The rapid development of remote sensing technology has dramatically advanced our ability to monitor and examine changing environments precisely. Global satellite technologies, led by space agencies like NASA, ESA, and JAXA, along with private enterprises, advances climate monitoring, disaster resilience, and oceanic carbon sequestration, promoting environmental sustainability through innovative missions and shared data. This chapter explores the nuances and uses of thermal, hyperspectral, and multispectral infrared imaging in environmental assessment. Multispectral imaging, which collects data in many specific spectral bands using sensors like Landsat, Sentinel series, and others, is essential for classifying various land cover types and assessing vegetation indices. Characterized by the ability to collect records in a mass of contiguous spectral bands, hyperspectral imaging enables the identification and classification of specified material, enabled by sensors that include Hyperion, AVIRIS, and CASI. Using sensors like drones and satellites, thermal infrared imaging, which quantifies the thermal radiation emitted, is vital for monitoring Earth’s temperatures and emissivity. The chapter will begin by explaining the essential standards of these imaging technologies, accompanied by an in-depth discussion on methodologies consisting of data acquisition techniques, preprocessing steps like radiometric and atmospheric corrections, and advanced record fusion methods that integrate multiple imaging modalities for a more suitable evaluation. Analytical methods, including spectral unmixing, algorithms, and thermal anomaly detection, could be explored. The chapter will then spotlight the various imaging technology programs in environmental evaluation. Thermal imaging helps detect plant stress and water content; on the other hand, multispectral and hyperspectral data are used in vegetation and forest monitoring to evaluate vegetation health, identify species, and estimate biomass precisely. These technologies also monitor indicators including algal blooms, turbidity, and chlorophyll concentration to measure the quality of the water; thermal imaging detects thermal pollution and its consequences on aquatic ecosystems widely. Hyperspectral imaging describes soil features, including its organic matter and mineral content, whereas multispectral and thermal data mainly evaluate the ground cover’s erosion, desertification, and deterioration. This chapter will also discuss the use of multispectral and hyperspectral data to evaluate the effects of climate change on various ecosystems, as well as the investigation of urban heat islands and their prevention through thermal infrared imaging, which is a very concerning issue nowadays. The utility and effectiveness of these technologies will be validated through real-world case studies that include urban heat island research in major cities, water assessment in water bodies, and deforestation monitoring in forest areas. Along with discussing the capacity of future use for imaging technology, the chapter will also discuss the critical present issues in remote sensing, including the large extent of data, processing complexity, and sensor constraints. Increasing environmental monitoring capabilities involves the advent of sensors with better resolutions, more robust data analytics, and the integration of artificial intelligence. This chapter aims to provide a thorough overview of multispectral, hyperspectral, and thermal infrared imaging in a categorized manner. It will also highlight the essential function these technologies play in improving our comprehension and management of environmental resources and their ability to cope with new environmental problems.