+ Site Statistics
References:
52,654,530
Abstracts:
29,560,856
PMIDs:
28,072,755
+ Search Articles
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ PDF Full Text
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Translate
+ Recently Requested

Crop Area Mapping Using 100-m Proba-V Time Series



Crop Area Mapping Using 100-m Proba-V Time Series



Remote Sensing 8(7): 585



A method was developed for crop area mapping inspired by spectral matching techniques (SMTs) and based on phenological characteristics of different crop types applied using 100-m Proba-V NDVI data for the season 2014-2015. Ten-daily maximum value NDVI composites were created and smoothed in SPIRITS (spirits. jrc. ec. europa. eu). The study sites were globally spread agricultural areas located in Flanders (Belgium), Sria (Russia), Kyiv (Ukraine) and Sao Paulo (Brazil). For each pure pixel within the field, the NDVI profile of the crop type for its growing season was matched with the reference NDVI profile based on the training set extracted from the study site where the crop type originated. Three temporal windows were tested within the growing season: green-up to senescence, green-up to dormancy and minimum NDVI at the beginning of the growing season to minimum NDVI at the end of the growing season. Post classification rules were applied to the results to aggregate the crop type at the plot level. The overall accuracy (%) ranged between 65 and 86, and the kappa coefficient changed from 0.43-0.84 according to the site and the temporal window. In order of importance, the crop phenological development period, parcel size, shorter time window, number of ground-truth parcels and crop calendar similarity were the main reasons behind the differences between the results. The methodology described in this study demonstrated that 100-m Proba-V has the potential to be used in crop area mapping across different regions in the world.

(PDF emailed within 0-6 h: $19.90)

Accession: 066319334

Download citation: RISBibTeXText

DOI: 10.3390/rs8070585


Related references

Obtaining crop-specific time profiles of NDVI: the use of unmixing approaches for serving the continuity between SPOT-VGT and PROBA-V time series. International Journal of Remote Sensing 35(7): 2615-2638, 2014

Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the US Central Great Plains. Remote Sensing Of Environment2: 3, 1096-1116, 2008

Crop area mapping in West Africa using landscape stratification of MODIS time series and comparison with existing global land products. International Journal of Applied Earth Observation and Geoinformation 14(1): 0-93, 2012

Evaluating Crop Area Mapping from MODIS Time-Series as an Assessment Tool for Zimbabwe's "Fast Track Land Reform Programme". Plos One 11(6): E0156630-E0156630, 2016

Mapping crop phenology using NDVI time-series derived from HJ-1 A/B data. International Journal of Applied Earth Observation and Geoinformation 34: 188-197, 2015

Classification of MODIS EVI time series for crop mapping in the state of Mato Grosso, Brazil. International Journal of Remote Sensing 32(22): 7847-7871, 2011

Mapping croplands, cropping patterns, and crop types using MODIS time-series data. International Journal of Applied Earth Observation and Geoinformation 69: 133-147, 2018

Energy crop mapping with enhanced TM/MODIS time series in the BCAP agricultural lands. Isprs Journal of Photogrammetry and Remote Sensing 124: 133-143, 2017

Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time series of remote sensing data. Agriculture Ecosystems & Environment 103(3): 545-560, August, 2004

A MODIS time series data based algorithm for mapping forest fire burned area. Chinese Geographical Science 23(3): 344-352, 2013

Estimating crop area using seasonal time series of Enhanced Vegetation Index from MODIS satellite imagery. Australian Journal of Agricultural Research 58(4): 316-325, 2007

Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index. Remote Sensing of Environment 119(none): 0-242, 2012

Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sensing of Environment 97(2): 137-162, 2005

The use of high-resolution image time series for crop classification and evapotranspiration estimate over an irrigated area in central Morocco. International Journal of Remote Sensing 29(1): 95-116, 2008

Improved maize cultivated area estimation over a large scale combining MODISEVI time series data and crop phenological information. Isprs Journal of Photogrammetry and Remote Sensing 94: 102-113, 2014