Inter-Comparison of ASTER and MODIS Surface Reflectance and Vegetation Index Products for Synergistic Applications to Natural Resource Monitoring

Miura, Tomoaki; Yoshioka, Hiroki; Fujiwara, Kayo; Yamamoto, Hirokazu

doi:10.3390/s8042480

Cited by 66 publications

(36 citation statements)

References 38 publications

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“…Huete et al [50] present the NDVI analysis and the Enhanced Vegetation Index (EVI); their results demonstrate the scientific usefulness of MODIS VI. Moreover, Miura et al [52] compared MODIS VI with the high-resolution Advanced Thermal Emission and Reflection Radiometer (ASTER) (15 m) and showed that they coincided well on a global scale.…”

Section: Datamentioning

confidence: 99%

Sixteen Years of Agricultural Drought Assessment of the BioBío Region in Chile Using a 250 m Resolution Vegetation Condition Index (VCI)

et al. 2016

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Drought is one of the most complex natural hazards because of its slow onset and long-term impact; it has the potential to negatively affect many people. There are several advantages to using remote sensing to monitor drought, especially in developing countries with limited historical meteorological records and a low weather station density. In the present study, we assessed agricultural drought in the croplands of the BioBío Region in Chile. The vegetation condition index (VCI) allows identifying the temporal and spatial variations of vegetation conditions associated with stress because of rainfall deficit. The VCI was derived at a 250 m spatial resolution for the 2000-2015 period with the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 product. We evaluated VCI for cropland areas using the land cover MCD12Q1 version 5.1 product and compared it to the in situ Standardized Precipitation Index (SPI) for six-time scales (1-6 months) from 26 weather stations. Results showed that the 3-month SPI (SPI-3), calculated for the modified growing season (November-April) instead of the regular growing season (September-April), has the best Pearson correlation with VCI values with an overall correlation of 0.63 and between 0.40 and 0.78 for the administrative units. These results show a very short-term vegetation response to rainfall deficit in September, which is reflected in the vegetation in November, and also explains to a large degree the variation in vegetation stress. It is shown that for the last 16 years in the BioBío Region we could identify the 2007/2008, 2008/2009, and 2014/2015 seasons as the three most important drought events; this is reflected in both the overall regional and administrative unit analyses. These results concur with drought emergencies declared by the regional government. Future studies are needed to associate the remote sensing values observed at high resolution (250 m) with the measured crop yield to identify more detailed individual crop responses.

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Section: Datamentioning

confidence: 99%

Sixteen Years of Agricultural Drought Assessment of the BioBío Region in Chile Using a 250 m Resolution Vegetation Condition Index (VCI)

et al. 2016

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“…Especially, monitoring of land changes can be achieved using multi-temporal and multiresolution data (Brack, 2007;McRoberts and Tomppo, 2007;Mezned et al, 2007;Miura et al, 2008;Muukkonen and Heiskanen, 2007).…”

Section: Data Analysis 231 Ndvi and Classificationmentioning

confidence: 99%

Study on Land Surface Temperature Characteristics of Hot Mud Eruption in East Java, Indonesia

Bayuaji

Watanabe²,

Tonooka³

et al. 2010

IJReSES

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Abstract. Hot mud has erupted in Sidoarjo, east Java, Indonesia since 29 May 2006. It started as natural gas exploration project and punctured a geological structure at a depth of 2.8 km, releasing unprecedented volume of hot mud volcano (5×104 m 3 /day). By November 2006, it was estimated that hot mud had spread over (2.89±0.10)×106 m 2 , swamping several villages with more than 10,000 people evacuated. In this research, by employing the advantage of spatial perspective of remote sensing imagery, the extent of hot mud spreading area and temperature distributions are derived from satellite images of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor onboard the Terra satellite. The mud spreading area was calculated using three visible/nearinfrared channels having a resolution of 15 m. Temperature distributions were calculated using the temperature/emissivity separation (TES) method on five thermal infrared channels with a resolution of 90 m. The standard and water vapor scaling (WVS) methods were applied in the atmospheric correction process prior to the TES process. The result showed that the mud continued spreading during five months after the eruption. After 3-5 months from the eruption, the estimated temperature was about 30-69°C in the mud spreading area. Also, estimations of the volume and weight of the hot mud were made on the basis of the visible of level 3A product of ASTER and ground survey data.

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“…Inter-sensor model equations relating IKONOS NDVI with ETM+ NDVI were also determined for multiple sensors over time. Miura et al [10] compared the products from ASTER and MODIS sensors for the visible/near-infrared surface reflectance and spectral vegetation indices (VIs), namely, NDVI and the Enhanced Vegetation Index (EVI). The results show that the surface reflectance products and NDVI of the two sensors compared well at a global scale.…”

mentioning

confidence: 99%

“…Though several studies are available for a variety of satellite sensors that have been applied to crop studies, there is no comparative work for the surface reflectance and NDVI between THEOS and Landsat 5 TM, especially for cassava and sugarcane [5][6][7][8][9][10][13][14][15][16]. Cassava and sugarcane are agricultural crops that are increasingly used for biofuels in Thailand [17].…”

mentioning

confidence: 99%

“…In addition, Landsat 5 TM was calibrated in 2003 and was further revised in 2007, based on the detectors' responses to pseudo-invariant desert sites and cross-calibration with ETM+ [22]. The important remote sensing products for the analysis of radiometric accuracy of a sensor are the surface reflectance and Normalized Difference Vegetation Index (NDVI) [5][6][7][8][9][10]. Thus, this study was conducted with four main objectives: (a) to investigate the spectral characteristics of two biofuel crops (cassava and sugarcane); (b) to compare the surface reflectance and NDVI between Landsat 5 TM and THEOS; (c) to develop NDVI regression models between THEOS and Landsat 5 TM for multiple satellite sensors; and (d) to perform classification and spatial accuracy assessment.…”

mentioning

confidence: 99%

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Inter-Sensor Comparison between THEOS and Landsat 5 TM Data in a Study of Two Crops Related to Biofuel in Thailand

et al. 2012

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Knowledge of the spatial distribution of biofuel crops is an important criterion to determine the sustainability of biofuel energy production. Remotely sensed image analysis is a proven and effective tool for describing the spatial distribution of crops using vegetation characteristics. Increases in the number of options and availability of satellite sensors have expanded the horizon of choices of imagery sources for appropriate image acquisitions. The Thailand Earth Observation System (THEOS) satellite is one of the newest satellite sensors. The growing number of satellite sensors warrants their comparative evaluation and the standardization of data obtained from various sensors. This study conducted an inter-sensor comparison of the visible/near-infrared surface reflectance and Normalized Difference Vegetation Index (NDVI) data collected from the Landsat 5 Thematic Mapper (TM) and THEOS. The surface reflectance and the derived NDVI of the sensors were randomly obtained for two biofuel crops, namely, cassava and sugarcane. These crops had low values of visible surface reflectance, which were not significantly (p < 0.05) different. In contrast, the crops had high values of near-infrared surface reflectance that differed significantly (p > 0.05) between the crops. Strong linear relationships between the remote sensing products for the examined sensors were obtained for both cassava and sugarcane. The regression models that were developed can be used to compute the NDVI for THEOS using those determined from Landsat 5 TM and vice versa for the given

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Inter-Comparison of ASTER and MODIS Surface Reflectance and Vegetation Index Products for Synergistic Applications to Natural Resource Monitoring

Cited by 66 publications

References 38 publications

Sixteen Years of Agricultural Drought Assessment of the BioBío Region in Chile Using a 250 m Resolution Vegetation Condition Index (VCI)

Sixteen Years of Agricultural Drought Assessment of the BioBío Region in Chile Using a 250 m Resolution Vegetation Condition Index (VCI)

Study on Land Surface Temperature Characteristics of Hot Mud Eruption in East Java, Indonesia

Inter-Sensor Comparison between THEOS and Landsat 5 TM Data in a Study of Two Crops Related to Biofuel in Thailand

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