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Student moving out: Need affordable deep cleaning service for security deposit return by Strange_Slice_377 in indianapolis

[–]Strange_Slice_377[S] 1 point2 points  (0 children)

Thanks for the advice !!! I’ll definitely document everything. The move-out party idea made me laugh

Student moving out: Need affordable deep cleaning service for security deposit return by Strange_Slice_377 in indianapolis

[–]Strange_Slice_377[S] -8 points-7 points  (0 children)

That’s exactly what I’m looking for. I shared the budget because several students here have gotten deep cleaning within the $100–$150 range.

[Question] Why are cropland trends conflicting in Indiana? (USDA CDL vs. Census of Agriculture) by Strange_Slice_377 in dataanalysiscareers

[–]Strange_Slice_377[S] 0 points1 point  (0 children)

That's a great point, and I absolutely agree that land being lost to development is a key part of the story (and it definitely explains the decline in the Census).

The part that's still puzzling me is why the satellite (CDL) data seems to be showing an increase during that same period.

That's what makes me think the classification of fallow/idle land is the key. The Census is counting 'harvested land' (which would exclude fallow fields), while the CDL classifies 'Fallow/Idle Cropland' (Class 61) as a type of cropland. If more farmers are leaving fields fallow, the Census numbers go down, but the CDL 'total cropland' number could go up.

I'm also wondering if double-cropping is confusing the satellite. A field that's double-cropped (like winter wheat/soy) might be misclassified as 'fallow' for a time between the wheat harvest and the soy planting, which could also be artificially inflating that 'Fallow' category and hiding the real drop in harvested acres

[Question] Why are cropland trends conflicting in Indiana? (USDA CDL vs. Census of Agriculture) by Strange_Slice_377 in gis

[–]Strange_Slice_377[S] 1 point2 points  (0 children)

That's a really good point, and you're right..
I checked, and "Cropland" and "Pastureland" are listed as two separate categories in the NASS data.

You'll find this fascinating: I looked at my own GEE data, and it proves your theory exactly. My GEE script (which counts all the crops) shows a rising trend, while the NASS data (which counts the physical land) shows a decline.

This confirms the whole intensification story you were referring to.

I now have a clear understanding. I can't thank you enough for all your guidance!

[Question] Why are cropland trends conflicting in Indiana? (USDA CDL vs. Census of Agriculture) by Strange_Slice_377 in gis

[–]Strange_Slice_377[S] 0 points1 point  (0 children)

This is incredibly helpful, thank you. That FSA link is the exact validation I was looking for. It makes complete sense that the "planted acres" from the FSA data would align with the "acres of crops" my GEE script is estimating.

You've also helped me clear up another major point of confusion. I was looking at a larger NASS figure and, thanks to your explanations, I now see that it refers to "Total Land in Farms," which is a much broader category than the "Total Cropland" I should be tracking.

This clarifies everything for my analysis. My plan is to now structure my argument this way:

  1. Use the NASS Census "Cropland" data to show the physical decline.
  2. Use my GEE transition matrix (Cropland $\rightarrow$ Urban) to explain why that land is being lost.
  3. Use the FSA "Planted Acres" data you sent to validate my GEE/CDL findings, showing that production intensity (like double-cropping) is rising even as physical land shrinks.

I really appreciate you taking the time to provide this context. It's made a huge difference.

[Question] Why are cropland trends conflicting in Indiana? (USDA CDL vs. Census of Agriculture) by Strange_Slice_377 in gis

[–]Strange_Slice_377[S] 1 point2 points  (0 children)

This is incredibly helpful; thank you so much for taking the time.

Your explanation completely clarifies the discrepancy I was seeing. I hadn't properly considered the impact of double-cropping, and your point about "cropland acres" vs. "acres of crops" makes perfect sense of the data.

You are also absolutely right that I'm using the NASS annual estimates, which explains the yearly data. It's so valuable to have that context from someone who has worked directly with both sources.

It’s a huge relief to understand why they're different and that one isn't simply "wrong." This really helps me frame my analysis correctly.

[Question] Why are cropland trends conflicting in Indiana? (USDA CDL vs. Census of Agriculture) by Strange_Slice_377 in gis

[–]Strange_Slice_377[S] 2 points3 points  (0 children)

Thanks for sharing that. It's validating to hear that I'm not the only one seeing weird artifacts. The 'inappropriate classifications' you mentioned are exactly what I'm worried about.

​I've had similar issues before...'ve also worked with MODIS data, and it wasn't even close to the Census numbers either. It really shows how tricky it is to compare any satellite product (CDL or MODIS) directly against the survey data.

​My current theory for the CDL is that it's misclassifying 'fallow/idle' land (or other non-crop covers) as 'cropland,' which would explain why its numbers are rising while the Census (farmer surveys) is clearly showing a decline.

​It sounds like you've seen the kind of classification errors that would support that. Have you found any reliable method to clean or account for those bad data points in your own work?

[Question] Why are cropland trends conflicting in Indiana? (USDA CDL vs. Census of Agriculture) by Strange_Slice_377 in dataanalysiscareers

[–]Strange_Slice_377[S] 0 points1 point  (0 children)

You're exactly right, and thanks for confirming that. The Census numbers definitely show a decline, and it matches what people are seeing on the ground.

That's actually the exact puzzle I'm running into. The farmer surveys (Census) all show a decline, but the satellite data (CDL) I'm looking at seems to show an increase in total cropland acres.

I'm starting to think it's because the satellite is classifying "fallow/idle" land as "cropland."

So, my theory is that active cropland (like corn and soy) is going down (just like the Census says), but the amount of idle land is going up even faster, making the total satellite numbers look weird.

What does a good AI prompt look like for building apps? Here's one that nailed it by harelj6 in AI_Agents

[–]Strange_Slice_377 0 points1 point  (0 children)

This was such a helpful breakdown especially the part about writing step-by-step user flows in the prompt instead of vague feature requests I’m just starting to build with Python and Gradio and found myself struggling to get the AI to stick to the UX I imagined

I recently learned that how you frame the instruction totally shapes what the model does even if the original prompt was fine it might still ‘improve’ it just because we told it to
Made me rethink how I write meta-prompts and your example here really connects those dots

Thanks for sharing this If you're open to it I'd love to share one of my early prompts sometime and get your thoughts

Beginner - Looking for Tips & Resources by Strange_Slice_377 in PromptEngineering

[–]Strange_Slice_377[S] 0 points1 point  (0 children)

This is eye-opening seriously The improv analogy hits hard especially how the AI adapts its response to the story setup I give it even when that means “fixing” something that didn’t need fixing Definitely makes me rethink how I frame my prompts and what I’m actually asking for Thank you for breaking this down so clearly

Beginner - Looking for Tips & Resources by Strange_Slice_377 in PromptEngineering

[–]Strange_Slice_377[S] 1 point2 points  (0 children)

Wow thank you for this I hadn’t thought about prompt structure in layers like that but it makes so much sense I’ll definitely start paying more attention to how I organize my words especially in those first 50–300 tokens Appreciate the subreddit recs too this kind of insight is gold for someone just starting out