Reference Data Standard Protocols Kamini Yadav Dr. Russ Congalton

Current Process Flow Chart ???this probably still need some tweak, after final discussions???

Testing Protocol on Mali data Evaluate Mali data collected in August 2015 by Murali, according to the flowchart made by Justin Large Scale, LS (>20ha) Medium Scale, MS(10-20 ha) Small Scale, SS(<10ha) Very Large Scale, VLS Very Very Large Scale, VVLS Field collected Created by Justin ???we need to define scale taking pixel resolution of satellite sensors: LS >=6.25 ha (MODIS 250m) but = 0.81 ha (3x3, 30 m) =100 ha (AVHRR 1000 m) but = 1600 ha???

Mali Ground Data (August 2015, Murali) Need to know/understand…… How to handle multiple crops in single sample? ??crop dominance (e.g., wheat 60%, barley 20%, others 20%) rather than crop type??? What does scale mean here? ??in previous slide we defined scale with their relationship to satellite sensor pixel sizes; so whether we map crop types or crop dominance, scale definitions are same?? How does this scale help in deciding homogeneous samples at 250m/90m sample unit? ??pure homogeneous samples for crop type are not feasible across the world especially at resolutions >30 m (0.09 ha). So, where we cant get pure single crop homogenity, we should define by crop dominance (e.g., wheat-barley system; corn-soybean system)?? What the date of the collection of crop data? ??as far as possible data is collected based on crop phenology. Again this maynot be always possible??

Steps to crosswalk the Mali data into our standard protocol format Extract the single crop samples because they conform to the homogeneity requirement due to the presence of a single crop ??In Africa, it is unlikely to find single crop even within a Landsat pixel (30 m x 30 m or 0.09 ha). So, where crop type is not feasible crop dominance is the way to go. Remember we have 4 products. For product 1 (crop no crop) it is possible to get sufficient number of homogeneous pixels, same for product 2 (irrigated vs. rainfed), where homogeneous crops are mapped we can get crop calendar for that (product 3). However, product 4 we may not be able to map crop type everywhere, but crop dominance)?? Check the homogeneity of each sampling unit in a 250mX 250m window on Google Earth (using high resolution imagery) ??homonenety should mean getting croplands right. Not crop type. Because I expect most pixels to have mixed crops at 250 m resolution in Africa. However, this is possible in USA, Canada, Europe??

Checking Mali data using Google Earth The images of some samples do not look like a single crop ??this will be most common for 250 m pixel. You will have crop dominance or mix of crops of various proportions?? Some samples might not have crops before the growing season (left as fallow) ??such data is useful for identifying crop, no crop?? Are the coordinates correct (are we in the right place)? ??likely coordinates are taken from road. People who use the data have to correct for this by moving the pixels to field centers??

Issue: Proximity to Road 2014 Need to implement some automated filter on the entire dataset based on some minimum distance to the road layer ?? People who use the data have to correct for this by moving the pixels to field centers….applying automated filter is even better (Justing, please let us know)?? All the samples near to road (within certain distance) must be flagged for evaluation or moved to the center of a field ??indeed. See previous response….also everyone I know have been doing this??

April 2014 November 2013 Issue - continued ??These are common problems of field work. People who use the data have to correct for this by moving the pixels to field centers??

Issue - continued February 2014 VVLS?? – very, very large scale Does this mean only homogeneous crops are there so that we can move the sample inside the field and away from the road? ??VVLS defined in slide 3. The above filed is homogeneous for MODIS 250m) but = 0.81 ha (3x3, 30 m) <=6.25 ha); SS = <=0.81 ha (3x3, 30 m)???:

2014 February 2015 VLS -Very Large scale?? We need to understand this scale term so that we can determine how far the samples can be moved away from the road and into the field and yet remain a homogeneous sample unit. ??see definition of scale in slide 3 and answers previously?? Issue - continued

March2013 Includes settlement in the yellow window. This is Large scale (LS) but does not look homogeneous??? ??Here is an example on how to deal with these. When one gets reference data, let us say thet have pure homogeneous pixels for class 1 : croplands, single crop, rainfed, LS (sample size N=22). The non pure samples are not used in classification, but used just in class identification. For example, the above pixel inspite of having a partial pixel in settlement, still may classify into class 1 : croplands, single crop, rainfed, LS. So, it helps in class identification and labeling?? Issue - Close to settlement

February 2011 June 2013 Include settlements in the yellow window ??samples such as this will be useful in class labeling. Suppose one of your unsupervised (e.g., class 56) Happens to be this class, then we can label the class As: croplands mixed with settlements??? Question - So close to settlements may be indication of the wrong geographic coordinates?? ?

September 2013 January 2014 The sample includes a waterbody in 250m by 250m homogeneous window? ??samples such as this will be useful in class labeling. Suppose one of your unsupervised (e.g., class 56) Happens to be this class, then we can label the class As: croplands mixed with water bodies or it may actually fall into : croplands, single crop, irrigated, rice dominant???

December 2013 Not homogeneous ??will be still valuable to identify classes?? Close to the coastline

Photograph taken of the sample unit does not look like Maize crop as mentioned in description ??not sure…ask murali?? February 2014 December2011

February 2014 Homogeneity vs. Scale Large scale?? In Google Earth, the 250x250m window does not look homogeneous; Photograph seems to be of more than one crops ??answered previously??

VLS…does this scene indicate homogeneity for one crop type?? ??probably it has one or more crop with about 20% tree cover?? Issue - homogeneity

Important Issues to be solved Identify the single crop sample units ??this should be attempted. But, landscape is diverse and fragmented. Probably if you drive in Mali, getting single crop fields of modis size (250m x 250m) will be very rare. It is possible to get 3 x 3, 30 m pixels (0.81 ha) as homogeneous unit. But, if the ladscape is all mixed crop, we should capture it as is?? Decide homogeneous samples from different scale levels – very confusing ??homogenity is possible for: (a) crop vs. no crop, (b) irrigated vs. rainfed. For crop type, homogenity may or maynot exist. All our field work is standardized for 250m x 250 m pixels (6.25 ha). In Africa, only a very small proportion of pixels will be homogeneous at this resolution. The same may well be true for even a 3 x 3 30m Landsat pixels (0.81 ha). In such cases we should capture mixed crops, just as is the reality in field (we can’t change this)?? Perform stratification and identify samples for each class label ?? If Justin can do this, terrific. However, if there are 1000 points collected, we split samples by 60 (600):40 (400) and share them with reference and validation teams. The people who do reference data work, validation data work can do this stratification themselves as well. But, all ground data points are precious and need to be retained. They may or maynot be homogeneous for crop type, but that is reality in field conditions?? In addition to minimum distance between samples (spatial autocorrelation), use minimum distance to roads, settlements, and waterbodies. This analysis must be added to the flow chart. ??ok. Something to keep in mind that when people gather data, they travel a minimum of 2-3 kilometers from one point to another…..so, this issue does not remove samples??

Thank you Questions?