جستجوی مقالات مرتبط با کلیدواژه « شاخص سطح برگ (LAI) » در نشریات گروه « جغرافیا »

Vegetation is a key component of the earth planet, which controls the energy and water exchanges between atmosphere and the Earth surface and plays an important role in the global energy cycles, such as oxygen, carbon dioxide, and water. Monitoring and management of vegetation are done using its biophysical and biochemical parameters such as LAI. Leaf area index (LAI) is one of the most important vegetation parameters that used in most of the applications such as water and carbon cycles modeling. Remote sensing in terms of their continuous and extensive cover is a unique tool for generating vegetation variables. Different retrieval approaches have been developed to extract biophysical parameters information from remote sensing data, which is divided into two broad classes, the statistical/experimental approaches and the physical approach. In the present study, the PROSAIL RT model (Radiation Transfer Model) based on the LUT table have been used to retrieve the LAI variable. Ground reference data collected during the SPARC 2003 campaign were also used to evaluate the accuracy of the retrieved variable. To drawback, the ill-posed problem, four categories of cost functions have been used: Information Measurement (IM), Minimum contrast (MC), Angle Measurement (SAM) and Least Square Error (LSE) and used the multiple Best solution instead of Single best solution. The results showed improvement in the LAI estimation of up to 12% for the multi-species canopy.

The aim of current research is to access pasture covering status in drought and rainy conditions during pasture germination beginning and climax periods in different altitudes of Shirvan darasi aquiferous zone at Meshkinshahr city. So, by using precipitation data, total daily, participation, minimum, maximum and mean temperature of Meshkinshahr were measured during 1996-2016 statistical period and were used for determining pasture growth in different periods and calculating standard precipitation index (SPI) in 3 time intervals with 1, 3 and 6 months and also TM Landset satellite images were applied for plant covering difference index (NDVI) and leaf area index (LAI) during pasture germination beginning and climax periods in different altitudes of studied zone. In order to investigation the relationship between studied indices, (R2) correlation, (R) Pearson correlation and RMSE (root mean of square error) coefficients were used. Based on SPI index results, precipitation position was normal in most of years in the region, but the most drying conditions have happened during April, May, June months for pasture growth period. Obtained results from implementation and evaluation of indices showed that the most correlation between leaf area index at standard participation and pasture germination climax periods at pasture germination beginning period was equal to 0/874, with the least error rate which it is equal to 1/32. According to Pearson correlation coefficient there is significant relationship between participation amount during pasture germination beginning period with pasture covering area at germination climax period. Generally, results showed that precipitation decline during early stages of pasture growth period has a more significant impact in determining growth conditions and pasture congestion compared to dry conditions in other pasture growth stages.