This dataset presents a detailed analysis of individual tree changes within farmlands across India for the years 2018 to 2022. Utilizing PlanetScope satellite images, isolated trees were mapped for each year. We used the farmland class of WorldCover to keep only trees falling into this class, which can cause unexpected patterns (e.g. large trees not mapped as they were not mapped as farmland). Each tree has the detection confidence of each year as an attribute. The change confidence is the aggregated confidence over 5 years and can be used as a measure of uncertainty in the detection. Trees that have detection confidence values below 0.5 are likely shrubs or misclassification, or the image quality was low. If a tree was detected in both 2018 and 2019, but not in 2020-2022, it has likely disappeared. The dataset contains about 0.5 billion trees, saved in the 355 files in the format of geopackage, grouped into 89 folders for zenodo ingestion. We use a grid system which was further subdivided in 4 files. The name of the gpkg files follows ps2_PSScene_2018-2022_gridIDs_195_308_000_0000_composite_lshm_0_0_0.gpkg. The gridIDs can be found in the file of india_grids.geojson. We also developed a viewer to explore the tree detection confidence: https://rs-cph.projects.earthengine.app/view/tree. Any usage must be solely for Noncommercial education or scientific research purposes, and publication in academic or scientific research journals. Licensee agrees that all such publications must include an attribution that clearly and conspicuously identifies Planet Labs PBC.