Assessing the capability of Modis fire detector products in identifying fires in Golestan State

The use of remote sensing is particularly important in identifying burned areas due to its extensive spatial coverage and the provision of information at different times. Today, Modis fire products are widely used for this purpose. The purpose of this study is to evaluate the capability of Modis MOD14, MOD14A2 (Terra), and MYD14, MYD14A2 (Aqua) fire detector products and to identify fire areas in Golestan state. First, a point map of all the images was generated, then to evaluate the accuracy of the fire products, the prepared point map for the products was compared with terrestrial reality data. If the location of each of the reported fires is consistent with the fires identified by the products, that location was correctly identified as the fire. Landsat images were used as a ground accuracy map to evaluate the accuracy of Modis images. The results showed that six regions identified by level 2 fire products and eight regions were detected by level 3 fire products were identified. The results show the accuracy of the images with a coefficient of R ^ 2 of 0.94 and a coefficient of RMSE of 426.12 ha. The studies conducted in this study show that to improve the performance of the text fire detection algorithm, this algorithm is proposed for the forests of Golestan province and following the conditions and characteristics of the fire area, its intensity, and area. Be developed to provide better results

Inter-comparison of multiple angle remotely sensed data across different spatial resolutions and sensors for determination of albedo

Surface albedo is one of the critical parameters required by studies of surface energy balance and climate models. Albedo is defined as the ratio of outgoing radiances to incoming irradiances over hemispherical view-illumination geometry. Remotely sensed albedo is usually based on multiple view angle observations and a Bidirectional Reflectance Distribution Function (BRDF) model. The accuracy of remotely sensed albedo depends on a variety of factors of which the main ones are the accuracy of atmospherically corrected observations, the reliability of observations, and the validity of the applied BRDF model. Fine spatial resolution airborne and satellite data are valuable for the validation of coarse spatial resolution satellite albedos as they may be validated using field measurements with higher reliability. In this study, a variety of remote sensing data and field measurements were used to estimate, validate and analyse albedo at different spatial resolutions. The main aim was to validate the MODIS albedo product under UK conditions using the methods of direct and indirect comparisons with other available data. The source of the fine spatial resolution data used was the NCAVEO Field Campaign 2006 that took place at the Chilbolton calibration test site in southern England. The CHRIS/PROBA albedo was used as a fine spatial resolution (34 m) albedo map to investigate the spatial variation of albedo. The results of this investigation provided valuable information about the possibility of the extension of the obtained albedo map from CHRIS/PROBA data. The MODIS albedo product with a coarser spatial resolution (500 m), relative to the NCAVEO datasets, was compared with the CHRIS/PROBA albedo map to examine the effect of spatial scale on the accuracy of albedo (direct comparison). The uncertainties in the obtained albedo maps, from both MODIS and CHRIS/PROBA, were mainly examined by testing the accuracy of the input reflectance data and the applied BRDF model (indirect comparison). The results showed the accuracy of the MODIS albedo product inferior to that claimed by the MODIS team

Validation of the MODIS reflectance product under UK conditions

Surface reflectance obtained from remote sensing data is the main input to almost all remote sensing applications. The availability and special characteristics of MODIS products have led to their use worldwide. Validation of the MODIS reflectance product is then crucial to provide information on uncertainty in the reflectance data, and in other MODIS products and in the applied surface-atmosphere models. Airborne CASI and SPOT data, collected during the NCAVEO 2006 Field Campaign, were applied to validate daily MODIS reflectance data over a site in southern England. The difference in the view geometry of at-nadir CASI and SPOT data and off-nadir MODIS data was dealt with using a semi-empirical bidirectional reflectance distribution function (BRDF) model. The validation results showed that for our particular study site, the absolute errors in the MODIS reflectance product were too large to allow the albedo data to be used directly in climate models. The errors were mainly related to the uncertainties in the MODIS atmospheric variables, the BRDF model, and undetected clouds and cloud shadows. More generally, the study highlights the extreme difficulty of achieving pixel-level validation of coarse spatial resolution satellite sensor data in an environment in which the atmosphere is constantly changing, and in which the landscape is characterised by high space-time heterogeneit