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

2021 ◽  
Author(s):  
Ramzi Benhizia ◽  
Yacine Kouba ◽  
György Szabó ◽  
Gábor Négyesi ◽  
Behnam Ata
Keyword(s):  
Landsat Imagery ◽  
Forest Harvesting ◽  
Pine Plantations ◽  
Land Change ◽  
Spatiotemporal Evolution ◽  
Future Evolution ◽  
Land Change Modeler ◽  
Main Driver ◽  
Open Land ◽  
Green Walls

Abstract: 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

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

2021 ◽  
Vol 13 (14) ◽  
pp. 7953
Author(s):  
Ramzi Benhizia ◽  
Yacine Kouba ◽  
György Szabó ◽  
Gábor Négyesi ◽  
Behnam Ata
Keyword(s):  
Landsat Imagery ◽  
Forest Harvesting ◽  
Tree Planting ◽  
Pine Plantations ◽  
Anthropogenic Pressure ◽  
Land Change ◽  
Spatiotemporal Evolution ◽  
Future Evolution ◽  
Land Change Modeler ◽  
Main Driver

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.

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

2021 ◽  
Vol 5 (2) ◽  
pp. 170
Author(s):  
Adnan Adnan ◽  
Fitra Saleh ◽  
Iradat Salihin
Keyword(s):  
Land Use ◽  
Landsat Imagery ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Land Change ◽  
Land Use Classification ◽  
Landsat 8 Oli ◽  
Land Change Modeler ◽  
Two Factors ◽  
Land Changes

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

The Spatiotemporal Evolution of Urban Impervious Surface for Chengdu, China

2021 ◽  
Vol 87 (7) ◽  
pp. 491-502
Author(s):  
Mujie Li ◽  
Zezhong Zheng ◽  
Mingcang Zhu ◽  
Yue He ◽  
Jun Xia ◽  
...  
Keyword(s):  
Neural Networks ◽  
Growth Rate ◽  
Urban Area ◽  
Landsat Imagery ◽  
Impervious Surface ◽  
Kappa Coefficient ◽  
Spatiotemporal Evolution ◽  
Urban Impervious Surface ◽  
The Past ◽  
Secondary Industry

The spatiotemporal evolution of an impervious surface (IS) is significant for urban planning. In this paper, the IS was extracted and its spatiotemporal evolution for the Chengdu urban area was analyzed based on Landsat imagery. Our experimental results indicated that convolutional neural networks achieved the better performance with an overall accuracy of 98.32%, Kappa coefficient of 0.98, and Macro F1 of 98.28%, and the farmland was replaced by IS from 2001 to 2017, and the IS area (ISA) increased by 51.24 km2; that is, the growth rate was up to 13.8% in sixteen years. According to the landscape metrics, the IS expanded and agglomerated into large patches from small fragmented ones. In addition, the gross domestic product change of the secondary industry was similar to the change of ISA between 2001 and 2017. Thus, the spatiotemporal evolution of IS was associated with the economic development of the Chengdu urban area in the past sixteen years.

scholarly journals Land Change Modeler for Analysing Diminishing of Vegetation in Bekasi

IJARCCE ◽  
2021 ◽  
Vol 10 (8) ◽  
Author(s):  
Herlawati a ◽  
Fata Nidaul Khasanah ◽  
Rafika Sari ◽  
Prima Dina Atika ◽  
Rahmadya Trias Handayanto
Keyword(s):  
Land Change ◽  
Land Change Modeler

scholarly journals MODELAGEM TEMPORAL DINÂMICA DO USO E OCUPAÇÃO DO SOLO BASEADO EM SIG PARA A BACIA DO RIO TAPACURÁ (PE)

2018 ◽  
Vol 37 (1) ◽  
pp. 193-210 ◽  
Author(s):  
Ana Paula Campos XAVIER ◽  
Richarde Marques da SILVA
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Multi Layer Perceptron ◽  
Land Change ◽  
Land Change Modeler

Este estudo teve por objetivo simular cenários de uso e ocupação do solo para t4 (2035), tendo como base as mudanças no uso do solo ocorridas em t1 (1989), t2 (2007) e t3 (2015) para a bacia do Rio Tapacurá, localizada no Estado de Pernambuco. Foi realizada a previsão do uso do solo para t3 (2015), usando três métodos: (a) Rede Neural Multi-Layer Perceptron (RNMLP), (b) Similarity-Weighted Instance-Based Machine Learning Algorithm (SimWeight) e (c) Regressão Logística (RL) e para a metodologia que mostrou melhor desempenho, foi realizada a predição dos cenários futuros para t4 (2035). Os cenários futuros simulados foram: (a) Cenário 1: de continuidade das transições e (b) Cenário 2: de continuidade das transições e intensificação da classe pecuária e expansão da área urbana, usando o módulo Land Change Modeler (LCM) do Idrisi TerrSet e imagens da cobertura do solo. Os resultados da previsão do uso do solo para 2015 mostraram que o melhor desempenho foi obtido usando o método RNMLP com treinamento de 84,22% e 10.000 iterações. A simulação dos cenários futuros para t4 mostrou intensificação das transições observadas nos três anos analisados, com previsão para expansão de cerca de 3% da classe pecuária para os dois cenários simulados.

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

2021 ◽  
Vol 12 (4) ◽  
pp. 655-669
Author(s):  
Miguel Angel Palomeque de la Cruz ◽  
Silvia Del Carmen Ruiz Acosta ◽  
Rodimiro Ramos Reyes ◽  
Miguel Alberto Magaña Alejandro ◽  
Adalberto Galindo Alcantara
Keyword(s):  
Ecological Sustainability ◽  
Land Change ◽  
Land Change Modeler ◽  
El Sistema ◽  
Sistemas De Informacion

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.

scholarly journals Utilização da ferramenta lcm do idrisi /taiga para análise de perdas e ganhos no uso da terra na zona de amortecimento da estação ecológica de Assis (SP)

2021 ◽  
Vol 21 (2) ◽  
pp. 249-263
Author(s):  
Layla Cristina de Freitas Assalve ◽  
Daniela Fernanda Da Silva Fuzzo
Keyword(s):  
Landsat 8 ◽  
Land Change ◽  
Landsat 8 Oli ◽  
Land Change Modeler ◽  
Landsat 5 Tm

Ao longo do tempo foram criados diversos tipos de manejos adequados para cada Unidade de Conservação (UCs), dentre eles, a Zona de Amortecimento (ZA) surge com o papel de filtrar os impactos negativos das atividades que ocorrem ao seu redor. Desta forma, o objetivo deste trabalho foi analisar as modificações do uso da terra na ZA da Estação Ecológica de Assis – SP, nos anos 2000 e 2017. Para a realização do trabalho foram utilizadas imagens dos satélites Landsat 5/TM e Landsat 8/OLI, as imagens foram processadas em ambiente SIG e geradas os mapeamentos de perdas e ganhos utilizando o módulo Land Change Modeler (LCM) do software Idrisi-Taiga, o qual apresenta grande importância para a realização de estudos ambientais. Foi possível observar, a redução da pastagem e o aumento das culturas temporárias na porção norte e leste da área, nesses dezessete anos analisados, obteve um ganho de área de 12,29 %. Destaca-se que o entorno se encontra tomado integralmente por cultura temporária e silvicultura, que afetam a conservação, podendo gerar a perda da biodiversidade e o desmatamento neste local, sendo assim o conhecimento dos parâmetros analisados permite a utilização de técnicas adequadas para a preservação efetiva. Portanto, a utilização de dados orbitais pode contribuir ao monitoramento das UCs evitando a degradação ambiental.

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