Publications

Zarei, M; Tazeh, M; Moosavi, V; Kalantari, S (2021). Investigating the Capability of Thermal-Moisture Indices Extracted from MODIS Data in Classification and Trend in Wetlands. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 49(10), 2583-2596.

Abstract
Wetlands are considered as dynamic ecosystems that have been changed by various factors and to protect the environment, it is necessary to identify these changes, but since terrain investigation of wetlands requires a lot of time and money, remote sensing technology can be used in this regard. The purpose of this research is to investigate the capability of TVDI, MTVDI, VTCI and TVX along with MODIS satellite products including NDVI, EVI and LST in wetland classification. Due to the multiplicity of images used, coding in MATLAB software was used. In some of the mentioned indicators, triangular and trapezoidal method was used, which uses the parameters of vegetation and surface temperature to detect surface moisture. For this purpose, six Iranian wetlands during the period 2000-2016 were studied. The images were classified using SVM method. This classification was done in March and August in all years. The study results showed that using the mentioned indicators will make it possible to classify all studied wetlands with kappa coefficient above 0.9 and overall accuracy above 0.94. On the one hand, investigation of area changes in wetlands has shown that no decreasing or increasing trend was found in the study period.

DOI:
10.1007/s12524-021-01408-4

ISSN:
0255-660X