<![CDATA[Indonesia is rich in germplasm, with approximately 38,000 plant species spread across the archipelago. However, significant deforestation has led to a decline in species distribution, with deforestation rates reaching 1 to 1.8 million hectares from 1985 to 1998. The Purwodadi Botanical Garden serves as a mini prototype of Indonesia's plant diversity but lacks an integrated database on tree species distribution. This study aims to utilize Deep Learning and remote sensing technology for tree species mapping in the Purwodadi Botanical Garden. Using the RCNN Deep Learning model in ArcGIS Pro, the data includes SPOT 6 and 7 imagery, field observations of tree species, and object labeling based on taxonomic levels. The RCNN model successfully detected 235 tree objects with an accuracy of 72%, Precision of 84.45%, Recall of 70.29%, F1-score of 0.76, and an Average Precision of 61%. The species diversity index (H’) was recorded at 3.919161, while the evenness index (E) was 0.973619, indicating high biodiversity. A total of 56 species with 341 individuals were identified, including rare species such as Tectona grandis L. f., Adansonia digitata L., and Syzygium cumini. These findings demonstrate that Deep Learning technology can effectively support biodiversity monitoring.]]>
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