FUTURE PREDICTION OF THE EXPANSION OF BUILT-UP AREAS IN BATAM FREE TRADE ZONE (FTZ) USING LAND CHANGE MODELER

The establishment of Batam City as a Free Trade Zone (FTZ) encourages the city’s growth, as manifested in massive built-up area expansion. The aim of this paper was to analyze the pattern of built-up area expansion in FTZ Batam in 2035 based on the corresponding pattern from 2000 to 2015. Land Change Modeler (LCM) was the instrument used to determine and analyze land cover changes in 2000–2015, from which future changes or built-up area expansion in 2035 were predicted using the validated 2020 land cover map as reference. The validation test based on the Kappa Index of Agreement yielded 96%. The prediction results showed that, compared with 2020, the built-up area in 2035 would have increased by 31.8% and expanded towards the outskirts of FTZ Batam. This sprawl follows the location of the primary activity centers in the FTZ, as allocated in Presidential Regulation of the Republic of Indonesia No. 87 of 2011. A new expansion is expected to continue into existing open space and extensive untouched forest areas. These research findings provide a concept that can be utilized to formulate certain policies and regional planning in the future.

Impacto de las actividades agropecuarias y petroleras sobre las coberturas naturales del campo petrolero Samaria, Tabasco

En las regiones tropicales del sureste de México, las actividades productivas de subsistencia, el crecimiento de las ciudades y la industria petrolera, están ocupando coberturas originales de vegetación selvática, vegetación hidrófita y cuerpos de agua. El objetivo del estudio fue valuar el efecto provocado por el crecimiento de las actividades primarias y de extracción de petróleo sobre las coberturas naturales, mediante la modelación del cambio de uso del suelo en el campo petrolero Samaria en los municipios de Cunduacán y Centro, Tabasco, México. Se realizó un análisis espacial con mapas de ocupación del suelo mediante Land Change Modeler y se determinaron ganancias, pérdidas, contribuciones, el cambio neto y las transiciones de cada categoría. Desde el inicio de la extracción de petróleo en 1965 hasta 2019, en el CPS, con una superficie de 8 052 ha, se perdieron 647 ha de humedales y 436 ha de vegetación arbórea, como consecuencia de la expansión de actividades primarias y la industria petrolera, las cuales ocuparon 1 287 ha de uso agrícola, 1 598 ha de uso pecuario, 269 ha de infraestructura petrolera y 775 ha de la zona urbana. Se concluye que la aplicación de Land Change Modeler fue novedosa para la evaluación de la degradación de los ecosistemas y la estimación de la distribución del cambio de coberturas naturales y usos artificiales en el campo petrolero Santamaria, estado de Tabasco.

Prediksi Perubahan Lahan Terbangun Dengan OBIA LCM Pada Citra Terfusi di Kota Kendari

Abstrak: Penggunaan lahan disetiap tahunnya akan mengalami perubahan. Perkembangan tersebut bisa jadi tidak terkendali, sehingga perencanaan prediksi perubahan lahan penting untuk dikaji. Dalam memprediksi dapat dilakukan dengan menggunakan citra, khususnya citra Landsat. Penelitian ini bertujuan untuk: (1) distribusi penggunaan lahan terbangun di Kota Kendari pada tahun 2014 dan 2019 dengan metode OBIA pada citra terfusi; (2) melihat arah perubahan penggunaan lahan terbangun di Kota Kendari pada tahun 2024 dan 2029 dengan metode Land Change Modeler (LCM). Metode yang digunakan dalam penelitian ini yaitu metode klasifikasi penggunaan lahan berbasis piksel OBIA dan pemodelan prediksi perubahan penggunaan lahan Land Change Modeler (LCM). Hasil penelitian ini antara lain: (1) luas lahan terbangun pada tahun 2014 di Kota Kendari seluas 6.061,85 hektar dan luas penggunaan lahan terbangun di Kota Kendari pada tahun 2019 seluas 6.716,96 hektar dengan perubahan penggunaan lahan terbangun tahun 2014 sampai dengan tahun 2019 dengan pertambahan luas 2,43%; (2) Arah perubahan penggunaan lahan terbangun di Kota Kendari diprediksikan cenderung berkembang ke arah Kecamatan Baruga karena dipengaruhi oleh dua faktor yaitu kemiringan lereng dan jaringan jalan. Kata Kunci : Penggunaan Lahan, Landsat 8 OLI, Penajaman Citra, OBIA, LCM Abstract: Land use will change every year. The development may be uncontrollable, so predictive planning of land changes is important to review. In predicting can be done using imagery, especially Landsat imagery. This study aims to:(1) the distribution of land use built in Kendari City in 2014 and 2019 with OBIA method on diffusion imagery; (2) see the direction of land use changes built in Kendari City in 2024 and 2029 with land change modeler (LCM) method. The methods used in this study are OBIA pixel-based land use classification method and land use change prediction modeling land change modeler (LCM). The results of this study include: (1) land area built in 2014 in Kendari City aswide as 6,061.85 hectars and land use area built in Kendari City in 2019 aswide as 6,716.96 hectars with land use changes built in 2014 to 2019 with an increase of 2.43%; (2) The direction of land use changes built in Kendari City is predicted to tend to develop towards Baruga Subdistrict because it is influenced by two factors, namely slope and road network. Keywords: Land Use, Landsat 8 OLI, Image Sharpening, OBIA, LCM

Spatiotemporal Land-Use Changes of Batticaloa Municipal Council in Sri Lanka from 1990 to 2030 Using Land Change Modeler

Land-use change is a predictable and principal driving force of potential environmental changes on all spatial and temporal scales. A land-use change model is a tool that supports the analysis of the sources and consequences of land-use dynamics. This study aims to assess the spatiotemporal land-use changes that occurred during 1990–2020 in the municipal council limits of Batticaloa. A land change modeler has been used as an innovative land planning and decision support system in this study. The main satellite data were retrieved from Landsat in 1990, 2000, 2010, and 2020. For classification, the supervised classification method was employed, particularly with the medium resolution satellite images. Land-use classes were analyzed by the machine learning algorithm in theland change modeler. The Markov chain method was also used to predict future land-use changes. The results of the study reveal that only one land-use type, homestead, has gradually increased, from 12.1% to 34.1%, during the above-mentioned period. Agriculture land use substantially declined from 26.9% to 21.9%. Bare lands decreased from 11.5% to 5.0%, and wetlands declined from 13.9% to 9.6%.

Monitoring the Spatiotemporal Evolution of the Green Dam in Djelfa Province, Algeria

Green walls and green dams are increasingly being considered as part of many national and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria), from 1972 to 2019, by using Landsat imagery, Land Change Modeler, and OpenLand package. The future evolution of pine plantations, for the year 2029, was also forecasted, based on an anthropogenic scenario (i.e., anthropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but, after that, pine plantations deteriorated significantly, due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land change modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation continues at the same rate, the green dam in the Moudjbara region will disappear during the next few decades. Being aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy, by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation. We strongly recommend moving away from the singular tree planting focus, to diversifying desertification control methods.

Modelación de cambios de coberturas y uso de suelo en Nacajuca, Tabasco

El crecimiento urbano de Nacajuca, Tabasco, ha transformado el sistema natural, siendo necesario conocer la actual configuración espacial de las coberturas naturales y los usos artificiales con la finalidad de proveer información de la dinámica espacial para el ordenamiento ecológico. El objetivo del estudio fue modelar los cambios de cobertura y uso del suelo (2000, 2008 y 2017), mediante un análisis multitemporal empleando el Land Change Modeler for ecological sustainability de IDRISI. Los resultados indican que en el periodo 2000-2008 se encontró la disminución de los humedales (1 796 ha) y un ligero aumento de la vegetación arbórea (689 ha), contrario al crecimiento urbano (796 ha) y elevado aumento del pastizal (2 168 ha). En el segundo periodo (2008-2017) se detectó la mayor pérdida de humedales (3 995 ha) y de vegetación arbórea (1 233 ha), mientras que el área urbana y el pastizal presentaron los mayores incrementos (1 365 y 4 378 ha). Las principales transiciones fueron en primer lugar, el cambio de grandes coberturas de humedales a pastizal y en segundo lugar la transformación de pastizal a urbano. La perturbación se relaciona con la dinámica de la zona metropolitana de Villahermosa y coincide con la pérdida de grandes superficies de humedales en las áreas analizadas. Ante esto, las alternativas para reducir los efectos del cambio de uso de suelo son la elaboración del ordenamiento ecológico territorial y del programa de desarrollo urbano donde se haga partícipe el uso de los Sistemas de Información Geográfica, la teledetección ambiental y la implementación de modelos geomáticos para el análisis espacial.

Uso e ocupação do solo: nascentes urbanas em Araxá, MG, Brasil / Land use and occupation: urban springs in Araxá, MG, Brazil

Este trabalho visou a comparação do uso e ocupação do solo nos anos de 2008 e 2014 para as nascentes urbanas da cidade de Araxá – MG. Para a realização de tal comparação foi utilizado o módulo Land Change Modeler (LCM) pertencente ao Sistema de Informação Geográfica Idrisi Selva 17.1. As nascentes em estudo foram analisadas nos dois anos com relação às seguintes classes de uso do solo: ocupação urbana, área de preservação permanente (APP), pastagem e agricultura. Foi constatado que as áreas de preservação permanente (APP) foram as que mais se modificaram, transformando-se em sua grande maioria em área urbana (57,42 hectares), outros 8,46 hectares e 9,63 hectares de pastagem e agricultura, respectivamente, se transformaram em área urbana também. Com relação ao processo inverso constatou-se que 20,88 hectares e 12,42 hectares de pastagem e agricultura, respectivamente, se transformaram em área de preservação permanente (APP) no entorno das nascentes.

Monitoring the Spatiotemporal Evolution of the Green Dam in Djelfa Province, Algeria

Green walls and green dams are increasingly being considered as part of many nation-al and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria) from 1972 to 2019 by using Landsat imagery, Land Change Modeler and Open Land package. The future evolution of pine plantations for the year 2029 was also forecasted, based on an anthropogenic scenario (i.e., an-thropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but after that, pine plantations deteri-orated significantly due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land Change Modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation con-tinues at the same rate, the green dam will disappear in the Moudjbara region during the next few decades. Aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation

Prediksi, Optimalisasi Penggunaan Lahan, dan Nilai Tanah di Kota Bekasi

Urban planning management plays an important role in sustainable development because cities are the main source of environmental degradation. Limited land with high land prices makes it difficult to organize the city. There have been many studies discussing urban planning, but most of them focus on one side, such as only prediction, optimization, or other aspects related to environment conservation. This study intends to discuss aspects of prediction, optimization and their relationship to land values in the city of Bekasi. Prediction results show the addition of buildings, especially in the city center. To optimize land use, especially in relation to high land prices in the city center, it is necessary to build vertical settlements. Keywords: Land Change Modeler, Geographic Information Systems, Clustering, Driving Factors Abstrak Manajemen tata kota memegang peranan penting dalam pembangunan berkelanjutan karena kota merupakan sumber utama permasalahan lingkungan. Keterbatasan lahan dengan harga tanah yang tinggi menyebabkan sulitnya penataan kota. Riset yang membahas perencanaan kota sudah banyak dilakukan, hanya saja kebanyakan focus kepada satu sisi, misalnya prediksi, optimalisasi, atau pun aspek-aspek lain yang terkait konservasi alam. Penelitian ini bermaksud membahas aspek-aspek prediksi, optimalisasi dan keterkaitannya dengan nilai tanah di kota Bekasi. Hasil prediksi menunjukan penambahan bangunan khususnya di pusat kota. Untuk mengoptimalkan penggunaan lahan, khususnya berkaitan dengan harga tanah yang tinggi di pusat kota, perlu dibangun pemukiman vertikal. Kata kunci: Land Change Modeler, Sistem Informasi Geografis, Klasterisasi, Faktor Pendorong Perubahan Lahan