برآورد رطوبت خاك بر مبناي داده هاي حرارتي سنجش از دور با استفاده از ضريب انتقال تبخير خاك

Thermal Remote Sensing of Soil Moisture Based on Soil Evaporation Transfer Coefficient

رطوبت خاك يك پارامتر هيدرولوژيكي مهم و تاثيرگذار در فعل و انفعالات بين فرايندهاي اتمسفر و سطح زمين است. ضريب انتقال تبخير خاك (ha) كه تنها بر اساس دما محاسبه مي شود براي تخمين رطوبت خاك بخشي از منطقه مركزي ايران استفاده و پياده سازي شده و نتايج آن مورد ارزيابي قرار گرفته است. براي محاسبه ي ha به دماي سطح خاك (LST)، دماي هوا و دماي خاك مرجع (خاك خشك بدون تبخير) نياز است. براي بررسي رابطه ي اين ضريب با رطوبت خاك در دو نوبت برداشت هاي زميني در قسمتي از منطقه مركزي ايران انجام شده و تعدادي از تصاوير سنجنده ي MODIS TERRA مربوط به خردادماه 1390 نيز استفاده شده است. براي محاسبه ي دماي خاك خشك مرجع، دو روش ماكزيمم دماي محلي و روش تشكيل فضاي مثلثي به كار برده شد كه استفاده از روش دوم براي اين منظور به عنوان يك ايده جديد مطرح شده است. روابط رگرسيوني مختلفي بين رطوبت خاك و ضريب انتقال تبخير خاك ارزيابي شد كه از اين ميان روابط رگرسيوني خطي و لگاريتمي نتايج بهتري را نشان دادند. ضريب R2 براي اين روابط 7/0 و بهتر از آن بوده است كه نشان دهنده قابليت اين ضريب براي محاسبه رطوبت خاك است. بر همين مبنا مي توان نقشه رطوبت خاك را براي منطقه مطالعاتي تهيه كرد. براي توسعه ي اين روش براي خاك هاي همراه با گياه استفاده از ha به همراه NDVI پيشنهاد مي شود.

Soil moisture is an important hydrological variable influencing the interactions between land surface and atmospheric processes. Different methods have been proposed in recent years among them are remote sensing thermal indices. In this paper, an index called temperature based soil evaporation transfer coefficient (ha) is used and evaluated based on in situ data. The coefficient is computed based on land surface temperature, air temperature and reference soil surface temperature. Estimation of the later quantity encounters some difficulties. In this paper, two methods were introduced for calculating reference soil surface temperature: a simplified method using the regional maximum temperature and a new method based on triangular LST- NDVI space. In situ experiments are performed to test the relationship between the calculated coefficient and soil moisture in two time periods during 30 May to 6 June 2011 in central Iran. MODIS images are used as remote sensing data. Different regression relations have been evaluated between ha coefficient and soil moisture. The results show improvements of the proposed new method. Evaluations prove that linear and logarithmic regression relations represent more acceptable results. Finally, soil moisture map is provided for whole study area. Abstracts of Papers in English 111 July the optimism of a Decision Maker (DM). An important issue that should be considered when determining the weighting vector for OWA is to define the DM’s OD. This determination is performed under uncertainty. The objective of this article is to calculate the sensitivity measure with respect to the DM’s OD in a process that extends the FPR with the help of OWA operator. FPR_OWA operator is one of the aggregation operators. The output of this operator depends on the DM’s OD. By changing DM’s OD, one can generate a wide range of strategies. In this article, the Fuzzy Linguistic Quantifiers (FLQ) method is used for calculating the OWA operator weighting vector. And then the sensitivity measure of alternatives with respect to the DM’s OD were calculated. Finally for making a decision with lower degree of risk, the FPR_OWA output and sensitivity of the operator with respect to the DM’s OD, were integrated using a composite measure. This measure was used to rank the solutions in a multicriteria decision making problem for choosing the best location for a new gas station