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Predicting poverty with vegetation index
Applied Economic Perspectives and Policy, 2021AbstractAccurate and timely predictions of the poverty status of communities in developing countries are critical to policymakers. Previous work has applied convolutional neural networks (CNNs) to high‐resolution satellite imagery to perform community‐level poverty prediction. Although promising, such imagery has limitations in predicting poverty among
Binh Tang, Yanyan Liu, David S. Matteson
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2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2015
The hyperspectral vegetation index (HVI) has shown promise in vegetation fields, but its relationship to the radar vegetation index (RVI) is not known in the context of various land covers. This work presents a comparative analysis of the HVI data derived from the AISA sensor and RVI values originating from the RADARSAT-2 quad-polarimetric synthetic ...
Yong-Hyun Kim +3 more
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The hyperspectral vegetation index (HVI) has shown promise in vegetation fields, but its relationship to the radar vegetation index (RVI) is not known in the context of various land covers. This work presents a comparative analysis of the HVI data derived from the AISA sensor and RVI values originating from the RADARSAT-2 quad-polarimetric synthetic ...
Yong-Hyun Kim +3 more
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2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
Information about vegetation status has widespread utility in agriculture, forestry, hydrology, and land-atmosphere interaction study. This paper presents an attempt to monitor the vegetation water content (VWC) by merging visible/infrared remote sensing and microwave remote sensing.
Hui Lu 0003 +3 more
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Information about vegetation status has widespread utility in agriculture, forestry, hydrology, and land-atmosphere interaction study. This paper presents an attempt to monitor the vegetation water content (VWC) by merging visible/infrared remote sensing and microwave remote sensing.
Hui Lu 0003 +3 more
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Theoretical and Applied Climatology, 2020
Soil moisture is a key land surface parameter that reflects conditions of drought in agricultural areas, such that variations in soil moisture significantly impact agricultural production. At a large spatial scale, soil moisture can be indicated using the temperature vegetation drought index (TVDI), which is based on soil moisture monitoring.
Huichao Zhao +5 more
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Soil moisture is a key land surface parameter that reflects conditions of drought in agricultural areas, such that variations in soil moisture significantly impact agricultural production. At a large spatial scale, soil moisture can be indicated using the temperature vegetation drought index (TVDI), which is based on soil moisture monitoring.
Huichao Zhao +5 more
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Remote Sensing Letters, 2019
This paper propose a universal normalized vegetation index (UNVI), which is an improved vegetation index (VI) based on the universal pattern decomposition method (UPDM), termed VIUPD. We also derive new matrices to facilitate convenient calculation of the UNVI based on data from the MODIS and Landsat-TM, ETM, OLI satellite sensors.
Lifu Zhang +6 more
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This paper propose a universal normalized vegetation index (UNVI), which is an improved vegetation index (VI) based on the universal pattern decomposition method (UPDM), termed VIUPD. We also derive new matrices to facilitate convenient calculation of the UNVI based on data from the MODIS and Landsat-TM, ETM, OLI satellite sensors.
Lifu Zhang +6 more
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2017
This is the survey for finding vegetation, deforestation of earth images from various related papers from different authors. This survey deals with remote sensing and normalized difference vegetation index with various techniques. We survey almost 100 theoretical and empirical contributions in the current decade related to image processing, NDVI ...
Suresh Kumar Nagarajan +1 more
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This is the survey for finding vegetation, deforestation of earth images from various related papers from different authors. This survey deals with remote sensing and normalized difference vegetation index with various techniques. We survey almost 100 theoretical and empirical contributions in the current decade related to image processing, NDVI ...
Suresh Kumar Nagarajan +1 more
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Transformed difference vegetation index (TDVI) for vegetation cover mapping
IEEE International Geoscience and Remote Sensing Symposium, 2003In this study, we present a new vegetation index, the TDVI: transformed difference vegetation index. This index shows the same sensitivity as the soil adjusted vegetation index (SAVI) to the optical proprieties of bare soil subjacent to the cover. It does not saturate like NDVI and SAVI and it shows an excellent linearity as a function of the rate of ...
Abderrazak Bannari +2 more
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Microwave vegetation index from SMOS
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012Monitoring global vegetation can be of importance in understanding land surface processes and their interactions with the atmosphere, biogeochemical cycle, and primary productivity. Previous research has shown that vegetation indices have become essential tools in this field.
Jiancheng Shi 0001, Yunqing Li
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IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
To effectively deal with the spring drought facing South Korea periodically since 2000, a monitoring system to keep tracing the drought is critical, along with the index indicating the severity of the drought in a quantified value. To conduct the in-depth evaluation of the behavior and intensity of the drought by region, a spatial analysis by area unit
Jung-Sool Park +2 more
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To effectively deal with the spring drought facing South Korea periodically since 2000, a monitoring system to keep tracing the drought is critical, along with the index indicating the severity of the drought in a quantified value. To conduct the in-depth evaluation of the behavior and intensity of the drought by region, a spatial analysis by area unit
Jung-Sool Park +2 more
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Vegetation index response to leaf area index and fractional vegetated area over cotton
IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120), 2002In an agricultural setting vegetation indices should accurately track the state of crop growth under conditions in which the radiometer field of view includes both active vegetative, senesced, and non-vegetative components. Ideally, they should also do so regardless of variation in viewing and background conditions.
S.A. Mauget, D.R. Upchurch
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