Land surface temperature (LST) is a crucial geophysical parameter related to surface energy and water balance of the land-atmosphere system. Satellite remote sensing provides the best way to measure LST and generate various LST products at regional and global scales.For this, after calculating NDVI, we can calculate the Land Surface Temperature for two decade 2000 and 2020.For these calculation we calculate Top of Atmosphere (TOA) radiance, spectral radiance to TOA brightness temperature, Normalized Difference Vegetation Index, Surface emissivity by Jiménez-Muñoz algorithm, finally used Land Surface Tempeature. 

For image segementation, we can first collected the sample of the living trees, for high to low vegetation, and water bodies. By applying support Machine vector tools, make image segmentation on the based of objects. Object detection finds bounding boxes around objects and classifies them. Instance segmentation adds, for every detected object, a pixel mask that gives the shape of the object.

The land use and land cover information utilized in this study has been derived from LANDSAT data. Land use and land cover (LULC) classification is a well-established technique for satellite image interpretation. Supervised classificationmethod was used to map LULC from LANDSAT satellite images and urban land of 2000 and 2020.Study area was classified into urban land, vegetation, barren land and water. Also shows the urban land of Karachi city rapidly increased from 2000 to 2020. The city expanded in the direction of Malir and Karachi west. 

LST mapping has also been done for estimation of land surface temperature and compared with associated environmental condition. LST, NDVI and LULC was calculated in the same period of April 2000 and 2020. Its shows the Land Surface Temperature of Karachi and adjoining areas. The LST results show that the highest temperature range 33-38 C observed over the Karachi west, north-west Malir. 

The NDVI is calculated from visible (red) and near infrared bands. The tool in the Image Analysis Window calculates how vigorous the vegetation is in an area. But it’s not the only index available, although it may be the most widely used. It shows the NDVI of Karachi in April 2000 and June 2020. 

NDVI values from 0.42 to -0.1 from 2020, observed for vegetation along the roads and housing scheme. The higher NDVI values range 0.3 to 1 observed in Karachi East and at few places in Malir and west.