scholarly journals Comparing of Land Change Modeler and Geomod Modeling for the Assessment of Deforestation (Case Study: Forest Area at Poso Regency, Central Sulawesi Province)

2018 ◽  
Vol 4 (8) ◽  
pp. 597-607 ◽  
Author(s):  
Irmadi Nahib ◽  
Turmudi Turmudi ◽  
Rizka Windiastuti ◽  
Jaka Suryanta ◽  
Ratna S Dewi ◽  
...  
Keyword(s):  
Forest Area ◽  
Land Change ◽  
Land Change Modeler ◽  
Central Sulawesi

scholarly journals Ecological impact of coal mines on lichens: A case study at Moghla coal mines Kalakote (Rajouri), J&K

2009 ◽  
Vol 1 (1) ◽  
pp. 24-26 ◽  
Author(s):  
Sangeeta Charak ◽  
Mukhtar A. Sheikh ◽  
Anil K. Raina ◽  
D. K. Upreti
Keyword(s):  
Coal Mining ◽  
Ecological Impact ◽  
Coal Mines ◽  
Forest Area ◽  
Mining Activities ◽  
Quantitative Parameters ◽  
Open Coal

The data on the frequency, density and abundance of the lichens growing around the Moghla Coal mines, Kalakote has been recorded and compared with lichens growing in a forest area away from the coal mines to work out effect of coal mines on the diversity and distribution of lichens. The data revealed that pollutants released by the open coal mining activities not only effected qualitative distribution but also have effect on the quantitative parameters. Over all 10 species of lichens belonging to 9 genera and 6 families have been recorded from the vicinity of coal mines as compared to 15 species, belonging to 9 genera and 7 families, recorded from the forest area.

scholarly journals Functional nature of the landscape phases of the suburban forest area of Lviv Vynnyky

2014 ◽  
pp. 395-402
Author(s):  
O. Babych
Keyword(s):  
Key Words ◽  
Specific Area ◽  
Forest Area ◽  
Functional Nature ◽  
Full Picture ◽  
Landscape Units ◽  
Functional Components

Functional components of the landscape units, phases and tracts of the suburban forest area of Lviv Vynnyky were analyzed. Case study of the forest geosystems, such as, for example, the landscape phases, shows the research of biometrical index of the forests which are concentrated specifically in this area. On the drawings of the landscape phases of this specific area the division of the forests, which shows the full picture of their areal division, is shown. Key words: landscape phases, landscape tracts, forest geosystems, suburban forest area of Lviv Vynnyky.

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

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

An adding/deleting approach to improve land change modeling: a case study in Qeshm Island, Iran

2019 ◽  
Vol 12 (11) ◽  
Author(s):  
Ali Kourosh Niya ◽  
Jinliang Huang ◽  
Ali Kazemzadeh-Zow ◽  
Babak Naimi
Keyword(s):  
Land Change ◽  
Qeshm Island ◽  
Land Change Modeling

scholarly journals A Remote Sensing Based Method to Detect Soil Erosion in Forests

2019 ◽  
Vol 11 (5) ◽  
pp. 513 ◽  
Author(s):  
Hanqiu Xu ◽  
Xiujuan Hu ◽  
Huade Guan ◽  
Bobo Zhang ◽  
Meiya Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Southern China ◽  
Red Soil ◽  
Forest Area ◽  
Landsat 8 ◽  
Large Spatial Scale ◽  
Five Factors

Rainwater-induced soil erosion occurring in the forest is a special phenomenon of soil erosion in many red soil areas. Detection of such soil erosion is essential for developing land management to reduce soil loss in areas including southern China and other red soil regions of the world. Remotely sensed canopy cover is often used to determine the potential of soil erosion over a large spatial scale, which, however, becomes less useful in forest areas. This study proposes a new remote sensing method to detect soil erosion under forest canopy and presents a case study in a forest area in southern China. Five factors that are closely related to soil erosion in forest were used as discriminators to develop the model. These factors include fractional vegetation coverage, nitrogen reflectance index, yellow leaf index, bare soil index and slope. They quantitatively represent vegetation density, vegetation health status, soil exposure intensity and terrain steepness that are considered relevant to forest soil erosion. These five factors can all be derived from remote sensing imagery based on related thematic indices or algorithms. The five factors were integrated to create the soil erosion under forest model (SEUFM) through Principal Components Analysis (PCA) or a multiplication method. The case study in the forest area in Changting County of southern China with a Landsat 8 image shows that the first principal component-based SEUFM achieves an overall accuracy close to 90%, while the multiplication-based model reaches 81%. The detected locations of soil erosion in forest provide the target areas to be managed from further soil loss. The proposed method provides a tool to understand more about soil erosion in forested areas where soil erosion is usually not considered an issue. Therefore, the method is useful for soil conservation in forest.

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