HI, 
I have sent it as a private response

On Wednesday, September 20, 2017 at 5:33:33 PM UTC+5:30, Justin wrote:
>
> thanks. As soon as you send it, I can compare with what I have and send 
> you two or three versions of villages for that area.
>
> I know sometimes generalized data for boundaries is good enough. But the 
> higher quality, more detailed data going into any dataset would be best. 
> Then you can generalize if it is too big or you do not need for analysis 
> purposes. But people become very upset when their boundaries are not 
> displayed correct, or when you tell them they are in one village/ city but 
> are actually in the next town or two over.
>
> Thanks for your help!
>
> Justtin
>
> On Wed, Sep 20, 2017 at 7:44 AM, Dilip Damle <[email protected] 
> <javascript:>> wrote:
>
>> Hi, 
>>
>> Will send in a day or two privately. I have at least two versions.
>>
>> On Wednesday, September 20, 2017 at 3:07:44 PM UTC+5:30, Justin wrote:
>>>
>>> Dilip,
>>> Can you send your boundaries? I can send back what I have so you can 
>>> compare and tell me if they are truly good enough
>>>
>>> Thanks
>>> Justin
>>>
>>> Thanks
>>>
>>> On Sep 20, 2017 2:24 AM, "Dilip Damle" <[email protected]> wrote:
>>>
>>>> >>This is not complete for all of India. The boundaries are also 
>>>> heavily generalized. 
>>>>
>>>> I think a Good enough Spatial data for useful boundaries, I mean a 
>>>> usable  boundary at ground level Does not exist. At least in digital form.
>>>>
>>>> I am working on a Block in Uttrakhand and trying to make as good as 
>>>> possible Georeferenced Village map.
>>>>
>>>> From the different versions on data available there is an area 
>>>> variation from about 25% to 200% and even more in rare cases
>>>>
>>>> So the village boundaries tell only the following. 
>>>>
>>>> 1. The general shape of village 
>>>>
>>>> 2. The adjacent villages in correct orientation. 
>>>>
>>>> Beyond that it is UNRELIABLE so the question of a Good quality boundary 
>>>> is far too away. 
>>>>
>>>> The situation may differ from state to state and location to location.
>>>>
>>>> Here is the area variation. In hectares The total block area matches 
>>>> reasonably
>>>>
>>>> Village Number GIS AREA  Revenue Records Area 
>>>> 1 601.91 888 
>>>> 2 144.43 46 
>>>> 3 542.76 591 
>>>> 4 109.19 101 
>>>> 5 343.24 418 
>>>> 6 94.58 153 
>>>> 7 128.16 125 
>>>> 8 348.82 406 
>>>> 9 192.34 205 
>>>> 10 386.91 398 
>>>> 11 183.28 192 
>>>> 12 201.04 189 
>>>> 13 65.26 60 
>>>> 14 241.54 271 
>>>> 15 65.57 41 
>>>> 16 264.62 328 
>>>> 17 80.66 72 
>>>> 18 272.74 278 
>>>> 19 332.67 267 
>>>> 20 263.73 21 
>>>> 21 107.21 139 
>>>> 22 32.89 18 
>>>> 23 129.43 106 
>>>> 24 35.74 29 
>>>> 25 157.12 151 
>>>> 26 75.34 185 
>>>> 27 75.34 180 
>>>> 28 80.37 81 
>>>> 29 78.60 322 
>>>> 30 332.86 205 
>>>> 31 401.28 443 
>>>> 32 115.64 94 
>>>> 33 221.42 156 
>>>> 34 289.91 275 
>>>> 35 180.00 189 
>>>> 36 38.47 19 
>>>> 37 669.13 686 
>>>> 38 195.84 147 
>>>> 39 176.93 204 
>>>> 40 237.92 201 
>>>> 41 197.96 93 
>>>> 42 178.93 235 
>>>> 43 139.76 199 
>>>> 44 150.22 142 
>>>> 45 337.39 362 
>>>> 46 140.16 130 
>>>> 47 329.78 297 
>>>> 48 148.92 137 
>>>> 49 53.27 61 
>>>> 50 189.64 177 
>>>> 51 271.95 301 
>>>> 52 537.06 546 
>>>> 53 98.52 112 
>>>> 54 216.79 240 
>>>> 55 221.72 221 
>>>> 56 169.23 159 
>>>> 57 256.80 172 
>>>> 58 244.65 180 
>>>> 59 323.52 342 
>>>> 60 155.57 139 
>>>> 61 198.16 226 
>>>> 62 551.58 547 
>>>> 63 181.48 154 
>>>> 64 191.56 202 
>>>> 65 116.32 75 
>>>> 66 222.39 91 
>>>> 67 674.67 477 
>>>> 68 131.45 205 
>>>> 69 186.58 180.00 
>>>> 70 275.32 192 
>>>> 71 161.26 140 
>>>> 72 205.72 184 
>>>> 73 153.82 198 
>>>> 74 153.15 147 
>>>> 75 122.96 113 
>>>> 76 195.78 148 
>>>> 77 88.32 92 
>>>> 78 172.03 88 
>>>> 79 38.98 20 
>>>> 80 290.14 213 
>>>> 81 140.46 63 
>>>> 82 227.49 217 
>>>> 83 315.18 213 
>>>> 84 192.45 297 
>>>> 85 148.57 224 
>>>> 86 304.51 228 
>>>> 87 330.13 302 
>>>> 88 362.33 303 
>>>> 89 842.47 787 
>>>> 90 854.31 301 
>>>> 91 413.11 459 
>>>> 92 246.49 196 
>>>> 93 141.21 188 
>>>> 94 50.20 43 
>>>> 95 224.15 421 
>>>> 96 330.24 320 
>>>> 97 257.30 305 
>>>> 98 122.78 126 
>>>> 99 76.21 82 
>>>> 100 82.24 77 
>>>> 101 281.56 335 
>>>> 102 447.84 622 
>>>> 103 163.20 243 
>>>> 104 225.56 98 
>>>> 105 77.61 61 
>>>> 106 191.88 132 
>>>> 107 166.23 161 
>>>> 108 419.17 497 
>>>> 109 179.60 178 
>>>> 110 114.45 53 
>>>> 111 129.30 129 
>>>> 112 190.41 72 
>>>> 113 152.22 180 
>>>> 114 214.67 244 
>>>> 115 51.76 78 
>>>> 116 193.90 267 
>>>> 117 133.99 96 
>>>> 118 233.88 224 
>>>> 119 106.42 81 
>>>> 120 89.75 51 
>>>> 121 120.77 92 
>>>> 122 70.04 84 
>>>> Total Block  26784.47 25947 
>>>>  
>>>>
>>>>
>>>>
>>>> On Wednesday, September 20, 2017 at 8:18:58 AM UTC+5:30, Justin wrote:
>>>>>
>>>>> This is not complete for all of India. The boundaries are also heavily 
>>>>> generalized. 
>>>>>
>>>>> Thanks for the update
>>>>>
>>>>> On Sep 19, 2017 9:47 PM, "nishadh" <[email protected]> wrote:
>>>>>
>>>>>> Hi Justin,
>>>>>>
>>>>>> I am in need of such data. The dataset having 2001-2011 will be much 
>>>>>> helpful in understanding air pollution emission from residential fuel 
>>>>>> consumption. Census of India 2011 has sample data on every village with 
>>>>>> number of houses using various fuels for cooking or lighting purposes. 
>>>>>> Data 
>>>>>> linking 2001 and 2011 housing listing table with spatial information 
>>>>>> could 
>>>>>> be a great data set in preparing high resolution air pollutant emission 
>>>>>> inventory for country level and studying temporal change.
>>>>>>
>>>>>> A good start for such scale data compile can be linking it with 
>>>>>> project on datameet village maping 
>>>>>> http://projects.datameet.org/indian_village_boundaries/
>>>>>>
>>>>>>
>>>>>> Regards,
>>>>>>
>>>>>> Nishadh
>>>>>>
>>>>>> -- 
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>>>>> -- 
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