI, PDI, MPDI, SM, EVI2 indices (R =
78% and R2 = 62%). The results of soil moisture estimation model showed that the moisture content
of the model had a linear correlation with soil surface moisture content (R = 62% and R2 = 38%).
Also the RMSE error value between model moisture and ground moisture values is 0.023.

Keywords: Soil Surface Moisture, LANDSAT8, USDA, Correlation, Satellite Images

همدقم 1 -

و دنک ی م لرتنک ار ذوفن ناز ی م کاخ تبوطر ،شراب ثداوحرد .دراد ی ی ک ژولورد ی ه فلتخم ی اهدن ی آرف رد ی مهم ی را سب شقن 1 کاخ تبوطر
نیمه هب .درا ذگ یم ریثات قرعت و ی ر خبت ناز ی ل و م ی س زا ی شان ثداوح ، شیاسرف یاهدنیآرف رب رتماراپ نیا .دوش م ی صخشم باناور رادقم هج ی تن رد
ی ار ز ،درا د یدایز ت ی مها ی رادز ی خبآ ت دم ی ر ی ی ی ، ارب فداصت شراب ی ع اقو و ی ی ها گ ش شوپ ، کاخ تبوطر یی ا ضف ی ع زوت هب طوبرم تاعالطا لیالد

ه ا باناور و ی ل س تانا ی رج ت ی ر ی دم و ب ی ن ی ش ی پ هب فمک ی ا و دنک ی م مهارف ف شخ ی اه هرود رد بآ عبانم ددجم ی زا س ی هب ی هن ارب ار ناکما ا ی ن
. [ 1 ] ت سا لوصحم هعسوت ی ی ارب ی ر ح ی تا غتم ف ی کاخ تبوطر ی ، عارز هاگد ی د زا . دنک یم
، 2 یطیحم ت سیز یاه دنیارف زا یعی سو شخب تیفیک هدننک لرتنک ریغتم و دنک یم هرا شا کاخ ییالاب شخب رد دوجوم بآ هب کاخ ت بوطر

یرایسب رد مهزاب یلو دسرب رظن هب زیچان تسا نکمم ناهج رد دوجوم بآ رادقم اب هسیاقم رد [ 2 ] . تسا 5 یسانشاوه و 4 یکینکتوئژ ، 3 یژولوردیه

Soil moisture

Enviormental

Hydrology

Geotechnical
Meteorology