Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand

Pimple, Uday; Sitthi, Asamaporn; Simonetti, Dario; Pungkul, Sukan; Leadprathom, Kumron; Chidthaisong, Amnat

doi:10.3390/su9020258

Cited by 46 publications

(61 citation statements)

References 55 publications

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“…Shuttle Radar Topographic Mission (SRTM) has been around since 2000 and been widely used for various applications. Among these studies, 1,2,4,6,8,9,14,[24][25][26][27] were all used SRTM data for correcting the topographic effect on EO Satellite data. ALOS World 3D-30m (AW3D30) is the Japan Aerospace Exploration Agency (JAXA) project to provide a global digital 3D map.…”

Section: Digital Elevation Model (Dem)mentioning

confidence: 99%

“…The decreased variation coefficient (CV) is a widely used method for validating topographic correction 1,9 . It is also referred to as a test of homogeneity 3,4,6,9,36,37 . To assess the effectiveness of each DEM, the means and standard deviation (SD) were calculated and compared for both before and after correction.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Figure 4a to figure 4d shows how all these DEM performed for each band, while 4e shows the different magnitude of CV changes. A good topographic correction should decrease CV values 6 . This case only happens for NIR bands.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Several studies have tested and applied these techniques on various datasets. [1][2][3][4][5][6][7][8][9] were using Landsat data (from MSS to OLI). 10,11 were performing the topographic correction on IKONOS data.…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of different DEMs for topographic correction on LAPAN-A3: preliminary results

Zylshal¹

2019

Sixth Geoinformation Science Symposium

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Topographic correction over the mountainous region is an essential preprocessing step for landuse/landcover extraction from earth observation (EO) satellite data. Until the time of this paper writing, there has not been any publication regarding topographic correction on LAPAN-A3 multispectral data. Topographic correction mainly grouped into two categories: band ratio and illumination modeling which required ancillary digital elevation model (DEM). This paper aims to evaluate three different DEM sources used for topographic correction on LAPAN-A3. These DEMs are Shuttle Radar Topographic Mission (SRTM), ALOS World 3D (AW3D), and nation-wide DEMNAS. The topographic corrections were performed over a subset of forested mountainous region in South Sulawesi, Indonesia. Minnaert correction algorithm was used in all three DEMs and evaluate the results. Performance evaluation was based on visual assessment, as well as spectral homogeneity of the pixel value before and after correction. The spectral homogeneity was calculated based on coefficient variation changes before and after correction. The initial results showed that SRTM produced the best visual appearance, while AW3D 30 performed the best in terms of highest reduction in coefficient variation.

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Section: Digital Elevation Model (Dem)mentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of different DEMs for topographic correction on LAPAN-A3: preliminary results

Zylshal¹

2019

Sixth Geoinformation Science Symposium

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“…These images belong to Path 6 and Rows 68 (10.64% cloud cover) and 69 (0% cloud cover) taken on 07 August and 22 July in 2017 (dry season). The LCC consisted of the following processing steps: (1) normalize topographic shadow on images (bands 2-7) with the Minnaert algorithm [88] (Appendix C), (2) extract training/validation samples, (3) apply a maximum likelihood classification (MLC) [55], and (4) reclassify misclassified pixels (Appendix D) by comparing results with participatory mapping zonification and high-resolution imagery from Google [89]. The resulting product is shown in Figure 4.…”

Section: Participatory Mappingmentioning

confidence: 99%

Impact of Heavy Metals on Community Farming Activities in the Central Peruvian Andes

et al. 2019

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The high mining potential of the Peruvian Andes has promoted booming foreign investments. The mining activity takes place on campesino community lands and headwaters. Once the government awards a mining concession, mining companies must regularly negotiate land rent with communities over the whole duration of the mining operation, often leading to disagreements. Our research objective is to identify the mining impacts on the farming activities of campesino communities in the Junin region, central Peruvian Andes. Using a mixed-methods approach involving in-depth interviews, water and soil analysis, land-cover classification and participatory mapping, we analyzed the mining-community agreements and the mining impacts on the farming lands. We arrived at two primary conclusions. First, mining activities in terms of heavy metal concentrations impact on farming lands, although the contribution of previous and concurrent activities cannot be distinguished. Second, the diverging and short-termed interests of the involved parties which circumscribe the agreements may potentially lead to conflicts.Minerals 2019, 9, 647 2 of 28 own the land [17,19]. Based on the canon minero, 50% of the taxes from the mining sector is distributed among the affected subnational governments (i.e., district and province) [20][21][22][23]. The subnational governments directly affected by mining may receive up to 70% of this tax [11,18,24], while campesino communities are excluded from receiving it directly. As a result, the communities tend to negotiate compensations separately with the mining companies. Both canon minero and compensations are aimed at reducing land-use conflicts. Despite this, conflicts increased (2005)(2006)(2007)(2008)(2009)(2010)(2011), reduced in 2012 and have remained constant (ca. 162 yearly conflicts) since then [19,[25][26][27][28][29][30][31][32][33][34][35][36][37]. In 2017, Peru allocated 16 million ha for mining concessions [38], although not all of these became viable mines. The most common mining practice in Peru is open-pit mining, as this model is preferred for exploiting metal deposits. There are 36 open-pit mines throughout the country [39]. The environmental impacts of open-pit mining mainly relate to water infiltration and supply to rivers [12,[40][41][42], which impact the socio-economic situation of local households [1,[43][44][45].Most studies have split these biophysical and socio-economic aspects rather than integrating them [43][44][45][46]. Therefore, an interdisciplinary approach [47] is suggested to broaden the understanding of the impacts of mining from different perspectives. In this sense, the overarching objective of this study is to identify the mining impacts on the farming activities of campesino communities in the Junin region. Therefore, we first analyzed the agreements between mining companies and communities via in-depth interviews with stakeholders. Then, we evaluated the influence by open-pit mining sites on the water and soil quality and assessed the effects on farming lands. The foll...

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Enhancing monitoring of mangrove spatiotemporal tree diversity and distribution patterns

Pimple

Simonetti²,

Peters

et al. 2022

Land Degrad Dev

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Spatiotemporal information on mangrove species assemblage of natural, disturbed, and rehabilitated is an essential prerequisite for effective strategies for biodiversity conservation and management. However, appropriate field‐based sampling strategies of spatial heterogeneity still hamper the detection of the species distribution and its temporal development. An increasing amount of remote sensing data seems the perfect way to tackle these challenges. With this article, we fill this gap by presenting a review of the challenges and limitations to assess the current status of species diversity. We conclude that species discrimination based on remote sensing techniques is still limited by atmospheric contamination and tidal fluctuations. The lack of accurate information on the spatiotemporal development of species diversity and forest structure further curtails an understanding of functional indicators and the predictive power of modeling approaches. Nevertheless, multi‐source remote‐sensing techniques could seemingly capture the landscape heterogeneity and support systematic sampling designs. Spatially balanced (systematic) training and validation data are necessary to compile robust spatiotemporal information, supporting reliable predictions for optimizing restoration efforts. A systematic sampling of spatiotemporal ecological information is vital to derive the historical state of mangroves, detecting their degradation, and predicting future patterns of species distribution that are generally crucial for restoration, and particularly to rehabilitate species diversity.

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Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand

Cited by 46 publications

References 55 publications

Performance evaluation of different DEMs for topographic correction on LAPAN-A3: preliminary results

Performance evaluation of different DEMs for topographic correction on LAPAN-A3: preliminary results

Impact of Heavy Metals on Community Farming Activities in the Central Peruvian Andes

Enhancing monitoring of mangrove spatiotemporal tree diversity and distribution patterns

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