scholarly journals Relative Contribution of the Topographic Influence on the Triangle Approach for Evapotranspiration Estimation over Mountainous Areas

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaosong Zhao ◽  
Yuanbo Liu
Keyword(s):  
Complex Terrain ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Surface Air Temperature ◽  
Temperature Correction ◽  
Topographic Effects ◽  
Topographic Correction ◽  
Relative Contribution ◽  
Triangle Method ◽  
Evapotranspiration Estimation

Evapotranspiration (ET) is an important component of the water budget. Estimation ET through remote sensing over a mountainous terrain is typically obstructed by topographic effects. In this paper, topographic corrections were applied to ET estimates using the surface-air temperature difference-Normalized Difference Vegetation Index ((Ts-Ta)-NDVI) triangle method with MODIS data for the Taihu Basin in China. The effect of topography on ET was evaluated over an area with a complex terrain. After applying the topographic correction, the results indicate that the ET decreased with elevation and slope. The slope had a stronger impact on ET than the elevation, which caused the corrected ET to decrease by 90% from 6.8 mm day−1to 0.6 mm day−1for slopes over 50°. On average, the corrected ET decreased by 10.4% and 32.1% for north- and south-facing slopes, respectively. The ET corrected using the triangle method strongly depended on the evaporative fraction correction, which can mainly be attributed to the surface temperature correction. We conclude that a topographic correction is necessary when the triangle method is applied to areas with a complex terrain.

scholarly journals Rapid primary productivity changes in one of the last coastal rainforests: the case of Kahua, Solomon Islands

2009 ◽  
Vol 36 (3) ◽  
pp. 253-260 ◽  
Author(s):  
IRENE GARONNA ◽  
IOAN FAZEY ◽  
MOLLY E. BROWN ◽  
NATHALIE PETTORELLI
Keyword(s):  
Remote Sensing ◽  
Primary Productivity ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Solomon Islands ◽  
Remote Sensing Data ◽  
Human Populations ◽  
Sensing Data ◽  
Relative Contribution ◽  
Indirect Impacts

SUMMARYThe growth of human populations has many direct and indirect impacts on tropical forest ecosystems both locally and globally. This is particularly true in the Solomon Islands, where coastal rainforest cover still remains, but where climate change and a growing human population is putting increasing pressure on ecosystems. This study assessed recent primary productivity changes in the Kahua region (Makira, Solomon Islands) using remote sensing data (normalized difference vegetation index, NDVI). In this area, there has been no commercial logging and there is no existing information about the state of the forests. Results indicate that primary productivity has been decreasing in recent years, and that the recent changes are more marked near villages. Multiple factors may explain the reported pattern in primary productivity. The study highlights the need to (1) assess how accurately remote sensing data-based results match field data on the ground; (2) identify the relative contribution of the climatic, socioeconomic and political drivers of such changes; and (3) evaluate how primary productivity changes affect biodiversity level, ecosystem functioning and human livelihoods.

scholarly journals Does topographic normalization of landsat images improve fractional tree cover mapping in tropical mountains?

2015 ◽  
Vol XL-7/W3 ◽  
pp. 261-267 ◽  
Author(s):  
H. Adhikari ◽  
J. Heiskanen ◽  
E. E Maeda ◽  
P. K. E. Pellikka
Keyword(s):  
Predictive Models ◽  
Vegetation Index ◽  
Incidence Angle ◽  
Vegetation Indices ◽  
Airborne Lidar ◽  
Tree Cover ◽  
Topographic Effects ◽  
Landsat Images ◽  
Topographic Correction ◽  
Tropical Mountains

Fractional tree cover (Fcover) is an important biophysical variable for measuring forest degradation and characterizing land cover. Recently, atmospherically corrected Landsat data have become available, providing opportunities for high-resolution mapping of forest attributes at global-scale. However, topographic correction is a pre-processing step that remains to be addressed. While several methods have been introduced for topographic correction, it is uncertain whether Fcover models based on vegetation indices are sensitive to topographic effects. Our objective was to assess the effect of topographic correction on the accuracy of Fcover modelling. The study area was located in the Eastern Arc Mountains of Kenya. We used C-correction as a digital elevation model (DEM) based correction method. We examined if predictive models based on normalized difference vegetation index (NDVI), reduced simple ratio (RSR) and tasseled cap indices (Brightness, Greenness and Wetness) are improved if using topographically corrected data. Furthermore, we evaluated how the results depend on the DEM by correcting images using available global DEM (ASTER GDEM, SRTM) and a regional DEM. Reference Fcover was obtained from wall-to-wall airborne LiDAR data. Landsat images corresponding to minimum and maximum sun elevation were analyzed. We observed that topographic correction could only improve models based on Brightness and had very small effect on the other models. Cosine of the solar incidence angle (<i>cos i</i>) derived from SRTM DEM showed stronger relationship with spectral bands than other DEMs. In conclusion, our results suggest that, in tropical mountains, predictive models based on common vegetation indices are not sensitive to topographic effects.

scholarly journals ANÁLISE DO IMPACTO DA CORREÇÃO ATMOSFÉRICA NO CÁLCULO DO ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA A PARTIR DE IMAGEM LANDSAT 8/OLI

2020 ◽  
Vol 13 (1) ◽  
pp. 076
Author(s):  
Cristiane Nunes Francisco ◽  
Paulo Roberto da Silva Ruiz ◽  
Cláudia Maria de Almeida ◽  
Nina Cardoso Gruber ◽  
Camila Souza dos Anjos
Keyword(s):  
Rio De Janeiro ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Response ◽  
Vegetation Indices ◽  
Atmospheric Correction ◽  
Landsat 8 ◽  
Topographic Effects ◽  
Landsat 8 Oli ◽  
Arithmetic Operations

As operações aritméticas efetuadas entre bandas espectrais de imagens de sensoriamento remoto necessitam de correção atmosférica para eliminar os efeitos atmosféricos na resposta espectral dos alvos, pois os números digitais não apresentam escala equivalente em todas as bandas. Índices de vegetação, calculados com base em operações aritméticas, além de caracterizarem a vegetação, minimizam os efeitos da iluminação da cena causados pela topografia. Com o objetivo de analisar a eficácia da correção atmosférica no cálculo de índices de vegetação, este trabalho comparou os Índices de Vegetação por Diferença Normalizada (Normalized Difference Vegetation Index - NDVI), calculados com base em imagens corrigidas e não corrigidas de um recorte de uma cena Landsat 8/OLI situado na cidade do Rio de Janeiro, Brasil. Os resultados mostraram que o NDVI calculado pela reflectância, ou seja, imagem corrigida, apresentou o melhor resultado, devido ao maior discriminação das classes de vegetação e de corpos d'água na imagem, bem como à minimização do efeito topográfico nos valores dos índices de vegetação.  Analysis of the atmospheric correction impact on the assessment of the Normalized Difference Vegetation Index for a Landsat 8 oli image A B S T R A C TThe image arithmetic operations must be executed on previously atmospherically corrected bands, since the digital numbers do not present equivalent scales in all bands. Vegetation indices, calculated by means of arithmetic operations, are meant for both targets characterization and the minimization of illumination effects caused by the topography. With the purpose to analyze the efficacy of atmospheric correction in the calculation of vegetation indices with respect to the mitigation of atmospheric and topographic effects on the targets spectral response, this paper compared the NDVI (Normalized Difference Vegetation Index) calculated using corrected and uncorrected images related to an inset of a Landsat 8 OLI scene from Rio de Janeiro, Brazil. The result showed that NDVI calculated from reflectance values, i.e, corrected images, presented the best results due to a greater number of vegetation patches and water bodies classes that could be discriminated in the image, as well the mitigation of the topographic effect in the vegetation indices values.Keywords: remote sensing, urban forest, atmospheric correction.

scholarly journals Monitoring the Water Stress of an Indoor Living Wall System Using the “Triangle Method”

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3261
Author(s):  
Xu Yuan ◽  
Kati Laakso ◽  
Chad Daniel Davis ◽  
J. Antonio Guzmán Q. ◽  
Qinglin Meng ◽  
...  
Keyword(s):  
Health Status ◽  
Water Stress ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Cloud Forest ◽  
Ecological Engineering ◽  
Remote Sensing Data ◽  
Living Wall ◽  
Triangle Method

Living walls are important vertical greening systems with modular prevegetated structures. Studies have suggested that living walls have many social benefits as an ecological engineering technique with notable potential for reconciliation ecology. Despite these benefits, there are currently no mature workflows or technologies for monitoring the health status and water stress of living wall systems. To partially fill the current knowledge gap related to water stress, we acquired thermal, multispectral, and hyperspectral remote sensing data from an indoor living wall in the Cloud Forest of the Gardens by the Bay, Singapore. The surface temperature (Ts) and a normalized difference vegetation index (NDVI) were obtained from these data to construct a Ts-NDVI space for applying the “triangle method”. A simple and effective algorithm was proposed to determine the dry and wet edges, the key components of the said method. The pixels associated with the dry and wet edges were then selected and highlighted to directly display the areas under water-stress conditions. Our results suggest that the proposed algorithm can provide a reasonable overview of the water-stress information of the living wall; therefore, our method can be simple and effective to monitor the health status of a living wall. Furthermore, our work confirms that the triangle method can be transferred from the outdoors to an indoor environment.

scholarly journals Geospatial Effect on the Mining Operation in Joda/Barbil Area of Odisha, India

2021 ◽  
pp. 36-55
Author(s):  
Siba Prasad Mishra ◽  
Kamal Kumar Barik ◽  
Smruti Ranjan Panda
Keyword(s):  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Surface Air Temperature ◽  
Mining Operation ◽  
Landsat 8 ◽  
Mining Areas ◽  
Illegal Mining ◽  
Comparison Of The Results

The study aims to investigate the Geospatial effect on the extraction operation in Joda and Barbil mining areas of Keonjhar district, Odisha, India. Present work involves the topography, soil, climate, and stratigraphy investigation of the area. The acquisition of Landsat 8 TIRS (Thermal Infrared), Landsat 5 TM (Thematic Mapper), and CARTOSAT DEM data of temporal and spatial satellite images from various websites. ARC GIS and ERDAS IMAGINE 9.2 software used to find the land use and land cover images (accuracy average 90%). Normalized Difference Vegetation Index (NDVI), and Surface air Temperature (SAT) of Barbil area for 2003, 2007, 2017 and 2018 have been estimated. Comparison of the results have shown that, there is increase in built up, and mining areas whereas the agricultural land and vegetation cover are down scaled. There is constant average SAT rise of 1-2°C in all the land cover classification between 2007 and 2018. The NDVI values show conversion of sparse from dense vegetation in the area. Poor operational strategies in mines operation, like corruption, illegal mining, lack of accountability, overburden wastes/ trailing disposal, ecologic degradation, waterlogging in mine pits, and human rights violations are the root causes of environmental deterioration of the study area. It is pertinent to implement strictly, the Mines and Minerals (Development and Regulation) Amendment Act, India, 2021, regular GIS application to assess the mines volume of extraction, strict vigilance and fixation of accountability for losses of existing mines values, and afforestation/ reforestation of degraded/lost forests in Barbil area.

scholarly journals The Daily Fire Hazard Index: A Fire Danger Rating Method for Mediterranean Areas

2020 ◽  
Vol 12 (15) ◽  
pp. 2356 ◽  
Author(s):  
Giovanni Laneve ◽  
Valerio Pampanoni ◽  
Riyaaz Uddien Shaik
Keyword(s):  
Moisture Content ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Hazard ◽  
Hazard Index ◽  
Temperature Correction ◽  
Mediterranean Forests ◽  
Moisture Index ◽  
Fire Weather Index ◽  
Regional Administration

Mediterranean forests are gravely affected by wildfires, and despite the increased prevention effort of competent authorities in the past few decades, the yearly number of fires and the consequent damage has not decreased significantly. To this end, a number of dynamical methods have been developed in order to produce short-term hazard indices, such as the Fire Probability Index and the Fire Weather Index. The possibility to estimate the fire hazard is based on the observation that there is a relationship between the characteristics of the vegetation (i.e., the fuel), in terms of abundance and moisture content, and the probability of fire insurgence. The density, type, and moisture content of the vegetation are modeled using custom fuel maps, developed using the latest Corine Land Cover, and using a number of indices such as the NDVI (Normalized Difference Vegetation Index), Global Vegetation Moisture Index (GVMI), and the evapotranspiration, derived from daily satellite imagery. This paper shows how the algorithm for the calculation of the Fire Potential Index (FPI) was improved by taking into account the effect of wind speed, topography, and local solar illumination through a simple temperature correction, preserving the straightforward structure of the FPI algorithm. The results were validated on the Italian region of Sardinia using official wildfire records provided by the regional administration.

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