Ambon is a city with the highest economic and population growth in Maluku Province, which makes built-up land have high and rapid growth so that it can reduce the carrying capacity of the city's land. This can lead to an imbalance between population and available housing and may result in higher population pressure on available areas. Prediction of spatial modeling is needed as a preventive measure to prevent excessive land cover changes in the future. This study aims to analyze the carrying capacity of residential areas and spatial modeling of land cover changes in Ambon City in 2010, 2015, and 2020 using Cellular Automata Markov Chain (CAMC) and identify settlement patterns based on population density in 2031 in Ambon city. The results of the Cellular Automata Markov Chain (CAMC) analysis show that the residential area in 2031 has increased to 7,910.03 ha and the development of residential areas in 2031 in Ambon City is centered on Sirimau District.

Kota Ambon merupahkan daerah dengan kasus COVID-19 tertinggi di provinsi Maluku yaitu 435 orang terkonfirmasi positif dan yang terkonfimasi suspek 10 orang. Kasus COVID-19 di Kota Ambon dari bulan maret-desember, cenderung meningkat setiap bulannya. Jumlah penderita COVID-19 di Kota Ambon meningkat disebabkan karena wilayah tersebut merupakan wilayah dengan jumlah penduduk yang banyak dibandingkan wilayah lain, jumlah penduduk Kota Ambon saat ini yaitu 371.650 Jiwa. Penelitian ini bertujuan untuk mengetahui sebaran spasial tingkat kejadian kasus positif COVID-19 dengan metode Kernel Density di Kota Ambon  dan untuk menganalisis hubungan antara kepadatan penduduk dan jumlah kasus Positif COVID-19 di Kota Ambon. Hasil analisis pola spasial sebaran tingkat kejadian kasus Positif COVID-19 terkonsentrasi pada wilayah-wilayah tertentu mengikuti jumlah penduduk dan faktor lingkungan lain di Kota Ambon. Sebaran spasial tingkat kejadian kasus Positif COVID-19 menunjukan, kelas tertinggi terdapat disekitar 22 desa dan Kelurahan dengan luas 1420 Hektar atau 4%, kelas sedang terdapat di 8 desa dan kelurahan dengan luas 2258 atau 7%, dan kelas rendah terdapat di 29 desa dan kelurahan  dengan luas 28877 atau 89%. Hubungan kepadatan penduduk dengan jumlah kejadian kasus Positif COVID-19 di Kota Ambon mempunyai korelasi yang  kuat dengan nilai (r) 0,620 dan mempunyai hubungan yang positif.

Kota Ambon merupakan ibukota dari provinsi Maluku yang berpotensi mengalami bencana tanah longsor. Topografi Kota Ambon yang didominasi oleh perbukitan dengan kelerengan yang curam menyebabkan Kota Ambon juga rawan akan bencana longsor dan banjir berdasarkan Indeks Risiko Bencana Indonesia (IRBI) 2018, Kota Ambon memiliki indeks risiko bencana tanah longsor 8.5 (sedang). Penelitian ini bertujuan untuk mengetahui tingkat kerentanan longsor, sebaran longsor di Kota Ambon dan upaya mitigasi di Kota Ambon. Untuk menghindari kerugian akibat bencana tersebut dilakukan tindakan pengelolaan resiko bencana yaitu dengan Pemetaan kerentanan bencana tanah longsor berbasis Sistem Informasi Geografis (GIS). Variabel yang digunakan dalam penelitian ini meliputi variabel ketinggian lahan/elevasi, jenis tanah, curah hujan, geologi, penggunanan lahan/land use. Penentuan titik sampel berdasarkan daerah yang sering terjadi tanah longsor. Pengambilan data dalam penelitian ini menggunakan metode observasi dan dokumentasi. Teknik analisis yang digunakan dalam penelitian ini yaitu: teknik pengharkatan/scoring, teknik tumpang susun peta/overlay, dan pembuatan klasifikasi kerentanan tanah longsor untuk mendapatkan daerah kerentanan tanah longsor. Hasil penelitian menunjukkan bahwa tingkat kerentanan longsor di Kota Ambon terdiri dari tiga kelas yaitu, rendah, sedang dan tinggi, dengan luasan masing-masing adalah 5.957,67 Ha atau 17,81%, dan 18.584,58 Ha atau 55,57 %, 8.900,11 Ha atau 26,61%.

Sirimau District has the largest population in Ambon City which has an impact on the need for higher residential land, this will certainly affect uncontrolled land cover changes and have an impact on land conversion and environmental damage. This study aims to analyze land cover changes in Sirimau District in 2012, 2017, and 2022, and predict land cover in 2031. This study uses the Cellular Automata Markov Chains (CA-MC) method. The results showed that in the period 2012-2031 the area of residential land cover and open land continued to increase along with the increase in population and the high need for built-up land. In contrast to the land cover of agricultural areas and non-agricultural areas, which experienced a decrease in area. The results of the research are expected to be used as a basis for making policies related to the arrangement and good use of space in the future

The phenomenon of urban growth has become an important issue that affects the land use system and land cover in a region for several reasons, such as population growth and the economy. This phenomenon has also become one of the main environmental issues lately because it has devastated urban ecosystems. Ternate Tengah District has the highest population growth rate in Ternate City and has experienced extensive urban development due to several reasons, such as the pace of urbanization, economic growth, and population. Urbanization accelerates the demand to land for living. As a result, there will be gaps or disparities between land needs and available land, a decline in environmental carrying capacity, and potential environmental harm in the future. Spatial modeling of future land covers is needed to provide data on policy-making. GIS and remote sensing methods have been widely introduced, but the most effective one is CA-Markov. This model has been used in various areas worldwide, but its application to predicting land use change in the populous city of a small island under threat of volcanic hazards like Ternate is limited. This study aims to evaluate and forecast the land-use changes brought on by urbanization in Ternate City's Central Ternate District. We used a cellular automata-Markov chain to examine and forecast land cover changes in 2002, 2012, 2022, and 2032. The findings indicate that residential area development will increase along with population expansion and land demand. The results of this study can support the policy-making related to the future arrangement and utilization of space in The Central Ternate District.