IndexIntroductionMethodologyImage pre-processing and analysisIntroductionA large part of the Rwandan population resides in agricultural communities where agriculture is the main source of income and livelihood. This could lead to severe land degradation due to agricultural activities and high demand for firewood. In addition to this, a large number of plots of land are being deforested. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay Biomass plays an important role by providing several ecosystem services that can help adapt and mitigate global climate change. Vegetation Spectral Index data is used to study the relationship between climate and vegetation at the landscape level, to assist land management and sustainable use of forests and other plant resources, and also to study the impacts of climate change and carbon sequestration by different vegetation types (Nurhussen, 2016 ). Currently, global vegetation cover has declined due to human-induced activities, mainly through deforestation for other diverse land uses. Remote sensing is broadly defined as a science of collecting and interpreting information about a target without being in physical contact with the target (Sabins, 1997). The remote sensing process mainly consists of analyzing and interpreting data collected by a sensor. Remote sensing approaches provide useful information on the topic under investigation from different points of view and include different techniques, ranging from traditional methods of visual interpretation to methods of digitally extracting information using sophisticated computing processes. This study aimed to analyze the seasonal change in biomass using satellite remotely sensed data, Musanze District, Rwanda, with the following specific objectives; Map the existing and current state of biomass in the Kimonyi sector, produce NDVI maps and trends of biomass classes in the study area, seasonally assess vegetation conditions, seasonally detect changes in plant biomass. Therefore, the study reveals that remote sensing is a powerful tool for monitoring biomass change over a given period, thus directly contributing to any planning activity, especially in the areas of environmental degradation and agriculture. Methodology The Kimonyi sector is one of the fifteen sectors of Musanze District in the Northern Province of Rwanda. . Kimonyi sector has 4 cells including Birira, Buramira, Mbizi and KivumuI. It has fifteen thousand five hundred and eighty-nine (15,589) inhabitants (NISR, 2012). The Kimonyi sector is located in the part of the volcanic plain with an average altitude of 1860 m and has an area of ​​21.60 km2 (Luis & Byizigiro, 2012). There are four seasons in the study area, namely long rainy season starting from March to May, long dry season starting from June to mid-September, short rainy season starting from October to November and finally the short rainy season starting from December to February. To perform this study, four Landsat 8 OLI/TIRS images from May 2016, August 2016, November 2016, and January 2017 were downloaded from the USGS web platform (www.earthexplorer.usgs.gov/.). Landsat satellite sensors provide data in 11 spectral bands with spatial resolution of 30 m for the multispectral band and 15 m for the panchromatic band. Image pre-processing and analysis Geometric registration of the image was performed in order to minimize all inherent geometric distortions.